RK's Musings

Silence

A beautiful poem via Jaisri :

Misunderstand me correctly…

Music begins where words cease.

When music ceases, silence!

When all arts aspire to

the condition of music;

What does music aspire to?

Silence.

The logic of music leads

eventually to silence!

Music must come from silence.

Come from it and return to it.

Perhaps everything will end in fire.

Fire, then silence.

That is how everything end, after all.

But, misunderstand me correctly.

I do not choose silence,

silence chooses me.

Anyway, I’m not taking any chances.

For a moment I savour the silence.

I listened until my ears could hear no more,

and silence resumed.

and I wrote this.

Steal like an Artist

Austin Kleon’s book is essentially a blog post turned in to a book .The basic theme of the book is that in art as in other forms, you have to steal. The word steal has a negative connotation and hence the book differentiates between two kinds of thefts:

Basically theft in this sense means that you are free from the burden of trying to be completely original. Most of the book is common sense stuff but how often do we really follow commonsense ? 

There are some nice visuals in the book. Some of them that I found interesting are :

Very often, ONLY when you have multiple ideas,
that you are capable of coming up with a perfect idea that works

 

It is better to separate your workspace in to analog and digital mode

Paul Graham in one of his essays says that he follows a similar configuration where he uses two computers, one connected to internet and the other offline, so that while working on something that requires concentration, the urge to browse randomly, check email, tweets, blogs is eliminated.

 

As Steve Jobs says, you cannot connect dots going forward.
However, dots you create in fact make you what you are.

 

All you need is a little space and a little time—a place to work, and some time to do it;
a little self-imposed solitude and temporary captivity.

“Be regular and orderly in your life, so that you may be violent and original in your work.”

— Gustave Flaubert

Doing vs Owning

Via Lemire

Over 20 years ago, back when I was in high school, I went on a sailboat trip. I was so impressed that I decided to own a sailboat one day. I realized that a sailboat was expensive, and I guess I thought that owning a boat would not only be cool, it would be a symbol of my success.

How did it go? Today, not only do I now own two sailboats, I’m building a third one. Of course, they are radio-controlled boats, about 4 feet tall and 2 feet long. I find that I really like to design and build these little boats.

Did I fulfill my dream? I am sure the younger self would be unimpressed by the small boats I own, but he would be floored by the two young boys who accompany me when I test them. My dream of owning a sailboat became irrelevant. Today, in 2012, if I wanted to go on a sailboat trip, I would probably rent one. And what would matter most to me is the look on the faces of my boys.

I find that this irrelevance of my earlier dreams is a common pattern throughout my life. My younger self was dreaming about having things and being someone. He thought this would bring happiness. He was wrong.

Today, I focus on doing things. I do not own very much and I am not someone important. But I do fun things. I write this blog, I write research papers, I build boats, I publish software, I play video games with my boys… These are the things that matter.

 

Quote for the day

Talent borrows, genius steals

- Oscar Wilde

Addiction :-)

The Pleasures of Reading in an Age of Distraction: Summary

Alan Jacobs, the author of this book is an English Professor at Wheaton College, Illinois. Given his position as a professor, his students and other people often ask him, “What are the 10 best books on literature that every educated person must read", "Dear Prof, Can you suggest some books to read this summer?", This book is written to answer all such questions. So one might think this book is basically a recommendation type / instructional / didactic guide to reading. Far from it, this 150 page long essay on reading at Whim, with no fixed pattern, with only one objective in mind, "Pleasure".

The book starts off with the author noticing that many people including his son are put off by books such as, “How to Read a Book?”, “ How to Read Literature like a Professor ?” , “ The New Lifetime Reading Plan” , etc. The premise behind all these kind of books is that reading needs to be systematically carried out and there are certain books that need to be read to appreciate and become good at understanding literature. Most of these books smell of Responsibility, Obligation and Virtue, the very attributes that make people make run away from reading. So, he says, reading needs a model that works, i.e "Read at Whim". The people who look out for such "10 best books to read" recommendations actually don't really want to read a book, but want to check things off from a mental bucket list. They want to say,“Yes, now I am done with this book”. Reading at Whim means reading something that gives you pleasure,i.e there is nobody that we are signaling to , nobody that we are trying to impress.It is really out of pure enthusiasm that one reads. One usually sees this in children when you give them a book. They read it for the pure joy of it. There are tons of authors out there who feel that reading must not be frivolous, meaning, Harry Potter is not serious book, in their opinion. In fact they have this assumed checklist of books that,`Ought to be read' by a serious reader. The author states that this model is broken, and says, "Read at Whim" should be the new model.

Ok, fine. You should read at Whim, So pick up whatever you feel like reading and the one that you think will give you pleasure. Done deal. 20 pages in to the book, the author makes this abundantly clear.So, Is there any point in going over the 130 odd pages in the book ?

Well, the rest of the book is NOT reiterating this message over and over again. `Reading at Whim' is the foundation of the model that the author talks about in the book. If this were the only principle that we follow, soon we will be facing with situations as these

• Let's say you like Jane Austen novels and you get joy/pleasure reading her words. However you soon hit a limit. She wrote only six novels. So, once you read these books, you would want to go back and read these books again. But,as we all know, too many rereading squeezed into too narrow a time frame will drain the books' power and leave them forever inert on the shelves. So you face this Law of Diminishing returns when all you want to read are a few select books.
• Let's say you like Lord of Rings and really loved reading it. Soon, you might start reading books that carry stories similar to Lord of Rings.Given the amount of books published in a year, it is certain that there will be enough imitators of hits. You might get frustrated reading those books as they fail to match up to the original. You might accept them for what they are, imitators of the original and keep reading. The second behavior can be dangerous as you might start accepting plots less clever, characters less vivid, prose less dynamic and thoughts less insightful.

So, you see reading at Whim can take us only so far. In this context, the author talks about the second element of the model, i.e self-knowledge and discernment. These are crucial to develop while reading. These will help you chuck the books midway, if you think prodding through the text doesn't give you pleasure. This also makes you aware of your tastes and preferences. “ Self-knowledge and Discernment” are precisely the things that you will not develop if you tend to follow somebody else's recommendations, maintain a list of books to be read, etc.

“How to Read a Book” and similar guides offload accountability for our reading: they say, implicitly, that self-knowledge and discernment aren't needful because experts can take care of that for us. But if we reject that implicit claim, the next question that needs to be addressed is,“ How to move from `blind propensity' to `informed consent' to `Whim's sovereignty' ” ? One of the suggestions by the author is to “Read Upstream”, i.e read books that your favorite authors have read as they give a peek in to your favorite books' characters, plots and imagination. This kind of upstream reading is also useful in math. You might come across a good application of a technique, but if you read upstream you might get to read all the trials and tribulations that went behind the technique etc. For example,Baire's failure in categorizing functions helped Lebesgue in defining measurable and non-measurable functions. If you read ONLY about Lebesgue and don't look in to the development made by Baire, you are likely to miss a lot of action. Reading upstream need not be only be about historical developments behind a technique. It might be about things that make you wonder, curious about life in general. If you look at Cantor's math and read about the Cantor's life, what shaped his ideas about infinite infinities, What drove him mad, what made him die alone in an asylum, What made his story tragic but his achievements a mathematical breakthrough, you will forever look upon George Cantor in a completely different light.

The author then makes a strong case for annotating the text/ reading with a pencil. By turning our passive reading style in to an active one, the book tends to offer more than what it might seem in the beginning. There is also warning against highlighting, as Highlighters allow you very quickly and easily to mark a text, but only by covering it with a bright color; and the very quickness and easiness of the process are inimical to the kind of active reading that is needed. This point is similar to Dr.Medina's finding mentioned in his book Brain Rules. By making the initial contact about an idea/phrase/character more elaborate , it is likely that one remembers better. By reading fast we miss on the opportunity of elaborate encoding. Obviously this does not apply to every book. One should not read Harry Potter with a pencil , such books are good when the reader goes with the momentum, the less stoppages the better. This means that as a reader, the decision to annotate or go with the flow of the book is important.

Reading Slowly is the next aspect that author focuses on. Most of us read fast because of the implicit thought that “ Time is too short to read all the books”. Yes time IS short, but one crucial aspect that gets neglected by making reading . `a race' ,is, “Books become better when they are reread. Unless you annotate , read slowly, your re-read would be equivalent to a new read". Reading fast - It's like you have the content uploaded in your working memory, feel good about it, check off that item from the list, move on to the next book." Considering the short term nature of working memory, its like all the content is in RAM. Once the application shuts off, RAM is erased. If you want the stuff to get stored in long term memory, you have to read slowly, annotate and MOST IMPORTANT part is to re-read. Whenever you have the urge to read a set of blogs / books in quick succession, pause and ask yourself, “ Do you want to read' ? ” or “Do you want to have read ?”. An honest answer will keep you off the speed track.

Via a Poem from W.H.Auden, the author makes a case for `eye-on-the-object' look that is needed for getting pleasure from a book, i.e we must cultivate attention while reading. We need to be attentive of words , phrases, characters, etc. so that we can lose ourselves in the process of reading. The poem mentioned in this context is very beautiful and goes like this,

You need not see what someone is doing to know if it is his vocation.

You have only to watch his eyes; a cook mixing a sauce, a surgeon

making a primary incision, a clerk completing a bill of lading,

wear the same rapt expression, forgetting themselves in a function.

How beautiful it is, that eye-on-the-object look.

There is a section that talks about a 12th century Abbot, Hugh's advice to his monks. Even though it belongs to advice centuries ago, it is equally relevant for people whose motives for reading are far from monastic. Hugh's advice on humility is relevant to the book as it says the reader should keep in mind three aspects,

• Hold no knowledge or writing whatsoever in contempt
• Should not blush to learn from any man
• When he has attained learning himself, he not look down upon anyone else.

These lessons mean that one should not only be attentive to what one studies, but also positively disposed towards it: friendly,even affectionate.

Amidst all this discussion about reading, the author takes a radical view point , i.e Schools can never teach students to deep-read. Irrespective of which class a student is in, there is always this feeling that, ` I will be graded' lurking in his mind. So, the kind of attentiveness that is proper to school is more of `hyper attention' than `deep attention'. Look at any kids curriculum, you will amazed at the QUANTITY that is covered as a part of syllabus. With grades and the competitive pressure, Can a student deep-read ? No , says the author as reading textbooks and the like-does not require extended unbroken focus. It requires discipline not raptness.I don't agree to this point. Yes, a student probably can't deep-read all subjects but I think focusing on a few subjects and understanding them really well, might be better than knowing a bit about all the subjects. Yes, the student might fall behind on the average grade across subjects, but he will graduate from a school or a college with a better frame of mind. However looking at the way the educational system in India, I think the author might be right as LOT is taught and tested from the young minds that there is no choice but to cram.

One of the most important points that I found relevant to my reading habits is : Reread. I tend to read math /stats books a lot and I find it imperative to reread them.Well, one aspect of summarizing and posting them to a blog is that, these summaries serve as a starting point when I reread a book. The author makes a strong case for reading and I quote the author ,

If most of us read too fast, most of us also read too many books and are unwisely reluctant to return to something we think we already know. I use "think" here advisedly, because , as my examples show, a first encounter with a worthwhile book is never a complete encounter and we are usually in error to make it a final one. But those who want to have read, who are checking books off their bucket list , will find the thought of rereading even more repulsive than the thought of reading slowly and ruminatively. And yet rereading a book can often be a more significant dramatic and new experience than encountering an unfamiliar work

This visual broadly gives the structure.model explained in the book

 

Takeaway :

We usually read for information or understanding or entertainment. Dismissing all the so called expert recommendations that one receives on reading, the book has one central message , "Read at Whim". It warns the reader from making reading in to a 'have read' activity.

Quote for the day

“Unless one is happy, one cannot bestow happiness on others.
Happiness is born of Peace and can reign only when there is no disturbance.
Disturbance is due to thoughts, which arise in the mind.
When the (thinking) mind is absent there will be perfect Peace.”

--- Ramana Maharshi

Stop What You’re Doing And Read This! : Summary

The preface to this book gives a reason behind the title for this book,

This year we learnt that there are many thousands of children across Britain who cannot read competently, that there are thousands who leave primary school unable to put together basic sentences. One in three teenagers reads only two books a year, or fewer, and one in six children rarely reads books outside of the classroom. Many parents do not read stories to their children, and many homes do not have books in them. Stories and poems, for these thousands of children, are not a source of enchantment or excitement. Books are are associated with school, or worse – they are associated with acute feelings of shame and frustration.

The ten people who have contributed to this book are from very different backgrounds. Some grew up with a multitude and variety of wonderful books within their reach; some had parents who imparted to them a fierce desire for books and for learning; for others, books were hard to come by, or even illicit. But all ten are united here in a passionate belief in the distinctive and irreplaceable pleasures and powers of reading. They describe a poem as a lifeline, a compass, or literature as the holding place of human value.They each contend that books are not just for the classroom, but must be made easily available beyond it, because great books are essential to a richer quality of life. These writers know that learning to read transformed their very brains, and that literature has helped them to express their questions and ideals, and molded their imagination and sense of self. This book is a manifesto. In a year of rude awakenings to low levels of literacy and a widespread apathy towards books and reading, this book demands an interruption. Stop What You’re Doing and Read. Read these essays, because they aim to convince you to make reading part of your daily life.

In this post, I have tried listing down some of the statements/comments/questions/remarks that I have found interesting in the ten essays penned in the book.

  Zadie Smith

• I have spent a lot of time in libraries. To go somewhere to study, because you have chosen to, with no adult looking over your shoulder and only other students for support and company – this was a new experience for me.
• I came to understand why silence is necessary for serious study, and what the point of coffee is.
• You might discover how quickly an afternoon with a toddler passes in a local library, quicker than practically anywhere else. You might realize that giving up smoking or writing a novel is easier to do when you are one of a group of people all seated on some fold-up chairs in a circle. It might strike you that what you really want in life is silence. Despite the many wonders of the Internet, you might suddenly long for the smell of the old books.

 

  Blake Morrison

• The best books give us a lifeline, a reason to believe, a way to breathe more freely.
• The existence of the text is a silent existence, silent until the moment in which a reader reads it. Only when the able eye makes contact with the markings on the tablet does the text come to active life. All writing depends on the generosity of the reader.
• It takes courage to own up dark thoughts and dangerous feelings. But poetry – the most intimate yet public of forms – is the ideal place.
• Poetry is a serious business, but it isn't solemn or funereal. All it insists on is that we read carefully, with concentration. The shortening of lines is a signal to slacken our pace.
• Reading catatonically can become a way of coping with travails. To read so as to limit the power that the real world has over us.
• When you are deep into a book, it's for yourself alone, But once you've finished, if it's any good, you want to share it with others – rehearse the story, assess the characters, discus what makes the book special. Children do this instinctively, and the growth of book clubs, reading groups and blogs reflects a continuing and perhaps increasing need for adults to share books in this way.
• Don't build a canon( reading list) just for the heck of it. Read at whim and don't be intimidated by experts
• Sometimes we find places that are very comforting just like books. We tend to keep these places a secret so that it doesn't get ruined when a lot of people discover it. Books are NOT like that. We have no investment in keeping it to ourselves. Share them. The world will be the better for it.

 

 Carmen Callil

• “Live always in the best company when you read”.This my and mother I did: we read for company
• To this day, I do not move outside the house without a book; inside my house they are my paintings, my decorations, my fellow travellers and my comfort.
• Books are shields against a terror of boredom, that curse of most childhoods
• Books are like gardens; a Kindle or an iPad is like a supermarket- it makes life easier, but one doesn't want to loiter in it. You can fiddle with books. Like gardens, they can be wonderful to look at.

 

 Tim Parks

• Only the sequence of signs matter. The writing is in the sequence of the signs. This is the one thing that we can't change. The experience is the sequence. The experience is not in any one moment of perception, but in the movement through the sequence from beginning to end, at our own speed, with interruptions.At beginning of each sentence we are projected towards the end. At the end we have the momentum of the beginning. Same with the paragraph, same with the chapter, same with the whole book, may be the trilogy. The beginning requires the end, the end the beginning. We are locked into a journey.
• It's learning how to take intense pleasure in reading that makes it so useful. There are two pleasures in reading, one enchantment and second , awareness of the same. Two seemingly diverse experiences make any reading a pleasure.
• Life is simply too short to read the wrong books, or even the right books at the wrong time.
• So, this novel, which was definitely not what you were looking for, now turns out to be exactly what you needed. It has allowed you to discover something new about yourself, because you were watching your reaction as you read it.

 

  Mark Haddon

• It also occurs to me that whilst I read different books these days, my reasons for reading have changed very little. It's the thrill of being transported to another world.
• Select the right words and put them in the right order and you can run a cable in to the hearts of strangers. Strangers in China, strangers not yet born.
• Books are like people. Some look deceptively attractive from a distance, some deceptively unappealing , some are easy company, some demand hard work that isn't guaranteed to pay off. Some become friends and some stay friends for life. Some change in our absence - or perhaps it's we who change in theirs - and we meet up again only to find that we don't get along any more. Unlike people, one can at least dump them or hand them to a friend without causing offense or feeling guilt.
• I am always in search of novels that understand and articulate precisely what it feels like to be a human being.
• Lay the novel alongside film and its specialness becomes obvious. Film promises everything. Ancient Rome, dinosaurs, talking dogs, car chases, sex, Mars, vampires... Such a boundless cornucopia that we forget what it can't do. It can't do smell or taste or texture. It can't tell us what is is like to inhabit a human body. Its eyes are always open. It fails to understand the importance of the things we don't notice. It can't show those long stretches of time when we are seeing nothing at all, just drifting in our own minds.
• The sense of being inside looking out, of seeing a world that belongs to everyone, but is nevertheless yours alone. It is this uncrossable gulf between me and not-me, between my private experience and yours, which lies at the heart of being human and which no other medium can touch, and this border is where the novel lives and moves and has its being.
• Talking about reading as the cause of anything is to get things back to front. Reading is primarily a symptom. Of a healthy imagination, of our interest in this and other worlds, of our ability to be still and quiet, of our ability to dream during daylight.
• If we want more people to enjoy better books, whatever that means, we should concentrate on the things that prevent people reading. Poverty, poor literacy, library closures, feelings of cultural exclusion. Alleviate any of these problems and reading will blossom. These are real threats, not technology, not the pervasive and risking fear that readers are being tempted else where by the shallow pleasures of Britain's got talent.
• Novel is just the right words in the right order.
• Films and television programs, plays and paintings and sculptures never really become friends in the way that novels do. We can admire, we can be impressed, we can be moved and consoled, but we rarely feel that peculiarly personal attachment we feel to a loved novel, because whilst writing novels is a long and solitary business, reading them is always a collaboration, and a good writer gives the reader space and encouragement to play their part so that when we close the final page, we have had an experience that is partly of our own making.

 

  Michael Rosen

• I can't really sort out who's who, real or imaginary, and I think this is how we all read when we have time and space to think about books.
• Dickens told us about a Miss Havisham whom he created, but when many of us read about that Miss Havisham, we bring her to life with the Miss Havishams we know in our lives.
• My father's performance had given such life to the characters that their vocabulary became ours, and they could now live with us on the campsite, and , it turned out, beyond, for years after.
• Part of the power of stories is the way in which we can see facets of this or that fictional person in the people we know, and scenes from the fictional world have echoes in the events of the real world.

 

  Dr.Jane Davis

• You think of reading as an individual, even a solitary activity, one that you want to defend as such, because usually, for devoted readers, the act of reading is deeply private. I'm going to argue, though, that even highly proficient readers might want to try shared reading, which is in equal measure about books and people. It isn't just about getting non-readers in to reading; it is about building relationships out of communal meanings. Sharing a books is a multiplier, as anyone who has ever read, night after night, to a story-besotted child will know.It is about mutual recognitions, sharing of selves.
• Read the poem alone and you have your own experience and imagination to touch the poem in to life. Read it with six others and you have six lives and six imaginations with which to inhabit this flexible human-shaped space.
• Over the last 100 or so years, the loss of religious as a reputable discourse in common life has led to a poverty of language and this to a poverty of contemplative thought and feeling about what we are, and what we need. We need some inner stuff, scaffolding to help us get around our inner space, something to help us map, explore and even settle those places where we are still primitive.
• What is that part of being human which is touched by silence, which recognizes an intense atmosphere when people are moved, which gets scared or exhilarated when alone in a big space, or when faced with a newborn baby? Science may gradually work this out that is our mainstream model these days for accredited seriousness, for what we can be confident in believing. But literature- too often now dismissed or misplaced - has always known that buried part, and in thousands of ways.
• What people instinctively know, and science is beginning to understand, is that what makes people happy, above all, is a network of supportive fellow creatures, a sense of purpose, challenge and meaningful occupation. Shared reading can provide all this. Get a few people together, pick up a good book and try it.

 

  Jeanette Winterson

• There are two dominant modes of experience offered to us at present - actual( hence our appetite for reality TV, documentaries and “true-life” drama) and virtual- the Web. Sometimes these come together as in bizarre concept of Facebook : relationships without the relating. Reading offers something else; an imaginative world.
• To cross the threshold of a book is to make a journey in total time. I don't think of reading as leisure time or wasted time and especially not as downtime. The total time of a book is more like uptime than downtime, in the way that salmon swim upstream to get home.
• Reading is becoming a casualty of the surf-syndrome of the web. Reading is not skimming for information. Reader is a deeper dive. Or a high climb. Nan Shepherd talks about the exhilaration of altitude. The air is thinner. The body is lighter. But you have to acclimatize. You have to acclimatize yourself to books.
• The consequences of homogenized mass culture plus the failure of our education system and our contempt for books and art, mean that not reading cuts off the possibility of private thinking, or of a trained mind, or of a sense of self not dependent on external factors.
• A trained mind is a mind that can concentrate. Attention Deficit Disorder is not a disease; it is a consequence of not reading. Teach a child to read and keep that child reading and you will change everything. And yes, I mean everything.

 

  Nicholas Carr

• For Emerson, the best books – the “true ones” – “take rank in our life with parents and lovers and passionate experiences, so medicinal, so stringent, so revolutionary ,so authoritative”.
• Books are not only alive; they give life, or at least give it a new twist.
• The groups of nerve cells , or neurons, that are activated in the brains of readers closely mirror those involved when they perform, imagine or observe similar real-world activities
• When we open a book, it seems that we really do enter, as far as our brains are concerned, a new world – one conjured not just out of the author's words, but out of our own memories and desires – and it is our cognitive immersion in that world that gives reading its rich emotional force.
• In our day-to-day lives we are always trying to manipulate or otherwise act on our surroundings, whether it's by turning a car's steering wheel or frying an egg or clicking on a link at a website. But when we open a book our expectations and our attitudes change drastically. Because we understand that “we cannot or will not change the work of art by our actions', we are relieved of our desire to exert an influence over objects and people and hence are able to “disengage our cognitive systems for initiating actions”. that frees us to become absorbed in the imaginary world of the literary work. We read the author's words with “poetic faith”.
• It is only when we leave behind the incessant busyness of our lives in society that we open ourselves to literature's transformative emotional power.
• Although early versions of popular e-readers like the Kindle and the Nook did a pretty good job of replicating the tranquility of a simple page of text, it now seems likely that the page's calm, and the immersive reading it encourages, will be broken as a book's words are made to compete for a reader's attention with a welter of on-screen tools, messaging systems and other eye-catching diversions. The very form of a book seems fated to change as the written word shifts to a new means of production and distribution.
• Reading is more than visual decoding of alphabetic symbols. It is a state of mind, a dream of life, and a book, if it is going to be a true book, needs to be more than a container of words; it needs to be shield against busyness, a transport to elsewhere. Stevens put it simply:”The house was quiet because it had to be”.

  Dr. Maryanne Wolf

Dr.Maryanne Wolf and Dr. Mirit Barzillai ask a set of questions that probe in to the “future of reading”. With the onslaught of information overload, increasing distractions ( twitter, instant messaging, etc.) there are many possible ways the “the reading brain” is going to shape up in the future; “shape up” is the word used as we are never born to read or write anything. Unlike vision or language, reading has no generic program that unfolds to create an ideal form of itself. Rather, learning to read lies outside the original repertoire of the human brain's functions and requires a whole new circuit to be built afresh with each new reader. The brain changes itself by building a versatile “reading circuit” out of a rearrangement of its original structures, such as visual, conceptual and language areas. In the last essay , the authors ask a lot of questions in this context,“How will the next generation of kids build a 'reading circuit' ”. Will the twitters/IM make the brain circuitry devoid of 'deep-reading' and instead build something completely new that is equipped to handle the kind of info overload that we are seeing ?

• We may already have within our grasp the tools to conceptualize that the “new readers” of the twenty-first century need: a differently evolving reading circuit, one that connects the existing expert deep-reading skills to the evolving information-processing skills in order to be able to use the resources of the twenty-first century external platforms of knowledge wisely and well. The task is to figure out how to get there. We will need many minds to plot this progression.

 Takeaway:

The book is a nice collection of essays about “reading” by ten authors ; all of the essays have one common theme – Make time to deep-read in your busy schedule.

Quote for the day

“Life is too short for a bad book or the right book at the wrong time.”

--- Tim Parks

 

Quote for the day

I'm astounded by people who want to 'know' the universe when it's hard enough to find your way around Chinatown.

-- Woody Allen

 

Quote for the day

The problem is that coding isn’t fun if all you can do is call things out of a library, if you can’t write the library yourself.  If the job of coding is just to be finding the right combination of parameters, that does fairly obvious things, then who’d want to go into that as a career ?

- Peter Siebel( Coders at Work )

How I became a Quant : Summary

The purpose of this post is to summarize the various stories mentioned in this book. This write up is a result of a marathon writing on this weekend. Actually it took more time to write than read the entire book!. In the process of summarizing, I have tried listing down some of the statements/remarks/suggestions(under the heading, learning's) made by these quants that are worth pondering upon.

David Leinweber

David Leinweber graduates from MIT and Harvard with a bachelors and PhD respectively. He lands up at RAND corporation to work on AI. After working many years on classified stuff, he moves to LISP machines Inc. Once the market turned harsh towards hardware firms, David moved to Inference Corporation, a software-only AI firm where he starts working on AI applied to finance. LISP, with its garbage collection mechanism is not really suited to real time financial trading applications. So, David goes on to start his own firm, Integrated Analytics where AI is used for stock picking. He launches, Market Mind, an AI based tool for equity trading. Soon after this startup success, he joins First Quadrant, a Quantitative investment management firm where his group starts managing $6 Billion. After First Quadrant, he starts another firm Codexa which doesn't take off. Subsequently he lands up as a faculty at Berkley.

Learning's:

• Markets are not instantaneously and perfectly efficient. Insights, and the ability to execute them rapidly in ever-faster electronic markets, will continue to be rewarded.
• There are secretive firms that consistently show up on lists of the highest-volume traders reported by the exchanges. Founders of these firms show up on lists of billionaires. Are they just the lucky typing monkeys? Are they the investment equivalent of the lady in Jersey who won the lottery three times? Probably not. They make too many separate bets, thousands every day. And they do too well, too consistently. To attribute their success purely to chance strains credulity.
• Stocks are stories, Bonds are mathematics
• The PhD quants think the technicians are essentially examining tea leaves and goat entrails. The technicians think that PhDs are hopeless geeks who wouldn't know a good trade if they sat next to it on a bus.

Ronald N Kahn

This story is about the quant Ronald N . Kahn who is generally known amongst practitioners through his popular book, Active Portfolio Management. Kahn graduates from Harvard with a PhD and joins BARRA in 1970s , a firm that was revolutionizing the area of finance at that time. Kahn learns every thing about finance and quantitative applications to finance from BARRA. It was an ideal play ground for an academic as the team mostly comprised PhDs who walked away from their own field and came to finance. One of the leaders at the firm, Richard Grinold offers Kahn to sit through his course at Berkley. Soon, they start collaborating on many projects and one of their outputs is the book on active portfolio management. After doing tons of quant work at BARRA, Kahn joins BGI, following his boss steps. His experience at BGI managing money turned out to be an equally a rewarding experience. So, in one sense Ronald N. Kahn followed the ideal path for a quant, i.e , do research for a couple of years and apply quant techniques in managing money.

Learning's:

• Undergraduates learned from their professors. But the role of a graduate student is to teach their advisor new things. I wonder if such a thing should be applied to our usual work place reviews. Imagine that a yearly review is based on, not only the contributions that XYZ makes to the firm, but also on what his/her colleagues learn from him/her over the past one year. Imagine there was strong incentive system in firms to impart skills/knowledge to coworkers. Indeed such a place would be great place to work.
• Important communication should always be in writing and limited to one page
• Success in finance would require one to acquire much more intuition and insight into the basic problems faced by investors and to build up a toolkit for analyzing those problems.
• My approach to quant finance was very different from what a formal education in this area would involve. Basically, I tried to master specific areasâlike interest rate optionsâand then branch out and master new areas, through new projects. It was a patchwork quilt approach. I hoped I could build enough sufficiently large patches that they would eventually form a substantial quilt.
• Is quant revolution over ?. Certainly much of the relevant theoretical underpinnings are in place. At the same time, there exist even today significant issues in need of rigorous quantitative analysis. Present-day debates over liability-driven investing prove that fundamental issues remain unresolved among investment professionals Other areas worthy of further research include hedge funds and, more generally, optimal leverage and shorting. Between these remaining fundamental issues and the never-ending competition amongst active managers for out performance, the need for quants has never been greater. There is plenty more to do in this challenging, interesting, and rewarding field.

Gregg E. Berman

This is the story of a quant who doesn't want to be called a quant. Quant is sometimes used pejoratively on Wall Street as in, `He is ONLY a quant'. After graduating from Princeton with a PhD , Berman realized that he was not cut out for academics. His first few jobs were at hedge funds where he wrote automated trading strategies for commodity futures and trades those strategies.In the first few years he was so fascinated by coding that he programmed even on 2 hour train daily commute. The years at hedge fund helped him understand markets, psychology of trading, the type of statistics that can be used, etc\dots He traded futures for a couple of years and did not particularly enjoy it during a bear market phase. He felt that trading was an activity where luck played a significant role in the success and his academic bent of mind, where hard work and smartness fetch results, was not accepting the vagaries of trading. He remarks,

I also found that that I had less of a stomach for the huge ups-and-downs of trading than I had previously believed. This was a hard lesson for me to acknowledge. After all, many people claim that if they just had some money to start with they could use it to make a fortune. Well, I had millions in potential capital at my discretion and was asked to do just that. But I couldn't. I very much wanted to, but I just couldn't come up with any systems or strategies that would make fortune in the commodities markets. The more I wracked my brain, the more I realized I liked the detailed analytical parts of my job much more than the trading parts

The big change in the career came when he moved to RiskMetrics and did a lot of quant work at JPMorgan. At JPMorgan he donned quit a few hats and became a true quant in Wall Streetish sense. The big takeaway from Berman's story is that quant is not a job but an attitude that one must develop, to do well in finance, and more so in today's tech driven finance.

Evan Schulman

This is the story of a quant, Evan Schulman, whose belief in efficient markets got strengthened in his initial years of work at a trust company analyzing pension accounts. After developing quant tools that helped portfolio managers focus on their stock selection , he came to believe that quantitative skills can improve trade processes, if not generate alpha. He subsequently joined Keystone group at Boston to develop quant stuff like `Implementation shortfall 'models.

After his stint at Keystone, he moved to Batterymarch and that was a key step in his career. At Batterymarch, the entire firm was working hard to lower commissions and to keep the market impact of trades to a minimum.Schulman executed the first program trade while at Keystone Funds. Lot of people on the Street know Schulman because of this first program trade thing. He not only helped computerize the firm-front, middle and back office-but also introduced an innovative trading system at Batterymarch. Schulman let brokers access its orders via computer to trade. He left Batterymarch to start Lattice Trading, a firm that offered an electronic trading product that was a forerunner to today's algorithmic trading.

What was Lattice core idea ? It was multi-broker system to allow for the fact that institutions tended to use several brokers in the conduct of business. Lattice became very popular and was bought by State Street. Evan then left to start another firm , Upstream technologies in 1999.In his earlier firm, the work was mostly for the institutional side. At Upstream, he and his co-founder Mark Hoffman decided to apply the tools, discipline, quality control to individual accounts, even the small ones. Upstream uses quant stuff to work on individually managed accounts that dominate mutual funds. As Evan remarks

Optimization is ideal for the accounts of individuals.

Today, Upstream technologies is a success story on Wall Street.

Learning's:

• A quant who believes in efficient markets can still add tremendous value to improving the investment process itself, be it on the institutional side or the retail side.
• Compound returns equal a function of the average return less half the variance. Meaning, the longer the time horizon, the greater the difference between arithmetic return and geometric return on investment
• Not all problems can be solved by throwing more bodies in to a mix. The performance and productivity of quants varies a lot. Sometimes just one or two quants can bring in radical changes to the business. I am reminded of Dragan Skoko and his tremendous contribution to the success of Batterymarch

Leslie Rahl

Leslie Rahl graduates from MIT in 1972 with a degree in Electrical engineering and realizes that she has no aptitude for circuit boards, electricity, or the mechanical facets of electrical engineer's trade. In a totally random combination of events, she lands up in Citi and spends 19 years doing trading and risk management. Starting from a job of trading options for a prop book, she starts handling interest rate trading book and eventually swap business. In 1994, she leaves Citi to start her own company, Capital Markets Risk Advisors and since then has grown her company to a decent size on Wall Street.

Her belief is that models are useful for trading and not valuation. This comes from a quant who has traded for 19 odd years , so there could be a bias in her statement. What surprises me is that she starts a risk management company where you are typically valuing something under extreme events. So, how is that she has spent the last 15 years on something she doesn't believe. Anyways, when asked how she became a quant ? , she replies ,`I was born a quant' and adds that being a quant helped her not only with solving quantitative problems, but has taught her an analytic framework for problem solving that applied equally well to non quantitative problems.

Learning's:

• It is better to run your own business / work for a smaller company/ startup than working in a big firm . When you count everything, Positives outnumber the negatives .

Thomas C. Wilson

Thomas Wilson, a graduate from Berkley and Stanford is not sure whether he would consider himself a quant or not. He believes in `asking the right question' as being crucially important than any mathematical technique. You ask the right question and then go about looking/ creating/developing/copying the mathematical techniques to solve the question. He remarks

I put on the other end of the continuum individuals whose contributions were driven more by âtheâ question, or the intuitive interpretation of the observed economic and financial phenomena, rather than by the quantitative techniques that were used to represent their intuition. For individuals at this end of the spectrum, phrasing the question seemed more important than the techniques used to find the answer. In this camp, I put such individuals as Akerlof, Stiglitz, Lucas, Diamond, and Dybvig, individuals whom I judge to have contributed more through the intuition behind the question then the actual quantitative techniques they used.Who can argue that the intuition and insights behind Akerlof âs market for lemons outshadows the relative simplicity of the algebra usedf to prove the point?

He is extremely honest in confessing that he has lesser mathematical expertise than the quants who get cited in finance papers, media. In his career, he has stumbled on three questions and has learnt/developed mathematical tools to answer the questions. In this book, Thomas Wilson lists some of the most important questions he has answered in his career.

Market Risk Era ( Early 1990's)

• Is it possible to calculate VaR for nonlinear portfolios from local risk information \verb#(e.g., deltas and gammas)#, which are readily available on the trading floor?
• How many independent factors are practically required to capture the risk of a multicurrency fixed income trading book?
• What happens to the tails of our VaR calculations if we have only estimates of volatilities and correlations and not their exact values?

Credit Risk Era ( Late 1990's)

• Do equity markets alone provide sufficient information to characterize the contemporaneous correlations between average sector default rates and migrations?
• How useful are other factors such as the level of real economic behavior as measured by GDP, interest rates as a surrogate for debt coverage, or foreign exchange rates for sectors with international competitors in explaining sector defaults and their correlations?
• Do equity markets, which react instantaneously to new information, effectively describe the autocorrelated time series properties of credit cycles?
• How can retail portfolios and large corporate exposures be integrated into the same portfolio model consistently?
• How can default only portfolio models be expanded to a mark-to-market approach comparable to market VaR?

Strategy Debate ( Late 1990's to Today)

• What are the inherent theoretical biases, and is it possible to make adjustments to correct for the biases?
• What is the appropriate cost of capital, by line of business, if capital is allocated based on the standalone risk of each underlying business? And, what role does earnings volatility play in the valuation of a bank or insurance company?

Learning's:

• Build your intuition before building your model
• Trust your intuition
• Challenge your intuition
• Be as good at your communication as you are at the theory
• The model is always wring - but that doesn't make it useless.

Neil Chriss

This is the story of Neil Chriss, known for this book `Black Scholes and beyond'. Neill Chriss received his PhD from Chicago University. In the initial few pages of this story, he gives a few reasons for leaving academia, especially leaving pure math for industry. He compares pure academic mathematicians to Explorers whereas applied mathematicians/practitioners to Mountain Climbers. Explorers take risk with out any guarantee that it will pay off. Mountain Climbers have a fixed goal, i.e the top of a mountain and thus spend their time getting there. Explorers have a different personality than Mountain Climbers, though in one's life it is very difficult to sometimes clearly demarcate one from another. In the case of Neil Chriss, he clearly says that he did not have that `passionate,ever thinking,every imagining' mathematical interest.

After his PhD from Chicago, he moves to University of Toronto to join the math department. Here he develops an interest in derivatives and writes a paper on `Option Pricing formula with volume as variable'. This paper gives way to interactions with Goldman team, mainly Derman and Kani from Quantitative Strategies group. He then ends up doing a summer job at Goldman and then receives a post doc at Harvard. However Wall Street appears more exciting to him and he lthus eaves Harvard for a job at Morgan Stanley. At Morgan Stanley, he starts collaborating with leading quants like Robert Almgren,Peter Muller etc.He finally moves to GSAM( Goldman Sachs Asset Managment) and starts managing money for the firm. He also becomes NYU Courant's math fin program director. This unique place offers him to meet many more quants like Jim Gatheral, Steve Allen, Peter Fraenkel, Nassim Taleb etc.

He ends his story with a prediction about the usage of quantitative techniques in finance. This book was written before the crash of 2008. So , the tone of the author is overtly optimistic in one sense where he predicts that quantitative asset management will dramatically change asset management business. Well, one might take that statement with a pinch of salt , after the massive beating that most of hedge funds took , in the past few years. Over all , I found the story of Neil Chriss very interesting as he has managed to do things in academia as well as Wall Street, despite declaring himself as a mountain climber. Well, he seemed to have climbed a lot of mountains to make up for not taking up a explorer's job

Learning's:

• You have to deeply care about math to become a full time mathematician( Explorer)
• Came to know of this book titled,`The Glass bead game'. Should read it someday
• You have to enjoy working with computers to become a productive quant
• Neil Chriss learnt probability , stochastic processes from scratch after joining as a faculty in math. Its never too late to learn stuff in one's life .You just have to have the right attitude.
• Take regular feedback of your work from other people
• Historically mathematicians had more interaction with the real world. Hence there is nothing to be embarrassed about leaving academics to pursue work in industry.
• Having a strong background in technology , having had the experience of writing tens of thousands of lines of code, was an advantage. To do anything largescale in quantitative finance requires good technology. Everything from the storage and retrieval of trade data to the execution of trades increasingly relies on technology that is efficient and reliable. Knowing how to build systems that work well now and can be maintained and grown is an important asset because as a business grows in complexity, the technology that drives it has to grow with it. It is all too easy to build a small system that works well but find that as it grows it grows out of control in complexity and becomes difficult to manage.

Peter Carr

After pursuing an undergraduate degree in accounting and economics from University of Toronto, Peter Carr heads to UCLA for a Phd in Finance and then follows it up with a Postdoc at Princeton.He mentions that his choice of UCLA was particularly helpful as it gave him time to pick up math and make up for his lack of formal training in mathematics.Obviously what he means by lack of enough math skills, is a relative statement. His time at Princeton proved important. His meeting with Dilip Madan changes his course of life and he heads to Wall Street and spends a successful quant career at Morgan Stanley, Bank of America and Bloomberg.His remarks about quants and quant career in general , are particularly encouraging. He remarks

Learning's:

• Although many academics think otherwise, mathematical finance is in its infancy with lots of low-hanging fruit to savor. If you want to be a quant, my advice is to see it as a calling, not a job. The money is incidental. It comes and goes. A good idea never goes away and if you are lucky, you’ll have a few before we all fade away into obscurity.
• Academics use English words to describe mathematical concepts and that one should never confuse the everyday meaning with its mathematical definition.
• Read and work voraciously to make up for a lack of formal training. Sometimes you end up doing a better job than people who are trained formally.

Mark Anson

With a PhD from Columbia University , Mark Anson proceeds to law school and then begins his career. While practicing law he realizes that his first love was always direct application of quantitative techniques and gets back to doing a quant role. One of his remarks he makes in this book, that needs to be kept in mind I guess by any aspiring quant is,

Quantitative skills are like a foreign language.The more you use the skills, the more honed they become. Conversely,failure to apply the skills on a regular basis leads to a slow dissipation

It is often that we learn some skill set/techniques in school or in a specific project and , we then move on. It is like storing something in the working memory and deleting it. Unless specific skills are put to repeated use in one form or the other, quants run a risk of losing them.

Mark Anson sees the uncertainty in the markets as a good breeding ground for sophisticated, innovative quant solutions. In the US context, he mentions that quant skills need to applied to avert the pension crisis, that will be a certainty by 2050, if nothings done in a proactive way.

Learning's:

• Be less concerned with dazzling audiences with quantitative skills or technical jargon and more concerned with understanding the empirical relationship between economic variables
• Math is a tool to apply to financial markets. You have decide whether you have to make it blunt or refined, based on the context, problem, etc.
• Traditional fundamental research will be less important in the future because the goal will not be to find undervalued stocks or bonds, but instead, to focus on financial outcomes.
• Love to embrace uncertainty as that is the reason quants are employed in the first place.

Bjorn Flesaker

Bjorn Flaseker starts off his quant story with a reference to Garbage Can Model and its relevance in a sell-side derivatives quant group. He remarks

I have personally found the Garbage Can Model to provide a useful framework for understanding and interpreting the behavior of organizations where I have worked, including, but not limited to, the importance of solutions looking for a problem, the importance of decision making opportunities, and the significant degree of randomness in actual choices made.

After doing Bachelors at Norway, he is told by his faculty members that he should look to do a PhD.Subsequently Flaseker joins UCLA for a PhD in finance. A chance attendance of a seminar on HJM model gives him a problem to work on , as a part of PhD thesis and so begins his quant journey. In his 5 years at Berkley, he meets a lot of other quant researchers (including his future wife).He subsequently moves to Illinois at Urbana-Champaign to take up a faculty job. During his stay at Urbana-Champaign, he works on various derivative models, early exercise models etc. In 1992, he gets a chance to present his work at Merill and subsequently is offered a job. His quant career begins at Merill and takes off.

Learning's:

• Collaboration matters. People matter in quant work (unlike the popular perception that quant is some lonely creature working on some arcane models)
• Revisit basics from time to time
• Make a business impact with your model from time to time. It need not be some sophisticated out of the world model. A straight forward model that solves a business problem is better than complicated pie-in-the-sky model.
• You never know when a model will become useful . In this context, the binomial trees that Flaseker worked on in the university was immensely helpful in making the first contribution at Merill

Peter Jäckel

Peter Jackel graduates with a PhD from Oxford, then ends up in a post-doc role at which point of time , he realizes that he had enough of short-term employment phase( post-doc). Typically as the post-doc position nears, one writes proposals for research grants, or looks for another post-doc position in some other university. Peter Jackel instead opts out of this race and looks out for a job in the industry. At the time of applying for these jobs, he claims that he had no knowledge of stochastic calculus, derivatives ,market knowledge etc. After a few interviews at various places, he lands up a job at Nikko securities where he is taken in as a model validation quant. He gets lucky here as he gets to meet Bruno Dupire and thus his real learning begins. In a matter of weeks, he learns about finite differencing solvers, forward Kolmogorov equations, Monte Carlo simulation techniques, and general derivatives replication theory..all the techniques that is today offered as a part of 18 to 24 month MFE program!. It is truly amazing that he learnt all of this in just a few weeks time.

Then after 17 months, Nikki securities goes through a major restructuring and he loses his job. This turned out to be another fortunate random event, as lands up in NatWest where he gets to meet Riccardo Rebanato. He learns a ton of stuff from him and implements a whole lot of model validation code. It is during this phase of life that he starts thinking about a proposal from John Wiley and sons , that he write a book on MonteCarlo methods. Well, as it turns out he was not all that interested in it except that he wanted to dispel one myth that was prevalent amongst every one using monte carlo methods, i.e Sobol numbers. There was a opinion that was taken for granted that Sobol numbers are suitable only for low dimensional problems. However Peter Jackel found that he could easily scale the dimensionality problem by using suitable initial conditions . Sobol numbers were perfect for his back testing and this lead him to write a book on MonteCarlo, that is now the staple diet of any MFE program.

After another rejig of teams at NatWest, Peter Jackel is moved to front desk where he is a part of team which builds a structured product quant library from scratch. His 3.5 years of work of coding the library taught him many more things from an implementation perspective. This is kind of reminder to any quant who doesn't want to program. The real learning of quant fin comes from programming, is the biggest takeaway from this story.

Learning's:

• Build your models transparently and to the highest standards so that you don't have to be afraid to be open about them; and bear in mind that you don't own the models you build for the company you work for- in fact, as quants, we own nothing, not even the paper we write on. We deliver a service to our employers. The company may have to share part of what we develop with other teams in the company and is at liberty to do so. The company may be obliged to share what we are doing with regulators. Always be aware that what we develop and implement may be subject to scrutiny.
• Anyone who wants to make it as a quant to spend some time in a model validation group: you get a lot more time to dedicate to analysis and learning than in the front office where there is a constant and relentless pressure for delivery of directly usable analytics
• Collaboration matters a lot in quant work
• Get the right balance between a general and a bespoke approach for any individual project
• Every thing you do as a quant is cumulative. No piece of code that you write is trivial. It will be used in some future work of yours. This also means that you should not be sloppy in your coding . Doing proper documentation matters. Following the right design pattern matters.
• Coding something from ground up is a wonderful experience and one must never hesitate to take up such a job, despite the risks that it might entail.

Andrew Davidson

This story of Andrew Davidson, is filled with the theme, `I am not a quant' in almost every other sentence that he writes. Having an undergraduate education from Harvard and MBA from Chicago, Andrew Davidson's first job was Exxon. The bureaucracy got to him and he left the firm to work at Merill and finally started his own company Andrew Davidson\& Co. The story is about Andrew's skepticism about

models used in the mortgage industry. He cites specific instances where disregarding theory sometimes better. He points at a number of places where he does not possess the skills of a true quant and infact revels in the fact that it is not needed to survive and make a successful quant career

Learning's:

• How traders and other participants describe the operation of the market, and how it truly operates, are two different things.
• A clear conceptual picture often is better solution than a mathematical model that misses a key component

Andrew B. Weisman

After graduating from Columbia with a PhD, Andrew B Weisman's takes up a consulting job with Lehmann where he immediately realizes the big gap between theory and practice.

In this book he remarks

I had my first epiphany as a quant researcher; it consisted of the fundamental realization that most of the trading that occurs on an interbank trading desk takes place on a timescale that, for the most part, defies fundamental economic analysis.In truth, longer-term market convictions based on well-structured,defensible analysis are apt to get in the way. Such speculative activity is more akin to playing Pong.1 It is primarily a reflexive activity,with the trader operating under no imperative to distinguish Margaret Thatcher from Terry Hatcher. In many cases, doing so would have been a tall order.

There is one statement that he makes which left me little surprised. Andrew remarks

The market tends to place a significant premium on complexity. Basically, one should never explain a simple concept or procedure in simple terms, or it will be robbed of its marketability. Keep the curtain firmly in place and crank the devil out of your thunder machine

Why have a curtain? Why should one not be transparent about the model ? Somehow makes me feel little uncomfortable as the above statement asks you to remain secret about your model. As long as the strategy is making money, shouldn't it be good enough to market it to clients ?

Learning's:

• Mean Variance Optimization in its plain form is dangerous and should not be used for portfolio allocation
• VaR is an ordinal measure and not a cardinal measure. It is easy to confuse between the two and sleep in peace until one day when the portfolio evaporates. Much like the thanksgiving turkey mentioned by Taleb, which until the day of its death feels good about the fact that it is being fed healthy food on a regular basis.

Clifford S. Asness

At the outset, Clifford Asness , says `Luck' has played a significant role in his success. After graduating with a PhD from Chicago, he joins GSAM and starts

working on building portfolio models as well as manging money. With in a few years with 4 models, his group starts managing $7 billion. Humbly, he attributes the good chunk of initial success at GSAM to luck. Subsequently he leaves GSAM to start AQR with a $1 Billion. The first two months of his startup are some of the worst times for the fund. The billion dollar fund loses 60% and has a huge drawdown. Subsequently Asness reins in the risk exposure of the fund and makes it a sustainable venture during the troublesome times. Rest is history. Today AQR is a huge success story with assets close to $40 Billion. In this book, Asness dispels a lot of myths surrounding quants such as

• Quants are data miners
• Quants use blackboxes
• LTCM's blowup shows the limit of Quantitative investing
• Quants are driving with rear-view mirror

Learning's:

• Being in industry, managing money does not mean, you don't publish stuff. Keep publishing articles / opinions / models regularly.
• Never be afraid to call a bluff a bluff.

Stephen Kealhofer

This is the story of a quant and an entrepreneur. Like other stories mentioned in this book, there are random events that shape this quant's story. Stephen Kealhofer's story starts off with a decision to move to Berkley as a faculty where he starts working on `default probability' models. The second significant event that happens in his life is a consulting assignment that involved developing a statistical rating model that Oldrich Vasicek had developed. This project helped him in getting in a good understanding of the practical difficulties of implementing models.The third significant event happens when he is consulted for analyzing Junk bond cases. This assignment resulted in creating a good database with variables that could be used to estimate the empirical default probabilities. The fourth significant event was meeting Mac McQuown who became the co-founder of Stephen's startup , KMV corporation. The other co-founder was the legendary Vasicek himself.

There is sometimes a myth that quants are these nerdy people who work with formulas and not good business people. Vasicek is a brilliant counter case for such a notion. Vasicek's model is something that any quant learns in his 101 course. The fact that the team was instrumental in building a company like KMV that ultimately got sold off to Moody's speaks volumes about the success quants can have in entrepreneurial ventures. Nowadays with most PhDs directly going in to quantitative money management, we might see many more quentrepreneurs . I loved this story because it actually talks about the hardships a quant startup goes through in explaining the work they do to , to established institutions and adding practical value to the business.

The fact that the trio built a company based on a model is something that any quant can take inspiration from and remind himself from time to time, that ,”One has to integrate whatever quantish stuff that he/she does with the business problem”. Pie-in-the-sky work is good but one should also focus on doing quant that is relevant to the business.

Learning's:

• Always keep in mind that model /quant work has to deliver business improvement / business value. One cannot divorce the modeling aspects of the problem from the nature of data available , nor from the business context the model would be used
• Even if you are not completely certain about it, take a position and start exploring the position. It is similar to "having a map is better than no map" situation where having a map will motivate people to explore.
• Finance is a beautiful field. It touches everything, so it is a license to explore the world
• There is more data in finance than any field I can think of. One of the many great things about markets is that they generate large amounts of high-quality data about the actions of people.
• Finance is a beautiful field. It touches everything, so it is a license to explore the world
• The path from data analysis to the implementation of business ideas is incredibly fast. In biotechnology, it is measured in decades; in finance we do it in months or even weeks.
• If you can deduce something useful, you get paid.

Julian Shaw

I found the story of Julian Shaw as one of the best quant stories in the book.

After completing a PhD from University of Toronto, Julian Shaw loses interest in pure mathematics. He takes up job at Gordon capital as he needed a better job than teaching math or computer science in his university. He has a very unique experience at Gordon capital which was populated by market makers, option traders, basically risk takers. Nobody was interested in quant stuff like risk management. Julian Shaw applies his quant skills and brings to the attention of the management of a trader using wrong vol estimates to price and subsequently trade. His work is not so well received in the beginning. However when the trader loses his money, then people start taking notice of him. But Julian Shaw sadly remarks , `Risk management's role should come before the trade goes haywire and not after'. In any case, Gordon Capital blows up and he moves CBIC, another firm where nobody wanted to listen to quant saying the positions carry a huge risk. So, Shaw leaves CBIC very quickly and through a random head-hunter call, lands up at Barclays. He then writes about a few war stories at Barclay that make an interesting read.

Learning's:

• Finance is more than just pricing models and arbitrage, more than picking up dimes in front of steamrollers and sweeping up golden crumbs. Finance is concerned with the way people organize production and distribution, which is a prerequisite for human welfare.
• The hardest part of quantitative analysis is framing the problem in the first place.Many quants aren't good at this, partly because they don't think it's their job. They want the PDE or whatever to be served up to them on a plate. Solving PDEs is a useful skill, but there is a lot of good software to do that. There is no good software for identifying options embedded in deals defined by verbose legal documents
• Most of JP Morgan quants have ditched complex multivariate stuff to simple historical simulation to capture VaR. This makes it easy to communicate to the trader. However there is an entire debate about whether VaR is good absolute measure of risk at all. Consensus is that it is merely a relative measure
• A crude but transparent risk system is more effective in practice than a sophisticated but opaque system!
• The quantitative firepower applied to problems in finance is inversely proportional to the amount of money at stake.
• Many quants from the physical sciences are too lazy or arrogant to learn some econometrics
• Unlearn two attitudes to become a good quant.
  • The first attitude is that specialization is good. Bad quants pretend they are still physicists or mathematicians or whatever; they can't be bothered learning new tricks from other disciplines, and they never learn much finance. 'If all you've got is a hammer everything looks like a nail.'
  • The second attitude to unlearn is the assumption that the failure of people to understand what you are saying proves how smart you are. In academia, one only cares what the other specialists in one's own field think. By contrast, in a financial institution nothing you do counts for anything unless you can convince the (usually) intelligent but nonmathematical people in charge to do something different from what they would have done otherwise. Despite Poincare's famous maxim that one doesn't really understand a mathematical theorem until one can explain it to the first person one meets on the street, most mathematicians can't even explain their theorems to other mathematicians! And they are proud of it!
• Quantitative finance is a craft and a trade. It is barely engineering, and it is certainly not a science. Good quantitative finance can be summed up as the art of leaving things out, plus the art of selecting the right tools.
• The test of a model is its ability to hedge a real portfolio in the markets
• One can't be an expert at everything but one does need to understand the essence of a wide range of mathematical and statistical techniques. It is rare that one needs to invent completely new techniques; usually you can find a problem with the same mathematical form, often in an apparently unrelated discipline. The art of the quant is to find appropriate tools and bolt them together to create an effective solution to the problem at hand.
• If you want to be more than a technician, you will have to learn some finance; finance is not a corollary (trivial or otherwise) of any mathematical science.
• Interview Tip : think up one money-making idea and be prepared to defend it. This will generate a lot more interest at your interview than the Malliavin calculus!
• Go through Peter Carr's FAQ's in Option Pricing Theory to see where you stand as far as understanding options theory is concerned.
• if you want to make your mark, find a really big financial problem and create a quantitative framework for dealing with it. You will need some imagination.

Steve Allen

After graduating from Columbia and NYU Courant, Steve Allen joins Chase Manhattan bank to work in their operations research department.Till then he had never worked with computers and so he taught himself languages needed for the job.The first year at Chase was frustrating for his team as there was a distinct lack of management interest in their quantitative skills. Despite the obvious discontentment in the environment, Steve Allen stuck to his job and started utilizing the time effectively. He learnt to code, take up special classes in the evenings to learn bond mathematics , interact with traders to suggest tweaks in their existing formulas, etc. Basically he kept his mind active.

Soon, things started changing at Chase when a new management comes in that is more interested in quantitative techniques.Steve then gets to use MonteCarlo simulations etc not for their finance department but to improve their operations. After spending quite a number of years in Operation research, he moves on to building an analytic and modeling support for the firm's traders and this he does it for 10 years. He self-learns differential equations, option theory and a lot of math that he never had a chance to learn. These 10 years proved to be extremely useful in Steve's career as he developed modeling + reporting skills that became valuable to Chase traders. These 10 years of effort(it reminds me of Malcom Gladwell's observation of the time to become an outlier) helped him in launching a successful risk management career.

Steve Allen's attributes his success to the environment as he says that it was environment that changed where quantitative techniques became more prominent in the area of trading and risk management. After a successful 35 year stint in the industry, Steve Allen became the program director for MFE at NYU courant. Does he think the field has become matured and there is no opportunity to be creative ? . He quips

If you want to have a good career, you had better find a way to be creative; it's unlikely that your personality will be charming enough to induce an employer to pay you well for routine performance. But I add that creativity takes many forms- it consists not just of finding some new mathematical solution but also of discovering new ways to communicate results and build consensus.

Learning's:

• Keep learning . Steve Allen's attitude can be inferred from this remark `I enjoyed an advantage in having to struggle to come up the curve mathematically. It put me in a good position to figure out how to educate others who were finding the new concepts difficult.'
• Always have a vague sense of outcome so that you don't become too theoretical, to the point that you miss the fact that you are modeling in finance-a social science.
• Crunching numbers is a good thing and it is better to show results to traders than talk about some arcane mathematical concept that they would be least likely to be interested in.

Mark Kritzman

Mark Kritzman graduates with a degree in economics and joins investment advisory department that managed asset allocation of pension fund clients. Here he comes across mean variance optimization technique that appeals to him as a method for asset allocation. He then gets an MBA from NYU to sharpen his quant skills. Post this,he moves on to the investment department of AT&T. This was a great place for Mark as he could interact with top notch people in the research team of AT&T. He moves to Banker's trust and then eventually starts his own firm.As of the book's publication, his firm Windham Capital Management , managed $30B of assets. He cites three main things that helped him develop quant skills.

1. First is AT&T research team where his one-one conversations / discussions with Bill Sharpe, Harry Markowitz, Bob Merton, Steve Ross, Jack Treynor, and Fischer Black helped him immensely in developing financial intuition.
2. Starting up a new firm gave him a ton of learnings as he had develop many applications himself
3. Contributing editor for Financial Analyst Journal role helped him get better at communicating difficult concepts in easy terms , devoid of jargon and symbolism.

Mark gives a list of problems that he solved in his quant career. The readings gives an idea of the kind of problems that one need to tackle in the industry to make a mark.

Learning's:

• Mathematical proficiency will not be sufficient to guarantee a successful career as a quant, especially as these skills become more commoditized. The successful quant should combine mathematical proficiency with an appreciation for economic and financial theory, and he or she must know which questions are really important

 

Bruce I. Jacobs and Kenneth N. Levy

This is a unique story of 2 quants who are managing billion dollar funds. These funds have close to 83 accounts totaling $9B as of 2010. If you read this story it does not sound like as you are reading the story of businessmen. If you ingore the fact that they are managing money, the activities the two quants mention in the book could as well be of 2 social scientists in a research lab.

Bruce gets a PhD from Wharton and ends up as a faculty at Wharton. He meets Ken while Ken is doing his doctoral education at Wharton. During 1970s , almost everyone in academia believed in `Efficient market hypothesis' and so Bruce ends up choosing PhD topic on the same. Bruce gets a little let down by the ivory tower thinking at academia and joins industry. He joins Prudential where he meets Ken again and this random event changes both their lives forever. Neither of them believed in Efficient market hypothesis and soon they started Jacobs Levy Equity Management in 1986. At one point in time before the crash of 2008, they were managing $20B. That's quite an achievement. From 0 to $20B in 24 years with focus on quant research is amazing. Their investment approach was based on market complexity. Their focus on Kaizen approach to quant can be inferred from their remark

Once modeled, return-predictor relationships are likely to change over time. The world is constantly evolving, and old inefficiencies can disappear, giving way to new ones. Merely tilting a portfolio toward historical anomalies does not produce consistent performance. It takes ongoing research on new inefficiencies, new sources of data, and new statistical techniques to keep an investment approach in synch with evolving opportunities.

While most of the then investment managers were using historical data, these quants believed that history was merely one realization from many that could have happened. So, they build a simulator that takes in to account possible alternate histories, alternate correlations etc and start managing their fund. They call this process `disentangling'. Well you can call it i guess, sophisticated bootstrapping, in todays world. First three years of the firm, they earned hardly anything.They did research , wrote papers and got them published. So, this is a kind of startup where founders wrote papers instead of thinking about money, sales, marketing etc. Why did they do it ? Why couldn`t they do it in academia itself? I have no answers but I guess the fact that you are in a startup makes one that much more focused on what they are doing things,than let`s say a rather relaxed university setting.

Basically they spent their first three years doing multi-variate analysis. Its actually very praise worthy that they started off doing focused multivariate analysis before even thinking of the usual stuff in a startup. Wow. these guys rock...I mean , you come across some people, who just write some ill researched trading strategy/portfolio management strategy and then start a firm, and then morph in to sales people. They come with fancy brochures and lot of ENGLISH. So, for all such people, this story should be a telling reminder that `Doing homework matters in Quant' . You just can't start a firm in a garage , build a fancy site and start pitching. Might work for other areas but definitely not for a quant shop.

In this case, the quants got their initial clients based on their published research articled on portfolio disentangling. It was difficult to convince the normal investors to put in money and so they found few pension managers willing to take that risk. Today their average account size runs in to 100 million dollars. They did a lot of research and tried them out in the market. I guess thats a big advantage of being in a smaller organization where things are nimble. They were among the first pension funds that shorted assets and soon they did a ton of quant stuff on long-short strategies and incorporated the same in to their investment strategies. With $20b in AUM, they also took time out to write three books that are popular amongst investment practitioner community. After reading this story, I was amazed what these two quants have done.

Learning's:

• Spend time in understanding concepts / techniques clearly
• Always simulate and backtest. Historical data is merely one realization
• It is possible to do extensive research even when you are managing money. So, this notion that sometimes we carry as traders being sharp , quick and quants being slow is not that universally applicable. These two quants show that managing money and doing research can happily coexist.

 

Tanya Styblo Beder

After graduating from Yale, Tanya Syblo Beber takes up a job in the M&A department at First Boston. She tries returning to Yale for a PhD but that never materializes. Instead she gets involved at a swap trading desk . After a few years at the desk, she starts a risk management consulting start up and runs it for about 13 years. Somehow this story sounds like an detailed CV rather than giving any pointers/cues for aspiring quants.

Allan Malz

Allan Malz story can be summarized in one phrase,` Being at the time place at the right time'. He was at the Fed during the Golden Age of Supervision, at RiskMetrics during and after the technology bubble, and at a hedge fund during what may prove the heyday of hedge funds. So, as one would guess, he attributes his quantdom to the way he responded to random events than anything else.

Peter Muller

Peter Muller is a star quant on Wall Street, who striked it big with his team, `Process Driven Trading' at Morgan Stanley. After graduating with a math degree from Princeton, he heads to California and ends up at BARRA, a startup that was doing innovative modeling stuff headed by Barr Rosenburg , a Berkley Professor. He meets Richard Grinold at BARRA and gets the financial intuition needed for any math nerd to make sense of the markets. Peter Muller wants to do a PhD , while at BARRA. However after attending a few classes at Berkley decides that industry provided many more interesting problems and challenges than academia. Once BARRA became huge, the start up culture was lost and Peter Muller developed Poker skills. He gets an idea of starting a fund based on BARRA's models, but applied to trading. Luckily he finds himself at Morgan Stanley and gets the authority to start a prop trading desk. And they rest is history. Peter Muller's PDT is one of the most successful trading desks in the world and nobody knows how they operate to this day. In this book, though, Peter promises to write a book someday titled,`How I became a trader ?'

Andrew J. Sterge

Andrew J. Sterge graduates from Princeton with a Phd in mathematics and heads out for his first job at CoreStates Financial Corp in Philadelphia, where he learns the first and probably the most important lesson for trading,"Cut your losses". He then joins Cooper Neff, an options trading firm where he interacts with Richard Cooper and Roy Neff, whom he calls the most important people in shaping him as a quant. Over a period of time Cooper Neff morphs in to a HFT firm and this is the place where Andrew finds the work challenging , fun and thus ends up contributing massively to the P\&L of the book. Cooper Neff gets acquired by BNP and Andrew spends another successful career in quant trading at BNP. Currently Andrew works at AQR as VP. One of his statements in the book, captures his focus and drive in becoming a successful quant trader

A big part of becoming a quant was the hunger I had to improve my life,
both literally and figuratively

This quant story is interspersed with a ton of lessons and pointers to aspiring quants and traders. Here are a sample

• Quant is not a destination but a process
• You have got to be a voracious reader of market microstructure , trading strategies , everything that is related to markets. This will give you an immense edge in trading.
• Read `The Microstructure of Securities Markets' book
• Start working and start playing with tick data. You have got to store, clean , manage, view, analyze, visualize tick data. These skills are essential to become a good hft trader.Also, It is a prerequisite for building market microstructure models.
• You cannot make yourself a successful quant with out implementation. The greatest research in the world does no good if it cannot be implemented
• Effective implementation requires a lot of courage on the quant's part.A quant must take responsibility for his work and live the P&L day to day. Handing a model off to a trading desk to then go work on another project is a subtle way a quant tries to gain a free option: Take all the credit if the model works, blame it on traders if it does not.Working every day with traders, making their pain and the firm's pain your own, and putting yourself at risk for possible failure, is your only hope if you want to be really great in this business.
• You cannot just take your backtests to a bank and ask them to give you the money. Implementation takes a Herculean effort from many people.
• Becoming a quant is most of the times a team effort
• Prices are determined by agents acting in their singular self-interest. The only way anyone knows a fair, equilibrium price has been established is for prices to overreact in both directions. I have set out to profit by making this process more efficient. In the two areas I really know anything about, options pricing and market microstructure, I read virtually every book and article published on those subjects and then find things to exploit that are not written about. Lastly, no model or mathematical insight can make money on its own. One needs a team that collectively understands every aspect of running a trading business. Becoming a quant is not an individual sport.

 

John F Marshall

This is the story of a quant who is deeply influenced by his childhood incident of visiting commodity futures trading floor. So, he does his bachelors at Fordham and then works as a commodity trader for 8 years. Subsequently, he gets a PhD and lands up in St Johns University. The highlight of Marshall's career is founding IAFE ( International Association of Financial Engineers) . They say that one wrong doing can erase all the good things that one does. In this case, even though this story is presented in this book, John Marshall was accused of insider information scam by Securities and Exchange Commission. He was accused of passing inside information about a multibillion-dollar corporate takeover to a professor at Pace University. The Pace professor, Alan L. Tucker, made more than $1 million trading on the tips in 2007, according to the S.E.C. The Justice Department convicted John Marshall and put him behind bars. Such a horrendous ending to an illustrious quant career.

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Finally the authors of this nice collection of quant war stories:

Richard R. Lindsey

Richard R. Lindsey is president and CEO of the Callcott Group, LLC, where he is responsible for directing research activities and advisory services. He is the Chairman of the International Association of Financial Engineers. Dr. Lindsey served as the Director of Market Regulation for the U.S. Securities and Exchange Commission (SEC) and as the Chief Economist of the SEC. He was a finance professor at the Yale School of Management before joining the SEC.He has a BS in Chemical Engineering from Illinois Institute of Technology, an MS in Chemical Engineering from Berkeley, an MBA from the University of Dallas, and a PhD in Finance from the University of California, Berkeley.

Barry Schachter

Barry Schachter is Director of Quantitative Resources at Moore Capital Management, where he is responsible for risk management, financial engineering and trade analysis. He is also a Fellow of the Program in Mathematics in Finance at the Courant Institute of New York University.Dr. Schachter received an MA and PhD in Economics from Cornell University, and a BS in Economics from Bentley College.

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Here is the summary in pdf format - Download

 Takeaway:

This book gives a nice collection of quant stories , people who have transitioned from academia to Wall Street and have made a strong case for applying quantitative skills to finance, be it managing money/ risk/ transaction costs.

NBCD Prerana

It’s a small world. I was talking to one of my colleagues about Kathalaya and he mentioned that his sister had attended some workshop at Kathalaya. At the same time, he mentioned about another NGO that badly needed a web presence. So, I just took some time out this week and designed a preliminary site for the NGO.

The NGO goes by the name North Bengal Council for the Disabled ( NBCD) and Prerana is one such initiative under NBCD.  They run a school for the blind at Siliguri, near Calcutta. Made a basic version of the website and I hope to change the design after 10-12 months of web presence. These 10-12 months would also help the NGO put in appropriate content/videos/images for the relevant pages.

http://nbcd-prerana.org/

Now this is another site, besides Kathalaya, that I have to maintain. I just hope that I will be able to take out a few hours on a weekly basis, to make updates to both these sites.

Quote for the day

Good quantitative finance can be summed up as the art of leaving things out, plus the art of selecting the right tools.

-- Julian Shaw ( Permal Group)

 

Peer review :-)

 

Quote for the day

Andrew B. Weisman on MVO(Mean Variance Optimization);

The use of this technique, in combination with the informationless performance-enhancement techniques that are frequently employed (knowingly or unknowingly) by professional investors, tends to produce portfolios that are optimized to produce maximal future period losses; systematically denigrated from a liquidity standpoint; and actively inclusive of managers that make use of money management strategies that imply catastrophic losses of capital. It is my firm belief that unless Harry Markowitz had a truly ironic sense of humor, this was not his intent. Since this time, savvy investors have begun to employ several compensating techniques in order to accommodate the peculiarities of hedge fund data, including conditional value at risk (CVaR) in recognition of the distinctly nonsymmetric, left tail-skewed, reality of hedge fund investing, resampled optimization in recognition of the frailties of error estimation and the fact that life is,sadly, out of sample

Quote for the day

The happiest of all lives is a busy solitude.

~Voltaire

All models are short volatility

Via Derman :

If You Use a Model, You Are Short Volatility

All models are analogies, and being analogies, they are limited in their scope. In physics you can describe ice, water and steam, and the phase transitions between them, with one unified theory, amazingly, and hence you can handle the extremes of freezing and boiling.

In finance or economics we have nothing like that. Even beautiful Black-Scholes-Merton ignores volatility variations, illiquidity, panic, government regulations on shorting, to name just a few things that lie outside it.

Therefore, when the world changes dramatically, every single model you can think of is likely to fail.  I would like the following principle to be engraved on the foreheads of all financial and economic model users: All models are short volatility. When volatility changes a lot, the model is going to fail.

Academic life in a nutshell

Stanford professor,John Perry, distills the essence of academic life :

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The Academic Trough

Being a Full Professor has a lot to be said for it. You are a duke or duchess in the medieval institution of the university. You receive a good salary, as big and nice an office as your department has available, first choice of class hours, and a lot of nice other perks. And there is also the wisdom and balanced judgment that comes with age. For example, I remember when I was an assistant professor, it seemed absurdly unfair that Full Professors, in addition to receiving a better salary, also received nicer offices and other perks. But now that I've got that wisdom and balanced judgment that comes with age, it all seems perfectly reasonable.

But something even better happens after you have been a Full Professor for a while. As your hair turns grey and age confers a look of distinction, people begin to treat to you in a certain deferential way. One has finally made it out of what I call the Academic Trough. It is this phenomenon I want to discuss and explain. The Academic Trough is a concept for understanding academic careers. It illuminates many puzzling phenomena that one observes on college and university campuses, and should also prove useful to people planning their careers or trying to understand the careers they have had.

The term ``Academic Trough" derives from the shape an academic career inscribes along two key dimensions. The vertical axis has to do with the importance that your colleagues attach to your potential and actual work beyond the Ph.d. The horizontal axis is time. The successful career typically inscribes a big U: the Academic Trough.

The top left part of the U represents the high esteem that your colleagues inside and outside the university have for you at the time you are hired. The bottom of the U corresponds to the point at which the successful academic receives tenure; of course, if the curve plummets too low, you don't receive tenure. What counts as "too low" depends on where you are. And the high point on the right corresponds to the the golden years I just mentioned, which seems to begin about five years after one becomes a full professor.

Several factors conspire to produce the trough. When you are just out of graduate school, you haven't done much, but your teachers have written inflated letters for you. You are overly-praised pure potential. When your future colleagues hire you, they are excited about what you are going to do (although perhaps if they compare notes they would find they don't all have the same thing in mind). People find very little to complain about in the potential works that you haven't written yet. If you are adept in your interviews, each of your future colleagues believes that in your works his or her own wonderful ideas will be adequately appreciated for the first time.

Of course, once you get a job, you have to start writing and publishing and are judged on the basis of this work. However brilliant you are, the effect of actual work inevitably diminishes the luster you had as an overly-praised graduate student. As tenure time nears, more and more people start to read your stuff, and more and more is at stake. This sort of thing is hard on your reputation. But if one survives this horrible process, the curve starts to rise again. The reason is simple: cognitive dissonance. That is the human tendency to put a happy face on the results of decisions we have made, however catastrophic they may actually be. Once your department votes you tenure, they have a vested interest in finding your work exciting, provocative, or at any rate basically OK. The head of steam built up by the positive tenure decision and cognitive dissonance should get you through to Full Professor, if you manage to complete any more work at all and carry out your teaching duties with a show of diligence.

The trough actually has a slight dip in it, as the process of reading, decision, cognitive dissonance and appreciation repeats itself on a smaller scale for promotion to Full Professor. Then the golden era begins, for the high point on the right of the U represents the period after this. The various committees that agreed to tenure and promotion, probably grudgingly, have ceased to remember the details. People just know you are a Full Professor and have been for a while. By this time, with a little luck, your hair is grey and you look distinguished or at least old. At this point, everyone assumes that you must have done something quite important, although they can't quite remember what. Once you realize that you will never again have your work crawled over by various committees charged with evaluating your basic worth as a human being, it becomes more fun. Bliss.

The trick, then, is to get a job based on work you haven't done, and stick around until the details of what you did are forgotten. That's when the true rewards of academia set in.

Listening below the noise : Summary

Yesterday was a rather unpleasant day for me. Whenever I am in a bad mood / I become restless I pick up this book by Anne D LeClaire, titled, “ Listening below the noise”. For some reason this book has been my best companion over the past few years. I reread parts of this book from time to time. This time around, I thought I should blog about this and write a few words about the book.

The author starts off by saying, “Like too many of us, I mistook a busy life to a rich one”, and cites her mid-life emptiness as one of the reasons for exploring “silence”. While strolling on the Cape Cod Beach on a warm afternoon in January 1992, she suddenly realizes that “silence” is the missing element in her life and decides to consciously inculcate it in her daily life. She then begins, as a whim, a unique ritual, i.e, maintaining a day of complete silence every other Monday.

Entry :

On the first day of silence, she realizes that her energy levels and productivity levels are far better than a normal day. She begins to wonder whether turning away from outside world is the first step to nourishing the inner world that is so very vibrant in every one of us. The first thing she realizes that silence and mindfulness reduces the habit of multi-tasking things in life. When we are doing something, i.e mindfully doing something, we cannot multi-task. Silence makes one realize that single-tasking is the way to do any work and is a far better and a peaceful alternative to multi-tasking. Is silence necessary for creativity? The author’s first brush with silence makes her feel that silence/solitude is probably a necessary condition to do creative work. In Silence, Our minds are more tuned to the creative energy that lies within us.

Staying in complete silence is not an easy practice, as everyone would agree. The author reflects on one such day when she has an immense urge towards breaking her “silence” tradition. She reveals one of her tricks, i.e, strike a bargain with oneself that it would be only a couple of hours of silence instead of maintaining one full day of silence. This little trick  sometimes becomes useful in centering her. However these bargains are only helpful for a temporary period of time. The quieter we become, the more we hear. What we hear might be unpleasant at times and hence there is a tendency to fill up the silence with noise, i.e songs/TV/Soap-opera/movies/empty chatter. On some level, we are afraid of what we will hear.

When we are in silence, there is one thing we definitely become aware, at least most of us I guess. There is a muddy messy space our inner garbage heap where we toss scraps too painful to consider or confront, the loss, pain, grief and disappointment that are all too real. When we weed out extraneous stimulation and let go of the reins of control, these things claim our attention. And it is silence that allows us the space and stillness in which to think about our motives, to examine our behavior, to see where we’ve fallen short. It is only when we drag our smallest, shabbiest parts into the light that we can move toward becoming whole. We are massively afraid of dealing with this compost. So, in that sense this is the reason we fill our lives with distractions so that we don’t get to meet this compost. However the wise thing to do is to actually confront this compost, to turn it over. For within the same mounds lies the fertile matter out of which new life arises and is nourished.

Cultivation :

It is also sometimes necessary to create boundaries in life for silence to walk in to our lives. May be cutting down on TV/ avoiding the idle chatter with someone, consciously weeding out distractions, etc are bare minimum steps that one must take for the silence to make presence in our lives. There is no guarantee that these restrictions on external stimulation would help one to remain silent as there is sometimes that internal chatter that drives away the silence ruthlessly.

Silence is Janus-faced. Like the Roman god Janus, silence holds two faces. To be silenced is not at all the same as choosing not to speak.A chasm lies between the two, as wide as that between fasting for a purpose and starvation. To be silenced is crippling, belittling, constricting, disempowering. Chosen stillness can be healing, expansive, instructive.

Let’s say you decide to have one day of complete silence. What if others in your family pick up a fight for some trivial reason ? The fact that you have chosen not to respond might fill you up with more resentment as you cannot vent out feelings. So , is the silence painful in such situations ? Well, not necessarily says the author narrating one such incident when silence helped in not messing up a situation and thus was invaluable in providing time and space to defuse a situation.

Silence enhances listening ability, i.e, listening to things that are left unsaid. Bird-watchers, Naturalists typically develop a keen sense of listening. One colleague of mine is so excited whenever he sees tigers/butterflies/birds etc. whenever he goes for a Jungle safari. To observe/spot/infer the kind of bird/butterfly, it demands a sense of stillness from a person. Unless you are fully present in the NOW and develop a keen ear, going on a Jungle safari is practically useless. Ability to remain Silent is a great skillset to have in such activities. Similarly even in our daily lives unless we are silent we cannot truly listen to others. We are merely talking and waiting to talk. We engage in chatter, not conversation, and our chatter reveals our egos’ needs: Love me, admire me, envy me, fear me, help me, see me. There is little space for truly hearing others. Silence in that sense enables true conversations to take place.

Fertilization :

Silence is the first essential for most of the creative endeavors. Even a creative act like choreography might need the choreographer to visualize the steps in silence and then make his/her troupe follow those steps. Personally I find silence very stimulating , be it for programming something, be it for writing a blog post , be it for practicing music. The attention we can give to work, complete and undistracted concentration does enable us to bring the best with in all of us. Like the solitary spider who busily weaves her web in perfect silence, we need to be alone and quiet for our subconscious to spin its creations. Stillness focuses the brain. And like the tensile strength of the spider’s strands, it buttresses and strengthens creativity. Another beneficial aspect of silence is it produces marked improvement in physical and psychological health. At what age, do we develop a low tolerance for quiet time? When do we begin to call it boredom? When do we begin the excessive yearning for entertainment and diversions? The prospect of loneliness can make us fear solitude and silence. The paradox is that those are the very measures that can heal us. The author concludes this section by pondering over her experiences of remaining silent for an entire week.

Harvest :

After 9 years of practicing this ritual, the author develops sudden resistance to this ritual. She has this intense urge to put an end to this ritual but finally bargains another 2 months with herself. During these two months, she reflects on the benefits of silence through the years . She also remembers her yoga teacher’s words:

Sometimes we go through a time  that looks like a setback but in reality that time is a place of preparation. A resting space. A gathering of energy. Like an archer pulling back the bowstring so the arrow can shoot forward.

She also realizes another benefit that silence bestows on people who practice it, i.e, the inner strength that it provides.Trees growing in a forest are fundamentally weaker and less able to weather wind and storms than ones that stand alone, because the solitary trees, without the shelter provided by the others, develop stronger, deeper roots. After two months of the bargain period, the author realizes that silent-day experiences have helped her develop a  spiritual way of living and is no longer a mere ritual. So ,she decides to continue the practice(till date).

Sowing :

In the final section of the book, the author provides a few ways to incorporate silence in to our daily lives.

I have read this book at least half a dozen times till now and every time it has made me appreciative of the importance of silence and solitude in one’s life. Sometimes when I am restless, I just pick up this book and read a random paragraph. The writing is so beautiful that it brings my restless mind to calmness and allows me to focus on my work.

Quote for the day :-)

Via gapingvoid:

Murakami’s schedule

Via NYT( The Fierce Imagination of Haruki Murakami)

Murakami sold his jazz club in order to devote himself, full time, to writing.

“Full time,” for Murakami, means something different from what it does for most people. For 30 years now, he has lived a monkishly regimented life, each facet of which has been precisely engineered to help him produce his work. He runs or swims long distances almost every day, eats a healthful diet, goes to bed around 9 p.m. and wakes up, without an alarm, around 4 a.m. — at which point he goes straight to his desk for five to six hours of concentrated writing. (Sometimes he wakes up as early as 2.) He thinks of his office, he told me, as a place of confinement — “but voluntary confinement, happy confinement.”

“Concentration is one of the happiest things in my life,” he said. “If you cannot concentrate, you are not so happy. I’m not a fast thinker, but once I am interested in something, I am doing it for many years. I don’t get bored. I’m kind of a big kettle. It takes time to get boiled, but then I’m always hot.”

That daily boiling has produced, over time, one of the world’s most distinctive bodies of work: three decades of addictive weirdness that falls into an oddly fascinating hole between genres (sci-fi, fantasy, realist, hard-boiled) and cultures (Japan, America), a hole that no writer has ever explored before, or at least nowhere near this deep.

Quote for the day

While most people were analyzing the benefits of why things could work and the negatives to why they wouldn’t, I was out doing and making things happen.

~ Lou Imbriano ( CEO of TrinityOne )

The Practicing Mind : Summary

The author of this book, Thomas M. Sterner, is a Piano technician for a major performing arts center. The author admits that , in his career spanning 25 years, he had faced a lot of challenges to keep himself disciplined and focused (considering the act of tuning and maintaining a piano , an instrument that has 88 notes , is repetitious and tedious by nature). Over a period of time, the author develops a mindset that has kept him productive.Through this book, Sterner tells his method of remaining disciplined.

Process not the Product

In any form of practice, it is important to focus on the process and not on the product. There are umpteen variations of this statement that one gets to hear.The author does acknowledge this fact but goes on to add his own flavor to this statement. He uses music as an example to show that focusing on the process takes care of the product , but not vice-versa. He says

Keep yourself process-oriented. Stay in the present. Make the process the goal and use the overall goal as a rudder to steer you efforts. Be deliberate, have an intention about what you want to accomplish, and be aware of that intention. Doing these things will eliminate the judgments and emotions that come from a product-oriented or results-oriented mind.

It’s How You Look At It

The author gives a beautiful analogy of a flower to shift one’s perspective towards everything in life. He says

Ask yourself: at what point in a flower's life, from seed to full bloom, has it reached perfection? Let's look at this right now and see what nature is teaching us every day as we walk past the flowers in our garden. At what point is a flower perfect? Is it when it is nothing more than a seed in your hand waiting to be planted? All that it will ever be is there in that moment. Is it when it first starts to germinate unseen under several inches of the soil? This is when it displays the first visible signs of the miracle we call creation. How about when it first pokes its head through the surface and sees the face of the sun for the first time? All of its energies have gone into reaching for this source of life; until this point, it has had nothing more than an inner voice telling it which way to grow to find it. What about when it begins to flower? This is when its own individual properties start to be seen. The shape of the leaves, the number of blooms are all unique to just this one flower, even among the other flowers of the same species. Or is it the stage of full bloom, the crescendo of all of the energy and effort it took to reach this point in its life? Let’s not forget that humble and quiet ending when it returns to the soil from where it came. At what point is the flower perfect? I hope you already know that the answer is that it is always perfect.

Using this example, the author suggests that by following present-minded approach , one can experience a tremendous relief from the fictitious, self-imposed pressures and expectations that only slow one’s progress.

Perception Changes Create Patience

Patience is probably at the top of everyone’s list  of most sought-after virtues. One of the reasons that we become impatient is we step out of the NOW  There is a saying that states that most of what we worry about never comes to pass. Thinking about a situation before you are in it only scatters your energy. The first step toward patience is to become aware of when your internal dialog is running wild and dragging you with it. If you are not aware of this when it is happening, which is probably most of the time, you are not in control. The second part is understanding and accepting that there is no such thing as reaching a point of perfection in anything. True perfection is both always evolving and at the same time always present within you, just like the flower.

Progress is a natural result of staying focused on the process of doing anything. When you stay on purpose, focused in the present moment, the goal comes to you with frictionless ease. However, when you constantly focus on the goal you are aiming for, you push it away instead of pulling it toward you. In every moment of your struggle, by looking at the goal and constantly referencing your position to it, you are affirming to yourself that you haven’t reached it. You only need to acknowledge the goal to yourself occasionally, using it as a rudder to keep you moving in the right direction.

Suppose you are trying to learn how to play a piece of music and you come from this new perspective. Your experience will be totally different than what we usually think of in terms of learning to play a musical instrument. In the old way, you are sure that you are not going to be happy or “successful” until you can play the piece of music flawlessly. Every wrong note you hit, every moment you spend struggling with the piece, is an affirmation that you have not reached your goal. If, however, your goal is learning to play the piece of music, then the feeling of struggle dissolves away. With each moment you spend putting effort into learning the piece, you are achieving your goal. An incorrect note is just part of learning how to play the correct note; it is not a judgment of your playing ability. In each moment you spend with the instrument, you are learning information and gaining energy that will work for you in other pieces of music. Your comprehension of music and the experience of learning it are expanding. All of this is happening with no sense of frustration or impatience. What more could you ask for from just a shift in perspective?

Four S words - Simplify, Small, Short and Slow

The author shows the interconnectedness between these words and the way these 4 words can be used to structure any work, be it following a fitness regimen / coding an algo / playing an instrument / cleaning up the house etc. Any task that is overwhelming at the first sight, might put us off and sometimes we tend to permanently shelve it. But once we simplify the goal, divide this simplified goal in small sections, do these sections in short durations at a slow pace, paradoxically , we get far more things done efficiently. This might sound all very obvious, but then it is relevant to ask oneself a question, “ When was the last time you did all the four things – Simplified a project, Took a small section, worked on it for a short time and more importantly slowly ? “ More than any other place, I can relate this to music. You can’t master a raaga without the 4 components mentioned. You have to simplify the goal of a 1.5 hr typical rendition of a raaga, Divide in to small sections ,Practice on one of the the small sections in a short interval , lets say 45 min, and more importantly practice it slowly. “ My Sitar guru was mentioning the other day about “Budhaditya Mukherjee”, a Sitar Maestro. In an interview, when asked about his practice regimen, he replied that he practiced 3 hrs in the morning and 3 hrs in the evening and more importantly , he does it EVERY SINGLE DAY. Unlike Ravi Shankar’s of the world who quote that they practice 15 hrs – 20 hrs a day, which seems to be practically impossible for a human being, Budhaditya Mukherjee’s ritual sounds more pragmatic and realistic. In the same interview, he also mentions that a combination of Simplify + Small + Short and Slow are quintessential to master a raaga.

Equanimity and DOC

Calmness and even-tempered are the words that go along with equanimity. These are the characteristics that are desirable when we are working on something. However there is an evil beast called “Judgement” that sometimes jumps upon us.Judgment is inevitable in our lives,  but it becomes pathological when we overdo it. Most of times we overdo it. We judge everything in life and most of it unconsciously. We imagine hypothetical scenarios and think about the possible outcomes and possible judgments that we would make / others would make in such scenarios. Its like running simulations to create parallel worlds and checking the parameter values. It is good in statistics as alternate worlds gives confidence intervals on parameters. It is detrimental when we are working on something as it robs us from the NOW. It happens to all of us. We are doing something, be it running/ reading / programming/ playing an instrument etc. Instead of just being in the present, we start judging it. We are thinking of the next activity that needs to be done / we think of some odd conversation with someone/ we imagine hypothetical situations etc. We try to engage ourselves unconsciously in things that have nothing to do with what we are CURRENTLY doing. The judgement gives rise to  emotions and they stem from a sense that “this is right and that is wrong” or “this is good and that is bad.” Right and good make us happy while bad and wrong make us upset or sad. We feel that right and good are at least approaching “ideal,” while wrong and bad are moving away from it. We all want to be happy and have an ideal life, but what constitutes right and wrong is neither universal nor constant. The evaluations and judgments we make unconsciously in every second of our lives jump-start our emotions and bring us so much anxiety and stress.What can be done about it ? Doing work with out judgement part is far more effective as the execution of the task would be that much more clinical.

The author suggests “meditation” as a means to get out of this ever-judgmental mode of mind. He also offers another adjunct method,which he calls “ DOC – Do + Observe + Correct”. He gives anecdotes and experiences from his work as a Piano technician that bring out the importance of DOC to perform tasks efficiently. Using DOC repetitively for most of the tasks that we do in our daily lives, it is possible to remove judgement that clouds our thinking and execution. The C in the DOC refers more to evaluation and not judgment. Evaluation comes before the action of passing judgement. After evaluation, you skip the judgement part and then go over DOC cycle, as judgment has no value in DOC mindset.

Teach and Learn from Children

Time perception is an integral part of the difference between adults and children. In general, Children don’t seem to have a sense of where they are going in life. There is today and that’s it. They live in the present moment, but not really by their own choice; it’s just how they are. So, making them do any activity like learning to play an instrument /  work on something which takes time and effort to master, is difficult as they don’t see a point in doing it. There is no instant gratification in learning math / learning an instrument. It is usually an activity which will involve a lot of struggle/failures etc. So,there is a paradox here. What’s frustrating as an adult, with regard to teaching them to stay in the present when they are engaged in something that requires perseverance, is that they can’t see the point. Why work at something that requires a long-term commitment, a perception of time outside the present moment? Children are always in the NOW and adults find it difficult to be in the NOW. Is there something that Parents and Children can learn and teach each other ? The author shares his experiences in dealing with her two daughters in this context.

Takeaway:

A Piano technician’s job from the outside looks repetitive. This book provides a different perspective of the work and in doing so, provides valuable guidance for deliberate practice. 

Quote for the day

Real Statistics is not primarily about the Mathematics which underlies it:
common sense and scientific judgment are more important.
But, there is no excuse for not using the right Mathematics when it is available.

- David Williams

Dare to be trivial

Rory Sutherland’s commencement speech

Quote for the day

“ Furious activity is no substitute for understanding.”

- Williams, H.H

Why cling ?

In most of the universities in India , statistics curriculum followed at undergraduate and graduate level, is completely outdated. The content taught, is relevant to times where there were:

• No computational capabilities - All computations had to be performed with paper and pencil.
• No graphing capabilities - Either  All graphs had to be generated with pencil, paper, and a ruler. (And complicated graphs—such as those requiring prior transformations or calculations using the
  data—were especially cumbersome.)
• Very small and very expensive data sets - Data sets were small (often not more than four to five points) and could be obtained only with great difficulty.

In other words, the situation is almost entirely the opposite of our situation today:

• Computational power that is essentially free.
• Interactive graphing and visualization capabilities on every desktop.
• Often huge amounts of data.

Then “Why do universities cling to outdated syllabi ? ” , is a question that leaves me puzzling.

Quote for the day

“ Names don’t constitute Knowledge.“

– Richard Feynman

Quote for the day

Life is a “ do-it-yourself ” project.

Your attitude and the choices you make today, help build your house you live in tomorrow.