I stumbled on to Kathalaya, an NGO based out of Bangalore, in early 2006. I was amazed at their efforts in keeping the spirit of story-telling alive in India. In early 2007 I had designed a website for Kathalaya and have been maintaining the site since then. Needless to say, I feel nice that I am able to at least contribute something to this wonderful group led by Geeta Ramanujam, which is trying to keep the tradition of story-telling alive.

Anupam Kher questions Sadhguru @ Mumbai :

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 )

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I went over this book to get some idea on STP. I was completely clueless on the things that happen at the back end, once the trade is placed with a broker. STP was introduced in Indian Markets by FT and few other vendors almost a decade ago. It has lead to a clear improvement in operational efficiency. Even though this book talks about .NET platform, I liked the chapter on STP that explained things using business case and .NET code.

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.

The core message of this book by Seth Godin, is “Mass Marketing is dead and its an era of marketing to wierds”. Seth clarifies the word wierd by defining as “ people who have chosen to avoid conforming to the masses, at least in some parts of their lives”. In one sense the book is a rehash of Seth’s other books There are some examples and illustrations that might motivate a reader to go over this 90 odd page book. The book starts off with an example of a zoo in Belgium.The zoo facing with dwindling crowds and hence falling revenues, pulls off a mass marketing campaign by focusing on “ A pregnant elephant”.This sort of marketing brings back the crowds to the zoo, but such examples are an exception than the rule, says Seth.  He describes a few situations that capture the changing market place both in the online and offline world. Here is a sample :

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Via Reuters :

Swiss bank UBS on Sunday increased the amount it said it had lost on rogue equity trades to $2.3 billion and alleged a trader concealed his risky deals by creating fictitious hedging positions in internal systems.UBS stunned markets on Thursday when it announced unauthorised trades had lost it some $2 billion. London trader Kweku Adoboli was charged on Friday with fraud and false accounting dating back to 2008.

“The loss resulted from unauthorised speculative trading in various S&P 500, DAX, and EuroStoxx index futures over the last three months,” UBS said in a brief statement.“The loss arising from this matter is $2.3 billion. As previously stated, no client positions were affected.”

This book by J.R.Norris is a classic reference for Markov Chains. It is unlikely that any paper on Markov chains in the recent times does not mention this book somewhere in the paper. I will try to attempt to summarize the main chapters of the book in this post.

The book starts off by saying that Markov process are random processes that don’t retain memory. When the state-space is restricted to finite or countably many, these processes are called Markov Chains. The intro gives a great clarity for any reader in listing the kind of chains that would be dealt in the book. The following gives a basic flavor of Markov chains that are dealt in the introductory chapters:

Via Delhi-IBSEN  festival 2010 :

This play is an adaptation of Henrik Ibsen’s “Lady from the sea” and is directed by Ila Arun.

The story is told in the folk form as the narrative through the balladeers, Bhopa and Bhopi, traditional story-tellers from Rajasthan, who use the Phad, or a painted scroll to tell their stories. The play begins with the Bhopi telling her husband that she had discovered a new phad, called ‘Ibsenji ka phad’, in her late father-in-law’s trunk. She persuades her husband to use this in their next performance, instead of the old, well-worn tales of gods and rajas. He reluctantly agrees and they start their story:

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I am hooked on to “Markov Chains” these days and they seem to fascinate me as the applications are in almost every field that I look at. I happened to go over Page Rank algo. From a Markov chain’s perspective, the algo can be summarized  in 2 steps

Step 1 : Represent a random surfer’s movement as a Markov chain

Here N is the total number of pages indexed by Google, Q is a transition matrix( irreducible, a periodic) that captures the transition probability of moving from one page to another , p is the page rank of the pages on the internet and alpha is adjustment factor to take in to consideration the inherent importance of a page.

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

Rory Sutherland’s commencement speech

“ Furious activity is no substitute for understanding.”

- Williams, H.H

MCMC brilliantly explained by Iain Murray :

Markov Chain Monte Carlo

[

Firstly, something about the puppies on the cover pages . The happy puppies are named Prior, Likelihood, and Posterior. Notice that the Posterior puppy has half-up ears, a compromise between the perky ears of the Prior puppy and the floppy ears of the Likelihood puppy. The puppy on the back cover is named Evidence. MCMC methods make it unnecessary to explicitly compute the evidence, so that puppy gets sleepy with nothing much to do. These puppy images basically summarize the essence of Bayes’ and MCMC methods.

A prediction for tech adoption in Indian markets via Celent :

Years ago, I read in John Naisbitt’s book that technology does not change as fast as you want / you predict. In fact things that we expect to happen always happen more slowly . The author shows a ton of examples to show how people were gung-ho about something but eventually it took years to pan out. In the case of HFT prediction too, I think the above time line is a overly optimistic estimate.

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.)

This book by Michael Lewis delves in to the reasons behind the mysterious success of Oakland Athletics, one of the poorest teams in US baseball league . In a game where players are bought at unbelievable prices , where winning / losing is a matter of who’s got the bigger financial muscle, Oakland A’s go on to make a baseball history with rejected players and rookie players .

“Is their winning streak a result of random luck OR Is there a secret behind their winning streak ? “ , is a question that Michael Lewis tries to answer. Like a sleuth, the author investigates the system and the person behind the system , Oakland A’s manager Billy Beane.

  [

These books are written by the Father-Son duo of Irwin & Peter Schiff, albeit at various points in time. The first book titled, ”How an economy grows and Why it doesn’t ?” was written by Irwin A Schiff in 1979 and his son has followed it up in 2010 with the second book titled,” How an economy grows and Why it crashes?”. Both books give a chance to ponder over the situation that US is in, financial crisis of 2008 which is still on with full force in 2011. I have summarized the first book here . In this post, I will try to summarize second book , that the author, Peter Schiff calls it “a riff of the original one”.

This is a graphic novel explaining the growth of a general economy from its barebones structure to a full-fledged economic system. Through an allegory , the author shows the deep malaise in the functioning of US economy. It starts off with three men on an island Able, Baker and Charlie who merely catch fish,eat, sleep. There is no credit, no investments, no savings to begin with. Able gets a brainwave to make a fishing net that will save him some time to pursue other activities. He under consumes for a day, takes risk , comes up with a fishing net, thus managing to catch 2 fish per day instead of 1 fish. This is the first time the island has a saving and a capital equipment (net). It is also the first time when one of the islanders can do some other activity than merely taking care of survival.

**“ Names don’t constitute Knowledge.“
**
– Richard Feynman

The book by sharon bertsch mcgrayne, is about Bayes’ theorem stripped off the math associated with it. In today’s world, statistics even at a rudimentary level of analysis (not referring to research but preliminary analysis) comprises forming a prior and improving it based on the data one gets to see. In one sense modern statistics takes for granted that one starts off with a set of beliefs and improves the beliefs based on the data. When this sort of technique or thinking was first introduced, it was considered equivalent to pseudo-science or may be voodoo science. During 1700s when Bayes’ theorem came to everybody’s notice, Science was considered extremely objective, rational and all the words that go with it. On the other hand, Bayes’ was talking about beliefs and improving the beliefs based on data. So, how did the world come to accept this perspective of thinking? In today’s world, there is not a single domain that is untouched by Bayesian Statistics. In finance and technology specifically, Google Search engine algos + Gmail spam filtering , Net flix recommendation service in e-tailing space , Amazon book recommendations, Black-Litterman model in finance, Arbitrage models based on Bayesian Econometrics etc. are some of the innumerable areas where Bayes’ philosophy is applied. Carol Alexander in her book on Risk Management says that, world needs Bayesian Risk Managers and remarks that , “Sadly most of risk management that is done is frequentist in nature” .

This book is a poor imitation of Steven Pressfield’s book , “Do the work ”.The author is a professional actor who seemed to have settled in to some creative director gig at a Church. The book is called “Untitled” and metaphorically refers to the blank page that faces any person at the beginning of a project, be it writing an article/book/painting/creating a biz etc. Everyone has to start with a blank page. In an writer’s life though, every novel and every little story of the novel begins with a blank page and he/she must fill in characters , narrative as he goes along. In that sense, “blank page“ is a demon that a writer needs to fight every day. 

Life is a “ do-it-yourself ” project.

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

I never had a chance to read Dawkins work and the following 5 lectures have motivated me immensely to read at least a couple of his famous books like “The Selfish gene” and “ Blind Watchmaker”.

Ep 1: Waking Up in the Universe - Growing Up in the Universe - Richard Dawkins
Ep2: Designed and Designoid Objects - Growing Up in the Universe - Richard Dawkins
Ep3: Climbing Mount Improbable - Growing Up in the Universe - Richard Dawkins
Ep4: The Ultraviolet Garden - Growing Up in the Universe - Richard Dawkins
Ep5: The Genesis of Purpose - Growing Up in the Universe - Richard Dawkins

This book is more an historical account of two scientists (Alexander von Humboldt, Carl Friedrich Gauss) than a work of fiction.Daniel Kehlmann weaves interesting fiction around these two brilliant scientists exploring their lives, their view points, their personalities that seem to be completely opposite. Alexander von Humboldt believed that knowledge comes from exploring the world, while Gauss pretty much developed everything sitting in an observatory.