Monday, November 26, 2012

Randomness in Markets and Life



Complied from works of Nassim Nicholas Taleb.



Randomness is everywhere from social science , life events or financial markets. Fat tails or wild events are probably the ones with massive impact.  Nature has designed us to fool ourselves easily , we are incompetent to understand randomness and that we are unable to know "what we do not know" . The lack of understanding of  "what we do not know"  is what makes us more prone to random events. We see hard working people on top but there is a group of people with high intellect on top so we cannot suggest which trait leads to success. Risk takers are able to capture profits and at the same time they are more prone to loss. 

Trick is to stay away from people who think they are thinkers but actually they are just mere entertainers. Journalists are somehow intellectual as they pin out the loop holes in society and are not part of herds. My principle hobby is to tease those who take themselves and their knowledge too seriously. Probability is something that fools us easily , it is not an engineering or science but it is knowledge of skepticism. It is the acceptance of ignorance and development of knowledge which we do not know.Skepticism is generally any questioning attitude towards knowledge, facts, or opinions/beliefs stated as facts and doubts regarding claims that are taken for granted elsewhere.
Hard work and discipline are part of success and not itself road to success as randomness and Black Swans can attack these and people may call you a looser or maybe someone who failed. But some state that chance plays no part in success , yet I see many not so hard working and not so intelligent people at top while few hard working geniuses failed. Risk takers are more prone to profits and failures and they usually are the confident geniuses. Black Swan can be good or bad, Google's success was a good Black Swan event while 9/11 was a bad Black Swan. Literary minds are more prone to randomness as many concepts lead to confusion and more thinking puts one to contradictions. Bad information is worse than no information as it makes us more prone to Black Swans. Small losses do not matter if profits are high, this is the code of a true risk taker but at the same time he should be educated enough to be able to estimate or catch the Black Swans as these may completely destroy him.

Never ask a guy if he is from Sparta , because if he is you will know by his habits and if he is not you are hurting him by asking him. In same way do not ask a trader how much profit he made or how mush loss he had to face it will make him sad. Accountants can never understand Randomness and Probability and even the financial movements are not to be calculated by accountants and they are book-keepers only.1990s saw the arrival of scientists in Wall Street, most of these were Phds and were mostly from Physics (Theoretical) along with Mathematics from Russia, France and China. Most of these came from Russia, Russian Physics-PHd quants were ruling the Wall Street. This was due to the reason that MBAs wanted more and in half the price firms were able to hire Russian Scientists trained under the most mathematical minds. In face Russian Physics departments were top at that time in Maths and Theoretical Physics. But the lack of knowledge in Probability is vital for me as it gives me profits but at the same time I need few to understand my theories on Randomness. More erudition in Probability and Science of Randomness will make my business go down but academically I might get more fame. Useful tools like Monte Carlo Simulation and Stochastic Models are known to many but real philosophy of randomness requires more than just models and machines. Perfection on randomness and probability requires the right information the calculation of biasness for which we need psychologists and other academics.


Learning from history is another way to forecast and understand current events. Children learn from their mistakes but I think adults suffer from same condition but though Machiavelli was smart enough to learn from history and infact wrote treatise from history and experiences, his experiences were those which he had to face due to rare randomness. Risk takers are those people who know enough through history , experiences that they are confident to put them in that random event.
Historical determinism is the word used to describe the study of history to forecast or understand randomness. Those who are good in predicting the past and good in predicting the future  so we read history to learn the mechanism of randomness. Civil servants or classical think tanks were those who were capable and meant to forecast human behaviours and social events. Journalists are ones who use Historical determination to understand the results of a random event. Wise perceive things about to happen and silence is far better.

Bell curve has 68% observation falling between standard deviation of 1 and -1 yet the intelligent brain accepts this accuracy. Experiences and statistics may have high randomness i. e I may have a bad experience with  a New Yorker but my friends may have opposite experience. Statistics can never be 100% true and those who fall in outliers or face the unexpected have their own approach as everyone prefers experience over statistics.

I like Philosophy of Karl Popper (all his ideas on epistemology, scientific methods and open society) and David Hume(especially his Epistemology and Problem of Induction) or to some extent I am obsessed with it. George Soros is the only "rich investor" who is intellectual and also a Professor type , the only money man with intellectual power. Soros learned and understood Popper and also went on to live a Popperian life. Soros spread the ideas of Popper in banking system and in society. Popper always had problems with Statisticians and especially statistical inference .He suggests that repeated events causes one to increase acceptance and hence the error of truth increases. One experiment is not enough  to get accurate result. The more data we have the more we are prone to traps.

In fact I came across Popper through Soros (Soros being my favourite investor)Popper is the man who is unworldly a man who was isolated, self focused , arrogant ,closed to outside world, independent and very bad listener and always firm on his beliefs though he helped people for good ideas and helped them to guide in their careers. Soros used more philosophy in banking than other banker, he was creative enough to apply every bit of Popper's philosophy in banking. Popper shared that Open Society is one where no permanent truth can exist and his idea was made to use by Friedrich Hayek .

What is the probability of winning New Jersey lottery twice...... 1/17 trillion. Randomness does not look random, we do know what events have high or low randomness but we are not able to catch it so in turn we are always fooled . Calculating randomness is hard for  every event (whether high or low randomness). High randomness though can either ruin you or make you billionaire but low randomness is not that massive in impact. Even when patients get the news of cancer etc their reaction is random towards it i. e some get sad and some even faint.
Brownian Random Walk used in finance has one condition that probability of success does not change with incremental step, same as Binomial model. Non-linearity and linearity is another effect that can cause drastic changes. If you try playing piano you may fail a lot of time and suddenly you start playing Chopin's sonatas .For such non-linear events we need not use Linear Statistical models as we will have large errors. Same is true for marginal benefit , the glass of water you drink after gym will have no effect and suddenly the 4th one satisfies you. 

Who exerted most influence in economics in past two centuries.... it was not Keynes, Milton Friedman , Samuelson or Marshall but they are two non-economists: Amos Tversky and Daniel Kahneman who made new ideas in Behavioural Finance/Economics. They worked on field of Heuristics and Rationality. 

The more out of the world you are i.e.  the more anarchist or rebel you are the more you are prone to randomness as you are not part of normal people and that you have less ability to predict social randomness. One great example is that of a man who is not into social media like me and so the recent music or most debated topic are not known to him and thus he faces trouble when he goes to a nightclub or even to a cafe for relaxation.  The more mathematics and Probability you know the more prone you are to randomness , this is because for events which are 2 dimensional or more are studied using sampling and other mathematical models and thus increasing error in results. Luckily the most events in a normal person's life are one dimensional. In same way if you are more emotional then it means you are less rational .Some people get angry when the car behind you gives you a loud horn when you do not act rapidly when light gets green , now 1 millisecond is not worth anything but for the back car it is something. Emotions also change your decisions accordingly , emotions might cause you to loose i. e some people leave their job if they are slightly taunted while more rational people or the less emotional think about the loss and stay calm and so are in control of their emotions and decisions in life.

But how do we know that we are going to face a rare and random event?This is the problem that needs to be perfected in order to avoid being fooled.

Sunday, November 25, 2012

Actuaries VS Quants


The following article is taken from August 2008 issue of The Actuary magazine.
    
Those working in the two fields of actuarial science and quantitative finance have not always been totally appreciative of each others’ skills. Actuaries have been dealing with randomness and risk in finance for centuries. Quants are the relative newcomers, with all their fancy stochastic mathematics. Rather annoyingly for actuaries, quants come along late in the game and thanks to one piece of insight in the early ‘70s completely change the face of the valuation of risk. The insight I refer to is the concept of dynamic hedging, first published by Black, Scholes and Merton in 1973. Before 1973 derivatives were being valued using the “actuarial method,” i.e. in a sense relying, as actuaries always have, on the Central Limit Theorem. Since 1973 and the publication of the famous papers, all that has been made redundant. Quants have ruled the financial roost. But this might just be the time for actuaries to fight back.   

I am putting the finishing touches to this article a few days after the first anniversary of the “day that quant died.” In early August 2007 a number of high-profile and previously successful quantitative hedge funds suffered large losses. People said that their models “just stopped working.” The year since has been occupied with a lot of soul searching by quants, how could this happen when they’ve got such incredible models?

In my view the main reason why quantitative finance is in a mess is because of complexity and obscurity. Quants are making their models increasingly complicated, in the belief that they are making improvements. This is not the case. More often than not each ‘improvement’ is a step backwards. If this were a proper hard science then there would be a reason for trying to perfect models. But finance is not a hard science, one in which you can conduct experiments for which the results are repeatable. Finance, thanks to it being underpinned by human beings and their wonderfully irrational behaviour, is forever changing. It is therefore much better to focus your attention on making the models robust and transparent rather than ever more intricate. As I mentioned in a recent wilmott.com blog, there is a maths sweet spot in quant finance. The models should not be too elementary so as to make it impossible to invent new structured products, but nor should they be so abstract as to be easily misunderstood by all except their inventor (and sometimes even by him), with the obvious and financially dangerous consequences. I teach on the Certificate in Quantitative Finance and in that our goal is to make quant finance practical, understandable and, above all, safe.
When banks sell a contract they do so assuming that it is going to make a profit. They use their complex models, with sophisticated numerical solutions, to come up with the perfect value. Having gone to all that effort for that contract they then throw it into the same pot as all the others and risk manage en masse. The funny thing is that they never know whether each individual contract has “washed its own face.” Sure they know whether the pot has made money, their bonus is tied to it. But each contract? It makes good sense to risk manage all contracts together but it doesn’t make sense to go to such obsessive detail in valuation when ultimately it’s the portfolio that makes money, especially when the basic models are so dodgy. The theory of quant finance and the practice diverge. Money is made by portfolios, not by individual contracts.
Imperial College London started the famous MSc Actuarial Finance , which gave birth to the new field of actuary concerned with investment banking.

Actuaries are better in accessing risk than Quants.

In other words, quants make money from the Central Limit Theorem, just like actuaries, it’s just that quants are loath to admit it! Ironic. It’s about time that actuaries got more involved in quantitative finance. They could bring some common sense back into this field. We need models which people can understand and a greater respect for risk. Actuaries and quants have complementary skill sets. What high finance needs now are precisely those skills that actuaries have, a deep understanding of statistics, an historical perspective, and a willingness to work with data.With Solvency II coming up in 2013 there will be sudden increase in the demand of actuaries.