বিভাগ আর্কাইভ: Wilmott ম্যাগাজিন

আমার প্রকাশিত (বা শীঘ্রই প্রকাশিত হবে) Wilmott ম্যাগাজিন কলাম টুকরা

Ambition vs. ক্ষুধা

Growing up in a place like India, I was told early in life that ambition was a bad thing to have. It had a negative connotation closer to greed than drive in its meaning. I suspect this connotation was rather universal at some point in time. Why else would Mark Anthony harp on Brutus calling Caesar ambitious?

ক্ষুধা, or its euphemistic twin ambition, probably had some role to play in the pain and suffering of the current financial turmoil and the unfolding economic downturn. কিন্তু, it is not just the greed of Wall Street. Let’s get real. Jon Steward may poke fun at the twenty something commodity trader earning his thirty million dollar bonus by pushing virtual nothingness around, but nobody complained when they were (or thought they were) making money. Greed is not confined to those who ran fifty billion dollar Ponzi schemes; it is also in those who put their (and other people’s) money in such schemes expecting a too-good-to-be-true rate of returns. They were also made of the sterner stuff.

Let’s be honest about it. We in the financial industry are in the business of making money, for others and for ourselves. We don’t get into this business for philanthropic or spiritual reasons. We get into it because we like the rewards. Because we know that “how to get rich quick” বা “how to get even richer” is the easiest sell of all.

We hear a lot about how the CEOs and other fat cats made a lot of money while other normal folks suffered. It is true that the profits were “private” while the losses are public, which is probably why the bailout plan did not get much popular support. But with or without the public support, bailout plan or not, like it or not, the pain is going to be public.

অবশ্যই, the CEOs of financial institutions with their private jets and eye-popping bonuses were guilty of ambition, but the fat cats didn’t all work in a bank or a hedge fund. It is the legitimization of greed that fueled this debacle, and nobody is innocent of it.


কেয়স এবং অনিশ্চয়তার,,en,উপর "বিগ ব্যাং তত্ত্ব চিন্তা,,en

The last couple of months in finance industry can be summarized in two words — chaos and uncertainty. The aptness of this laconic description is all too evident. The sub-prime crisis where everybody lost, the dizzying commodity price movements, the pink slip syndrome, the spectacular bank busts and the gargantuan bail-outs all vouch for it.

The financial meltdown is such a rich topic with reasons and ramifications so overarching that all self-respecting columnists will be remiss to let it slide. সব পরে, a columnist who keeps his opinions to himself is a columnist only in his imagination. I too will share my views on causes and effects of this turmoil that is sure to affect our lives more directly than anybody else’s, but perhaps in a future column.

The chaos and uncertainty I want to talk about are of different kind — the physics kind. The terms chaos and uncertainty have a different and specific meanings in physics. How those meanings apply to the world of finance is what this column is about.

Symmetries and Patterns

Physicists are a strange bunch. They seek and find symmetries and patterns where none exists. I remember once when our brilliant professor, লি Smolin, described to us how the Earth could be considered a living organism. Using insightful arguments and precisely modulated articulation, লি একটি বাধ্যকারী ক্ষেত্রে যে পৃথিবী, আসলে, একটি প্রাণীর হচ্ছে সন্তুষ্ট সব শর্ত. লি এর দৃশ্যে বিন্দু এত ছিল না কিনা বা পৃথিবী আক্ষরিক জীবিত ছিল, but that thinking of it as an organism was a viable intellectual pattern. Once we represent the Earth in that model, we can use the patterns pertaining to organism to draw further predictions or conclusions.

Expanding on this pattern, I recently published a column presenting the global warming as a bout of fever caused by a virus (us humans) on this host organism. Don’t we plunder the raw material of our planet with the same abandon with which a virus usurps the genetic material of its host? In addition to fever, typical viral symptoms include sores and blisters as well. Looking at the cities and other eye sores that have replaced pristine forests and other natural landscapes, আমরা প্রকৃতপক্ষে আমাদের হোস্ট আর্থ পূতিগন্ধময় নৃশংসতার inflicting যে কল্পনা করা কঠিন নয়. Can’t we think of our city sewers and the polluted air as the stinking, তার শরীরের উপর আলসার ক্ষরণ?

While these analogies may sound farfetched, we have imported equally distant ideas from physics to mathematical finance. Why would stock prices behave anything like a random walk, unless we want to take Bush’s words (যে “Wall Street got drunk”) literally? কিন্তু গম্ভীরভাবে, Brownian motion has been a wildly successful model that we borrowed from physics. আবার, once we accept that the pattern is similar between molecules getting bumped around and the equity price movements, the formidable mathematical machinery and physical intuitions available in one phenomenon can be brought to bear on the other.

Looking at the chaotic financial landscape now, I wonder if physics has other insights to offer so that we can duck and dodge as needed in the future. Of the many principles from physics, chaos seems such a natural concept to apply to the current situation. Are there lessons to be learned from chaos and nonlinear dynamics that we can make use of? May be it is Heisenberg’s uncertainty principle that holds new insights.

Perhaps I chose these concepts as a linguistic or emotional response to the baffling problems confronting us now, but let’s look at them any way. It is not like the powers that be have anything better to offer, এটা?

Chaos Everywhere

In physics, chaos is generally described as our inability to predict the outcome of experiments with arbitrarily close initial conditions. উদাহরণস্বরূপ, try balancing your pencil on its tip. পরিষ্কারভাবে, you won’t be able to, and the pencil will land on your desktop. এখন, note this line along which it falls, and repeat the experiment. Regardless of how closely you match the initial conditions (of how you hold and balance the pencil), the outcome (the line along which it falls) is pretty much random. Although this randomness may look natural to us — সব পরে, we have been trying to balance pencils on their tips ever since we were four, if my son’s endeavours are anything to go by — it is indeed strange that we cannot bring the initial conditions close enough to be confident of the outcome.

Even stranger is the fact that similar randomness shows up in systems that are not quite as physical as pencils or experiments. নিন, উদাহরণস্বরূপ, the socio-economic phenomenon of globalization, which I can describe as follows, admittedly with an incredible amount of over-simplification. দীর্ঘ সময় আগে, we used to barter agricultural and dairy products with our neighbours — বলে, a few eggs for a litre (or was it pint?) of milk. Our self-interest ensured a certain level of honesty. We didn’t want to get beaten up for adding white paint to milk, উদাহরণস্বরূপ. These days, thanks to globalization, people don’t see their customers. A company buys milk from a farmer, adds god knows what, makes powder and other assorted chemicals in automated factories and ships them to New Zealand and Peru. The absence of a human face in the supply chain and in the flow of money results in increasingly unscrupulous behaviour.

Increasing chaos can be seen in the form of violently fluctuating concentrations of wealth and fortunes, increasing amplitudes and frequency of boom and bust cycles, exponential explosion in technological innovation and adaptation cycles, and the accelerated pace of paradigm shifts across all aspects of our lives.

It is one thing to say that things are getting chaotic, quite another matter to exploit that insight and do anything useful with it. I won’t pretend that I can predict the future even if (rather, especially if) I could. তবে, let me show you a possible approach using chaos.

One of the classic examples of chaos is the transition from a regular, laminar flow of a fluid to a chaotic, turbulent flow. উদাহরণস্বরূপ, when you open a faucet slowly, if you do it carefully, you can have a pretty nice continuous column of water, thicker near the top and stretched thinner near the bottom. The stretching force is gravity, and the cohesive forces are surface tension and inter-molecular forces. As you open the faucet still further, ripples begin to appear on the surface of the column which, at higher rates of flow, rip apart the column into complete chaos.

In a laminar flow, macroscopic forces tend to smooth out microscopic irregularities. Like gravity and surface tension in our faucet example, we have analogues of macroscopic forces in finance. The stretching force is probably greed, and the cohesive ones are efficient markets.

There is a rich mathematical framework available to describe chaos. এই ফ্রেমওয়ার্ক ব্যবহার, I suspect one can predict the incidence and intensity of financial turmoils, though not their nature and causes. তবে, I am not sure such a prediction is useful. Imagine if I wrote two years ago that in 2008, there would be a financial crisis resulting in about one trillion dollar of losses. Even if people believed me, would it have helped?

Usefulness is one thing, but physicists and mathematicians derive pleasure also from useless titbits of knowledge. What is interesting about the faucet-flow example is this: if you follow the progress two water molecules starting off their careers pretty close to each other, in the laminar case, you will find that they end up pretty much next to each other. But once the flow turns turbulent, there is not telling where the molecules will end up. একইভাবে, in finance, suppose two banks start off roughly from the same position — say Bear Stearns and Lehman. Under normal, laminar conditions, their stock prices would track similar patterns. But during a financial turbulence, they end up in totally different recycle bins of history, as we have seen.

If whole financial institutions are tossed around into uncertain paths during chaotic times, imagine where two roughly similar employees might end up. অর্থাৎ, don’t feel bad if you get a pink slip. There are forces well beyond your control at play here.

Uncertainty Principle in Quantitative Finance

The Heisenberg uncertainty principle is perhaps the second most popular theme from physics that has captured the public imagination. (The first one, অবশ্যই, is Einstein’s E = mc2.) It says something seemingly straightforward — you can measure two complementary properties of a system only to a certain precision. উদাহরণস্বরূপ, if you try to figure out where an electron is (measure its position, যে) more and more precisely, its speed becomes progressively more uncertain (বা, the momentum measurement becomes imprecise).

Quantitative finance has a natural counterpart to the uncertainty principle — risks and rewards. When you try to minimize the risks, the rewards themselves go down. If you hedge out all risks, you get only risk-free returns. Since risk is the same as the uncertainty in rewards, the risk-reward relation is not quite the same as the uncertainty principle (যা, as described in the box, deals with complementary variables), but it is close enough to draw some parallels.

To link the quantum uncertainty principle to quantitative finance, let’s look at its interpretation as observation altering results. Does modelling affect how much money we can make out of a product? This is a trick question. The answer might look obvious at first glance. অবশ্যই, if we can understand and model a product perfectly, we can price it right and expect to reap healthy rewards. সুতরাং, নিশ্চিত, modelling affects the risk-reward equation.

কিন্তু, a model is only as good as its assumptions. And the most basic assumption in any model is that the market is efficient and liquid. The validity of this assumption (বা উহার অভাব) is precisely what precipitated the current financial crisis. If our modelling effort actually changes the underlying assumptions (usually in terms of liquidity or market efficiency), we have to pay close attention to the quant equivalent of the uncertainty principle.

Look at it this way — a pyramid scheme is a perfectly valid money making model, but based on one unfortunate assumption on the infinite number of idiots at the bottom of the pyramid. (মনে আসছে, the underlying assumption in the sub-prime crisis, though more sophisticated, may not have been that different.) Similar pyramid assumptions can be seen in social security schemes, পাশাপাশি. We know that pyramid assumptions are incorrect. But at what point do they become incorrect enough for us to change the model?

There is an even more insidious assumption in using models — that we are the only ones who use them. In order to make a killing in a market, we always have to know a bit more than the rest of them. Once everybody starts using the same model, I think the returns will plummet to risk-free levels. Why else do you think we keep inventing more and more complex exotics?

Summing up…

The current financial crisis has been blamed on many things. One favourite theory has been that it was brought about by the greed in Wall Street — the so-called privatization of profits and socialization of losses. Incentive schemes skewed in such a way as to encourage risk taking and limit risk management must take at least part of the blame. A more tempered view regards the turmoil as a result of a risk management failure or a regulatory failure.

This column presents my personal view that the turmoil is the inevitable consequence of the interplay between opposing forces in financial markets — risk and rewards, speculation and regulation, risk taking and risk management and so on. To the extent that the risk appetite of a financial institute is implemented through a conflict between such opposing forces, these crises cannot be avoided. আরও খারাপ, the intensity and frequency of similar meltdowns are going to increase as the volume of transactions increases. This is the inescapable conclusion from non-linear dynamics. সব পরে, such turbulence has always existed in the real economy in the form cyclical booms and busts. In free market economies, selfishness and the inherent conflicts between selfish interests provide the stretching and cohesive forces, setting the stage for chaotic turbulence.

Physics has always been a source of talent and ideas for quantitative finance, much like mathematics provides a rich toolkit to physics. In his book, একটি চূড়ান্ত তত্ত্ব স্বপ্ন, Nobel Prize winning physicist Steven Weinberg marvels at the uncanny ability of mathematics to anticipate physics needs. একইভাবে, quants may marvel at the ability of physics to come up with phenomena and principles that can be directly applied to our field. আমার, it looks like the repertoire of physics holds a few more gems that we can employ and exploit.

বক্স: Heisenberg’s Uncertainty Principle

Where does this famous principle come from? It is considered a question beyond the realms of physics. Before we can ask the question, we have to examine what the principle really says. Here are a few possible interpretations:

  • Position and momentum of a particle are intrinsically interconnected. As we measure the momentum more accurately, the particle kind of “spreads out,” as George Gamow’s character, জনাব. Tompkins, puts it. অর্থাৎ, it is just one of those things; the way the world works.
  • When we measure the position, we disturb the momentum. Our measurement probes are “too fat,” বলিতে কি. As we increase the position accuracy (by shining light of shorter wavelengths, উদাহরণস্বরূপ), we disturb the momentum more and more (because shorter wavelength light has higher energy/momentum).
  • Closely related to this interpretation is a view that the uncertainty principle is a perceptual limit.
  • We can also think of the uncertainly principle as a cognitive limit if we consider that a future theory might surpass such limits.

The first view is currently popular and is related to the so-called Copenhagen interpretation of quantum mechanics. Let’s ignore it for it is not too open to discussions.

The second interpretation is generally understood as an experimental difficulty. But if the notion of the experimental setup is expanded to include the inevitable human observer, we arrive at the third view of perceptual limitation. এই দেখুন, it is actually possible to “derive” the uncertainty principle, based on how human perception works.

Let’s assume that we are using a beam of light of wavelength lambda to observe the particle. The precision in the position we can hope to achieve is of the order of lambda. অর্থাৎ, Delta x approx lambda. In quantum mechanics, the momentum of each photon in the light beam is inversely proportional to the wavelength. At least one photon is reflected by the particle so that we can see it. সুতরাং, by the classical conservation law, the momentum of the particle has to change by at least this amount(approx constant/lambda) from what it was before the measurement. সুতরাং, through perceptual arguments, we get something similar to the Heisenberg uncertainty principle

Delta x.Delta p approx constant

We can make this argument more rigorous, and get an estimate of the value of the constant. The resolution of a microscope is given by the empirical formula 0.61lambda/NA, যেখানে NA is the numerical aperture, which has a maximum value of one. সুতরাং, the best spatial resolution is 0.61lambda. Each photon in the light beam has a momentum 2pihbar/lambda, which is the uncertainty in the particle momentum. So we get Delta x.Delta p approx 4hbar, approximately an order of magnitude bigger than the quantum mechanical limit.

Through more rigorous statistical arguments, related to the spatial resolution and the expected momentum transferred, it may possible to derive the Heisenberg uncertainty principle through this line of reasoning.

If we consider the philosophical view that our reality is a cognitive model of our perceptual stimuli (which is the only view that makes sense to me), my fourth interpretation of the uncertainty principle being a cognitive limitation also holds a bit of water.

লেখক সম্পর্কে

The author is a scientist from the European Organization for Nuclear Research (সি ই আর এন), who currently works as a senior quantitative professional at Standard Chartered in Singapore. More information about the author can be found at his blog: http//www.Thulasidas.com. The views expressed in this column are only his personal views, which have not been influenced by considerations of the firm’s business or client relationships.

Commodity Prices — Who’s Holding the Cards?

অর্থনীতিবিদ অনেক হাত আছে. এক হাত, তারা ভাল কিছু ঘোষণা হতে পারে. অন্য দিকে, তারা বলতে পারেন, “ভাল, এত না.” তাদের কিছু এমনকি একটি তৃতীয় বা চতুর্থ হাত থাকতে পারে. আমার প্রাক্তন বস, একটি অর্থনীতিবিদ নিজেকে, একবার তিনি এই হাত কিছু বন্ধ চপ পারে আকাঙ্ক্ষিত যে মন্তব্য.

In the last couple of months, I plunged right into an ocean of economist hands as I sat down to do a minor research into this troubling phenomenon of skyrocketing food and commodity prices.

প্রথম “হাত” নির্দিষ্ট যে খাদ্য চাহিদা (and energy and commodities in general) এশিয়ার উঠতি দৈত্যদের মধ্যে জনসংখ্যা ও পরিবর্তন খরচ নিদর্শন বৃদ্ধির কারণে তরঙ্গায়িত হয়েছে. সুপরিচিত চাহিদা ও সরবরাহের দৃষ্টান্ত দাম ঢেউ ব্যাখ্যা, মনে হবে. এটা যে হিসাবে হিসাবে সহজ?

অন্য দিকে, আরো এবং আরো খাদ্য শস্য জৈব জ্বালানি উৎপাদন করে, বাগানে হচ্ছে. জৈব-জ্বালানি মূল কারণ চাহিদা? জৈব জ্বালানিতে কারণ জ্যোতির্বিদ্যা অশোধিত তেলের দাম আকর্ষণীয়, সবকিছু মূল্য ও ড্রাইভ যা. Is the recent OPEC windfall driving the price increases? তাদের পক্ষে বাজার বাঁকানো যে ধনী দেশগুলোর মধ্যে খাদ্য ভর্তুকির সম্পর্কে কি?

Supply Side Difficulties

When explaining the food prices, one economic opinion puts the blame squarely on the supply side. এটা খাদ্য উৎপাদন দেশে দরিদ্র আবহাওয়া একটি অটল আঙুল পয়েন্ট, এবং প্যানিক ব্যবস্থা সাপ্লাই চেইন উপর আরোপিত, যেমন রপ্তানি নিষিদ্ধকরণ ও ছোট স্কেল মজুদ হিসাবে, যে মূল্য ও ড্রাইভ.

Looking at the bigger picture, let’s study oil as a proxy commodity and study its dynamics. Because of its effect on the rest of the economy, oil is indeed a good proxy.

In the case of oil, the dearth on the supply side is more structural, it is argued. The production capacity has stagnated over the last thirty years or so [1]. No infrastructural improvements have been made after the seventies. প্রকৃতপক্ষে, new methodological improvements are expensive for all the easy methods have been fully exploited; all the low-hanging fruits have been picked, বলিতে কি.

The harder-to-reach “fruits” include deep sea explorations, crude oil from sand and, somewhat more tenuously, bio-fuels. The economic viability of these sources of oil depends on the oil price. Oil from sand, উদাহরণস্বরূপ, has an operating cost in the range of $20 থেকে $25, as Shell’s CFO, Peter Voser is quoted as stating [2]. At $100 a barrel, oil from sand clearly becomes an economically viable source. Bio-fuels also are viable at high oil prices.

The huge investments involved in exploiting these new sources and their unpredictable economic viability exert strong upward pressure on oil prices, purely from the supply side, regardless of the demand situation. Once you invest a huge amount banking on a sustained high oil price, and then find that the oil market has softened below your viability level, you have to write off the investment, forcing losses and consequent price hikes.

With the high level of oil prices, investments are moving into infrastructure enhancements that will eventually ease the supply side crunch. But these fixes are slow in coming and are not going to ease the current dearth for about a decade. অর্থাৎ, the high prices are here to stay. অন্তত, so say the economists subscribing this supply side explanation of things.

Demand Spike

Although I personally find it hard to believe, people assure me that the exponential demand explosion in the emerging economies was completely unforeseen. My friend from a leading investment bank (who used to head their hybrids desk) told me that there was no way they could have anticipated this level of demand. I should probably shelve my scepticism and believe those in the know.

One thing I do know from personal experience is that the dynamics of a demand crash is different in emerging economies for a variety of reasons. প্রথম সব, identical movements in fuel prices have different impact in the overall spending pattern depending on the proportion they represent in the purchasing power of an average consumer. একটি 30% increase in the pump price, উদাহরণস্বরূপ, might mean a 5% reduction in the purchasing power to a US consumer, while it might mean 20% reduction for an Indian customer.

এছাড়া, retail fuel prices in India are regulated and supported by government subsidies. Subsidies act as levies delaying the impact crude oil price movements. But when the crude oil prices rise beyond a certain point, the subsidies become untenable and the retail fuel prices surge upward, ushering in instant demand crash.

I came across another view of the skyrocketing oil prices in terms of the Middle-Eastern and American politics. The view was that the Saudi oil capacity is going to increase by about 10% soon and the prices will drop dramatically in the first quarter of 2009. It was argued that the drop will come as boost to the new American president, and the whole show is timed and stage-managed with a clear political motivation.


All these different opinions make my head spin. আমার গোলা দেখুন, I always suspected that the speculation in commodities market might be the primary factor driving the prices up. আমি একটি সাম্প্রতিক মার্কিন সিনেটে সাক্ষ্য পড়া যখন আমি আমার সন্দেহের মধ্যে খণ্ডিত অনুভূত যেখানে একটি সুপরিচিত হেজ ফান্ড ম্যানেজার, মাইকেল মাস্টার [3], shed light on the financial labyrinth of futures transactions and regulatory loopholes through which enormous profits were generated in commodity speculation.

Since speculation is my preferred explanation for the energy and indeed other commodity price movements, I will go over some of the arguments in some detail. I hasten to state that the ideas express in this article are my own personal views (and perhaps those of Michael Masters [3] পাশাপাশি). They do not represent the market views of my employer, their affiliates, the Wilmott Magazine, or anybody else. এছাড়া, some of these views are fairly half-baked and quite likely to be wrong, in which case I reserve the right to disown them and bequeath them to a friend of a friend. (এছাড়াও, see the box on Biased Opinions).

Masters points out that there is no real supply crunch. Unlike the Arab Oil Embargo time in 1973, there are no long lines at the gas pump. Food supplies are also healthy. So some new mechanism must be at work that drives up the commodity demand despite the price level.

Masters blames the institutional investors (pension funds, sovereign wealth funds, university endowments etc.) for the unreasonable demand on commodity futures. Since futures prices are the benchmark for actual physical commodities, this hoarding of the futures contracts immediately reflects in the physical spot prices and in the real economy. And as the prices climb, the investors smell blood and invest more heavily, stoking a deadly vicious cycle. Masters points out that the speculative position in petroleum is roughly the same as the increase in demand from China, debunking the popular notion that it is the demand spike from the emerging giants of Asia that is driving the oil price. একইভাবে, bio-fuel is not the driver in food prices — the speculators have stockpiled enough corn futures to power the entire US ethanol industry for a year.

Although quants are not terribly interested in the transient economic drivers of market dynamics or trading psychology, here is an interesting thought from Mike Master’s testimony. A typical commodity trader initiating a new trade is pretty much insensitive to the price of the underlying. He has, বলে, a billion dollars to “put to work,” and doesn’t care if the position he ends up holding has five million or ten million barrels of oil. He never intends to take delivery. This price-insensitivity amplifies his impact on the market, and the investor appetite for commodities increases as the prices go up.

Most trading positions are directional views, not merely on the spot price, but on volatility. In a world of long and short Vega positions, we cannot expect to get a full picture of trading pressures exerted on oil prices by studying the single dimension of spot. Is there a correlation between the oil prices and its price volatility?

Figure 1
চিত্র 1. Scatter-plot of WTI Spot prices in Dollar and its volatility. Although the plot shows random clusters at low spot levels, at price > $75 (highlighted in the purple box), there appears to be a structure with significant correlation.

চিত্র 1 shows a scatter plot of the WTI spot price vs. the annualized volatility from publicly available WTI spot prices data [4]. Note than my definition of volatility may be different from yours [5]. এক নজরে, there appears to be little correlation between the spot price and volatility. Indeed the computed correlation over all the data is about -0.3.

তবে, the highlighted part of the figure tells a different story. As the spot price climbed over $75 per barrel, the volatility started showing a remarkable correlation (এর 0.7) with it. Was the trading activity responsible for the concerted move on both prices and volatility? That is my theory, and Michael Masters may agree.

Hidden Currency Theory

Here is a dangerous thought — could it be that traders are pricing oil in a currency other than the once mighty dollar? This thought is dangerous because international armed conflicts may have arisen out of precisely such ideas. But an intrepid columnist is expected to have a high level of controversy affinity, so here goes…

We keep hearing that the oil price is down on the back of a strong dollar. There is little doubt that the oil prices are highly correlated to the strength of the dollar in 2007 এবং 2008, as shown in Table 1. Let’s look at the oil prices in Euro, the challenging heavy-weight currency.

Figure 1
চিত্র 2. Time evolution of the WTI spot price in Dollar and Euro. The Euro price looks more stable.

At first sight, চিত্র 2 does appear to show that the price is more stable when viewed in Euro, হিসাবে প্রত্যাশিত. But does it mean that the traders are secretly pricing their positions in Euro, while quoting in Dollar? Or is it just the natural tandem movement of the Euro and WTI spots?

If the hidden currency theory is to hold water, I would expect stability in the price levels when priced in that currency. কিন্তু, more directly, I would naively expect less volatility when the price is expressed in the hidden currency.

Figure 1
চিত্র 3. WTI Volatilities measured in Dollar and Euro. They are nearly identical.
Figure 1
চিত্র 4. Scatter-plot of WTI volatilities in Dollar and Euro. The excess population above the dividing line of equal volatilities implies that the WTI spot is more volatile when measured in Euro.

চিত্র 3 shows the WTI volatilities in Dollar and Euro. They look pretty much identical, which is why I replotted them as a scatter-plot of one against the other in Figure 4. If the Dollar volatility is higher, we will find more points below the red line, which we don’t. So it should mean that the hidden currency theory is probably wrong [6].

A good thing too, for nobody would be tempted to bomb me back to the stone ages now.

Human Costs

The real reasons behind the food and commodity price crisis are likely to be a combination of all these economic factors. কিন্তু সঙ্কট নিজেই বিশ্বের নির্বিচার একটি নীরব সুনামি হয়, জাতিসংঘের ওয়ার্ল্ড ফুড প্রোগ্রাম এটা বন্ধ রাখে.

খাদ্যের দাম বৃদ্ধি, অপ্রীতিকর যদিও, is not such a big deal for a large number of us. আমাদের প্রথম বিশ্বের আয়, আমাদের অধিকাংশ নিবেন 20% খাদ্য আমাদের বেতন. এটা হয়ে থাকে 30% একটি ফলে 50% দাম বৃদ্ধি, আমরা অবশ্যই এটা পছন্দ করবেন না, কিন্তু আমরা যে অনেক ভোগ করতে হবে না. আমরা ট্যাক্সি ভর উপর নিচে কাটা করতে হতে পারে, বা ফাইন ডাইনিং, কিন্তু এটা আমাদের বিশ্বের শেষ হয় না.

আমরা উপরের হয় 10% income bracket (as the readers of this magazine tend to be), আমরা এমনকি বৃদ্ধি লক্ষ্য করা না হতে পারে. আমাদের জীবনধারা উচ্চ খাদ্য মূল্য প্রভাব সংক্ষিপ্ত হতে হবে — বলে, a business-class holiday instead of a first-class one.

এটা নীচে কাছাকাছি একটি ভিন্ন গল্প. আমরা কম উপার্জন $1000 একটি মাস, এবং আমরা ব্যয় করতে বাধ্য করা হয় $750 পরিবর্তে $500 খাদ্য, it may mean a choice between a bus ride and legging it. যে পর্যায়ে, the increase in food prices does hurt us, and our choices become grim.

কিন্তু অনেক কঠোর বাস্তবতা সম্মুখীন যারা এই পৃথিবীতে মানুষের দাম দৃষ্টিশক্তি কোন শেষ সঙ্গে অঙ্কুর আছে. Their choices are often as terrible as Sophie’s Choice. যা সন্তানের ক্ষুধার্ত আজ রাতে ঘুমাতে যায়? বাকি জন্য অসুস্থ এক বা খাবার জন্য মেডিসিন?

আমরা খাদ্য সংকট তৈরি বাজার বাহিনীর জগন্নাথদেব বিরুদ্ধে সব ক্ষমতাহীন. আমরা বাস্তবানুগভাবে এই নীরব সুনামি অবশ্যই পরিবর্তন করতে পারবেন না, যদিও, এর অন্তত বর্জ্য মাধ্যমে পরিস্থিতি বর্ধিত করার চেষ্টা করবেন না যাক. আপনি ব্যবহার করতে হবে কি শুধুমাত্র কিনুন, এবং আপনি প্রয়োজন কি শুধুমাত্র ব্যবহার. আমরা যারা সাহায্য করতে পারবেন না, এমনকি যদি সবসময় ক্ষুধার্ত যারা যেতে হবে, তারা লিপ্সা মারা হবে, কি দূরে ছুঁড়ে তাদের অপমান না. হাঙ্গার একটি ভয়ংকর ব্যাপার. আপনি আমাকে বিশ্বাস করেন না, একটি দিনের জন্য উপবাস চেষ্টা. ভাল, এমনকি আপনি যদি না এটি চেষ্টা করুন — জন্য এটা কোথাও কেউ সাহায্য করতে পারে.


Commodity speculation by institutional investors is one of the driving factors of this silent tsunami of rising food prices. Their trading strategies have been compared to virtual hoarding in the futures market, driving up real prices of physical commodities and profiting from it.

I don’t mean to portray institutional investors and commodity traders as criminal masterminds hiding behind their multiple monitors and hatching plots to swindle the world. The ones I have discussed with do agree on the need to curtail the potential abuse of the system by closing the regulatory loopholes and setting new accountability frameworks. তবে, we are still on the rising edge of this influx of institutional funds into this lucrative asset class. Perhaps the time is not ripe enough for robust regulations yet. Let us make a bit more money first!

Reference and Endnotes

[1] Jeffrey Currie et al. “The Revenge of the Old ‘Political’ Economy” Commodities (Goldman Sachs Commodities Research), মার্চ 14, 2008.
[2] Business Times, “Shell counts rising cost of squeezing oil from sand in Canada,” মার্চ 18, 2008. HTTP://business.timesonline.co.uk/tol/business/article3572646.ece
[3] Testimony of Michael W. Masters (Managing Member / Portfolio Manager, Masters Capital Management, LLC) before the Committee on Homeland Security and Governmental Affairs. মে 20, 2008. http://hsgac.senate.gov/public/_files/052008Masters.pdf
[4] Cushing, OK WTI Spot Price FOB (Dollars per Barrel) Data source: Energy Information Administration. HTTP://tonto.eia.doe.gov/dnav/pet/hist/rwtcd.htm
[5] I define the WTI volatility on a particular day as the standard deviation of the spot price returns over 31 days around that day, annualized by the appropriate factor. Using standard notations, the volatility on a day t is defined as:
sigma (t) = sqrt {frac{1}{{31}}sumlimits_{t - 15}^{t + 15} {left( {ln left[ {frac{{S(t)}}{{S(t - 1)}}} right] - mu } right)^2 frac{{252}}{{31}}} }
[6] Given that the correlation between EUR/USD and WTI Spot is positive (মধ্যে 2007 এবং 2008), the volatility, when measured in Euro, is expected to be smaller than the volatility in Dollar. The expected difference is tiny (সম্পর্কে 0.3% পরম) because the EUR/USD volatility (defined as in [5]) সম্পর্কে 2%. The reason for the counter-intuitive finding in Figure 4 is probably in my definition of the volatility as in [5].
[7] Monwhea Jeng, “A selected history of expectation bias in physics,” American Journal of Physics, জুলাই 2006, Volume 74, Issue 7, পিপি. 578-583. HTTP://arxiv.org/pdf/physics/0508199

বক্স: Biased Opinions

As an ex-experimental physicist, I am well aware of the effect of bias. Once you have a favoured view, you can never be free of bias. It is not that you actively misrepresent the data to push your view. But you tend to critically analyze the data points that do not match your view, and tend to be lenient on the ones that do.

উদাহরণস্বরূপ, suppose I do an experiment to measure a quantity that Richard Feynman predicted to be, বলে, 1.37. I repeat the experiment three times and get values 1.34, 1.30 এবং 1.21. The right thing to do is to report a measurement of 1.29 with an error of 0.06. কিন্তু, knowing the Feynman prediction (এবং, আরো গুরুত্বপূর্ণ, knowing who Feynman is), I would take a hard look at the 1.21 trial. If I find anything wrong with it (which I will, because no experiment is perfect), I might repeat it and possibly get a number closer to 1.37. It is biases of this kind that physicists try very hard to avoid. See [7] for an interesting study on biases in physics.

In this column, I do have a favoured view — that the main driver of the commodity price inflation is speculation. In order to avoid pushing my view and shaping my readers’ opinion, I state clearly that there is a potential of bias in this column. The view that I have chosen to favour has no special reason for being right. It is just one of the many “hands” popular among economists.

লেখক সম্পর্কে
The author is a scientist from the European Organization for Nuclear Research (সি ই আর এন), who currently works as a senior quantitative developer at Standard Chartered in Singapore. The views expressed in this column are only his personal views, which have not been influenced by considerations of the firm’s business or client relationships. More information about the author can be found at his web site: http://www.Thulasidas.com.

Software Nightmares

To err is human, but to really foul things up, you need a computer. So states the remarkably insightful Murphy’s Law. And nowhere else does this ring truer than in our financial workplace. সব পরে, it is the financial sector that drove the rapid progress in the computing industry — which is why the first computing giant had the word “business” in its name.

The financial industry keeps up with the developments in the computer industry for one simple reason. Stronger computers and smarter programs mean more money — a concept we readily grasp. As we use the latest and greatest in computer technology and pour money into it, we fuel further developments in the computing field. অর্থাৎ, not only did we start the fire, we actively fan it as well. But it is not a bad fire; the positive feedback loop that we helped set up has served both the industries well.

This inter-dependency, healthy as it is, gives us nightmarish visions of perfect storms and dire consequences. Computers being the perfect tools for completely fouling things up, our troubling nightmares are more justified than we care to admit.

Models vs. Systems

Paraphrasing a deadly argument that some gun aficionados make, I will defend our addiction to information technology. Computers don’t foul things up; people do.

আপনি মনে করবেন না, I am not implying that we always mess it up when we deploy computers. But at times, we try to massage our existing processes into their computerised counterparts, creating multiple points of failure. The right approach, পরিবর্তে, is often to redesign the processes so that they can take advantage of the technology. But it is easier said than done. To see why, we have to look beyond systems and processes and focus on the human factors.

In a financial institution, we are in the business of making money. We fine-tune our reward structure in such a way that our core business (of making money, যে) runs as smoothly as possible. Smooth operation relies on strict adherence to processes and the underlying policies they implement. In this rigid structure, there is little room for visionary innovation.

This structural lack of incentive to innovate results in staff hurrying through a new system rollout or a process re-engineering. They have neither the luxury of time nor the freedom to slack off in the dreaded “business-as-usual” to do a thorough job of such “non-essential” things.

এছাড়া, there is seldom any unused human resource to deploy in studying and improving processes so that they can better exploit technology. People who do it need to have multi-facetted capabilities (business and computing, উদাহরণস্বরূপ). Being costly, they are much more optimally deployed in the core business of making more money.

Think about it, when is the last time you (or someone you know) got hired to revamp a system and the associated processes? The closest you get is when someone is hired to duplicate a system that is already known to work better elsewhere.

The lack of incentive results in a dearth of thought and care invested in the optimal use of technology. Suboptimal systems (which do one thing well at the cost of everything else) abound in our workplace. In time, we will reach a point where we have to bite the bullet and redesign these systems. When redesigning a system, we have to think about all the processes involved. And we have to think about the system while designing or redesigning processes. This cyclic dependence is the theme of this article.

Systems do not figure in a quant’s immediate concern. What concerns us more is our strongest value-add, namely mathematical modelling. In order to come up with an optimal deployment strategy for models, তবে, we need to pay attention to operational issues like trade workflow.

I was talking to one of our top traders the other day, and he mentioned that a quant, no matter how smart, is useless unless his work can be deployed effectively and in a timely manner. A quant typically delivers his work as a C program. In a rapid deployment scenario, his program will have to plug directly into a system that will manage trade booking, risk measurements, operations and settlement. The need for rapid deployment makes it essential for the quants to understand the trade lifecycle and business operations.

একটি ট্রেড জীবন

Once a quant figures out how to price a new product, his work is basically done. After coaxing that stochastic integral into a pricing formula (failing which, a Crank-Nicholson or Monte Carlo), the quant writes up a program and moves on to the next challenge.

It is when the trading desk picks up the pricing spreadsheet and books the first trade into the system that the fun begins. Then the trade takes on a life of its own, sneaking through various departments and systems, showing different strokes to different folks. This adventurous biography of the trade is depicted in Figure 1 in its simplified form.

At the inception stage, a trade is conceptualized by the Front Office folks (বিক্রয়, structuring, trading desk – shown in yellow ovals in the figure). They study the market need and potential, and assess the trade viability. Once they see and grab a market opportunity, a trade is born.

Fig. 1: Life of a Trade

Even with the best of quant models, a trade cannot be priced without market data, such as prices, Volatilities, rates and correlations and so on. The validity of the market data is ensured by Product Control or Market Risk people. The data management group also needs to work closely with Information Technology (IT) to ensure live data feeds.

The trade first goes for a counterparty credit control (the pink bubbles). The credit controllers ask questions like: if we go ahead with the deal, how much will the counterparty end up owing us? Does the counterparty have enough credit left to engage in this deal? Since the credit exposure changes during the life cycle of the trade, this is a minor quant calculation on its own.

বস্তুত, the Front Office can do the deal only after the credit control approves of it. Credit Risk folks use historical data, internal and external credit rating systems, and their own quantitative modelling team to come up with counterparty credit limits and maximum per trade and netted exposures.

Right after the trade is booked, it goes through some control checks by the Middle Office. These fine people verify the trade details, validate the initial pricing, apply some reasonable reserves against the insane profit claims of the Front Office, and come up with a simple yea or nay to the trade as it is booked. If they say yes, the trade is considered validated and active. যদি না, the trade goes back to the desk for modifications.

After these inception activities, trades go through their daily processing. In addition to the daily (or intra-day) hedge rebalancing in the Front Office, the Market Risk Management folks mark their books to market. They also take care of compliance reporting to regulatory bodies, as well as risk reporting to the upper management — a process that has far-reaching consequences.

The Risk Management folks, whose work is never done as Tracy Chapman would say, also perform scenario, stress-test and historical Value at Risk (আছে) computations. In stress-tests, they apply a drastic market movement of the kind that took place in the past (like the Asian currency crisis or 9/11) to the current market data and estimate the movement in the bank’s book. In historical VaR, they apply the market movements in the immediate past (typically last year) and figure out the 99 percentile (or some such pre-determined number) worst loss scenario. Such analysis is of enormous importance to the senior management and in regulatory and compliance reporting. In Figure 1, the activities of the Risk Management folks are depicted in blue bubbles.

In their attempts to rein in the ebullient traders, the Risk Management folks come across in their adversarial worst. But we have to remind ourselves that the trading and control processes are designed that way. It is the constant conflict between the risk takers (ফ্রন্ট অফিস) and the risk controllers (Risk Management) that implements the risk appetite of the bank as decided by the upper management.

Another group that crunches the trade numbers every day from a slightly different perspective are the Product Control folks, shown in green in Figure 1. They worry about the daily profit and loss (পি / L) movements both at trade and portfolio level. They also modulate the profit claims by the Front Office through a reserving mechanism and come up with the so called unrealized P/L.

This P/L, unrealized as it is, has a direct impact on the compensation and incentive structure of Front Office in the short run. Hence the perennial tussle over the reserve levels. In the long term, তবে, the trade gets settled and the P/L becomes realized and nobody argues over it. Once the trade is in the maturity phase, it is Finance that worries about statistics and cash flows. Their big picture view ends up in annual reports and stake holders meetings, and influences everything from our bonus to the CEO’s new Gulfstream.

Trades are not static entities. During the course of their life, they evolve. Their evolution is typically handled by Middle Office people (grey bubbles) who worry about trade modifications, fixings, knock-ins, knock-outs etc. The exact name given to this business unit (and indeed other units described above) depends on the financial institution we work in, but the trade flow is roughly the same.

The trade flow that I described so far should ring alarm bells in a quant heart. Where are the quants in this value chain? ভাল, they are hidden in a couple of places. Some of them find home in the Market Risk Management, validating pricing models. Some others may live in Credit Risk, estimating peak exposures, figuring out rating schemes and minimising capital charges.

Most important of all, they find their place before a trade is ever booked. Quants teach their home banks how to price products. A financial institution cannot warehouse the risk associated with a trade unless it knows how much the product in question is worth. It is in this crucial sense that model quants drive the business.

In a financial marketplace that is increasingly hungry for customized structures and solutions, the role of the quants has become almost unbearably vital. Along with the need for innovative models comes the imperative of robust platforms to launch them in a timely fashion to capture transient market opportunities.

In our better investment banks, such platforms are built in-house. This trend towards self-reliance is not hard to understand. If we use a generic trading platform from a vendor, it may work well for established (read vanilla) পণ্য. It may handle the established processes (read compliance, reporting, settlements, audit trails etc.) ভাল. But what do we do when we need a hitherto unknown structure priced? We could ask the vendor to develop it. কিন্তু তারপর, they will take a long time to respond. এবং, when they finally do, they will sell it to all our competitors, or charge us an arm and a leg for exclusivity thereby eradicating any associated profit potential.

Once a vended solution is off the table, we are left with the more exciting option of developing in-house system. It is when we design an in-house system that we need to appreciate the big picture. We will need to understand the whole trade flow through the different business units and processes as well as the associated trade perspectives.

ট্রেড দৃষ্টিভঙ্গি

The perspective that is most common these days is trade-centric. এই দেখুন, trades are the primary objects, which is why conventional trading systems keep track of them. একসঙ্গে কাজে গুচ্ছ রাখুন, আপনি একটি পোর্টফোলিও পেতে. একসঙ্গে কয়েক পোর্টফোলিও রাখুন, আপনি একটি বই আছে. পুরো গ্লোবাল মার্কেটস বই নিছক একটি সংগ্রহ. এই দৃষ্টান্ত ভাল কাজ করেছে এবং বিভিন্ন সম্ভাব্য দেখ মধ্যে সেরা আপস সম্ভবত.

But the trade-centric perspective is only a compromise. ট্রেডিং তলায় কার্যক্রম বিভিন্ন দৃষ্টিকোণ থেকে দেখা যাবে. Each view has its role in the bigger scheme of things in the bank. কিভাবে, উদাহরণস্বরূপ, are model-centric. They try to find commonality between various products in terms of the underlying mathematics. If they can reuse their models from one product to another, potentially across asset classes, they minimize the effort required of them. Remember how Merton views the whole world as options! I listened to him in amazement once when he explained the Asian currency crisis as originating from the risk profile of compound options — the bank guarantees to corporate clients being put options, government guarantees to banks being put options on put options.

Unlike quants who develop pricing models, quantitative developers tend to be product-centric. তাদের, it doesn’t matter too much even if two different products use very similar models. They may still have to write separate code for them depending on the infrastructure, market data, conventions etc.

Traders see their world from the asset class angle. সাধারণত সম্পত্তির ক্লাস উপর ভিত্তি করে একটি নির্দিষ্ট ট্রেডিং desks সঙ্গে যুক্ত, their favourite view cuts across models and products. ব্যবসায়ীদের, all products and models are merely tools to making profit.

IT folks view the trading world from a completely different perspective. তাদের একটি সিস্টেম কেন্দ্রিক দেখুন, where the same product using the same model appearing in two different systems is basically two different beasts. এই দেখুন, বিশেষ করে ব্যবসায়ীদের দ্বারা প্রশংসা করা হয় না, বা কিভাবে অনেক ডেভেলপার.

One view that all of us appreciate is the view of the senior management, একটুর জন্য নিচের লাইন এফআরএস হয়, যা. বড় bosses কিছু অগ্রাধিকার (পণ্য কিনা, সম্পত্তির ক্লাস বা সিস্টেম) অর্থ শর্তাবলী তারা শেয়ারহোল্ডারদের আনা. Models and trades are typically not visible from their view — যদি না, অবশ্যই, দুর্বৃত্ত ব্যবসায়ীদের একটি নির্দিষ্ট পণ্য বা একটি নির্দিষ্ট মডেল ব্যবহার করে অনেক টাকা নষ্ট. বা, somewhat less likely, they make huge profits using the same tricks.

When the trade reaches the Market Risk folks, একটি পোর্টফোলিও বা বই স্তর দেখুন একটি ট্রেড স্তর দৃশ্য দৃষ্টিকোণ থেকে একটি সূক্ষ্ম পরিবর্তন আছে. গাণিতিকভাবে তুচ্ছ যদিও (সব পরে, পার্থক্য অ্যাগ্রিগেশন শুধুমাত্র একটি ব্যাপার), এই পরিবর্তন সিস্টেম নকশা বিষয় রয়েছে. Trading systems have to maintain a robust hierarchical portfolio structure so that various dicing and slicing as required in the later stages of the trade lifecycle can be handled with natural ease.

The busy folks in the Middle Office (who take care of trade validations and modifications) are obsessed with trade queues. They have a validation queue, market operation queue etc. আবার, the management of queues using status flags is something we have to keep in mind while designing an in-house system.

When it comes to Finance and their notions of cost centres, বাণিজ্য বুকিং সিস্টেমের বাইরে প্রায় কাছাকাছি. কিন্তু, they manage trading desks and asset classes cost centres. কোন ট্রেডিং প্ল্যাটফর্ম আমরা নকশা সেইসাথে তাদের নির্দিষ্ট প্রয়োজনীয়তা সাড়া সিস্টেমের মধ্যে পর্যাপ্ত আঙ্গুলসমূহ প্রদান করেছে.

Quants and the Big Picture

সবচেয়ে কয়েক, বিশেষ করে জুনিয়র পর্যায়ে, despise the Big Picture. তারা সি সম্ভাব্যতার সূত্রাবলি পাথুরি বিয়ে তাদের বাস্তব কাজ থেকে ক্ষোভ হিসাবে মনে . Changing that mindset to some degree is the hidden agenda behind this column.

As my trader friends will agree, এটি স্থাপন করা যাবে না, যদি না বিশ্বের সেরা মডেল অখাদ্য. Deployment is the fast track to the big picture — no point denying it. এছাড়া, in an increasingly interconnected world where a crazy Frenchman’s actions instantly affect our bonus, what is the use of denying the existence of the big picture in our nook of the woods? পরিবর্তে, let’s take advantage of the big picture to empower ourselves. Let’s bite the bullet and sit through a “Big Picture 101.”

আমরা আমাদের সংকীর্ণ পরিবর্তন, কার্যকর যদ্যপি, প্রতিষ্ঠানের মধ্যে একটি আমাদের ভূমিকা বোঝার এবং মান হাতে কাজ ফোকাস, we will see the potential points of failure of the systems and processes. We will be prepared with possible solutions to the nightmarish havoc that computerized processes can wreak. And we will sleep easier.

Risks and Rewards

Everything in life comes at a cost — with a price tag seldom denominated in dollars and cents, and almost always hidden.

In our profession as quants and traders, we know we cannot accumulate if we don’t speculate (as P. জি. Wodehouse puts it). So we accept and even welcome some of these price tags. We take certain risks, which we hope are calculated and understood, so that we can bring unto our employers what is theirs. These are good risks.

Bad risks are those we cannot understand and quantify, or measure and hedge against. They are bad because, even if we rake in some profits, we are never sure that they are commensurate with the downside we are throwing ourselves open to.
Market risk is a good risk. We know how to measure and model it, hedge against and reap rewards from it. We have smart people with bulging foreheads solving stochastic differential equations for us and simplifying the risk-reward equation.

Operational risk is a bad one. We can put as many software locks and control processes as we want around it. But we cannot prevent the rogue elements amongst us from sharing their passwords over a beer in some French brasserie. আরও খারাপ, we have no idea what the rewards are when we expose ourselves to certain levels of operational risk. নরক, we don’t even know what the levels are because we have no means of quantifying it.

Incomplete appreciation of the risks involved in many situations is an almost philosophical factor that comes around to haunt us. It is not that we underestimate the risks; it is more like we are not aware of certain ramifications. The inconvenient warming of our home planet, উদাহরণস্বরূপ, is a consequence that the Wright brothers and Henry Ford simply could not have been aware of.

No such thing as a free lunch — the seemingly unlimited and practically free supply of nuclear energy has a not-so-hidden cost: the necessity to dispose of or securely store dangerous waste for, বলে, twenty thousand years. How do you store something for that long? সব পরে, twenty thousand years ago, we were only barely human!

But the list of such boons and associated banes is endless. Think of the prosperity that a flattened world (using Thomas Friedman’s lingo) brought to emerging economies like India and China, which came at the expense of the cultural values that took thousands of years of careful nurturing.

A personal ramification of our high-powered corporate life is the alarming level of stress that we put ourselves through. Stress comes from market movements. As the sub-prime market tanked and heads started to roll, some of us had to worry about our heads. Fat bonuses of the first quarter usher in tax worries; lean bonuses indicate uncertain corporate future. Rogue traders burn billions and expose everybody to scrutiny and associated stresses. Even the lack of stress brings in some worries that the corporate world is perhaps passing us by!

When I first switched to the finance industry in late 2005, I happened to flip through an issue of the Bloomberg Market magazine. On of the first things struck me was that most of the advertisements seemed to be of expensive cars or alcohol. Is alcoholism the cost we readily dish out so that we can afford a gleaming dream machine?

Is stress a price worth paying for our corporate success? Are the risks worth their rewards?

Married to the Job — Till Death Do Us Part?

Stress is as much a part of our corporate careers as death is a fact of life. কিন্তু, it is best to keep the two (career and death) separate. This is the message that was lost on some hardworking young souls here in Singapore who literally worked themselves to death. So do a lot of Japanese, if we are to believe the media.

The reason for death in sedentary jobs is the insidious condition called deep vein thrombosis. This condition develops because of extended hours spent sitting, when a blood clot forms in the lower limbs. The clot then travels to the vital organs in the upper body, where it wreaks havoc including death.

The trick in avoiding such an untimely demise, অবশ্যই, is not to sit for long. But that is easier said than done, when job pressure mounts, and deadlines loom.

Here is where you have to get your priorities straight. What do you value more? Quality of life or corporate success? The implication in this choice is that you can’t have both, as illustrated in the joke in investment banking that goes like: “If you can’t come in on Saturday, don’t bother coming in on Sunday!”

আপনি, তবে, make a compromise. It is possible to let go a little bit of career aspirations and improve the quality of life tremendously. This balancing act is not so simple though; nothing in life is.

Undermining work-life balance are a few factors. One is the materialistic culture we live in. It is hard to fight that trend. Second is a misguided notion that you can “make it” প্রথম, then sit back and enjoy life. That point in time when you are free from worldly worries rarely materializes. তৃতীয়ত, you may have a career-oriented partner. Even when you are ready to take a balanced approach, your partner may not be, thereby diminishing the value of putting it in practice.

These are factors you have to constantly battle against. And you can win the battle, with logic, discipline and determination. তবে, there is a fourth, much more sinister, factor, which is the myth that a successful career is an all-or-nothing proposition, as implied in the preceding investment banking joke. It is a myth (perhaps knowingly propagated by the bosses) that hangs over our corporate heads like the sword of Damocles.

Because of this myth, people end up working late, trying to make an impression. But an impression is made, not by the quantity of work, but by its quality. Turn in quality, impactful work, and you will be rewarded, regardless of how long it takes to accomplish it. Long hours, আমার দৃশ্যে, make the possibility of quality work remote.

Such melancholy long hours are best left to workaholics; they keep working because they cannot help it. It is not so much a career aspiration, but a force of habit coupled with a fear of social life.

To strike a work-life balance in today’s dog eat dog world, you may have to sacrifice a few upper rungs of the proverbial corporate ladder. Raging against the corporate machine with no regard to the consequences ultimately boils down to one simple realization — that making a living amounts to nothing if your life is lost in the process.

Spousal Indifference — Do We Give a Damn?

After a long day at work, you want to rest your exhausted mind; may be you want to gloat a bit about your little victories, or whine a bit about your little setbacks of the day. The ideal victim for this mental catharsis is your spouse. But the spouse, in today’s double income families, is also suffering from a tired mind at the end of the day.

The conversation between two tired minds usually lacks an essential ingredient — the listener. And a conversation without a listener is not much of a conversation at all. It is merely two monologues that will end up generating one more setback to whine about — spousal indifference.

Indifference is no small matter to scoff at. It is the opposite of love, if we are to believe Elie Weisel. So we do have to guard against indifference if we want to have a shot at happiness, for a loveless life is seldom a happy one.

“Where got time?” ask we Singaporeans, too busy to form a complete sentence. এর… সময়! At the heart of all our worldly worries. We only have 24 hours of it in a day before tomorrow comes charging in, obliterating all our noble intensions of the day. And another cycle begins, another inexorable revolution of the big wheel, and the rat race goes on.

The trouble with the rat race is that, এটা শেষে, even if you win, you are still a rat!

How do we break this vicious cycle? We can start by listening rather than talking. Listening is not as easy as it sounds. We usually listen with a whole bunch of mental filters turned on, constantly judging and processing everything we hear. We label the incoming statements as important, দরকারী, trivial, pathetic, ইত্যাদি. And we store them away with appropriate weights in our tired brain, ignoring one crucial fact — that the speaker’s labels may be, and often are, completely different.

Due to this potential mislabeling, what may be the most important victory or heartache of the day for your spouse or partner may accidentally get dragged and dropped into your mind’s recycle bin. Avoid this unintentional cruelty; turn off your filters and listen with your heart. As Wesley Snipes advises Woody Herrelson in White Men Can’t Jump, listen to her (or him, as the case may be.)

It pays to practice such an unbiased and unconditional listening style. It harmonizes your priorities with those your spouse and pulls you away from the abyss of spousal apathy. But it takes years of practice to develop the proper listening technique, and continued patience and deliberate effort to apply it.

“Where got time?” we may ask. ভাল, let’s make time, or make the best of what little time we got. অন্যথায়, when days add up to months and years, we may look back and wonder: Where is the life that we lost in living?

চাপ এবং অনুপাত একটা ধারনা

আমরা মানসিক চাপ ও পরিচালনা করতে পারেন, এটা আমাদের কর্পোরেট অস্তিত্ব অনিবার্য যে দেওয়া? স্ট্রেস বিরুদ্ধে প্রচলিত কৌশল ব্যায়াম অন্তর্ভুক্ত, যোগশাস্ত্র, ধ্যান, শ্বাস কৌশল, পরিবার ইত্যাদি reprioritizing. এই তালিকায় যোগ করুন, আমি আপনার সাথে শেয়ার করতে চাই যে চাপ যুদ্ধ আমার নিজের গোপন অস্ত্র আছে. এই অস্ত্র খুব ক্ষমতাশালী হতে পারে; তাই যত্ন সঙ্গে তাদের ব্যবহার.

আমার গোপন কৌশল এক অনুপাত একটা ধারনা বিকাশ হয়, এটা শব্দ হতে পারে নিরীহ. অনুপাত সংখ্যার পদ হতে পারে. এর ব্যক্তি সংখ্যা দিয়ে শুরু করা যাক, উদাহরণস্বরূপ. প্রতি সকালে, আমরা কাজ করতে আসা, আমরা নির্দলীয় মুখের হাজার হাজার দেখতে, প্রায় সব তাদের নিজ নিজ কাজ করে যাচ্ছে. তাদের তাকান একটি মুহূর্ত নিন — তাদের নিজস্ব ব্যক্তিগত চিন্তা এবং খেয়াল সঙ্গে প্রতিটি, উদ্বেগ এবং চাপ.

তাদের প্রতিটি, শুধুমাত্র বাস্তব চাপ তাদের নিজস্ব. আমরা জানি যে, একবার, কেন আমরা অন্য কেহ তুলনায় আমাদের নিজস্ব মানসিক চাপ কোন গুরুত্বপূর্ণ রাখা হবে? ব্যক্তিগত নিছক সংখ্যার রসাস্বাদন আমাদের চারপাশের সব চাপ, আমরা এটা সম্পর্কে চিন্তা করা বন্ধ করে, দৃষ্টিভঙ্গি আমাদের উদ্বেগ করা হবে.

আমাদের আকার শর্তাবলী অনুপাত এছাড়াও উপর চিন্তা করার কিছু. আমরা আমাদের কাজের যে একটি বড় বিল্ডিং এর একটি ক্ষুদ্র ভগ্নাংশ ব্যাপৃত. (পরিসংখ্যানগত ভাষী, এই কলামের পাঠক একটি বড় কোণার অফিস ব্যাপৃত সম্ভবত হয় না!) ভবন আমাদের প্রিয় শহর যে স্থান একটি ক্ষুদ্র ভগ্নাংশ দখল করে. সমস্ত শহর বিশ্বের মানচিত্রে একটি বিন্দু সাধারণত তাদের আকার একটি অতিরঞ্জন, যাতে অতি ক্ষুদ্র.

আমাদের বিশ্বের, পৃথিবী, ধুলো একটি নিছক কণিকা কয়েক মাইল একটি উল্কা থেকে, আমরা কোনো অনুমেয় আকারের একটি উল্কা যেমন সূর্য যদি মনে করেন. সূর্য এবং তার সৌর সিস্টেম আপনি যদি আপনার পিসিতে ওয়ালপেপার হিসাবে আমাদের ছায়াপথ ছবি লাগাতে যাতে অতি ক্ষুদ্র, তারা কয়েক হাজার স্থানীয় বড় সঙ্গে একটি পিক্সেল ভাগ করা হবে! এবং আমাদের ছায়াপথ — আমার সম্পর্কে যে শুরু না! আমরা তাদের অগণিত কোটি কোটি আছে. আমাদের অস্তিত্ব (সব আমাদের উদ্বেগ এবং চাপ দিয়ে) is almost incomprehensibly small.

আমাদের অস্তিত্বের অর্থহীনতা স্থান মধ্যে সীমাবদ্ধ থাকবে না; এটি হিসাবে ভাল সময় প্রসারিত করে. এটা অনুপাত একটা ধারনা আসে যখন সময় চতুর. এর মহাবিশ্ব হিসাবে মনে করি 45 পুরাতন বছর. কতক্ষণ আপনি আমাদের অস্তিত্ব যে স্কেল মধ্যে মনে হয় না? Eight seconds if we are very lucky!

আমরা তারা ধুলো আউট তৈরি করা হয়, একটি নিছক মহাজাগতিক তাত্ক্ষণিক জন্য গত, এবং তারপর তারা ধুলো মধ্যে আবার চালু. এই সময় ডিএনএ মেশিন, আমরা অজানা জেনেটিক আলগোরিদিম চালানো, আমরা আমাদের আকাঙ্খার এবং সাফল্য জন্য ভুল যা, বা চাপ এবং বিরক্তির. শিথিল করা! চিন্তা করবেন না, ভাল থাকা!

অবশ্যই, যে রিপোর্ট আগামীকাল বাইরে যেতে না হয়, তাহলে আপনি তিরস্কার করতে পারে. বা, your trader may bite your head off if that pricing model is delayed again. বা, আপনার সহকর্মী যে backstabbing ইমেল প্রেরণ করতে পারেন (ও Bcc আপনার বস) আপনি তাদের অসন্তুষ্ট যদি. কিন্তু, don’t you get it, এই মন numbingly বিশাল বিশাল মহাবিশ্বের, এটা একটা তিল কোন ব্যাপার না. কিছু বড় বড় প্রকল্প, আপনার মানসিক চাপ এমনকি স্ট্যাটিক শব্দ হয় না!

মানসিক চাপ সব একটি স্তর বজায় রাখার জন্য আর্গুমেন্ট একটি মন্দ ভাবা ধারণা উপর নির্ভর যে চাপ এইডস উত্পাদনশীলতা. এটা না. উত্পাদনশীলতা কী কাজ এ আনন্দের একটি মনোভাব হয়. আপনি reprimands এবং backstabs এবং accolades সম্পর্কে উদ্বেজক বন্ধ যখন, এবং শুরু আপনি কি করবেন সেবন, উৎপাদনশীলতা ঠিক এরকম. আমি এটি একটি বিট আদর্শবাদী এটাতো জানেন, কিন্তু কাজ আমার সবচেয়ে উৎপাদনশীল টুকরা যে ভাবে ঘটেছে. সেবন আমি কি আমি কোন দিনের জন্য অঙ্কুর হবে একটি আদর্শ.

Stress and Metaphysics

Realizing that our existence is a mere blink of an eye in time, and less than a speck of dust in space is a powerful way of cutting our stress to size. My favorite weapon, তবে, is even more potent. I ask myself a basic question — what are space and time to begin with?

These may sound like silly metaphysical musings that have no relevance to real life. But they have been the subject matter of many lifelong quests over the ages. If we, humanity as a whole, cannot stop pondering over such things, it is probably because they form the basis of our existence. এছাড়া, our stress takes place in space and time.

Philosophical grand-standing aside, let’s get to the meat of the problem: স্থান কি? Space seems to be closely associated with our sense of sight. It also forms the basis of our reality — everything happens in space and time. এই কারণে, “What are space and time?” is a question that cannot be reduced to simpler elements in our reality.

We can, তবে, approach the issue by posing a similar question “What is sound?” Sound is an experience associated with hearing, পরিষ্কারভাবে. But what is it? The answer is hinted at in the age-old conundrum of a falling tree in a deserted forest. Does it make sound? A popular topic of conservation in cocktail parties, this question is also a serious contemplative inquiry for a Zen monk.

The knee-jerk response to the question is, হাঁ, the tree does make sound. It’s just that there is nobody to hear it. But hear what exactly?

অবশ্যই, the falling tree creates air pressure waves. কিন্তু, the waves are not sound. These waves create an electrical signal in the ear, if an ear is present. Electrical signals are electrical signals, not sound. These signals, when transported to the brain, induce neuronal firing, which is still not sound. It is a fallacy to think of sound as anything physical, anything real. Sound is an experience or a cognitive representation associated with the input signals (which are the pressure waves, we think. But are they?)

We can draw similar analogies between other sensations and the corresponding signals — taste and smell to chemical composition, উদাহরণস্বরূপ. What about sight? What is the “sensation” or the cognitive representation associated with sight? It is what we think of as space.

অবশ্যই, we think of space as real, as the basis of our reality. It takes more than this short column to shake our belief in it. That’s why I wrote my book — অবাস্তব ইউনিভার্স.

আমার, the unreal nature of what we consider reality is more than a constant contemplation. It is a source of a Zen-like immunity against stress and other worldly worries.

হ্যাঁ, stress is the cost exacted by the corporate chain of command. It is a cost most of us happily pay, for the rewards are abundantly clear. But we have to be aware of the risks associated with the rewards — both in accepting them and in declining them.

Quant Talent Management

The trouble with quants is that it is hard to keep them anchored to their moorings. Their talent is in high demand for a variety of reasons. The primary reason is the increasing sophistication of the banking clients, who demand increasingly more structured products with specific hedging and speculative motives. Servicing their demand calls for a small army of quants supporting the trading desks and systems.

Since structured products are a major profit engine on the trading floor of most banks, this demand represents a strong pull factor for quants from competing institutions. There is nothing much most financial institutions can do about this pull factor, except to pull them back in with offers they can’t refuse.

But we can try to eliminate the push factors that are hard to identify. These push factors are often hidden in the culture, ethics and the way things get done in institutions. তারা, সুতরাং, specific to the geographical location and the social settings where the banks operate.

Performance Appraisal — Who Needs It?

Performance appraisal is a tool for talent retention, if used wisely. কিন্তু, if misused, it can become a push factor. Are there alternatives that will aid in retaining and promoting talent?

As it stands now, we go through this ordeal of performance appraisal at least once every year. Our career progression, bonus and salary depend on it. So we spend sleepless nights agonizing over it.

In addition to the appraisal, we also get our “key performance indicators” or KPIs for next year. These are the commandments we have to live by for the rest of the year. The whole experience of it is so unpleasant that we say to ourselves that life as an employee sucks.

The bosses fare hardly better though. They have to worry about their own appraisals by bigger bosses. On top of that, তারা আমাদের জন্য KPI আজ্ঞাও তৈরি করতে হবে,,en,একটি পেশা প্রশংসনীয় প্রতিবাদ প্রতিনিধিত্ব করা কঠিন,,en,তারা নিজেদেরকে বলছে যে তাদের মনিব হিসাবে তাদের জীবন হ্রাস পায়,,en,যে কর্মক্ষমতা মূল্যায়ন ব্যায়াম সম্পর্কে কেউ রোমাঞ্চিত হয় দেওয়া,,en,আমরা এটা কেন করছি,,en,কে এটা প্রয়োজন,,en,কর্মক্ষমতা মূল্যায়ন পিছনে উদ্দেশ্য মহান,,en,এটি ভাল পারফরম্যান্সের প্রতিফলন এবং দরিদ্র শোকে শাস্তি প্রদান করে,,en,পুরানো গাজর এবং লাঠি ব্যবস্থাপনা পারাদিগম,,en,এই উদ্দেশ্য সহজে আনুষ্ঠানিক মূল্যায়ন প্রক্রিয়া প্রয়োজন ছাড়া একটি ছোট প্রতিষ্ঠানের মধ্যে পূরণ করা হয়,,en,ছোট ব্যবসা মালিকরা জানেন কে রাখা এবং কে ছালা,,en,কিন্তু হাজার হাজার কর্মচারীর সাথে একটি বৃহৎ কর্পোরেট সংস্থা,,en,কিভাবে আপনি একটি ন্যায্য এবং সামঞ্জস্যপূর্ণ ক্ষতিপূরণ প্রকল্প ডিজাইন করবেন,,en,সমাধান,,en,পরামর্শদাতা ফর্মগুলির ডিজাইন করে এবং একটি ইউনিফর্ম প্রক্রিয়া সংজ্ঞায়িত করার জন্য একটি সুনির্দিষ্ট অর্থ প্রদান করতে হয়,,en — a job pretty darned difficult to delegate. সব সম্ভাবনা, they say to themselves that their life as a boss sucks!

Given that nobody is thrilled about the performance appraisal exercise, why do we do it? Who needs it?

The objective behind performance appraisal is noble. It strives to reward good performance and punish poor shows — the old carrot and stick management paradigm. This objective is easily met in a small organization without the need for a formal appraisal process. Small business owners know who to keep and who to sack. But in a big corporate body with thousands of employees, how do you design a fair and consistent compensation scheme?

The solution, অবশ্যই, is to pay a small fortune to consultants who design appraisal forms and define a uniform processtoo uniform, সম্ভবত. Such verbose forms and inflexible processes come with inherent problems. One problem is that the focus shifts from the original objective (carrot and stick) to fairness and consistency (one-size-fits-all). আপনি মনে করবেন না, most bosses know who to reward and who to admonish. But the HR department wants the bosses to follow a uniform process, thereby increasing everybody’s workload.

Another, more insidious problem with this consultancy driven approach is that it is necessarily geared towards mediocrity. When you design an appraisal process to cater to everybody, the best you can hope to achieve is to improve the average performance level by a bit. Following such a process, the CERN scientist who invented the World Wide Web would have fared badly, for he did not concentrate on his KPIs and wasted all his time thinking about file transfers!

CERN is a place that consistently produces Nobel laureates. How does it do it? Certainly not by following processes that are designed to make incremental improvements at the average level. The trick is to be a center for excellence which attracts geniuses.

অবশ্যই, it is not fair to compare an average bank with CERN. But we have to realize that the verbose forms, which focus on averages and promote mediocrity, are a poor tool for innovation management, especially when we are trying to retain and encourage excellence in quant talent.

A viable alternative to standardized and regimented appraisal processes is to align employee objectives with those of the institutions and leave performance and reward management to bosses. With some luck, this approach may retain fringe geniuses and promote innovation. অন্ততপক্ষে, it will alleviate some employee anxiety and sleepless nights.

To Know or Not To Know

One peculiar push factor in the Asian context is the lack of respect for technical knowledge. Technical knowledge is not always a good thing in the modern Asian workplace. যদি আপনি সতর্ক থাকুন না, অন্যদের আপনার দক্ষতার সদ্ব্যবহার করা এবং আপনি তাদের দায়িত্ব ডাম্প হবে. আপনি যতদিন তারা আপনার দক্ষতা সম্মান হিসাবে এটি মনে না হতে পারে. কিন্তু, প্রায়ই তারা আপনার কাজের জন্য ক্রেডিট বরা এবং মানুষ ব্যবস্থাপনা দক্ষতা হিসাবে কাজ টালা তাদের ক্ষমতা উপস্থাপন.

People management is better rewarded than technical expertise. This differentiation between experts and middle-level managers in terms of rewards is a local Asian phenomenon. এখানে, those who present the work seem to get the credit for it, regardless of who actually performs it. We live in a place and time where articulation is often mistaken for accomplishments.

In the West, technical knowledge is more readily recognized than smooth presentations. You don’t have to look beyond Bill Gates to appreciate the heights to which technical expertise can take you in the West. অবশ্যই, Gates is more than an expert; he is a leader of great vision as well.

Leaders are different from people managers. Leaders provide inspiration and direction. They are sorely needed in all organizations, big and small.

Unlike people mangers, quants and technical experts are smart cookies. They can easily see that if they want to be people managers, they can get started with a tie and a good haircut. If the pickings are rich, why wouldn’t they?

This Asian differentiation between quants and managers, সুতরাং, makes for a strong push factor for some quants who find it worthwhile to hide their technical skills, get that haircut, grab that tie, and become a people manager. অবশ্যই, it comes down to your personal choice between fulfilment and satisfaction originating from technical authority on the one hand, and convenience and promotions arising from people skills on the other.

I wonder whether we have already made our choices, even in our personal lives. We find fathers who cannot get the hang of changing diapers household chores. Is it likely that men cannot figure out washing machines and microwaves although they can operate complicated machinery at work? We also find ladies who cannot balance their accounts and estimate their spending. Is it really a mathematical impairment, or a matter of convenience? সময়ে সময়ে, the lack of knowledge is as potent a weapon as its abundance.

How Much is Talent Worth?

Banks deal in money. Our profession in finance teaches us that we can put a dollar value to everything in life. Talent retention is no different. After taking care of as much of the push factors as we can, the next question is fairly simple: How much does it take to retain talent?

My city-state of Singapore suffers from a special disadvantage when it comes to talent management. We need foreign talent. It is nothing to feel bad about. It is a statistical fact of life. For every top Singaporean in any field — be it finance, science, medicine, sports or whatever — we will find about 500 professionals of equal calibre in China and India. Not because we are 500 times less talented, just that they have 500 times more people.

অপ্রতিরোধ্য পরিসংখ্যান শীর্ষকতার সঙ্গে মিলিত,,en,নির্দিষ্ট কিছু দেশে তাদের নির্বাচিত বা দুর্ঘটনাজনিত বিশেষজ্ঞগণের মধ্যে বিশেষ শ্রেষ্ঠত্ব রয়েছে,,en,আমরা চীন মধ্যে আরো হার্ডওয়্যার বিশেষজ্ঞদের খুঁজে আশা করি,,en,ভারতে আরও সফটওয়্যার গুরু,,en,ইন্দোনেশিয়ার আরও ব্যাডমিন্টন খেলোয়াড়,,en,পশ্চিমে আরো উদ্যোক্তা আত্মা এবং ব্যবস্থাপক দক্ষতা,,en,আমরা যেমন বিশেষজ্ঞদের প্রয়োজন,,en,তাই আমরা তাদের ভাড়া,,en,কিন্তু আমরা তাদের কত টাকা দিতে হবে,,en,এটা যেখানে অর্থনীতি আসে,,en,চাহিদা ও সরবরাহ,,en,আমরা সর্বনিম্ন সম্ভাব্য প্যাকেজ অফার যে প্রতিভা দানা হবে,,en,আমি একটি বিদেশী প্রতিভা হিসেবে সিঙ্গাপুর আসেন যখন আমি একটি প্রবাসী প্যাকেজ ছিল,,en,এটি একটি মোটামুটি উদার প্যাকেজ ছিল,,en,কিন্তু হুঁশিয়ার ভাষায় কথা বলে যে যদি আমি একজন হয়ে যাই,,en,স্থানীয়,,en,আমি বেশ কিছুটা হতাশ হব,,en,আমি কয়েক বছর পরে স্থানীয় হয়েছি,,en,এবং আমার ক্ষতিপূরণ একটি ফলাফল হিসাবে হ্রাস,,en,আমার প্রতিভা পরিবর্তন হয়নি,,en, certain countries have special superiority in their chosen or accidental specializations. We expect to find more hardware experts in China, more software gurus in India, more badminton players in Indonesia, more entrepreneurial spirit and managerial expertise in the west.

We need such experts, so we hire them. But how much should we pay them? That’s where economics comes in — demand and supply. We offer attractive expatriate packages that the talents would bite.

I was on an expatriate package when I came to Singapore as a foreign talent. It was a fairly generous package, but cleverly worded so that if I became a “local” প্রতিভা, I would lose out quite a bit. I did become local a few years later, and my compensation diminished as a consequence. My talent did not change, just the label from “foreign” থেকে “local.”

This experience made me think a bit about the value of talent and the value of labels. The local quant talents, too, are beginning to take note of the asymmetric compensation structure associated with labels. This asymmetry and the consequent erosion of loyalty introduce another push factor for the local quant talents, as if one was needed.

The solution to this problem is not a stricter enforcement of the confidentiality of salaries, but a more transparent compensation scheme free of anomalies that can be misconstrued as unfair practices. অন্যথায়, we may see an increasing number of Asian nationals using Singapore-based banks as a stepping stone to greener pastures. আরও খারাপ, we may see (as indeed we do, these days) locals seeking level playing fields elsewhere.

We need to hire the much needed talent whatever it costs; but let’s not mistake labels for talent.

Handling Goodbyes

Losing talent is an inevitable part of managing it. What do you do when your key quant hands in the dreaded letter? It is your worst nightmare as a manager! Once the dust settles and the panic subsides, you should ask yourself, what next?

Because of all the pull and push factors discussed so far, quant staff retention is a challenge. New job offers are becoming increasingly more irresistible. At some stage, someone you work closely with — be it your staff, your boss or a fellow team member — is going to say goodbye. Handling resignations with tact and grace is no longer merely a desirable quality, but an essential corporate skill today.

We do have some general strategies to deal with resignations. The first step is to assess the motivation behind the career choice. Is it money? যদি তাই হয়, a counter offer is usually successful. Counter offers (both making them and taking them) are considered ineffective and in poor taste. অন্তত, executive search firms insist that they are. কিন্তু তারপর, they would say that, wouldn’t they?

If the motivation behind the resignation is the nature of the current or future job and its challenges, a lateral movement or reassignment (possibly combined with a counter offer) can be effective. If everything fails, then it is time to bid goodbye — amicably.

It is vitally important to maintain this amicability — a fact often lost on bosses and HR departments. Understandably so because, by the time the counter offer negotiations fail, there is enough bitterness on both sides to sour the relationship. Brush those wounded feelings aside and smile through your pain, for your paths may cross again. You may rehire the same person. বা, you may end up working with him/her on the other side. Salvage whatever little you can for the sake of positive networking.

The level of amicability depends on corporate culture. Some organizations are so cordial with deserting employees that they almost encourage desertion. Others treat the traitors as the army used to — with the help of a firing squad.

Both these extremes come with their associated perils. If you are too cordial, your employees may treat your organization as a stepping stone, concentrating on acquiring only transferable skills. On the other extreme, if you develop a reputation for severe exit barriers in an attempt to discourage potential traitors, you may also find it hard to recruit top talent.

The right approach lies somewhere in between, like most good things in life. It is a cultural choice that an organization has to make. But regardless of where the balance is found, resignation is here to stay, and people will change jobs. পরিবর্তন, as the much overused cliché puts it, is the only constant.

আপ summing…

In a global market that demands ever more customization and structuring, there is an unbearable amount of pull factor for good quants. Quant talent management (acquisition and retention) is almost as challenging as developing quant skills yourself.

While powerless against the pull factor, banks and financial institutions should look into eliminating hidden push factors. Develop respect and appreciation for hard-to-replace talents. Invent innovative performance measurement metrics. Introduce fair and transparent compensation schemes.

When it all fails and the talent you so long to retain leaves, handle it with tact and grace. At some point in the future, you may have to hire them. Or worse, you may want to get hired by them!

Benford এবং তোমার ট্যাক্সসমূহ

কিছুই নির্দিষ্ট কিন্তু মৃত্যু এবং করের হয়, তারা বলে. মৃত্যুর সামনে, আমরা আমাদের সকল চিকিৎসা বিস্ময়কর কিছু inroads তৈরীর হয়, অন্তত এটা পিছিয়ে যদি না আসলে এটা এড়ানো. কিন্তু করের আসে, আমরা আমাদের ট্যাক্স রিটার্ন মধ্যে সৃজনশীলতা একটি বিট ছাড়া অন্য কোন প্রতিরক্ষা আছে.

এর আঙ্কেল স্যাম আপনি তাকে $ 75K পাওনা মনে করে শুরু করা যাক বলতে. আপনার সৎ মতামত, পরিষ্কার চিত্র $ 50k চিহ্ন সম্পর্কে. তাই আপনি যদি আপনার ট্যাক্স deductible রসিদ আঙুলে. হার্ড কাজ অগণিত ঘন্টা পর, fyou নিচে নম্বর আনা, বলে, $65থেকে. একটি quant হিসাবে, আপনি একটি IRS নিরীক্ষা সম্ভাবনা অনুমান করতে পারেন. এবং যদি আপনি একটি সংখ্যা করা যাবে (ডলার একটি প্রত্যাশা মূল্য) এটা থেকে হতে পারে যে ব্যথা ও দুর্ভোগ থেকে.

এর সম্পর্কে আপনি হতে একটি ট্যাক্স নিরীক্ষা ঝুঁকি নিরূপণ যে অনুমান করা যাক 1% এবং এটা $ 15K সুর আপনি সিদ্ধান্তগ্রহণ দাবি সৃজনশীল পেতে ঝুঁকি মূল্য যে সিদ্ধান্ত. আপনি ট্যাক্স রিটার্ন পাঠাতে এবং আঁট বসতে, জ্ঞান ফিটফাট নিরীক্ষিত হচ্ছে আপনার মধ্যে মতভেদ মোটামুটি পাতলা হয় যে. আপনি একটি বড় সারপ্রাইজ আছে. আপনি ভাল এবং সত্যিই যদৃচ্ছতা দ্বারা বোকা বানানো হবে, এবং IRS প্রায় অবশ্যই আপনার ট্যাক্স রিটার্ন সময়ে কাছাকাছি কটাক্ষপাত করতে হবে.

ট্যাক্স রিটার্ন গণনা সৃজনশীলতা কদাপি বহন করেনা বন্ধ. আশা ব্যথা এবং যাতনার আপনার গণনার IRS আপনি audits সঙ্গে যা ফ্রিকোয়েন্সি সঙ্গে সামঞ্জস্যপূর্ণ হয় না. একটি নিরীক্ষা সম্ভাবনা, আসলে, আপনি আপনার ট্যাক্স deductions ফোলান চেষ্টা অনেক বেশী. আপনি আপনার পক্ষে বিরুদ্ধে স্তুপীকৃত সম্ভাবনা এই নৈকতলীয় জন্য Benford দোষারোপ করতে পারেন.


Benford তার প্রবন্ধে খুব পাল্টা স্বজ্ঞাত কিছু উপস্থাপন [1] মধ্যে 1938. তিনি প্রশ্ন জিজ্ঞাসা: কোনো সাংখ্যিক প্রথম সংখ্যা বিতরণের কি, বাস্তব জীবনের তথ্য? এক নজরে, উত্তর হবে সুস্পষ্ট বলে মনে হয়. সব সংখ্যা একই সম্ভাবনা থাকা উচিত. কেন র্যান্ডম তথ্য যে কোন এক অঙ্ক করতে পছন্দ হতে পারে?

চিত্র 1. আর্থিক লেনদেনের ধারণাগত পরিমাণে প্রথম সংখ্যা সংঘটন এর ফ্রিকোয়েন্সি. রক্তবর্ণ বক্ররেখা পূর্বাভাস বন্টন. উল্লেখ্য যে অসম্মান বাহুল্যও এ 1 এবং 5 মানুষের মত নাগরিকদের নির্বাচন করার ঝোঁক, কারণ রক্তবর্ণ বক্ররেখা উপরে আশা করা হয় 1/5/10/50/100 মিলিয়ন. বাড়তি এ 8 এটা এশিয়ার একটি ভাগ্যবান সংখ্যা বিবেচনা করা হয় কারণ বলে আশা করা হচ্ছে.

Benford দেখিয়েছেন যে একটি প্রথম ডাক “প্রাকৃতিকভাবে” সংখ্যা হতে অনেক বেশি 1 বরং অন্য কোন ডাক চেয়ে. আসলে, প্রতিটি অঙ্ক প্রথম অবস্থান হচ্ছে একটি নির্দিষ্ট সম্ভাবনা আছে. ডাক 1 সর্বোচ্চ সম্ভাবনা আছে; ডাক 2 সম্পর্কে 40% এবং তাই প্রথম অবস্থান করা সম্ভাবনা কম. ডাক 9 সব, সর্বনিম্ন সম্ভাবনা আছে; এটি সম্পর্কে 6 প্রথম অবস্থান করা সম্ভাবনা কম বার.

আমি প্রথম একটি ওয়াকিফহাল সহকর্মী থেকে এই প্রথম ডাক ঘটনাটি শুনে, আমি এটা অদ্ভুত ছিল. আমি naively থেকে সব সংখ্যা জন্য ঘটনার প্রায় একই ফ্রিকোয়েন্সি দেখতে প্রত্যাশিত হবে 1 থেকে 9. তাই আমি আর্থিক তথ্য বৃহৎ পরিমাণ সংগ্রহ করা, সম্পর্কে 65000 সংখ্যা (এক্সেল অনুমতি দেয় হবে হিসাবে অনেক), এবং প্রথম অঙ্ক দিকে তাকিয়ে. আমি Benford একেবারে ডান হতে পাওয়া, চিত্র হিসাবে দেখানো হয়েছে 1.

প্রথম অঙ্ক সম্ভাবনা অভিন্ন থেকে বেশ দূরে, চিত্র হিসাবে 1 শো. বন্টন, আসলে, লগারিদমিক. কোনো অঙ্ক ঘ সম্ভাবনা লগ দেওয়া হয়(1 + 1 / ঘ), যা চিত্র রক্তবর্ণ বক্ররেখা 1.

এই skewed বন্টন আমি তাকান যে ঘটেছে তথ্য একটি ব্যতিক্রম হয় না. এটা কোনো নিয়ম “প্রাকৃতিকভাবে” তথ্য. এটা Benford এর আইন. Benford প্রাকৃতিকভাবে তথ্য একটি বৃহৎ সংখ্যা সংগ্রহ (সহ জনসংখ্যা, নদী এলাকায়, পদার্থবিদ্যার ধ্রুবকের, তাই সংবাদপত্র রিপোর্ট থেকে সংখ্যা) এবং এই গবেষণামূলক আইন সম্মান দেখিয়েছেন যে,.


একটি পরিমাণগত ডেভেলপার হিসেবে, আমি আমার সমস্যা বুঝতে সাহায্য করবে যে নিদর্শন দেখতে সক্ষম হবে আশা করি যে একটি কম্পিউটারে জিনিস অনুকরণ করার ঝোঁক. সিমুলেশন মধ্যে নিষ্পত্তি করা হবে প্রথম প্রশ্ন জিনিসটা কি একটি অস্পষ্ট পরিমাণ সম্ভাবনা বন্টন মত “স্বাভাবিকভাবেই সংখ্যা ঘটছে” হবে. আমি বন্টন আছে, আমি সংখ্যা উৎপন্ন এবং সংঘটন তাদের ফ্রিকোয়েন্সি দেখতে প্রথম সংখ্যা তাকান করতে পারেন.

একটি গণিতজ্ঞ অথবা একটি quant করুন, স্বাভাবিক লগারিদম যে আরো প্রাকৃতিক কিছুই নেই. তাই প্রাকৃতিকভাবে সংখ্যার জন্য প্রথম প্রার্থী বিতরণ আরভি Exp মত(আরভি), যেখানে আরভি একটি অবিশেষে বিতরণ র্যান্ডম পরিবর্তনশীল (শূন্য এবং দশ মধ্যে). এই পছন্দ পিছনে যুক্তিপূর্ণ প্রাকৃতিকভাবে সংখ্যায় ডিজিটের নম্বর অবিশেষে শূন্য এবং একটি ঊর্ধ্ব সীমা মধ্যে বিতরণ করা হয় যে একটি দায়িত্বগ্রহণ.

প্রকৃতপক্ষে, আপনি অন্যান্য চয়ন করতে পারেন, প্রাকৃতিকভাবে সংখ্যার জন্য কল্পনাকারী ডিস্ট্রিবিউশন. আমি দুই ব্যবহার করে অন্যান্য প্রার্থী ডিস্ট্রিবিউশন একটি দম্পতি অবিশেষে বিতরণ চেষ্টা (শূন্য এবং দশ মধ্যে) র্যান্ডম ভেরিয়েবল RV1 এবং RV2: RV1 Exp(RV2) এবং EXP(RV1 RV2). এই সব ডিস্ট্রিবিউশন স্বাভাবিকভাবেই সংখ্যা ঘটছে জন্য ভাল অনুমান হতে শয্যাত্যাগ, চিত্র দেখানো হিসাবে 2.

চিত্র 2. সিমুলেশন প্রথম সংখ্যা বিতরণের সংখ্যা "প্রাকৃতিকভাবে", ভবিষ্যদ্বাণী তুলনায়.

আমি সঠিকতার একটি ভুতুড়ে ডিগ্রী Benford এর আইন অনুসরণ উত্পন্ন যে সংখ্যা প্রথম সংখ্যা. কেন এই না ঘটতে? কম্পিউটার সিমুলেশন সম্পর্কে ভাল জিনিস হল যে আপনি গভীর খনন এবং অন্তর্বর্তী ফলাফল তাকান করতে পারেন. উদাহরণস্বরূপ, ডিস্ট্রিবিউশনের সাথে আমাদের প্রথম সিমুলেশন: আরভি Exp(আরভি), আমরা প্রশ্ন জিজ্ঞাসা করতে পারেন: আমরা একটি নির্দিষ্ট প্রথম ডাক পান, যার জন্য আরভি মান কি কি? উত্তর চিত্র 3 এ দেখানো হয়. উল্লেখ্য, প্রথম অঙ্ক দিতে আরভি মধ্যে রেঞ্জ 1 যে দিতে চেয়ে অনেক বড় 9. প্রায় ছয় গুণ বড়, আসলে, হিসাবে প্রত্যাশিত. প্যাটার্ন কৃত্রিম স্বাভাবিক সংখ্যার হিসাবে পুনরাবৃত্তি নিজেই লক্ষ্য করুন কিভাবে “উপর গুটানো” এর প্রথম অঙ্ক থেকে 9 থেকে 1 (একটি দূরত্বমাপণী দ্রুতগামী হিসাবে).

চিত্র 3 এ. একটি মধ্যে রেঞ্জ অবিশেষে বিতরণ (মধ্যে 0 এবং 10) আরভি Exp বিভিন্ন প্রথম সংখ্যা হতে যে দৈব চলক আরভি(আরভি). উল্লেখ্য, এর প্রথম অঙ্ক 1 বাকি তুলনায় অনেক বেশি ঘন ঘন ঘটে, হিসাবে প্রত্যাশিত.

একই প্রবণতা দুই র্যান্ডম ভেরিয়েবল সঙ্গে আমাদের কল্পনাকারী সিমুলেশন দেখা যায়. RV1 Exp বিভিন্ন প্রথম সংখ্যা বৃদ্ধি দিতে যে তাদের যৌথ ডিস্ট্রিবিউশন অঞ্চলে(RV2) চিত্র 3b দেখানো হয়. গভীর নীল বৃহৎ swathes লক্ষ্য করুন (প্রথম ডাক সংশ্লিষ্ট 1) এবং লাল swathes তাদের এলাকার তুলনা (প্রথম অবস্থান 9).

চিত্র 3B. দুই যুগ্ম বিতরণ অঞ্চলে অবিশেষে বিতরণ (মধ্যে 0 এবং 10) RV1 Exp বিভিন্ন প্রথম সংখ্যা হতে র্যান্ডম ভেরিয়েবল যে RV1 এবং RV2(RV2).

এই ব্যায়াম সম্পর্কে আমি সিমুলেশন থেকে সংগ্রহ প্রত্যাশী ছিল অন্তর্দৃষ্টি দেয়. প্রথম অবস্থানে ছোট সংখ্যা অধিকতর ভারী জন্য কারণ প্রাকৃতিকভাবে সংখ্যার বন্টন সাধারণত একটি সরু এক হয়; নম্বর একটি ঊর্ধ্ব সীমা থাকে, এবং আপনি উপরের সীমা কাছাকাছি পেতে, সম্ভবত ঘনত্ব ছোট এবং ছোট হয়ে যায়. আপনি প্রথম ডাক পাস 9 এবং তারপর থেকে উপর গুটানো 1, হঠাৎ তার পরিসীমা অনেক বড় হয়ে.

এই ব্যাখ্যা সন্তোষজনক হয়, বিস্ময়কর সত্য প্রাকৃতিক ডিস্ট্রিবিউশন সম্ভাবনা বন্ধ tapers কিভাবে এটা কোন ব্যাপার না. এটা প্রায় কেন্দ্রীয় সীমা উপপাদ্য ভালো হয়. অবশ্যই, এই সামান্য সিমুলেশন কোন কঠোর প্রমাণ. আপনি একটি কঠোর প্রমাণ খুঁজছি হয়, আপনি হিল এর কাজ তা জানতে পারেন [3].

জালিয়াতি সনাক্তকরণ

আমাদের করফাঁকি যন্ত্রণার Benford দায়ী করা যেতে পারে, যদিও, প্রথম অঙ্ক ঘটনাটি মূলত সাইমন Newcomb ২ দ্বারা একটি প্রবন্ধে বর্ণনা করা হয়েছিল [2] গণিত আমেরিকান জার্নাল মধ্যে 1881. এটা ফ্রাঙ্ক Benford দ্বারা rediscovered ছিল 1938, যাকে সব মহিমা (বা দোষ, বেড়া যা পার্শ্ব উপর নির্ভর করে আপনি নিজেকে খুঁজে পেতে) গিয়েছিলাম. আসলে, আমাদের ট্যাক্স দুর্দশা পিছনে আসল অপরাধী থিওডোর পার্বত্য হতে পারে হয়েছে. তিনি 1990 সালে নিবন্ধের একটি সিরিজ প্রচারের ছটা থেকে অস্পষ্ট আইন আনা. তিনি এমনকি একটি পরিসংখ্যান প্রমাণ উপস্থাপন [3] ঘটনাটি জন্য.

আমাদের ব্যক্তিগত ট্যাক্স যন্ত্রণার সৃষ্টি ছাড়াও, Benford আইন অনেক জালিয়াতি ও অনিয়মের চেক একটি অত্যন্ত গুরুত্বপূর্ণ ভূমিকা পালন করতে পারে [4]. উদাহরণস্বরূপ, একটি কোম্পানির হিসাব থেকে প্রথম ডাক বন্টন সৃজনশীলতা বাড়াতেও প্রকাশ করা হতে পারে. কর্মচারী পরিশোধ দাবি, পরিমাণে পরীক্ষা, বেতন পরিসংখ্যান, মুদি দাম — সবকিছু Benford আইন বিষয়. এটা এমনকি বাজারে হেরফেরের সনাক্ত করতে ব্যবহার করা যেতে পারে স্টক মূল্য প্রথম সংখ্যা কারণ, উদাহরণস্বরূপ, Benford বন্টন অনুসরণ অনুমিত হয়. যদি তারা না, আমরা সতর্ক হতে হবে.


চিত্র 4. একটি সিমুলেশন মধ্যে প্রথম এবং দ্বিতীয় সংখ্যা যুগ্ম বিতরণ, পারস্পরিক সম্পর্ক প্রভাব দেখাচ্ছে.

গল্পের নৈতিক সহজ: আপনার ট্যাক্স রিটার্ন সৃজনশীল করবেন না. আপনি ধরা হবে. আপনি একটি আরো বাস্তবসম্মত ট্যাক্স সিদ্ধান্তগ্রহণ প্যাটার্ন জেনারেট করার জন্য এই Benford বন্টন ব্যবহার করতে পারেন, মনে হতে পারে. কিন্তু এই কাজ কঠিন শোনাচ্ছে হয়. আমি এটা উল্লেখ না যদিও, সংখ্যার মধ্যে একটি পারস্পরিক সম্পর্ক আছে. দ্বিতীয় অঙ্ক হচ্ছে সম্ভাবনা 2, উদাহরণস্বরূপ, প্রথম অঙ্ক হয় উপর নির্ভর করে. চিত্র তাকান 4, যা আমার সিমিউলেশন এক পারস্পরিক সম্পর্ক গঠন দেখায়.

এছাড়া, নির্দেশানুযায়ী IRS সিস্টেম অনেক বেশি বাস্তবধর্মী হতে পারে. উদাহরণস্বরূপ, তারা যেমন স্নায়ুর নেটওয়ার্ক বা সমর্থন ভেক্টর মেশিন হিসাবে একটি উন্নত ডেটা মাইনিং বা প্যাটার্ন স্বীকৃতি সিস্টেম ব্যবহার করে হতে পারে. নির্দেশানুযায়ী IRS লেবেল করা হয়েছে যে তথ্য মনে রাখুন (অসফল প্রতারণা করার চেষ্টা যারা ট্যাক্স রিটার্ন, এবং ভাল নাগরিক যারা) এবং তারা সহজেই ট্যাক্স evaders উদীয়মান ধরা ক্লাসিফায়ার প্রোগ্রাম শেখাতে পারেন. তারা এখনো এই অত্যাধুনিক প্যাটার্ন স্বীকৃতি আলগোরিদিম ব্যবহার করা হয় না, আমার বিশ্বাস, তারা, এই নিবন্ধটি দেখে. এটি করের আসে, এটা আপনার বিরুদ্ধে স্তুপীকৃত করা হয়, কারণ যদৃচ্ছতা সবসময় আপনি মূর্খ হবে.

কিন্তু গম্ভীরভাবে, Benford আইন আমরা সচেতন হতে হবে যে একটি টুল. আমরা নিজেদেরকে সাংখ্যিক তথ্য সব ধরণের সত্যতা সন্দেহ এটি যখন এটা অপ্রত্যাশিত উপায়ে আমাদের সাহায্য করতে আসতে পারে. আইন উপর ভিত্তি করে একটি চেক বাস্তবায়ন করা সহজ এবং ফাঁদে ফেলা কঠিন. এটা সহজ এবং মোটামুটি সার্বজনীন. সুতরাং, এর Benford বীট চেষ্টা করুন না; এর পরিবর্তে তাকে যোগদান দিন.

[1] Benford, ফল. “অস্বাভাবিক নাম্বার আইন.” Proc. আমের. ফিল. Soc. 78, 551-572, 1938.
[2] Newcomb ২, এস. “প্রাকৃতিক সংখ্যায় ডিজিটের ব্যবহার ফ্রিকোয়েন্সি উপর রাখবেন.” আমের. জে. গণিত. 4, 39-40, 1881.
[3] পার্বত্য, টি. পি. “উল্লেখযোগ্য ডাক আইন পরিসংখ্যান আহরণ.” রাজ্য. সী. 10, 354-363, 1996.
[4] Nigrini, এম. “আমি আপনার নম্বর পেয়েছেন.” জে. হিসাববিদ্যা 187, পিপি. 79-83, মে 1999. HTTP://www.aicpa.org/pubs/jofa/may1999/nigrini.htm.

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Quant Life in Singapore

Singapore is a tiny city-state. Despite its diminutive size, Singapore has considerable financial muscle. It has been rated the fourth most active foreign exchange trading hub, and a major wealth management center in Asia, with funds amounting to almost half a trillion dollars, according to the Monitory Authority of Singapore. This mighty financial clout has its origins in a particularly pro-business atmosphere, world class (well, better than world class, in fact) infrastructure, and the highly skilled, cosmopolitan workforce–all of which Singapore is rightfully proud of.

Among the highly skilled workforce are scattered a hundred or so typically timid and self-effacing souls with bulging foreheads and dreamy eyes behind thick glasses. They are the Singaporean quants, and this short article is their story.

Quants command enormous respect for their intellectual prowess and mathematical knowledge. With flattering epithets like “rocket scientists” or simply “the brain,” quants silently go about their jobs of validating pricing models, writing C++ programs and developing complicated spreadsheet solutions.

But knowledge is a tricky thing to have in Asia. If you are known for your expertise, it can backfire on you at times. Unless you are careful, others will take advantage of your expertise and dump their responsibilities on you. You may not mind it as long as they respect your expertise. But, they often hog the credit for your work and present their ability to evade work as people management skills. And people managers (who may not actually know much) do get better compensated. This paradox is a fact of quant life in Singapore. The admiration that quants enjoy does not always translate to riches here.

This disparity in compensation may be okay. Quants are not terribly interested in money for one logical reason–in order to make a lot of it, you have to work long hours. And if you work long hours, when do you get to spend the money? What does it profit a man to amass all the wealth in the world if he doesn’t have the time to spend it?

Besides, quants seem to play by a different set of rules. They are typically perfectionist by nature. At least, I am, when it comes to certain aspects of work. I remember once when I was writing my PhD thesis, I started the day at around nine in the morning and worked all the way past midnight with no break. No breakfast, lunch or dinner. I wasn’t doing ground-breaking research on that particular day, just trying to get a set of numbers (branching ratios, as they were called) and their associated errors consistent. Looking back at it now, I can see that one day of starvation was too steep a price to pay for the consistency.

Similar bouts of perfectionism might grip some of us from time to time, forcing us to invest inordinate amounts of work for incremental improvements, and propelling us to higher levels of glory. The frustrating thing from the quants’ perspective is when the glory gets hogged by a middle-level people manager. It does happen, time and again. The quants are then left with little more than their flattering epithets.

I’m not painting all people managers with the same unkindly stroke; not all of them have been seduced by the dark side of the force. But I know some of them who actively hone their ignorance as a weapon. They plead ignorance to pass their work on to other unsuspecting worker bees, including quants.

The best thing a quant can hope for is a fair compensation for his hard work. Money may not be important in and of itself, but what it says about you and your station in the corporate pecking order may be of interest. Empty epithets are cheap, but it when it comes to showing real appreciation, hard cash is what matters, especially in our line of work.

Besides, corporate appreciation breeds confidence and a sense of self-worth. I feel that confidence is lacking among Singaporean quants. Some of them are really among the cleverest people I have met. And I have traveled far and wide and met some very clever people indeed. (Once I was in a CERN elevator with two Nobel laureates, as I will never tire of mentioning.)

This lack of confidence, and not lack of expertise or intelligence, is the root cause behind the dearth of quality work coming out of Singapore. We seem to keep ourselves happy with fairly mundane and routine tasks of implementing models developed by superior intelligences and validating the results.

Why not take a chance and dare to be wrong? I do it all the time. For instance, I think that there is something wrong with a Basel II recipe and I am going to write an article about it. I have published a physics article in a well-respected physics journal implying, among other things, that Einstein himself may have been slightly off the mark! See for yourself at http://TheUnrealUniverse.com.

Asian quants are the ones closest to the Asian market. For structures and products specifically tailored to this market, how come we don’t develop our own pricing models? Why do we wait for the Mertons and Hulls of the world?

In our defense, may be some of the confident ones that do develop pricing models may move out of Asia. The CDO guru David Li is a case in point. But, on the whole, the intellectual contribution to modern quantitative finance looks disproportionately lopsided in favor of the West. This may change in the near future, when the brain banks in India and China open up and smell blood in this niche field of ours.

Another quality that is missing among us Singaporean parishioners is an appreciation of the big picture. Clichés like the “Big Picture” and the “Value Chain” have been overused by the afore-mentioned middle-level people managers on techies (a category of dubious distinction into which we quants also fall, to our constant chagrin) to devastating effect. Such phrases have rained terror on techies and quants and relegated them to demoralizing assignments with challenges far below their intellectual potential.

May be it is a sign of my underestimating the power of the dark side, but I feel that the big picture is something we have to pay attention to. Quants in Singapore seem to do what they are asked to do. They do it well, but they do it without questioning. We should be more aware of the implications of our work. If we recommend Monte Carlo as the pricing model for a certain option, will the risk oversight manager be in a pickle because his VaR report takes too long to run? If we suggest capping methods to renormalize divergent sensitivities of certain products due to discontinuities in their payoff functions, how will we affect the regulatory capital charges? Will our financial institute stay compliant? Quants may not be expected to know all these interconnected issues. But an awareness of such connections may add value (gasp, another managerial phrase!) to our office in the organization.

For all these reasons, we in Singapore end up importing talent. This practice opens up another can of polemic worms. Are they compensated a bit too fairly? Do we get blinded by their impressive labels, while losing sight of their real level of talent? How does the generous compensation scheme for the foreign talents affect the local talents?

But these issues may be transitory. The Indians and Chinese are waking up, not just in terms of their economies, but also by unleashing their tremendous talent pool in an increasingly globalizing labor market. They (or should I say we?) will force a rethinking of what we mean when we say talent. The trickle of talent we see now is only the tip of the iceberg. Here is an illustration of what is in store, from a BBC report citing the Royal Society of Chemistry.

China Test
National test set by Chinese education authorities for pre-entry students As shown in the figure, in square prism ABCD-A_1B_1C_1D_1,AB=AD=2, DC=2\sqrt(3), A1=\sqrt(3), AD\perp DC, AC\perp BD, and foot of perpendicular is E,

  1. Prove: BD\perp A_1C
  2. Determine the angle between the two planes A_1BD and BC_1D
  3. Determine the angle formed by lines AD and BC_1 which are in different planes.
UK Test
Diagnostic test set by an English university for first year students In diagram (not drawn to scale), angle ABC is a right angle, AB = 3m BC = 4m

  1. What is the length AC?
  2. What is the area of triangle ABC (above)?
  3. What is the tan of the angle ABC (above) as a fraction?

The end result of such demanding pre-selection criteria is beginning to show in the quality of the research papers coming out of the selected ones, both in China and India. This talent show is not limited to fundamental research; applied fields, including our niche of quantitative finance, are also getting a fair dose of this oriental medicine.

Singapore will only benefit from this regional infusion of talent. Our young nation has an equally young (professionally, that is) quant team. We will have to improve our skills and knowledge. And we will need to be more vocal and assertive before the world notices us and acknowledges us. We will get there. After all, we are from Singapore–an Asian tiger used to beating the odds.

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