वर्ग पुरालेख,,en,दिलबर्ट जैसे विचार,,en,कठोर परिश्रम,,en,बड़े बोनस के लिए एक तर्क यह है कि अधिकारी इसके लिए कड़ी मेहनत करते हैं और इसे उचित और चौकोर कमाते हैं,,en,यह सच है कि इनमें से कुछ अधिकारी काफी समय खर्च करते हैं,,en,तक,,en,सेवा,,en,घंटे एक दिन,,en,यहां स्पॉटलाइट के तहत एआईजी के कार्यकारी के अनुसार,,en,लंबे घंटे और कड़ी मेहनत हमें स्वचालित रूप से बनाते हैं,,en,जो जीवन में सर्वश्रेष्ठ के हकदार हैं,,en,ट्रेसी चैपमैन के रूप में इसे डालता है,,en,मैं सिंगापुर में टैक्सी ड्राइवरों से मिला हूं, जो उल्लू-शिफ्ट के घंटे से पहले सड़कों पर चलते हैं, इससे पहले कि वे भी टूट सकते हैं,,en,जाहिरा तौर पर किराए के लिए कैबियों का भुगतान करना काफी अधिक है,,en,और वे ज्यादातर अधिकारियों की तुलना में लगातार लंबे समय तक काम करते हैं,,en,हमारे नैतिक क्षितिज से परे है,,en,मानव झुग्गी कुत्तों के लिए कचरा डंप करते हैं जो वे खा सकते हैं या बेच सकते हैं,,en,बैक-ब्रेकिंग लेबर,,en,मैं कल्पना करता हूँ,,en,लंबे समय तक,,en: The Wilmott Magazine

My published (or soon to be published) column pieces in The Wilmott Magazine

Risk – Wiley FinCAD Webinar

This post is an edited version of my responses in a Webinar panel-discussion organized by Wiley-Finance and FinCAD. The freely available Webcast is linked in the post, and contains responses from the other participants — Paul Wilmott and Espen Huag. An expanded version of this post may later appear as an article in the Wilmott Magazine.

What is Risk?

When we use the word Risk in normal conversation, it has a negative connotation — risk of getting hit by a car, for instance; but not the risk of winning a lottery. In finance, risk is both positive and negative. At times, you want the exposure to a certain kind of risk to counterbalance some other exposure; at times, you are looking for the returns associated with a certain risk. Risk, in this context, is almost identical to the mathematical concept of probability.

But even in finance, you have one kind of risk that is always negative — it is Operational Risk. My professional interest right now is in minimizing the operational risk associated with trading and computational platforms.

How do you measure Risk?

Measuring risk ultimately boils down to estimating the probability of a loss as a function of something — typically the intensity of the loss and time. So it’s like asking — What’s the probability of losing a million dollars or two million dollars tomorrow or the day after?

The question whether we can measure risk is another way of asking whether we can figure out this probability function. In certain cases, we believe we can — in Market Risk, for instance, we have very good models for this function. Credit Risk is different story — although we thought we could measure it, we learned the hard way that we probably could not.

The question how effective the measure is, is, in my view, like asking ourselves, “What do we do with a probability number?” If I do a fancy calculation and tell you that you have 27.3% probability of losing one million tomorrow, what do you do with that piece of information? Probability has a reasonable meaning only a statistical sense, in high-frequency events or large ensembles. Risk events, almost by definition, are low-frequency events and a probability number may have only limited practical use. But as a pricing tool, accurate probability is great, especially when you price instruments with deep market liquidity.

Innovation in Risk Management.

Innovation in Risk comes in two flavors — one is on the risk taking side, which is in pricing, warehousing risk and so on. On this front, we do it well, or at least we think we are doing it well, and innovation in pricing and modeling is active. The flip side of it is, of course, risk management. Here, I think innovation lags actually behind catastrophic events. Once we have a financial crisis, for instance, we do a post-mortem, figure out what went wrong and try to implement safety guards. But the next failure, of course, is going to come from some other, totally, unexpected angle.

What is the role of Risk Management in a bank?

Risk taking and risk management are two aspects of a bank’s day-to-day business. These two aspects seem in conflict with each other, but the conflict is no accident. It is through fine-tuning this conflict that a bank implements its risk appetite. It is like a dynamic equilibrium that can be tweaked as desired.

What is the role of vendors?

In my experience, vendors seem to influence the processes rather than the methodologies of risk management, and indeed of modeling. A vended system, however customizable it may be, comes with its own assumptions about the workflow, lifecycle management etc. The processes built around the system will have to adapt to these assumptions. This is not a bad thing. At the very least, popular vended systems serve to standardize risk management practices.

Risk: Interpretation, Innovation and Implementation

A Wiley Global Finance roundtable with Paul Wilmott

Featuring Paul Wilmott, Espen Haug and Manoj Thulasidas


How do you identify, measure and model risk, and more importantly, what changes need to be implemented to improve the long-term profitability and sustainability of our financial institutions? Take a unique opportunity to join globally recognised and respected experts in the field, Paul Wilmott, Espen Haug and Manoj Thulasidas in a free, one hour online roundtable discussion to debate the key issues and to find answers to questions to improve financial risk modelling.

Join our experts as they address these fundamental financial risk questions:

  • What is risk?
  • How do we measure and quantify risk in quantitative finance? Is this effective?
  • Is it possible to model risk?
  • Define innovation in risk management. Where does it take place? Where should it take place?
  • How do new ideas see the light of day? How are they applied to the industry, and how should they be applied?
  • How is risk management implemented in modern investment banking? Is there a better way?

Our panel of internationally respected experts include Dr Paul Wilmott, founder of the prestigious Certificate in Quantitative Finance (CQF) and Wilmott.com, Editor-in-Chief of Wilmott Magazine, and author of highly acclaimed books including the best-selling Paul Wilmott On Quantitative Finance; Dr Espen Gaarder Haug who has more than 20 years of experience in Derivatives research and trading and is author of The Complete Guide of Option Pricing Formulas and Derivatives: Models on Models; and Dr Manoj Thulasidas, a physicist-turned-quant who works as a senior quantitative professional at Standard Chartered Bank in Singapore and is author of Principles of Quantitative Development.

This debate will be critical for all chief risk officers, credit and market risk managers, asset liability managers, financial engineers, front office traders, risk analysts, quants and academics.

Physics vs. Finance

Despite the richness that mathematics imparts to life, it remains a hated and difficult subject to many. I feel that the difficulty stems from the early and often permanent disconnect between math and reality. It is hard to memorize that the reciprocals of bigger numbers are smaller, while it is fun to figure out that if you had more people sharing a pizza, you get a smaller slice. Figuring out is fun, memorizing — not so much. Mathematics, being a formal representation of the patterns in reality, doesn’t put too much emphasis on the figuring out part, and it is plain lost on many. गणितीय सटीकता के साथ उस कथन को दोहराने के लिए,,en,गणित वाक्यगत रूप से समृद्ध और कठोर है,,en,लेकिन शब्दार्थ कमजोर,,en,सिंटेक्स अपने आप बन सकता है,,en,और अक्सर एक अनियंत्रित घोड़े की तरह अपने शब्दार्थ सवार को हिलाते हैं,,en,यह विभिन्न अर्थ रूपों में कायापलट कर सकता है जो एक दूसरे से बहुत अलग दिखते हैं,,en,उस जटिल संख्या को नोटिस करने में कुछ साल लगते हैं,,en,वेक्टर बीजगणित,,en,निर्देशांक ज्यामिति,,en,रैखिक बीजगणित और त्रिकोणमिति सभी यूक्लिडियन ज्यामिति के अनिवार्य रूप से अलग-अलग वाक्य-विन्यास हैं,,en,जो गणित में उत्कृष्ट करते हैं,,en,मैं आशा करता हूँ,,en,जो प्रतीत होता है जंगली वाक्य रचना जानवर में लगाम लगाने के लिए अपने स्वयं के अर्थ परिप्रेक्ष्य विकसित किए हैं,,en,भौतिक विज्ञान भी उन्नत गणित की खाली औपचारिकताओं को सुंदर अर्थ संबंधी संदर्भ प्रदान कर सकता है,,en,मिन्कोवस्की अंतरिक्ष और रीमानियन ज्यामिति को देखें,,en — math is syntactically rich and rigorous, but semantically weak. Syntax can build on itself, and often shake off its semantic riders like an unruly horse. Worse, it can metamorphose into different semantic forms that look vastly different from one another. It takes a student a few years to notice that complex numbers, vector algebra, coordinate geometry, linear algebra and trigonometry are all essentially different syntactical descriptions of Euclidean geometry. Those who excel in mathematics are, I presume, the ones who have developed their own semantic perspectives to rein in the seemingly wild syntactical beast.

Physics also can provide beautiful semantic contexts to the empty formalisms of advanced mathematics. Look at Minkowski space and Riemannian geometry, for instance, और आइंस्टीन ने उन्हें हमारी कथित वास्तविकता के विवरण में कैसे बदल दिया,,en,गणितीय औपचारिकता को शब्दार्थ प्रदान करने के अलावा,,en,विज्ञान महत्वपूर्ण सोच और एक क्रूरतापूर्ण वैज्ञानिक अखंडता पर आधारित विश्वदृष्टि को भी बढ़ावा देता है,,en,यह किसी के निष्कर्ष की जांच करने का एक दृष्टिकोण है,,en,मान्यताओं और परिकल्पना निर्दयता से अपने आप को समझाने के लिए कि कुछ भी अनदेखी नहीं की गई है,,en,कहीं यह प्रायोगिक भौतिकी की तुलना में अधिक स्पष्ट नहीं है,,en,भौतिक विज्ञानी त्रुटियों के दो सेट के साथ अपने माप की रिपोर्ट करते हैं,,en,एक सांख्यिकीय त्रुटि इस तथ्य का प्रतिनिधित्व करती है कि उन्होंने केवल टिप्पणियों की एक सीमित संख्या बनाई है,,en,और एक व्यवस्थित त्रुटि जो कार्यप्रणाली में अशुद्धि के लिए जिम्मेदार है,,en,मान्यताओं आदि,,en. In addition to providing semantics to mathematical formalism, science also promotes a worldview based on critical thinking and a ferociously scrupulous scientific integrity. It is an attitude of examining one’s conclusions, assumptions and hypotheses mercilessly to convince oneself that nothing has been overlooked. Nowhere is this nitpicking obsession more evident than in experimental physics. Physicists report their measurements with two sets of errors — a statistical error representing the fact that they have made only a finite number of observations, and a systematic error that is supposed to account for the inaccuracies in methodology, assumptions etc.

हमें इस वैज्ञानिक अखंडता के प्रतिपक्ष की अपनी गर्दन को देखने के लिए दिलचस्प लग सकता है,,en,जो डॉलर और सेंट शब्दार्थ के साथ स्टोकेस्टिक पथरी के वाक्यविन्यास को दर्शाता है,,en,एक तरह का जो वार्षिक रिपोर्ट में समाप्त होता है और प्रदर्शन बोनस उत्पन्न करता है,,en,कोई यह भी कह सकता है कि वैश्विक अर्थव्यवस्था पर इसका गहरा प्रभाव है,,en,इस प्रभाव को देखते हुए,,en,हम अपने परिणामों में त्रुटियों और आत्मविश्वास का स्तर कैसे निर्धारित करते हैं,,en,इसे एक उदाहरण के साथ समझाने के लिए,,en,जब कोई ट्रेडिंग सिस्टम किसी ट्रेड के P / L की रिपोर्ट करता है,,en,सत्तर लाख,,en,या यह है,,en,बाद वाला,,en,स्पष्ट रूप से,,en,वित्तीय संस्थान के लिए अधिक मूल्य रखता है और पूर्व की तुलना में अधिक पुरस्कृत किया जाना चाहिए,,en,हम इसके बारे में जानते हैं,,en,हम रिटर्न की अस्थिरता और संवेदनशीलता के संदर्भ में त्रुटियों का अनुमान लगाते हैं और पी / एल भंडार लागू करते हैं,,en — quantitative finance, which decorates the syntactical edifice of stochastic calculus with dollar-and-cents semantics, of a kind that ends up in annual reports and generates performance bonuses. One might even say that it has a profound impact on the global economy as a whole. Given this impact, how do we assign errors and confidence levels to our results? To illustrate it with an example, when a trading system reports the P/L of a trade as, say, seven million, is it $7,000,000 +/- $5,000,000 or is it $7,000, 000 +/- $5000? The latter, clearly, holds more value for the financial institution and should be rewarded more than the former. We are aware of it. We estimate the errors in terms of the volatility and sensitivities of the returns and apply P/L reserves. लेकिन हम अन्य व्यवस्थित त्रुटियों को कैसे संभालते हैं,,en,हम बाजार की तरलता पर हमारी मान्यताओं के प्रभाव को कैसे मापते हैं,,en,सूचना समरूपता आदि।,,en,और परिणामी त्रुटियों के लिए डॉलर का मान निर्दिष्ट करें,,en,यदि हम इस के त्रुटि प्रसार के बारे में छानबीन कर रहे थे,,en,शायद का वित्तीय संकट,,en,के बारे में नहीं आया होगा,,en,हालांकि गणितज्ञ हैं,,en,भौतिकविदों के रूप में इस तरह के महत्वपूर्ण आत्म-संदेह से मुक्त,,en,ठीक इसके कारण कि उनकी वाक्य-रचना संबंधी विद्या और उसके शब्दार्थ संदर्भों के बीच कुल विच्छेद,,en,कुछ ऐसे हैं जो अपनी मान्यताओं की वैधता को लगभग गंभीरता से लेते हैं,,en,मुझे मेरा यह प्रोफेसर याद है जिसने हमें गणितीय प्रेरण सिखाया था,,en,ब्लैकबोर्ड पर इसका उपयोग करते हुए कुछ मामूली प्रमेय साबित करने के बाद,,en,हाँ यह व्हाइटबोर्ड के युग से पहले था,,en,उन्होंने हमसे पूछा कि क्या उन्होंने इसे साबित किया है,,en,हम कहा,,en? How do we measure the impact of our assumptions on market liquidity, information symmetry etc., and assign dollar values to the resulting errors? If we had been scrupulous about error propagations of this, perhaps the financial crisis of 2008 would not have come about.

Although mathematicians are, in general, free of such critical self-doubts as physicists — precisely because of a total disconnect between their syntactical wizardry and its semantic contexts, in my opinion — there are some who take the validity of their assumptions almost too seriously. I remember this professor of mine who taught us mathematical induction. After proving some minor theorem using it on the blackboard (yes it was before the era of whiteboards), he asked us whether he had proved it. We said, sure, उसने ठीक हमारे सामने किया था,,en,उसने फिर कहा,,en,"आह,,en,लेकिन आपको खुद से पूछना चाहिए कि क्या गणितीय प्रेरण सही है? ” अगर मैं उसे एक महान गणितज्ञ मानता हूं,,en,यह शायद हमारे अतीत के आम रोमांटिक प्रशंसकों की वजह से है जो हमारे पिछले शिक्षकों को गौरवान्वित करते हैं,,en,लेकिन मुझे पूरा यकीन है कि मेरे महिमामंडन में संभावित गिरावट की पहचान उनके बयान के साथ लगाए गए बीजों का एक सीधा परिणाम है।,,en,हो सकता है कि मेरे प्रोफेसर ने इस आत्म-संदेह व्यवसाय को बहुत दूर ले लिया हो,,en,हमारी तर्कशक्ति और तर्क की पृष्ठभूमि पर सवाल उठाना शायद स्वस्थ या व्यावहारिक नहीं है,,en,हम जिन परिणामों पर पहुँचे हैं उनकी पवित्रता सुनिश्चित करना अधिक महत्वपूर्ण है,,en,हमारे निपटान में दुर्जेय वाक्यात्मक मशीनरी को नियोजित करना,,en. He then said, “Ah, but you should ask yourselves if mathematical induction is right.” If I think of him as a great mathematician, it is perhaps only because of the common romantic fancy of ours that glorifies our past teachers. But I am fairly certain that the recognition of the possible fallacy in my glorification is a direct result of the seeds he planted with his statement.

My professor may have taken this self-doubt business too far; it is perhaps not healthy or practical to question the very backdrop of our rationality and logic. What is more important is to ensure the sanity of the results we arrive at, employing the formidable syntactical machinery at our disposal. स्वस्थ आत्म-शंका का एक परिणाम बनाए रखने का एकमात्र तरीका और परिणामी विवेक जांच वास्तविकता के पैटर्न और गणित में औपचारिकता के बीच संबंध की रक्षा करना है।,,en,और वह,,en,गणित के साथ-साथ प्रेम विकसित करने का सही तरीका होगा,,en,गणित और पैटर्न,,en,ज्यादातर बच्चों को पैटर्न पसंद होता है,,en,गणित सिर्फ पैटर्न है,,en,तो जीवन है,,en,जीवन का वर्णन करने का एक औपचारिक तरीका है,,en,या कम से कम पैटर्न हम जीवन में मुठभेड़,,en,अगर जीवन के बीच संबंध,,en,पैटर्न और गणित को बनाए रखा जा सकता है,,en,यह इस प्रकार है कि बच्चों को गणित से प्यार करना चाहिए,,en,और गणित के प्यार को एक विश्लेषणात्मक क्षमता उत्पन्न करनी चाहिए,,en,या जिसे मैं गणितीय क्षमता कहूंगा,,en,ज्यादातर चीजों को अच्छी तरह से समझने और करने के लिए,,en,मैंने एक कनेक्शन लिखा था,,en,तीन बातें कुछ वाक्य पहले,,en. And that, in my opinion, would be the right way to develop a love for math as well.

Math and Patterns

Most kids love patterns. Math is just patterns. So is life. Math, therefore, is merely a formal way of describing life, or at least the patterns we encounter in life. If the connection between life, patterns and math can be maintained, it follows that kids should love math. And love of math should generate an analytic ability (or what I would call a mathematical ability) to understand and do most things well. For instance, I wrote of a connection “between” three things a couple of sentences ago. मुझे पता है कि यह खराब अंग्रेजी है क्योंकि मुझे एक त्रिभुज के तीन कोने दिखाई देते हैं और फिर एक कनेक्शन से कोई मतलब नहीं है,,en,एक अच्छा लेखक शायद इसे सहज रूप से बेहतर बना देगा,,en,मेरे जैसे गणितीय लेखक को उस शब्द का एहसास होगा,,en,इस संदर्भ में काफी अच्छा है,,en,व्याकरण की अपनी सूझबूझ के आधार पर इसे बनाने में आकस्मिक मुआवजे की भरपाई की जा सकती है,,en,मैं इसे किसी पुस्तक या प्रकाशित कॉलम में नहीं छोड़ूंगा,,en,इस एक को छोड़कर क्योंकि मैं इसे उजागर करना चाहता हूं।,,en,मेरा कहना है कि यह गणित के लिए मेरा प्यार है जो मुझे बड़ी संख्या में चीजों को अच्छी तरह से करने देता है,,en,एक लेखक के रूप में,,en,मैंने अच्छा प्रदर्शन किया है,,en,लेकिन मैं अपनी सफलता का श्रेय साहित्यिक प्रतिभा के बजाय एक निश्चित गणितीय क्षमता को देता हूं,,en,मैं एक किताब की शुरुआत कभी नहीं करना चाहूंगा,,en. A good writer would probably put it better instinctively. A mathematical writer like me would realize that the word “between” is good enough in this context — the subliminal jar on your sense of grammar that it creates can be compensated for or ignored in casual writing. I wouldn’t leave it standing in a book or a published column (except this one because I want to highlight it.)

My point is that it is my love for math that lets me do a large number of things fairly well. As a writer, for instance, I have done rather well. But I attribute my success to a certain mathematical ability rather than literary talent. I would never start a book with something like, “वह सबसे अच्छा समय था,,en,यह सबसे बुरा समय था।,,en,शुरुआती वाक्य के रूप में,,en,लेखन के सभी गणितीय नियमों द्वारा मैंने अपने लिए तैयार किया है,,en,यह एक उपाय नहीं है,,en,फिर भी हम सभी जानते हैं कि डिकेंस का उद्घाटन,,en,मेरा कोई नियम नहीं,,en,अंग्रेजी साहित्य में शायद सबसे अच्छा है,,en,मैं शायद किसी दिन कुछ इसी तरह खाना बनाऊंगा क्योंकि मैं देखता हूं कि यह पुस्तक को कैसे सारांशित करता है,,en,और विषमता और हैस के बीच असमानता को उजागर करता है और इसके विपरीत लीड कैरेक्टर इत्यादि,,en,मैं देखता हूं कि यह कैसे काम करता है और इसे मेरी रसोइया नियमों में आत्मसात कर सकती है,,en,अगर मैं कभी भी समझ सकता हूं कि कैसे,,en,और आत्मसात की प्रक्रिया प्रकृति में गणितीय है,,en,खासकर जब यह एक सचेत प्रयास है,,en,इसी तरह के फजी नियम-आधारित दृष्टिकोण आपको एक बहुत ही चतुर कलाकार होने में मदद कर सकते हैं,,en,कर्मचारी,,en, it was the worst of times.” As an opening sentence, by all the mathematical rules of writing I have formulated for myself, this one just doesn’t measure up. Yet we all know that Dickens’s opening, following no rules of mine, is perhaps the best in English literature. I will probably cook up something similar someday because I see how it summarizes the book, and highlights the disparity between the haves and the have-nots mirrored in the contrasting lead characters and so on. In other words, I see how it works and may assimilate it into my cookbook of rules (if I can ever figure out how), and the process of assimilation is mathematical in nature, especially when it is a conscious effort. Similar fuzzy rule-based approaches can help you be a reasonably clever artist, employee, प्रबंधक या कुछ भी जिस पर आप अपने दर्शनीय स्थल निर्धारित करते हैं,,en,यही कारण है कि मैंने एक बार अपनी पत्नी से कहा कि मैं भारतीय शास्त्रीय संगीत सीख सकता हूं, क्योंकि मैं व्यावहारिक रूप से बहरा हूं।,,en,इसलिए गणित से प्यार करना एक अच्छी बात है,,en,बावजूद इसके स्पष्ट नुकसान विज़-ए-विज़ चीयरलीडर्स के रूप में,,en,लेकिन मुझे अभी तक अपने केंद्रीय विषय को संबोधित नहीं करना है,,en,हम अगली पीढ़ी के बीच गणित के लिए प्यार को कैसे सक्रिय रूप से प्रोत्साहित और विकसित करते हैं,,en,मैं लोगों को गणित में अच्छा बनाने की बात नहीं कर रहा हूं,,en,मैं शिक्षण तकनीकों के प्रति चिंतित नहीं हूं,,en,मुझे लगता है कि सिंगापुर पहले से ही अच्छा काम कर रहा है,,en,लेकिन लोगों को गणित पसंद करने के लिए उसी तरह से प्राप्त करना पसंद करते हैं,,en,उनका संगीत या कार या सिगरेट या फुटबॉल थोड़ा और अधिक कल्पना लेता है,,en,मुझे लगता है कि हम अंतर्निहित पैटर्न को अग्रभूमि पर रखकर इसे पूरा कर सकते हैं,,en, which is why I once bragged to my wife that I could learn Indian classical music despite the fact that I am practically tone-deaf.

So loving math is a probably a good thing, in spite of its apparent disadvantage vis-a-vis cheerleaders. But I am yet to address my central theme — how do we actively encourage and develop a love for math among the next generation? I am not talking about making people good at math; I’m not concerned with teaching techniques per se. I think Singapore already does a good job with that. But to get people to like math the same way they like, say, their music or cars or cigarettes or football takes a bit more imagination. I think we can accomplish it by keeping the underlying patterns on the foreground. इसलिए मेरे बच्चों को बताने के बजाय कि,,en,के अपेक्षा बड़ा है,,en,की तुलना में छोटा है,,en,मैं उनसे कहता हूं,,en,आप कुछ बच्चों के लिए एक पिज्जा ऑर्डर करते हैं,,en,क्या आपको लगता है कि अगर हम चार बच्चे या छह बच्चे इसे साझा करते हैं तो प्रत्येक अधिक मिलेगा,,en,भौगोलिक दूरी और डिग्री पर मेरे पहले उदाहरण से,,en,मैं कल्पना करता हूं कि मेरी बेटी एक दिन यह पता लगाएगी कि प्रत्येक डिग्री,,en,या लगभग 100 कि.मी.,,en,द्वारा सही किया गया,,en,चार मिनट जेट अंतराल का मतलब है,,en,वह भी आश्चर्य हो सकता है क्यों,,en,डिग्री और मिनट और सेकंड में दिखाई देता है,,en,और संख्या प्रणाली के आधार पर और कुछ के बारे में जानें,,en,गणित वास्तव में जीवन पर एक समृद्ध दृष्टिकोण को जन्म देता है,,en,यह सब हमारे हिस्से में है शायद इस समृद्धि का आनंद लेने के लिए साझा करना है,,en,यह मेरी आशा है,,en,मठ का प्यार,,en,अगर आपको गणित से प्यार है,,en,तुम एक गीक हो,,en,आपके भविष्य में स्टॉक विकल्प के साथ,,en,लेकिन कोई चीयरलीडर्स नहीं,,en 1/4 is bigger than 1/6 because 4 is smaller than 6, I say to them, “You order one pizza for some kids. Do you think each will get more if we had four kids or six kids sharing it?”

From my earlier example on geographic distances and degrees, I fancy my daughter will one day figure out that each degree (or about 100km — corrected by 5% and 6%) means four minutes of jet lag. She might even wonder why 60 appears in degrees and minutes and seconds, and learn something about number system basis and so on. Mathematics really does lead to a richer perspective on life. All it takes on our part is perhaps only to share the pleasure of enjoying this richness. At least, that’s my hope.

Love of Math

If you love math, you are a geek — with stock options in your future, but no cheerleaders. इसलिए बच्चे को गणित से प्यार करना एक संदेहास्पद उपहार है,,en,क्या हम वास्तव में उन पर एहसान कर रहे हैं,,en,मेरे एक उच्च पदस्थ मित्र ने मुझे इसे देखने के लिए कहा,,en,न केवल गणित में रुचि रखने वाले बच्चों की एक जोड़ी के रूप में,,en,लेकिन देश में एक सामान्य शैक्षिक प्रयास के रूप में,,en,एक बार यह एक सामान्य घटना बन जाती है,,en,गणित whizkids सामाजिक स्वीकृति और लोकप्रियता के समान स्तर का आनंद ले सकता है,,en,एथलीट और रॉक स्टार,,en,वास्तविकता पर नहीं आशाओं के आधार पर कामना करना,,en,मैं हमेशा गणित पसंद करने वाले लोगों में से था,,en,मुझे अपने हाई स्कूल के दिनों की याद है, जहाँ मेरे एक मित्र भौतिकी के प्रयोगों के दौरान लंबे गुणा और भाग करेंगे,,en,जब मैं एक और दोस्त के साथ टीम बनाऊंगा और लघुगणक को देखने की कोशिश करूंगा,,en,जो लगभग हमेशा जीता है,,en,यह वास्तव में मायने नहीं रखता था कि कौन जीता,,en — are we really doing them a favor? Recently, a highly placed friend of mine asked me to look into it — not merely as getting a couple of kids interested in math, but as a general educational effort in the country. Once it becomes a general phenomenon, math whizkids might enjoy the same level of social acceptance and popularity as, say, athletes and rock stars. Wishful thinking? May be…

I was always among people who liked math. I remember my high school days where one of my friends would do the long multiplication and division during physics experiments, while I would team up with another friend to look up logarithms and try to beat the first dude, who almost always won. It didn’t really matter who won; मात्र तथ्य यह है कि हम खेल को उस तरह से उपकरण देंगे जैसे कि किशोरों ने संभवतः एक जयजयकार-भविष्य को चित्रित किया था,,en,जैसा की यह निकला,,en,लंबे समय तक गुणा करने वाला आदमी मध्य पूर्व में एक उच्च पदस्थ बैंकर बन गया,,en,कोई संदेह नहीं है कि उसकी प्रतिभा के लिए धन्यवाद जयजयकार-फ़ोबिक का नहीं,,en,गणित- pliclic तरह,,en,जब मैं आईआईटी में स्थानांतरित हो गया,,en,यह गणितीय उल्लास पूरे नए स्तर पर पहुंच गया,,en,यहां तक ​​कि सामान्य geekiness के बीच जिसने IIT हवा को अनुमति दी,,en,मुझे कुछ लोग याद हैं जो बाहर खड़े थे,,en,वहां था,,en,चालाक,,en,जिसने मुझे अपनी कुँवारी किंगफिशर से मिलवाने का संदिग्ध सम्मान दिया,,en,दर्द,,en,बहुत दर्द होता है,,en,जाहिर है यार,,en,जब हम,,en,कम गीक्स,,en,गणितीय कलाबाजी की अपनी विशेष पंक्ति का आसानी से पालन करने में विफल रहा,,en,हम सभी को गणित से प्यार था,,en,यह कहां से आया,,en. As it turned out, the long-multiplication guy grew up to be a highly placed banker in the Middle East, no doubt thanks to his talents not of the cheerleader-phobic, math-phelic kind.

When I moved to IIT, this mathematical geekiness reached a whole new level. Even among the general geekiness that permeated the IIT air, I remember a couple of guys who stood out. There was “Devious” who also had the dubious honor of introducing me to my virgin Kingfisher, and “Pain” would drawl a very pained “Obviously Yaar!” when we, the lesser geeks, failed to readily follow a his particular line of mathematical acrobatics.

All of us had a love for math. But, where did it come from? और दुनिया में मैं इसे एक सामान्य शैक्षिक उपकरण कैसे बनाऊंगा,,en,एक बच्चे के लिए प्रेम गणित लागू करना बहुत मुश्किल नहीं है,,en,तुम बस इसे मज़ेदार बनाओ,,en,दूसरे दिन जब मैं अपनी बेटी के साथ गाड़ी चला रहा था,,en,उसने कुछ आकार बताया,,en,वास्तव में उसकी दादी के माथे पर टक्कर है,,en,आधी गेंद के रूप में,,en,मैंने उसे बताया कि यह वास्तव में एक गोलार्ध था,,en,फिर मैंने उसे बताया कि हम दक्षिणी गोलार्ध में जा रहे हैं,,en,न्यूजीलैंड,,en,अगले दिन हमारी छुट्टी के लिए,,en,यूरोप की तुलना में ग्लोब के दूसरी तरफ,,en,जिसके कारण वहां गर्मी थी,,en,और अंत में,,en,मैंने उसे बताया कि सिंगापुर भूमध्य रेखा पर था,,en,मेरी बेटी लोगों को सही करना पसंद करती है,,en,तो उसने कहा,,en,यह नहीं था,,en,मैंने उसे बताया कि हम किस बारे में थे,,en,भूमध्य रेखा के उत्तर में डिग्री,,en,मुझे उम्मीद है कि मैं सही था,,en,और मेरा उद्घाटन देखा,,en? Imparting the love math to one kid is not too difficult; you just make it fun. The other day when I was driving around with my daughter, she described some shape (actually the bump on her grandmother’s forehead) as half-a-ball. I told her that it was actually a hemisphere. Then I highlighted to her that we were going to the southern hemisphere (New Zealand) for our vacation the next day, on the other side of the globe compared to Europe, which was why it was summer there. And finally, I told her Singapore was on the equator. My daughter likes to correct people, so she said, no, it wasn’t. I told her that we were about 0.8 degrees to the north of the equator (I hope I was right), and saw my opening. मैंने उससे पूछा कि वृत्त की परिधि क्या है,,en,और उसे बताया कि पृथ्वी की त्रिज्या लगभग 6000 किमी थी,,en,और काम किया कि हम भूमध्य रेखा के उत्तर में लगभग 80 किमी दूर थे,,en,जो कि पृथ्वी के चारों ओर 36,000 किमी के महान चक्र की तुलना में कुछ भी नहीं था,,en,फिर हमने काम किया कि हमने ए,,en,पी के मूल्य पर सन्निकटन,,en,इसलिए सही संख्या लगभग 84 किमी थी,,en,मैं उसे बता सकता था कि हमने दूसरा बनाया है,,en,त्रिज्या पर सन्निकटन,,en,संख्या 90 किमी से अधिक होगी,,en,उसके लिए इन चीजों को काम करना मजेदार था,,en,मुझे लगता है कि गणित के प्रति उसका प्यार थोड़ा बढ़ा है,,en,Dylan231,,cy,एक अच्छा अभिभावक कैसे बनें,,en,पीछे देखते हुए कि मैंने अपने बच्चों को कैसे पाला,,en,मैं यह कैसे कर रहा हूं,,en,क्योंकि वे अभी भी बच्चे हैं,,en,एक अभिभावक के रूप में मैं कितना अच्छा हूं, इस बारे में मेरी मिश्रित भावनाएं हैं,,en,संपूर्ण,,en,मैं सभ्य रहा हूं,,en, and told her that the radius of the earth was about 6000km, and worked out that we were about 80km to the north of the equator, which was nothing compared to 36,000km great circle around the earth. Then we worked out that we made a 5% approximation on the value of pi, so the correct number was about 84km. I could have told her we made another 6% approximation on the radius, the number would be more like 90km. It was fun for her to work out these things. I fancy her love for math has been augmented a bit.

Photo by Dylan231

In Our Defense

The financial crisis was a veritable gold mine for columnists like me. I, for one, published at least five articles on the subject, including its causes, the lessons learned, and, most self-deprecating of all, our excesses that contributed to it.

Looking back at these writings of mine, I feel as though I may have been a bit unfair on us. I did try to blunt my accusations of avarice (and perhaps decadence) by pointing out that it was the general air of insatiable greed of the era that we live in that spawned the obscenities and the likes of Madoff. But I did concede the existence of a higher level of greed (or, more to the point, a more sated kind of greed) among us bankers and quantitative professionals. I am not recanting my words in this piece now, but I want to point out another aspect, a justification if not an absolution.

Why would I want to defend bonuses and other excesses when another wave of public hatred is washing over the global corporations, thanks to the potentially unstoppable oil spill? Well, I guess I am a sucker for lost causes, much like Rhett Butler, as our quant way of tranquil life with insane bonuses is all but gone with the wind now. Unlike Mr. Butler, however, I have to battle and debunk my own arguments presented here previously.

One of the arguments that I wanted to poke holes in was the fair compensation angle. It was argued in our circles that the fat paycheck was merely an adequate compensation for the long hours of hard work that people in our line of work put in. I quashed it, I think, by pointing out other thankless professions where people work harder and longer with no rewards to write home about. Hard work has no correlation with what one is entitled to. The second argument that I made fun of was the ubiquitous “talent” angle. At the height of the financial crisis, it was easy to laugh off the talent argument. Besides, there was little demand for the talent and a lot of supply, so that the basic principle of economics could apply, as our cover story shows in this issue.

Of all the arguments for large compensation packages, the most convincing one was the profit-sharing one. When the top talents take huge risks and generate profit, they need to be given a fair share of the loot. Otherwise, where is the incentive to generate even more profits? This argument lost a bit of its bite when the negative profits (by which I indeed mean losses) needed to be subsidized. This whole saga reminded me of something that Scott Adams once said of risk takers. He said that risk takers, by definition, often fail. So do morons. In practice, it is hard to tell them apart. Should the morons reap handsome rewards? That is the question.

Having said all this in my previous articles, now it is time to find some arguments in our defense. I left out one important argument in my previous columns because it did not support my general thesisthat the generous bonuses were not all that justifiable. Now that I have switched allegiance to the lost cause, allow me to present it as forcefully as I can. In order to see compensation packages and performance bonuses in a different light, we first look at any traditional brick-and-mortar company. Let’s consider a hardware manufacturer, for instance. Suppose this hardware shop of ours does extremely well one year. What does it do with the profit? Sure, the shareholders take a healthy bite out of it in terms of dividends. The employees get decent bonuses, hopefully. But what do we do to ensure continued profitability?

We could perhaps see employee bonuses as an investment in future profitability. But the real investment in this case is much more physical and tangible than that. We could invest in hardware manufacturing machinery and technology improving the productivity for years to come. We could even invest in research and development, if we subscribe to a longer temporal horizon.

Looking along these lines, we might ask ourselves what the corresponding investment would be for a financial institution. How exactly do we reinvest so that we can reap benefits in the future?

We can think of better buildings, computer and software technologies etc. But given the scale of the profits involved, and the cost and benefit of these incremental improvements, these investments don’t measure up. Somehow, the impact of these tiny investments is not as impressive in the performance of a financial institution compared to a brick-and-mortar company. The reason behind this phenomenon is that thehardwarewe are dealing with (in the case of a financial institution) is really human resources — people — you and me. So the only sensible reinvestment option is in people.

So we come to the next questionhow do we invest in people? We could use any number of euphemistic epithets, but at the end of the day, it is the bottom line that counts. We invest in people by rewarding them. Monetarily. Money talks. We can dress it up by saying that we are rewarding performance, sharing profits, retaining talents etc. But ultimately, it all boils down to ensuring future productivity, much like our hardware shop buying a fancy new piece of equipment.

Now the last question has to be asked. Who is doing the investing? Who benefits when the productivity (whether current or future) goes up? The answer may seem too obvious at first glanceit is clearly the shareholders, the owners of the financial institution who will benefit. But nothing is black and white in the murky world of global finance. The shareholders are not merely a bunch of people holding a piece of paper attesting their ownership. There are institutional investors, who mostly work for other financial institutions. They are people who move large pots of money from pension funds and bank deposits and such. In other words, it is the common man’s nest egg, whether or not explicitly linked to equities, that buys and sells the shares of large public companies. And it is the common man who benefits from the productivity improvements brought about by investments such as technology purchases or bonus payouts. At least, that is the theory.

This distributed ownership, the hallmark of capitalism, raises some interesting questions, I think. When a large oil company drills an unstoppable hole in the seabed, we find it easy to direct our ire at its executives, looking at their swanky jets and other unconscionable luxuries they allow themselves. Aren’t we conveniently forgetting the fact that all of us own a piece of the company? When the elected government of a democratic nation declares war on another country and kills a million people (speaking hypothetically, of course), should the culpa be confined to the presidents and generals, or should it percolate down to the masses that directly or indirectly delegated and entrusted their collective power?

More to the point, when a bank doles out huge bonuses, isn’t it a reflection of what all of us demand in return for our little investments? Viewed in this light, is it wrong that the taxpayers ultimately had to pick up the tab when everything went south? I rest my case.

Money — Love it or Hate it

Whatever its raison-d’etre may be, there is a need for more, and an unquenchable greed. And paradoxically, if you want to try to quench a bit of your greed, the best way to do it is to fan the greed in others. This is why the email scams (you know, the Nigerian banker requesting your help in moving $25 million of unclaimed inheritance, or the Spanish lottery eager to give you 67 million Euros) still hold a fascination for us, even when we know that we will never fall for it.

There is only a thin blurry line between the schemes that thrive on other people’s greed and confidence jobs. If you can come up with a scheme that makes money for others, and stay legal (if not moral), then you will make yourself very rich. We see it most directly in the finance and investment industry, but it is much more widespread than that. We can see that even education, traditionally considered a higher pursuit, is indeed an investment against future earnings. Viewed in that light, you will understand the correlation between the tuition fees at various schools and the salaries their graduates command.

When I started writing this column, I thought I was making up this new field called the Philosophy of Money (which, hopefully, somebody would name after me), but then I read up something on the philosophy of mind by John Searle. It turned out that there was nothing patentable in this idea, nor any cash to be made, sadly. Money comes under the umbrella of objective social realities that are quite unreal. In his exposition of the construction of social reality, Searle points out that when they give us a piece of paper and say that it is legal tender, they are actually constructing money by that statement. It is not a statement about its attribute or characteristics (like “This is a glass of water”) so much as a statement of intentionality that makes something what it is (like “You are my hero”). The difference between my being a hero (perhaps only to my six-year-old) and money being money is that the latter is socially accepted, and it is as objective a reality as any.

I conclude this article with the nagging suspicion that I may not have argued my point well enough. I started it with the premise that money is an unreal meta-thing, and wound up asserting its objective reality. This ambivalence of mine may be a reflection of our collective love-hate relationship with money – perhaps not such a bad way to end this column after all.

Photo by 401(K) 2013

Money — Why do We Crave it?

Given that the investment value is also measured and returned in terms of money, we get the notion of compound interest and “putting money to work.” Those who have money demand returns based on the investment risk they are willing to assume. And the role of modern financial system becomes one of balancing this risk-reward equation. Finance professionals focus on the investment value of money to make oodles of it. It not so much that they take your money as deposits, lend it out as loans, and earn the spread. Those simple times are gone for good. The banks make use of the fact that investors demand the highest possible return for the lowest possible risk. Any opportunity to push this risk-reward envelope is a profit potential. When they make money for you, they demand their compensation and you are happy to pay it.

Put it that way, investment sounds like a positive concept, which it is, in our current mode of thinking. We can easily make it a negative thing by portraying the demand for the investment value of money as greed. It then follows that all of us are greedy, and that it is our greed that fuels the insane compensation packages of top-level executives. Greed also fuels fraud – ponzi and pyramid schemes.

Indeed, any kind of strong feeling that you have can be bought and sold for personal gain of others. It may be your genuine sympathy for the Tsunami or earthquake victims, your voyeuristic disgust at the peccadilloes of golf icons or presidents, charitable feeling toward kidney patients of whatever. And the way money is made out of your feelings may not be obvious at all. Watching the news five minutes longer than usual because of a natural disaster may bring extra fortune to the network’s coffers. But of all the human frailties one can make money out of, the easiest is greed, I think. Well, I may be wrong; it may actually be that frailty that engendered the oldest profession. But I would think that the profession based on the lucrative frailty of greed wasn’t all that far behind.

If we want to exploit other people’s greed, the first thing to ask ourselves is this: why do we want money, given that it is a meta-entity? I know, we all need money to live. But I am not talking about the need part. Assuming the need part is taken care of, we still want more of it. Why? Say you are a billionaire. Why would you want another billion? I think the answer lies in something philosophical, something of an existential angst, although those with their billions would the last ones to admit it. The reason behind this deep-rooted need for more is a quest for a validation, or a justification for our existence, and a meaning and purpose for our life. It is all part of that metaphorical holy grail. I know, it sounds a bit nutty, but what else could it be? The Des Cartes of our time would say, “I have loads of money, therefore I am!”

The Ultra Rich

Let’s first take a look at how people make money. Loads of it. Apparently, it is one of the most frequently searched phrases in Google, and the results usually attempt to separate you from your cash rather than help you make more of it.

To be fair, this column won’t give you any get-rich-quick, sure-fire schemes or strategies. What it will tell you is why and how some people make money, and hopefully uncover some new insights. You may be able to put some of these insights to work and make yourself rich – if that’s where you think your happiness lies.

By now, it is clear to most people that they cannot become filthy rich by working for somebody else. In fact, that statement is not quite accurate. CEOs and top executives all work for the shareholders of the companies that employ them, but are filthy rich. At least, some of them are. But, in general, it is true that you cannot make serious money working in a company, statistically speaking.

Working for yourself – if you are very lucky and extremely talented – you may make a bundle. When we hear the word “rich,” the people that come to mind tend to be

  1. entrepreneurs/industrialists/software moguls – like Bill Gates, Richard Branson etc.,
  2. celebrities – actors, writers etc.,
  3. investment professionals – Warren Buffet, for instance, and
  4. fraudsters of the Madoff school.

There is a common thread that runs across all these categories of rich people, and the endeavors that make them their money. It is the notion of scalability. To understand it well, let’s look at why there is a limit to how much money you can make as a professional. Let’s say you are a very successful, highly-skilled professional – say a brain surgeon. You charge $10k a surgery, of which you perform one a day. So you make about $2.5 million a year. Serious money, no doubt. How do you scale it up though? By working twice as long and charging more, may be you can make $5 million or $10 million. But there is a limit you won’t be able to go beyond.

The limit comes about because the fundamental economic transaction involves selling your time. Although your time may be highly-skilled and expensive, you have only 24 hours of it in a day to sell. That is your limit.

Now take the example of, say, John Grisham. He spends his time researching and writing his best-selling books. In that sense, he sells his time as well. But the big difference is that he sells it to many people. And the number of people he sells his product to may have an exponential dependence on its quality and, therefore, the time he spends on it.

We can see a similar pattern in software products like Windows XP, performances by artists, sports events, movies and so on. One performance or accomplishment is sold countless times. With a slight stretch of imagination, we can say that entrepreneurs are also selling their time (that they spend setting up their businesses) multiple times (to customers, clients, passengers etc.) All these money-spinners work hard to develop some kind of exponential volume-dependence on the quality of their products or the time they spend on them. This is the only way to address the scalability issue that comes about due to the paucity of time.

Investment professionals (bankers) do it too. They develop new products and ideas that they can sell to the masses. In addition, they make use of a different aspect of money that we touched upon in an earlier column. You see, money has a transactional value. It plays the role of a medium facilitating economic exchanges. In financial transactions, however, money becomes the entity that is being transacted. Financial systems essentially move money from savings and transforms it into capital. Thus money takes on an investment value, in addition to its intrinsic transactional value. This investment value is the basis of interest.

Philosophy of Money

Money is a strange thing. It is quite unlike any otherthingthat we know. Its value manifests itself only in a social context where we have pre-agreed conventions as to what it should be. In this sense, money is not a thing at all, but a meta-thing, which is why you are happy when your boss gives you a letter stating that you got a fat bonus even though you never actually see the physical thing. Well, if it is not physical, it is metaphysical, and we can certainly talk about the philosophy of money.

The first indication of the meta-ness of money comes from the fact that it has a value only when we assign it a value. It doesn’t possess an intrinsic value that, for instance, water does. If you are thirsty, you find that water has enormous intrinsic value. Of course, if you have money, you can buy water (or Perrier, if you want to be sophisticated), and quench your thirst.

But we may find ourselves in situations where we may not be able to buy things with money. Stranded in a desert, for instance, dying of thirst, we may not be able to buy water despite our sky-high credit limits or the hundreds of dollars we may have in our wallet. One reason for this inability of ours is obviouswe may be alone. The basic transactional value of money evaporates when we have nobody to transact with.

The second dimension of the meta-ness of money is economical. It is illustrated in the well-worn supply-and-demand principle, assuming transactional liquidity (which is a term I just cooked up to sound erudite, I confess). I mean to say, even if we have willing sellers of water in the desert, they may see that we are dying for it and jack up the pricejust because we are willing and able to pay. This apparent ripping off on the part of the devious vendors of water (perfectly legal, by the way) is possible only if the commodity in question is in plentiful supply. We need commodity liquidity, as it were.

It is when the liquidity dries up that the fun begins. The last drop of water in a desert has infinite intrinsic value. This effect may look similar to the afore-mentioned supply-and-demand phenomenon, but it really is different. The intrinsic value dominates everything else, much like the strong force over short distances in particle physics. And this domination is the flipside of the law of diminishing marginal utility in economics.

The thing that looks a bit bizarre about money is that it seems to run counter to the law of diminishing marginal utility. The more money you have, the more you want it. Now, why is that? It is especially strange given its lack of intrinsic value. Great financial minds could not figure it out, but came up with pithy and memorable statements like, “Greed, for lack of a better word, is good.Although that particular genius was only fictional, he does epitomize much of the thinking in the modern corporate and financial world. Good or bad, let’s assume that greed is an essential part of human nature and look at what we can do with it. Note that I want to do somethingwithit, not “about” itan important distinction. I, intrepid columnist that I am, want to show you how to use other people’s greed to make more money.

Photo by 401(K) 2013