Most of us know that the value of an option increases when the uncertainty of the underlying increases. This is because options provide asymmetric payoff to the holder, allowing her to exercise the option in favorable circumstances and simply walk away in other situations. In a similar fashion, executives in large companies seem to hold management options provided to them by the shareholders of the firm. As uncertainty increases, the value of these management options increase. They allow the managers to exercise them if the company does well and claim “no-fault” if it does not. This has led to the culture of “no-consequence” management in which the chiefs claim high bonuses if the company (and the economy in general) gets lucky and blame everything else if things do not work out.
This has been ably demonstrated recently by investment banking executives who have claimed high bonuses in good times and appealed for bailouts in bad times. More subtly, the same phenomena have been happening in every other company. Managers of most large companies typically claim that the success of the company is due to their hard work but often blame the economy, government and other factors if the company fails. This is an option held by the managers of the firm. They exercise these options to their own benefits in good times and simply walk away in bad times.
Executive options will increase in value when the uncertainty of outcomes increases. The value of the executive, thus, is higher under chaos than in a stable regime. This means that it is dominant for executives of firms to increase uncertainty that automatically enhances their own value. A chaotic economy, thus, provides the executives of firms (especially the large ones) an automatic increase in worth. To correct this situation, negative bonuses and other creative incentives have to be implemented to make the pay-offs symmetric. Otherwise, we will prolong the “no-consequence” management culture that will make the economy worse off, save the executives.
Categories: Policy · economics
Many companies and organizations continue to measure time taken to complete defined activities and continue to use that as a proxy for productivity. When the end output is well defined and has low uncertainty in quality and quantity, such measurements may provide reasonable estimate of productivity. However, if the end product is not a tangible good or it shows significant uncertainty in quality, the time taken to complete the activity that aids in its production is not necessarily related to productivity.
For example, consider a car manufacturer who produces a tangible good (cars) with clearly measurable quantity output. Intuition may tell us that employees’ time spent inside the factory is a good proxy for the company’s profits (and hence the productivity of the employee). But this is not necessarily so. If the quality of the automobile has a significant impact on the buying habits of existing and future customers, it is not the production quantity that is related to profitability – it is the quality of products. Hence, measuring raw time spent inside the factory (that is related to quantity of production) is not useful in measuring productivity.
Similarly, if the company is producing intangible goods such as information (pharmaceuticals, hi-technology), measuring time of employees is not useful to manage the company better. Status-quo managers, some of them growing up in the industrial era and some others educated in the process-centric institutions and consulting firms may not only waste valuable resources by implementing time tracking systems but also create wrong signals on how to manage the company better. It is the implementation of such antiquated ideas of productivity measurement and management that is driving many large companies to the brink of disaster. Unless shareholders understand this and promptly remove such managers from these companies, the end outcomes will likely become more predictable.
Categories: business leaders · business model
If a hypothesis predicts an outcome and the observations far exceed the predictions in a measurable quantitative scale, is the hypothesis proven to be just correct, more correct or possibly incorrect? A recent story in the Times of London, poses this question in terms of climate change. It appears that the melting of the ice caps far exceed the predictions from simulations based on green house gas emissions, using the most pessimistic inputs. Supporters of the end of the world by CO2 hypothesis, may use this observation to convince themselves that, indeed, the world is fast progressing toward disaster. However, if observations do not quite fit the predictions, then, we may want to step back and consider a reformulation of the hypothesis.
There are both long cycle and unknown effects superimposed on short cycle and possibly known effects on the climate. The net effect of these phenomena is difficult to determine precisely. It is clear that pumping massive amounts of green house gases into the atmosphere may not be a good thing. But part of this comes from cows and Methane emitting volcanoes in the Atlantic in addition to aircrafts and automobiles. It may well be advisable to dial back our own emissions but that may not have much impact on the short cycle phenomena. To make matters worse, we are the victims of unknown long cycle phenomena that may have an even higher impact on what may happen to the climate.
As environmentalists lose sleepless nights cursing industrial development and ignorant automobile enthusiasts, worrying about the melting ice caps and rising sea levels, they may also want to consider the possibility that much of it is unavoidable.
Categories: Policy · Science
Amid the billions of $ wasted in the financial industry in forecasting financial asset values based on historical prices and financial statement analysis, two basic principles seem to have been forgotten.
(a) Financial assets are a mechanism to divide real asset values and transact
(b) Financial asset values are driven only by the underlying real asset values
Since financial asset values depend both on the current and future expectations of real asset values, any forecasting of the future, if need to be undertaken, has to start in the real markets. In real markets, value increases only by innovation and entrepreneurship. Contrary to popular belief, the behemoths of the industrial era, churning out yesterday’s products at a faster rate, aided by a low currency and the temporary appetite for status quo products from developing countries, add little value to the real economy. To improve real asset values, innovation rate has to increase and market conditions for entrepreneurship have to improve.
There are two major problems here for the economy – one strategic and the other tactical. On the strategic side, we have to create conditions that nourish innovation. Education is an important component of it. However, status quo designs of education systems rely on ideas from the last century – when prescriptive syllabus aided by physical experimentation was considered best. Such education may not improve innovation and may create a generation of educated people looking for jobs when no such jobs are available. A modernization of the education system and significant investment in this area will ultimately improve innovation and real asset values.
On the tactical side, we have to remove the impediments that currently exist for efficient flow of capital to those who seek to advance ideas. Arrogance from getting lucky in the 90s and related incompetence is prevalent in financial intermediaries, who are supposed to be helping this process. Printing money and giving it out to large institutions in the hope that they will spread it around efficiently is a bad policy. A new financial system has to take shape – one that is much smaller and nimble and one that understand value is actually created in real markets and not in bank vaults and trading floors.
Unless we focus on both improving innovation through a redesign of the education system and improving capital flow by a redesign of the financial system, any short term gains seen in financial assets will remain, short-term.
Categories: Policy
Investment banks who architected monopoly positions in the recent financial crisis, have been riding high again. With profits and bonuses soaring, some have been reestablishing themselves as the rulers of the universe and the keeper of the most of the world’s brain cells. Some have even paid back the “bailout” money – at least the ones that came through the front door but not the back door. The “smart” ones have been able to convince the public that the money that they received in insurance payments from the troubled insurer are theirs to keep and even to pay bonuses for its elite.
More troubling than the arrogance is the short memories of these companies. They appear to have already forgotten that the reason the US tax payers bailed their incompetence out was the possibility of the complete collapse of the financial system. They made this happen by taking excess leverage – granted to them by ignorant regulators of the past. But they seem to be set to play the movie again – hoping that the taxpayers will come to their rescue next time they lose big. I would love to have an uncle too who will let me gamble and keep the profits but bail me out when I lose.
Judging by the enormous profits taken in by the extremely smart investment banks lately, it looks like the taxpayers will be on the hook again soon. But this time, they may not have the grand father in the treasury to keep them out of trouble.
Categories: Finance
Many have been perplexed by the ups and downs of financial markets, disconnected from the real markets. Some may argue that the recent rise in the value of the financial assets has been predictable from analyzing the trends – technology waves, slow-down in foreclosures and other such metrics. Many such analyses describe why profits could rise in the future but point out the risks of them not materializing. Some are sure of the end outcome but unsure of the time it may take.
Extrapolating real market trends into financial markets is dangerous as known information generally do not produce trends. If a trend is seen in the financial markets, it is generally driven by artificial liquidity – money chasing money. Such trends have a tendency to break catastrophically. For example, some may argue that they could have easily predicted Apple’s stock price rise – driven by its popular iPhone platform. What they are forgetting however is an important aspect of investing. If one bought Apple at a low price just a few months ago and made a handsome profit, it is because she was gambling and some win in gambles, sometimes. When one buys a stock, however, she also buys the risk of the stock not performing. For technology companies such risk is high. Apple could have easily gone down if its new technology platform were not a hit.
Making money in the stock market is not rare but doing it consistently is. Large amounts of money can be made by taking commensurate amounts of risk. Risk adjusted excess return, alpha, however has been fleeting.
Categories: Finance
If human behavior is rational, one would expect actions that maximize long term utility. Since each individual is free to be strategic within constraints, the actions of the individual should reflect an attempt at maximizing long term utility. However, such actions are affected by the individual’s assumptions about the present and the future. This basic set of assumptions is what defines each individual and not the actions taken in accordance with them. It is possible that actions can be predicted if assumptions are known and hence the individual is only differentiated by her assumptions. Assumptions, however, are formed over time – influenced by the environment, friends, culture, religion and the society at large that constantly interact with the individual.
All catalysts for behavioral modifications – through incentives in private markets such as companies and profits in public markets – work on influencing the individual’s actions given generic assumptions. The theories that explain the working of the firm and the markets, implicitly assume that bounded rationality occurs because of limited information. It may not be the lack of information that bounds rationality – perhaps it is the excess of it. Since assumptions are based on information gathered by the individual over time through various actions, the more information is available, the more varied the assumptions are likely to be among individuals. This is because assumptions are the result of the processing of information by the individual, affected by unique environmental characteristics. Hence, we may find rationality is bounded because of variety in assumptions aided by excess information.
Thus, it is possible that rationality cannot be defined in the absence of assumptions. If assumptions are hidden, rationality cannot also be tested. Since assumptions are defined by the individual, they cannot be rejected. It is likely that rationality will be high under two conditions. A complete lack of information may mean generic assumptions and thus an ignorant individual is possibly rational. Similarly, a lack of variety in assumptions – as may happen if human society advances to the next level – may enhance the probability of rationality. So, it is not lack of information that creates bounded rationality; it is the variety in assumptions held by the individuals.
Categories: Science · economics
Lately, in the financial press and television as well as in quite corners of the local drinking holes, you find many who describe how they saw the whole thing coming – the financial meltdown, the real estate bubble, the commodity bubble, the hedge fund collapse – everything. It was so clear – the leverage was high, the debt levels unsustainable and “smart guys’ in Wall street were making stupid bets on everything. If any of these people had such infinite wisdom just 24 months ago, they could have retired the richest in the world. So, the question keeps popping up why these sages still work for a living or why they are drinking their sorrows away.
The answer may be simple – in hindsight everything is crystal clear. But since neither special theory of relativity nor quantum mechanics allow a safe passage to the future, such retrospective knowledge is as good as garbage. The ability to “see” what has happened is of no value – but if some believe that history will give them guidance for the future, they are entering fool’s paradise. Conventional wisdom appears to be that the world is ending – the Mayans prescribed the violent end to civilization in 2012. The prognosticators see troubles everywhere – private equity, US debt levels, US $ hyperinflation – it is the most deadly cocktail of problems. If any of these prognosticators shorted the US stock market, consistent with their beliefs just 6 months ago, they would have been carried out in a stretcher by now. Not to be left behind, many academics have also jumped on the bandwagon to hell – some predicting the end of humanity earlier than 2012.
If the world is expected to end in 2012, the discounted value of the world just a mere 2 years away to today will be nearly zero. Since the asset values have not collapsed to zero, there is a probability that we may find each other at the long side of 2012. But then, the doomsayers may be right as well. If the world does end, the most satisfying outcome will be the elimination of the prognosticators themselves.
Categories: Finance
An average of a set of observations is an alluring metric and many decisions are currently made on this wonderfully and holistically sounding statistic. Hypothesis testing is often conducted based on the assumption of normality when observations are presumed to fall on both sides of the average in a beautiful bell curve. Many scientific disciplines – medicine, engineering and economics – routinely employ averages and normality assumptions in making critical decisions.
However, averages can be quite deceiving when the normality assumption does not hold. It has been said that the average IQ in the living room with few people dramatically shot up whenever Einstein walked in. Similarly, performance of many funds is tolerable if you remove a few extreme observations. Weather is forecastable, except when it is not. Diseases can be conquered with medicines that sometimes kill you. Similarly, if earth’s polarity shifted many times in less than 10K year cycles and there were few episodes when nothing happened for millions of years, average time between episodes will be high but that is not comforting.
In a histogram of historical observations, it is often the case that the average is significantly shifted to the right of the mode (most likely outcome). Both the use of averages in decision-making as well as the use of hypothesis testing based on normality assumptions is fundamentally faulty as most events show skewness in the time between occurrences as well as the severity of an occurrence. In business, financiers and economists often use average cash flows in calculating a net present value of an investment or stock. In pharmaceutical research, bell curves are used to accept outcomes by discarding the probability of extreme events as small. In engineering, failure data provides a safety margin based on averages. In all these cases, the decision-maker is being coxed into a level of comfort by the misguided power of normality statistics. None of these decisions are likely optimal as they are based on the wrong assumptions. Higher moments (skewness and kurtosis) are necessary ingredients in making any decisions based on historical observations.
Categories: Science
Experiments in Physics, Biology and Economics have become increasingly more expensive and they, unfortunately, produce no or irrelevant results. The scientific process, that helped humans navigate early years of science and technology, has become a major hindrance to advance knowledge further. The idea has been to create a hypothesis that fits with the status quo framework and then design experiments to prove an aspect of the framework. The success of the experiment, thus, does not prove the theory and only increases the probability of the theory being correct. As the complexity in theory increases linearly, the complexity in experiments needed to prove components of the theory seem to have increased exponentially.
CERN’s attempt at producing the Higgs boson in the Large Hadron Collider is one such situation. The existence of this elusive particle does not prove the hypothesized framework but only enhances the probability of it being correct. More importantly, the existence of the Higgs boson may create challenges to other established notions such as the irreversibility of time – making it very difficult to understand why we would spend over $10 Billion to do so. In such cases, it may be better to suspend physical experimentation as we may have reached the complexity threshold and further knowledge increase is unlikely to happen by following the conventional processes of hypothesis creation and attempting to find physical proof.
Humans have gone through these types of situations before. Our ability to abstract a situation moved us from the need to physically see something before we act. Art allowed us to imagine and add color to both observable and imagined things. We are approaching this threshold in science as well, where abstraction is more efficient – with mathematics being the dominant tool. Experiments, if needed, may have to be designed to be flexible – i.e. not to prove a hypothesis but to keep the end outcome undefined. Such experiments may have a higher probability of advancing knowledge at a much lower cost to society. As complexity increases, the frameworks are likely to switch faster and thus flexible experiments that have a higher probability to shift knowledge is more valuable than those with prescribed and rigid outcomes.
Categories: Policy · Science
