Research Articles

In finance, arbitrage is an essential framework to understand asset pricing. However, the study of anomalies also called as premiums, which are not arbitrageable has led to a debate regarding whether markets are efficient in correcting price imbalances or is inefficiency a reality. This is why the Economics Nobel prize 2013 was awarded to both the behavioral and fundamental school. This paper explains the circular argument between the three schools of thought. The Fama school which uses factors to explain asset performance, the behavioral school which is focused on psychological biases and the old Beta school which consider the arguments of value vs. growth are all fleeting.

Information is an assumption for modern finance. The Efficient Market Hypothesis uses information to back its case for efficiency. The EMH case is weak, but as Martin Swell (2011) explains until a flawed hypothesis is replaced by better hypothesis, criticism is of limited value. This paper challenges the information assumption in EMH based on the idea laid out first by Kenneth E. Boulding (1966), highlights the body of work discussing information relevance, information irrelevance, information content since Ball and Brown (1968) and illustrates how ‘Mean Reversion Framework’ (2015) can be used to re-explain the transformation of information from relevance to irrelevance, also referred to as the ‘Reversion Diversion Hypothesis’.

Searching for alpha is searching through inefficiency because there are no supernormal returns in efficiency. This seems intuitive and correct because there is a cost to searching through inefficiency. And agents who spend that cost have to be rewarded for that effort. The case for inefficiency is unassailable.

I really don’t know why Richard Thaler chose this headline for a research paper. Many other behavioral finance academic papers also capture attention. “Can the markets add and subtract?”; “The winner’s curse”; “The gambler’s fallacy”, “Does the stock market overreact?” While the popularity of the subject has increased and behavioral biases have got so pervasive that everybody seems to be biased, the question is whether the behavioral finance experts are bias-free?

Style box for the investor is a visual representation of investment characteristics for stocks, fixed income and mutual funds offered as a comparative tool to investors around the world for helping them determine asset allocations based on their risk preference.

Over the post-event dinner at the Princeton – UChicago quant conference, the conversation veered to the definition of an intelligent system. My co-speaker (a physicist) from the conference defined an intelligent system as a system that is entropy reducing.

Quantum physics may not seem much to have to do with risk and investing, but with subjects like psychophysics explaining the statistical behavior in psychological behavior, it’s just a matter of time that science could explain more of markets. John Gribbin’s biographic work on Schrödinger has a lot of jargon relevant for understanding universal behavior. Apart from wave nature, the book talks about a multiplicity of waves, symmetry of ‘time’, statistical laws, natural behavior, entanglement, natural events and how everything depends on probability. Uncertainty and chance are a part of science. Laws can co-exist with uncertainty and error. This is what makes quantum physics a bit incomprehensible. As according to behavioral finance, the majority can’t calculate and comprehend probability (uncertainty).

Disruption is happening all the time. And it will happen in the active investing business too. What is active investing? Anything which starts from intraday trading to mutual funds to hedge funds can be bundled as active investing. Anything which is designed to conserve capital (even if it does not) and deliver absolute returns is Active. Anything non-standardized using fundamental analysis, quantitative, technical, behavioral or based on interdisciplinary studies also would come under the same classification. Anything not Passive can also be called Active. Anything held for a periodic rebalancing of 3 months and higher (say up to 60 months) would be more towards Passive.

Is there was a way to build a portfolio of non-leveraged short positions? This is new territory because industry’s focus on building models for a long-only focused market, but also because short, and long-short enter the alternative or hedge territory, an underrepresented segment globally. The idea of a short index does not exist while the short ETFs are in their nascency. As global money managers still are predominantly ‘buy and close’ rather than buy with a short hedge. As markets become harder to understand, the lines between trading and investing have finally started to blur.

Building my case from last time (the fortune index), where I suggested databases should talk to themselves and if natural systems express universal laws like patterns, divergences, seasonality, and constants then the data generated or derived from these natural systems should also express this universality. And if the data also express this universality then the question to be asked here is whether the universality character lies in something common to data rather than to a natural system.