Article Detail

Behavioral Finance and Technical Analysis

Journal 32: Applied Finance

Kosrow Dehnad

Behavioural finance has challenged many claims of efficient market hypothesis (EMH). Unfortunately many of these challenges are in the form of anecdotal evidence and lack quantification. This article uses market data together with some simple statistics to show that in practice certain assertions of EMH and mathematical finance can be rejected with a high degree of confidence. The working of the FX market is used to demonstrate certain shortcomings of elegant results in mathematical finance that render them irrelevant in practice. An approach based on Markov chains is developed to model certain heuristic notions such as “fast market,” “support,” and “resistance,” that are widely used by “technical analysts” and practitioners. Using market observation, it is shown that this model better fits historical data than that implied by the assumption that daily returns are independent and normally distributed.

Behavioral finance started as an irritating challenge to advocates of efficient market hypothesis (EMH) and was initially ignored by them. It exposed instances of investors’ behavior that contradicted the main tenets of EMH which assumes that investors are rational decision makers and that at each instant the prices of securities reflect all available information about them. This implies that all the efforts by security analysts and traders to beat the market are futile and that investors should simply construct a portfolio consisting of a combination of risk-free assets and the “market” portfolio which best suits their risk appetite and lay back and enjoy the fruits of their investments. The EMH found an ally in the mathematical finance community where the above assumptions implied that prices were a martingale process, thus enabling the researchers in that field to use the techniques of Brownian motion to prove many elegant theorems. Further, by blending some supposedly “minor” simplifying assumptions with their work, such as absence of bid-ask spread or taxes, or homogeneity of time, or the ability of investors to lend and borrow at the same rate and as much as they desire, theoreticians opened the floodgates of dynamic hedging and option replication that has become an industry in itself.

There has, however, been growing evidence contradicting EMH such as: performance of investors such as Warren Buffet, George Soros, and Peter Lynch who have beaten the market year after year; the mini crash of 1987; the great recession of 2008, and the flash crash of 2010. Moreover, studies in behavioral finance have shown that certain hardwired biases and habits of humans make them a far cry from the rational and calculating decision makers who pounce on any opportunity to maximize their profit. As such anecdotal evidence have accumulated, exponents of EMH had to reluctantly modify their stances by introducing different flavors of efficiency, such as strong form efficiency, weak form efficiency, etc., and in all cases the statement of “all available information about a stock” is left as a nebulous concept. It should be pointed out that certain market practitioners, the so-called technical analyst or chartists, never paid any attention to the results of mathematical finance and EMH that are against the very grain of their work. These practitioners believe that certain price patterns repeat themselves and provide profit opportunities. Consequently, they pore over historical data and draw charts with acronyms such as “support,” “resistance,” “channel,” “head-and-shoulder,” and “momentum,” which according to EMH have no informational value whatsoever, in order to gain insight into market sentiment that hopefully will give them a trading edge. Justification of chartists for their approach to market is very intuitive and suffers from a lack of quantification though they use certain statistical terms such as moving averages or ratios. To justify some of these approaches psychologists have joined the foray and tried to provide an explanation for the way market behaves using psychology. Figure 1 is a cognitive psychology explanation of oscillation of prices that fall into a rising or falling band called a “channel.”

Most market observers are familiar with statements such as, “the market showed a number of abrupt rises interrupted by sideways movement in the congestion area, previous buyers selling to take home profits, and the new buyers taking advantage of an opportunity to get in. Sellers, also participating all the way up, each time noted that the market reached new higher peaks and that they should have stayed firm. Small drops were therefore used to come back in, and each increase provoked new buy interests.” Such descriptions that often lack hard data and statistical analysis to support them are in part responsible for the fact that the EMH camp dismiss some of the findings of behavioral finance by statements such as, “are these the tip of the iceberg or the whole iceberg?” Because in the absence of any statistical analysis, such descriptions of the causes of market behavior remain an interesting read at best. This article attempts to use statistical methods and market data to demonstrate that continuous time models based on Brownian motion disregard some of the basic characteristics of some markets and the behavior of their participants. This inattention has major practical implications and renders some of the results in mathematical finance a theoretical construct at best.

jailer