Chris Wagstaff takes a look at investment styles that lead investors to make the investment decisions they do
Since the early 1960s, academics and market practitioners alike have debated the efficient markets hypothesis (EMH). That is, whether stock prices reflect all publicly available information, react instantaneously and rationally to market news and move independently of past trends.
Behind the theory lies a key assumption that investors are rational, risk adverse, seek to maximise their wealth, and possess a limitless capacity to source and process information accurately. The implication of the EMH, that one cannot consistently outperform the market on a risk-adjusted basis, has always loomed over the active fund management community, which seeks to do just that.
However, the existence of pricing anomalies, markets over- and undershooting their fundamental values and the emergence of predictable patterns in equity market returns has given rise to a new way of thinking about the determination of security pricing. Behavioural finance analyses the way in which bias enters investors' decision-making processes and helps explain why these anomalies and patterns arise.
Overconfidence, based on an over exaggerated belief in one's own skill or ability to influence events, lies at the very heart of behavioural finance.
This overconfidence can stem from several sources, the first being selective memory. While poor investment decisions are often put down to bad luck, success is attributed to skill.
Many investors also suffer from hindsight bias and memory bias. The former is the tendency for individuals to convince themselves that they could have predicted a stock outperforming the market for instance, while the latter is the belief that they did predict the outperformance, when in fact they did not.
Overconfidence typically leads to investors placing too much faith in their stock selection and forecasting skills and trade excessively as a result. This means they incur substantial transactions costs and also add to market volatility in the process.
Overconfidence also manifests itself in investors, analysts and some strategists failing to incorporate new information into their original forecasts. By under-reacting to price-sensitive information, share prices experience post-earnings announcement drift, providing a short-term profit opportunity for those investors who capitalise upon this misplaced overconfidence.
Traditional finance theory assumes investors are risk adverse and view risk symmetrically. In reality, most are loss averse and view profits and losses asymmetrically. When faced with a guaranteed loss or an even chance to enter into a double or eliminate the loss gamble, most investors prefer to gamble.
Faced with the choice of whether to take a guaranteed sum of the same size or take the exact same double or quits gamble as before, most would opt for the guaranteed sum. In both cases, loss aversion is exhibited.
This behaviour may explain why many investors take profits on their winning investments too soon and hold onto their loss-making investments for too long.
Investors' failure to measure risk consistently or objectively often manifests itself in buying stocks at the top of the market and selling out at the bottom. This is explained by a tendency to be optimistic when markets are rising, or when a gain has recently been made, while becoming overly pessimistic, or loss averse, as markets fall or when a loss has recently been incurred. Excessive monitoring of share prices can also lead to an over-exaggerated view of volatility being formed, resulting in increased loss aversion.
Finance theory also assumes that investors can decipher investment information accurately without bias, no matter how it is presented. Most people, however, are heavily influenced in their decision making by the frame, or the form, the information takes rather than its substance.
For instance, the perceived risk and loss aversion associated with a particularly volatile stock will differ considerably depending on whether the past year's performance is presented in the form of a bar chart depicting weekly percentage price changes or as a linear line graph plotting cumulative absolute performance.
Most pricing anomalies in financial markets are said to stem from representativeness, or heuristics, the process by which investors try to simplify the complexities of making investment decisions. In order to gain a sense of familiarity and confidence, this information-gathering process tends to focus on particular facts or figures rather than the big picture and relies on extrapolating trends from a series of random events.
Typically, there is an over-reliance on past performance. This can manifest itself in investors becoming overly optimistic about stocks with a good track record and overly pessimistic about past losers, causing prices to depart from fundamental values. Investors can similarly become overly enthusiastic about top-performing funds, believing that fund managers periodically benefit from the Midas touch. Investors can therefore not only find it difficult to distinguish between genuine trends and random events but also between luck and manager skill in the case of outperforming funds.
Although momentum effects usually exacerbate this trend in relative performance for up to a year or so, empirical evidence suggests that superior risk-adjusted returns can be made by adopting a contrarian view, as relative performance reverses in the medium term.
By trying to simplify investment decision-making, investors can often end up taking on more risk. By assuming that the co-movement between the share prices of two oil companies, for example would always be greater than that between the share prices of two companies in unrelated industry sectors, without investigating their respective correlations and standard deviations, can often throw up some nasty surprises.
When investors are navigating uncharted waters, they derive comfort from anchors or benchmarks that they believe will assist them in their decision-making, even though this information may be totally irrelevant to the decision being made.
In blatant violation of the EMH, investors frequently use past share price data, especially recent highs and lows, as anchors against which to judge the attractiveness of a particular share price. However, as companies are constantly reinventing themselves and investor attitudes to certain stocks change as investment styles move in and out of favour, there is no reason for a stock price to return to or surpass its high, unless fresh news about the company comes to light. As the technology, media and telecoms experience has demonstrated, just when you thought a share could not possibly go any lower, it halves in value.
Emotional attachment to stock, or moral anchoring, also leads to sub-optimal decision-making.
Overconfident analysts reluctant to move away from their original earnings forecasts despite new information in company earnings announcements are also susceptible to anchoring effects. In conjunction with overconfidence, this leads to post earnings announcement drift.
Even experienced strategists suffer anchoring effects. By anchoring themselves to past market levels and performances, most equity strategists in the mid to late-1990s consistently underpredicted subsequent market rises.
Many strategists also suffer from gambler's fallacy ' a phenomenon closely linked to loss aversion ' by confusing the law of small numbers with the law of large numbers. For instance, after a run of heads from three flips of a coin, many people would believe that a tail was due based on their intuition about random sequences from coin tosses.
Applying this to equity markets, a three-year bull run would be expected by many strategists to turn tail the following year on the basis that the market has risen so far and so fast that it could not possibly go any higher.
This is precisely what happened in the US in 1998 after three consecutive years of 20%+ returns from the S&P500, based on US strategists' intuition that equity markets generally correct once in every three years and returns eventually revert to the mean.
Moreover, as markets hover at all-time highs, inexperienced investors tend to become more confident of their ability to outperform the market than their more experienced counterparts, not least because of the latter's susceptibility to gambler's fallacy and being anchored to past events and the former's vulnerability to overconfidence.
Although behavioural finance provides a useful insight to understanding how bias enters into investor decision-making behaviour, it does not provide a guaranteed path to riches.
After all, as the technology bubble experience showed, playing the rational investor when irrational price movements have gathered considerable momentum can prove to be an act of folly.
However, this has not prevented the emergence of a significant market in the US for behavioural finance mutual funds, given the potential to exploit anomalies thrown up by overconfidence, gambler's fallacy and an inability for many market participants to overcome the effects of anchoring, adjustment conservatism and loss aversion.
It will probably be only a matter of time before these funds and their underlying philosophy enter the mainstream and challenge the popularity of the index tracker market and its EMH underpinnings.
• The EMH is whether stock prices reflect all publicly available information, react instantaneously to market news and move independently of past trends.
• By trying to simplify investment decision-making, investors can often take on more risk.
• Investors' failure to measure risk often means they buy at the top and sell at the bottom.
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