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2.1.2 Investor Segmentation

Several studies have been conducted in regard to categorising investors into various subgroups, based on financial knowledge, allocation strategies and personality, (Bailard et al. 1986; Gunnarsson and Wahlund 1997; Harrison 1994; Pompian 2012; Waneryd 2001; Wood and Zaichkowsky 2004) instead of treating them as a homogeneous and wholly rational unit, as done by MPT. Keller and Siegrist (2006) divided investors into 'Safe Players', 'Open Books', 'Money Dummies' and 'Risk Seekers', by virtue of their risk attitudes and perceptions toward securities, the stock market and gambling. Age is also found to be a causal factor in risk aversion (Riley and Chow 1992), along with one's occupation, wherein corporate executives and lawyers are found to be more risk averse (Barnewall 1987) and even the Myers– Briggs Type Indicator (MBTI) has been used to segment investors (Filbeck et al. 2005). Gender yields differences as well, with female investors exhibiting more risk aversion than male investors (Barsky et al. 1997). Unlike classical finance, behavioural finance does not view investors as having the same standardised and rational goals, instead construing the former as unique segments with varying and sometimes opposing aims.

2.1.3 Securities Markets

The capstone of capital markets research theorises that it is not possible to con- sistently achieve above average market returns, given the current information. This is more formally defined as the Efficient Market Hypothesis (EMH), which has three major forms, 'weak', 'semi-strong' and 'strong'. This theory, developed in the 1960s (Fama 1965; Samuelson 1965), state that when faced with new information some investors may underreact and others may overreact with an overall random pattern that conforms to a normal distribution. This results in a situation wherein market prices cannot be reliably exploited to make abnormal profits. Some of the classical finance thread espouses the maxim that the best established fact in eco- nomics is the efficiency of securities markets (Jensen 1978). However, many feel, especially in the aftermath of the recent financial crisis, that the blind trust in such a framework (Volcker 2011) along with deregulation, such as the Gramm–Leach– Biley Act,[1] has led to the downward spiral of the global economy. Brusquely put by Shiller (1981), the failure of the efficient market model is so dramatic, that it would seem impossible to attribute the failure to such things as data errors, price index problems or changes in tax laws. Behavioural finance sees the flaws in financial markets as due to cognitive biases and human error, as outlined below.

Investor sentiment, defined as the belief about future cash flows and investment

risks that are not justified by the facts available (Baker and Wurgler 2007), is one of the central tenets of behavioural finance. This phenomenon proposes to explain sudden swings in the markets, for example, the rise and fall of internet stocks in the 1990s (Baker and Wurgler 2013). Baker and Wurgler (2007) have shown that it is possible to measure investor sentiment, creating indices of the latter for the global markets and find that it plays a critical role in international market volatility (Baker et al. 2012).

Investors irrationally hold on to losing stocks, known as the disposition effect, [2]possibly to avoid confronting their incorrect investment decisions (Hirshleifer 2001; Shefrin and Statman 1985). This effect can cause underreaction to news, leading to predictable returns and post-announcement price drift[3] (Frazzini 2006). The dis- position effect is highest in non-professional and low-income investors (Dhar and Zhu 2002), reflecting that investors cannot be thought of a single and rational unit.

There exists the momentum effect, where past winners almost always outperform past losers (Jegadeesh and Titman 2001b). Stocks that perform the best or worst over a 3–12 months period tend to continue to perform well or poorly respectively over the subsequent 3–12 months (Jegadeesh and Titman 1993). Under the EMH, any predictable patterns in return should be swiftly eliminated. However, momentum profits have been found in most major developed markets in the world, excluding Japan (Jegadeesh and Titman 2001a). Whilst returns appear to exhibit momentum in the short–medium run, they tend to revert to fundamentals in the long run (Hong and Stein 1999).

Specifically concerning the internet boom, investor sentiment played a major

role in the stock prices of firms. Those that dropped the 'dotcom' naming con- ventions to dissociate themselves from the internet sector after the price crash saw a positive announcement effect (Cooper et al. 2005). It thus appears that the effect of investor sentiment is so severe that it can cause price variations even from mani- festations as trite as company name changes.

Research has shown that certain times of the year, in this case, January, predicate certain feelings in stock market investors, with the market performing well overall and smaller stocks out-performing larger ones (Anderson et al. 2007; Keim 1983; Rozeff and Kinney 1976). January is viewed to be one month of renewed optimism, with investors, regardless of their failure in that year, concluding that they can correct their mistakes on the next attempt, resulting in a perpetual January Effect cycle (Ciccone 2011; Polivy and Herman 2002). There is also evidence that it is the risk premium and not the risk itself that is higher in January, perhaps indicating that the January effect is due to higher compensation for risk in that month, rather than due to just risk (Sun and Tong 2010). The fact that disappointed investors never seem to learn, and mitigate that the cycle is testament to their irrationality, running against the grain of the everrational investors in the MPT sphere. Recent findings also indicate that the January effect is weakening (Jones and Pomorski 2002), but it is unclear whether this means that investors are becoming more rational, or some other effect is at play.

Notwithstanding monthly effects, even different days of the week predicate varying effects in the market, with the highest returns on Wednesday, and the lowest on Monday (Berument and Kiymaz 2001) and with the highest selling activity on the present day (Abraham and Ikenberry 1994). Also, Friday's returns are lower when Saturday is a trading day (Keim and Stambaugh 1983), with little reasonable explanation (Gibbons and Hess 1981), and the last trading day before holidays exhibits abnormally high returns (Ariel 1990; Kim and Park 1994). Returns from the May–October period are lower than the remainder of the year, known as the 'Halloween Indicator' and are often negative, but no explanation has been posited for this effect thus far (Bouman and Jacobsen 2002).

Even lunar phases have an effect on the stock market, with lower returns on days around a full moon than compared to those around a new moon (Floros and Tan 2013; Yuan et al. 2006). This has been observed for all the major U.S. stock indexes, and several other countries, but with no effects on return volatility or trading volume (Dichev and Janes 2003). Such effects are impossible to reconcile with rational means of price setting, and are clearly in opposition to all forms of the efficient markets hypothesis.

The weather affects markets as well; sunshine is positively correlated with stock returns (Dowling and Lucey 2005; Hirshleifer and Shumway 2003). The weather in New York City is has a long history of significant correlation with major stock indexes (Saunders 1993), completely unjustifiable by the MPT. Geomagnetic storms, during their recovery phase, also appear to negatively affect several inter- national stock indices, with a more pronounced effect for smaller capitalisation stocks, perhaps due to the profound effect on people's moods and that small cap- italisation stocks are generally held by individuals, who are likely to be more affected by mood than institutional investors (Krivelyova and Robotti 2003).

Sports results also affect market returns, with losses in international soccer matches having negative effects on global stock markets (Edmans et al. 2007). There also exists the Super Bowl Stock Market Predictor, [4] which if used as an investment strategy, over the 1967–1988 period, yields higher returns than a buy and hold strategy over the same period, clearly inconsistent with the efficient markets hypothesis (Krueger and Kennedy 1990). The Super Bowl also has other effects, with abnormal buying activity amongst small traders for recognised Super Bowl advertisers' shares (Fehle et al. 2005).

In relation to stock market data, it is found that despite investors acquiring useful information, they somehow misinterpret it and underperform the market (Barber and Odean 2000; Odean 1999). The type of audience to which the information is presented, is also significant. Unsophisticated investors[5] assess a firm's earnings performance to be higher when presented with more positive pro-forma earnings prior to Generally Accepted Accounting Principles (GAAP) earnings, than com- pared to when only shown GAAP earnings. Sophisticated investors, however, were not affected by the order of presentation or the information presented (Elliot 2006; Victoravich 2010).

In the perfect markets imagined by Miller and Modigliani, dividend policy is inconsequential to a firm's value, and stockholders should complain if a firm pays tax dividends, given that dividends are taxed at a higher rate than capital gains. However, stockholders often do the opposite, complaining when dividends are cut (Thaler and Bondt 1995). This illogical mode of thought may be because investors psychologically resist utilising their capital and view dividends as a separate gain when the stock price rises, and a fall back for price drops (Shefrin and Statman 1984). Repeatedly, the axioms of conventional finance have been challenged by contemporary financial phenomena.

Fashions and fads also affect securities prices, especially since investors are influenced by their social environment and are pressured to conform (Aronson 1991). For example, a downtrend may occur during a financial crisis, when investors irrationally decide to unload their holdings, as per the actions of their neighbour, or when a market guru prescribes the latest stock or investment heu- ristic. Investors face an uphill task when it comes to selecting securities, given the staggering amounts available. As most investors do not have access to a retail broker to suggest what they should purchase, they end up buying what is discussed in the media, those which have performed unusually well or poorly (Odean 1999).

The above phenomena could be explained by herding, [6] which may also have led

to bank panics, when depositors run on banks, seeing other depositors proceeding as such. Several herding models exist (Brunnermeier 2001), and there are higher levels of herding in small stocks (Wermers 1999). Furthermore, stocks bought by herds have higher returns than those sold by herds (Wermers 1999). Analysts release earnings forecasts that do not vary much from prior expectations, with a tendency to report forecasts similar to those released by other analysts, although their private information may justify differing forecasts (Trueman 1994).

Age also appears to play a part, as younger analysts are more prone to herding than their older contemporaries, with the former forecasting closer to the consensus forecast (Hong et al. 2000). It is observed that the twin stock of multinational companies, with nearly identical cash flows, move more like the markets where they trade most intensively than otherwise expected (Froot and Dabora 1999). This is in opposition to the classical finance paradigm that predicts that an asset's price is unaffected by its trade location.

Although behavioural finance is unable to resolve all the conundrums that exist within finance, it has done an admirable job of attempting to explain some of the ever irrational behaviour of investors, by passing every boom and bust. Whilst trading frequency seems to eliminate some market anomalies (Dhar and Zhu 2002; List 2003), perennial issues such as the Closed-End Fund Puzzle[7] and Equity Premium Puzzle[8] (Mehra and Prescott 1985) are still unresolved, although insights have been provided by the mechanisms of behavioural finance (Bernartzi and Thaler 1995; Lee et al. 1991). The overarching aim of behavioural finance is then not to replace the methods that compose classical finance, but to explain market anomalies, and complement existing frameworks that are already in place.

As a whole, behavioural finance explores how investors act in given situations,

and attempts to explain market anomalies. However, the means by which one pursues such goals is yet unexplored. Delving into the means of goal pursuit are necessary to understand how and why participants move toward these goals. Without comprehending these means, the market effects observed in behavioural finance will only be observed, never truly understood. Failing to grasp the means and underlying motivations of these behaviours, policies implemented to prevent future financial crises which are unlikely to be effective. Regulatory focus theory, as described in the following section, is putforth to explain the relationship between one's motivations and the associated goal.

  • [1] The Gramm-Leach-Biley Act repealed part of the Glass-Steagall Act of 1933, removing market barriers among banks, securities and insurance companies that prohibited any one institution from acting as both an investment bank, commercial bank or insurance company. With the Gramm-Leach-Biley Act, consolidation was allowed. Thus, people were then able to invest and save at the same financial institution
  • [2] The disposition effect is the tendency of investors to sell shares whose price has increased, while keeping those that have dropped in value
  • [3] The post-announcement price drift is the tendency for a stock's cumulative abnormal returns to move in a direction that will yield results that are higher or lower than analysts' predictions
  • [4] The Super Bowl Stock Market Predictor indicates that, if the Super Bowl is won by a team from the old National Football League, the stock market will finish the year higher than it began (Stovall, 1989). However, if the game is won by a team from the old American Football League, the market will finish lower than it began
  • [5] Sophisticated investors are those who possess stock market investment experience, and knowl- edge acquired through this experience and other practices, such as, completion of finance and accounting courses and certifications
  • [6] Herding can be defined as behaviour patterns that are correlated across individuals
  • [7] Since closed-end funds are exchange traded, their prices are different from the net asset value, defined as the closed-end fund puzzle
  • [8] The equity premium puzzle stems from the fact that the demand for government bonds is high, despite the fact that they return less than stocks, and why there is even a demand at all
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