Investor sentiment has a, sometimes erroneous, effect on stock market valuations. There is evidence that higher risk stocks become overpriced in periods of optimistic sentiment and undervalued when sentiment is pessimistic. Optimism attracts equity investment by unsophisticated, overconfident, retail investors in risky opportunities while such traders are less active in pessimistic periods. Thus sentiment can wrongly influence company share prices, and both investors and CFOs planning financial strategy should be wary.
In finance, a capital asset's sensitivity to risk is often represented by the quantity beta (β), and investment opportunities that have a high risk profile are known as ‘high beta’ stocks. In this research it is hypothesized that ‘high beta’ stocks are unduly influenced by sentiment due to the investment decisions taken by ‘noise’ traders.
It is assumed that stock traders analyse all the relevant fundamental data in order to make rational investments. However many investors, known in the finance industry as ‘noise’ traders, make decisions to buy, sell, or hold stocks based on general trends or noise. These traders’ decisions, made without the use of fundamental data, are often irrational and erratic. The presence of noise traders in financial markets can cause stock prices to diverge from expected levels even if all other traders are rational.
In their research Constantinos Antoniou, John A. Doukas, and Avanidhar Subrahmanyam, from Warwick Business School, Old Dominion University, and UCLA Anderson School of Management, looked at all common stocks listed on the New York Stock Exchange, AMEX and the Nasdaq, and examined the relation between beta pricing and variations in the degree of unsophisticated trading due to the dynamics of investor sentiment.
In the context to equity investment, the phrase ‘sentiment’ refers to whether or not an agent possesses excessively positive or negative expectations, and evidence from research in decision sciences shows that positive sentiment results in overly optimistic views, and vice versa.
Previous research has suggested that unsophisticated trading will be more prevalent and impactful in optimistic periods. In this new research it is argued that the heightened noise trader activity in optimistic periods will not affect all companies equally, but will be disproportionately concentrated among high beta stocks. Preference for high beta stocks is particularly strong among unsophisticated retail investors (i.e. those who trade the most and earn the lowest returns – typically young, single males).
Their analyses using earnings expectations, fund flows, the probability of informed trading, and order imbalances do provide evidence that noise traders are more bullish about high beta stocks when sentiment is optimistic, while investor behaviour appears to accord more closely with rationality during pessimistic periods.
The ultimate consequence of retail investors’ (noise traders) actions in investing disproportionately in high risk stocks, when market sentiment is optimistic, is to cause stock value inflation and eventual underperformance, leading to lack of investor confidence, share price drops and a significant impact on a company’s prospects.
Both the security market line (SML) which represents a capital asset’s expected rate of return and the opportunity cost of investing in that asset, and the CAPM, a model that describes the relationship between risk and expected return are influenced by optimistic sentiment periods.
These effects according to this research appear to be exaggerated because periods of optimism attract equity investment by unsophisticated, overconfident, traders in risky opportunities (high beta stocks), while such traders stay along the sidelines during pessimistic periods. Thus, high beta stocks become overpriced in optimistic periods, but during pessimistic periods, noise trading is reduced.
These results have important implications for organizations, indicating that CFOs can use the CAPM for capital budgeting decisions in pessimistic periods, but not optimistic ones, assuming such periods can be identified. Thus, for real investments undertaken during periods of optimism, it may be more appropriate to derive valuations from model-free methods, using, for example, comparables, and price multiples such as the P/E ratio.
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