Why Noise Traders Do Not Move Markets

Total Length: 1593 words ( 5 double-spaced pages)

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Analysis of “Investor Sentiment, Beta, and the Cost of Equity Capital”

In the study by Antoniou, Doukas and Subrahmanyam (2015), the researchers look at CAPM, beta, noise traders, periods of optimism and periods of pessimism to test a number of hypotheses: first, that optimistic times lure noise traders into buying high beta stocks, which causes high beta stocks to be overpriced;

Noise traders are defined as “young, single males, who lose the most from investing, and are the most susceptible to overconfidence” (Antoniou et al., 2015, p. 352). This definition is not explicitly given but is rather stated in terms of most unsophisticated traders being characterized by these qualities. Considering that about 90% of the market consists of insititutional investors—not retail buyers and certainly not noise investors—the ability of a small percentage of unsophisticated investors to drive price action in high beta stocks for a sustained period of time should be viewed as dubious at best. Volume alone should be an indication of how much interest is occurring in high beta stocks—and if high beta stocks are being pushed upwards in price during optimistic periods on low volume, there is likely to be an opposite reaction among sophisticated short sellers, which will inevitably drive the price down if support levels are not bolstered by buyers other than noise traders. If high beta stocks maintain high prices for a sustainable period (even if that period is optimistic—a problematic term in and of itself since the entire market has been “optimistic” since the first round of QE and only now with quantitative tightening seeming like a sure thing does a hint of pessimism begin to be surfacing) there is very likely to be a good portion of institutional investors also buying. So the hypothesis that noise investors are responsible for inflating high beta stocks over a sustained period of optimism is likely inaccurate at best.

The second hypothesis is that during pessimistic periods, noise traders flee high beta stocks because sell side analysts are less euphoric (“optimistic”) in their analysis, which causes high beta stocks to be positively priced. The problem with this hypothesis, as with the first one, is that perceptions of overpricing and underpricing are completely subject and depend entirely on one’s perspective, which is only proven correct or incorrect over time as the stock prices rises or falls in response to market conditions, news catalysts, and myriad other factors. To suggest that noise investors along are responsible for price action in high beta stocks is to ignore the realities of market conditions and wider economic and financial conditions in the developed world, where institutional investors and fund investors have been forced into adopting a risk-on strategy to obtain the desired yield, as interest rates have been kept near zero since the crisis of 2007-2009.
Now that the Fed Funds Rate is rising, one can see the anxiety of the market, with volatility rising and high beta stocks seeing investors get weak hands. A better factor to study would have been to measure high beta stock price action by movement in the Fed Funds Rate—but the researchers’ interest is in noise investors and whether they are the reason high beta stocks have lower returns in optimistic periods than in pessimistic periods (the noise investors cause the stocks to be overbought in optimistic periods). The conclusion should be foregone—but it is not, so it is helpful to observe other forces in the market that could account for the overbought status of high beta stocks in optimistic times.

First there is the rise of algorithmic trading that dominates the market today. It is estimated that 90% of volume in equities market is due to algorithmic trading. That is an astonishing figure but it corresponds with the percentage of trading done by institutional investors. So these figures alone indicate that if any stock is overbought one has to look at who or what is doing the buying and noise investors are simply not that powerful or influential of a force in today’s markets to account for that status. If anything, they are momentum traders—but then so too are many quant fund managers. Algorithmic trading has ushered in the era of buying the dip (but that is in large part thanks to a market supported by QE). It remains to be seen whether the buy-the-dip approach will be sustained with QT.

Nonetheless, with so many trades being done by algorithms that could easily be characterized as noise investors too since they are programmed to look at data (headlines, non-sequiturs, and just about anything that can be imagined) before making a decision on whether to buy or sell: their only difference is that they can do….....

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References

Antoniou, C., Doukas, J. A., & Subrahmanyam, A. (2015). Investor sentiment, beta, and the cost of equity capital. Management Science, 62(2), 347-367.

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