Retail investors overblowing value of high risk stocks

13 May 2015

Overconfident and naïve retail investors jump on high risk stocks when market sentiment is optimistic, overblowing their actual value and leading them to underperform, research has found.

These ‘noise’ traders – as they are known in finance – push up the value of risky stocks when market sentiment is optimistic, reducing their rate of return. But when sentiment is pessimistic, noise traders stay out of the market so riskier – or high beta - stocks earn higher returns on average.

Constantinos Antoniou, Assistant Professor of Finance and Behavioural Science at Warwick Business School, said: “This is because such unsophisticated traders, who may often face leverage constraints or simply be averse to borrowing, prefer high beta stocks during optimistic periods, as these promise higher perceived benefits from trading.

“On the other side of the coin, in periods of pessimism noise traders perceive equity investments as unattractive and participate less strongly in the stock market, so normal beta pricing prevails and these stocks produce the average returns their risk indicates according to traditional models.”

For the paper, Investor Sentiment, Beta, and the Cost of Equity Capital, due to be published in Management Science, Dr Antoniou, John Doukas, of Old Dominion University, and Avanidhar Subrahmanyam, of UCLA, looked at all common stocks listed on the New York Stock Exchange, AMEX and the Nasdaq.

“It had been thought that returns on stocks rise according to how risky they are – known as the capital asset pricing model (CAPM) - until a seminal study by Eugene Fama and Kenneth French in 1992 showed that the riskiness of a stock was unrelated to returns,” said Dr Antoniou. “Just why this is has been something of a mystery.

“This study examines this question and the relationship between the price of high beta stocks and variations in the amount of unsophisticated noise traders buying those stocks. When market sentiment is optimistic more noise traders will buy stocks, but studies have shown that these unsophisticated retail investors look for and expect higher returns.

“We argue that the heightened noise trader activity in optimistic periods will not affect all companies equally, but will be disproportionately concentrated among high beta stocks.”

This explains why the CAPM breaks down. During boom times noise traders will flood the market buying up risky stocks, so overpricing them, but during pessimistic times they will stay on the sidelines, so the market will be more in line with the CAPM. Overall these effects cancel out, so remaining hidden.

Looking at stocks from 1996 to 2010 on the three exchanges the study found high beta stocks produced poor returns during optimistic periods. The researchers then used different measures to see if noise trading increased during periods when market sentiment was optimistic.

Dr Antoniou added: “Our results across all measures consistently show that noise traders are indeed relatively more bullish and active for high beta stocks when sentiment is optimistic.”

As a result of this high optimism and bullish behaviour, the mutual funds studied experienced an average increase of inflows of $22 billion during optimistic periods relative to pessimistic ones.

The researchers also found large amounts invested into high beta stocks during optimistic periods, but no variation in flows across high and low beta stocks during pessimistic periods and that small noise traders are more active during a bullish market.

“These results have important implications for organisations, indicating that CFOs can use the capital asset pricing model for capital budgeting decisions in pessimistic periods, but not optimistic ones,” said Dr Antoniou. “It may be more appropriate to use other methods to derive valuations when the market is optimistic.”

Constantinos Antoniou teaches Behavioural Finance on the MSc Finance, which is also taught part-time at WBS London and Foundations of Finance on Warwick Business School's Undergraduate programme.

 

 

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