Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for October 2021 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for October 2021 (Final)
1st ETF 2nd ETF 3rd ETF

Betting Against Lottery Stocks

| | Posted in: Animal Spirits, Volatility Effects

Do lottery traders create the low-volatility (betting-against-beta) effect by overpricing high-beta stocks? In the December 2014 version of their paper entitled “Betting against Beta or Demand for Lottery”, Turan Bali, Stephen Brown, Scott Murray and Yi Tang investigate whether demand for lottery-like stocks drives the empirically low (high) abnormal returns of stocks with high (low) betas. They measure lottery demand for a stock as the average of its five highest daily returns over the past month. They measure beta for a stock as the slope from a regression of its daily excess (relative to the risk-free rate) stock returns versus daily excess stock market returns over the past 12 months. They hypothesize that lottery traders drive current prices of stocks with high lottery demand upward, thereby depressing their expected returns. They further hypothesize that stocks with high lottery demand tend to be high-beta stocks. Using daily and monthly returns and characteristics for a broad sample of U.S. common stocks (excluding those priced under $5), associated firm accounting data and relevant financial variables during July 1963 through December 2012 (594 months), they find that:

  • A betting-against-beta effect is evident in the sample.
    • The average monthly difference in gross returns between the tenths of stocks with the lowest and highest betas is a statistically weak 0.35% per month.
    • This raw return translates to a statistically significant gross monthly four-factor (market, size, book-to-market, momentum) alpha of 0.51%, about equally balanced between long side of the hedge portfolio (0.22%) and short side (0.29%).
    • The low-beta side of the hedge portfolio holds relatively smaller stocks (average 1.9% of total market capitalization) than the high-beta side (12.9%), and the low-beta side is less liquid than the high-beta side.
  • There is a strong negative relationship between lottery demand and future stock returns.
    • The average monthly difference in gross returns between the tenths of stocks with the lowest and highest lottery demands is a very statistically significant 1.15%.
    • This raw return translates to a statistically significant gross monthly four-factor alpha of 1.40%, which comes mostly from the short side of the hedge portfolio (1.14%).
  • The alpha of the betting-against-beta hedge portfolio disappears after controlling for lottery demand. However, the economic and statistical significance of lottery-demand hedge portfolio alpha persists after controlling for beta.
  • Lottery demand creates the betting-against-beta effect via upward price pressure (and thus downward expected return pressure) on high-beta stocks.
    • On average, market beta and lottery demand have a high positive correlation across stocks.
    • When this correlation is relatively high (low), the betting-against-beta effect strengthens (weakens).
    • When aggregate lottery demand is relatively high (low), the betting-against-beta effect is relatively strong (weak).
  • Individual investors drive lottery demand, such that stocks with low institutional ownership drive the betting-against-beta effect.

In summary, evidence indicates that demand for lottery-like stocks drives the betting-on-beta or low-volatility effect, mostly due to poor future performance of high-lottery demand/high-beta stocks.

Cautions regarding findings include:

  • Returns and alphas are gross, not net. Accounting for monthly portfolio reformation and shorting costs would reduce reported returns and alphas. Shorting of some stocks may not be feasible.
  • Trading on lottery demand is mostly a short play, with reliable exploitation requiring many short positions over extended periods. Such a portfolio may bear sharp drawdowns.

See also a summary of prior related work in “Overpaying for Jumpy Stocks?”.

Login
Daily Email Updates
Filter Research
  • Research Categories (select one or more)