Academic work on timing……………
Market Timing with Moving Averages
Paschal Glabadanidis2
University of Adelaide
Business School
November 9, 2012
I present evidence that a moving average (MA) trading strategy third order stochastically dominates buying
and holding the underlying asset in a mean-variance-skewness sense using monthly returns of value-weighted
decile portfolios sorted by market size, book-to-market cash-flow-to-price, earnings-to-price, dividend-price,
short-term reversal, medium-term momentum, long-term reversal and industry. The abnormal returns are
largely insensitive to the four Carhart (1997) factors and produce economically and statistically significant
alphas of between 10% and 15% per year after transaction costs. This performance is robust to different
lags of the moving average and in subperiods while investor sentiment, liquidity risks, business cycles, up
and down markets, and the default spread cannot fully account for its performance. The MA strategy works
just as well with randomly generated returns and bootstrapped returns. I also report evidence regarding the
profitability of the MA strategy in seven international stock markets. The performance of the MA strategies
also holds for more than 18,000 individual stocks from the CRSP database. The substantial market timing
ability of the MA strategy appears to be the main driver of the abnormal returns. The returns to the
MA strategy resemble the returns of an imperfect at-the-money protective put strategy relative to the
underlying portfolio. Furthermore, combining several MA strategies into a value/equal-weighted portfolio
of MA strategies performs even better and represents a unified framework for security selection and market
timing.
and holding the underlying asset in a mean-variance-skewness sense using monthly returns of value-weighted
decile portfolios sorted by market size, book-to-market cash-flow-to-price, earnings-to-price, dividend-price,
short-term reversal, medium-term momentum, long-term reversal and industry. The abnormal returns are
largely insensitive to the four Carhart (1997) factors and produce economically and statistically significant
alphas of between 10% and 15% per year after transaction costs. This performance is robust to different
lags of the moving average and in subperiods while investor sentiment, liquidity risks, business cycles, up
and down markets, and the default spread cannot fully account for its performance. The MA strategy works
just as well with randomly generated returns and bootstrapped returns. I also report evidence regarding the
profitability of the MA strategy in seven international stock markets. The performance of the MA strategies
also holds for more than 18,000 individual stocks from the CRSP database. The substantial market timing
ability of the MA strategy appears to be the main driver of the abnormal returns. The returns to the
MA strategy resemble the returns of an imperfect at-the-money protective put strategy relative to the
underlying portfolio. Furthermore, combining several MA strategies into a value/equal-weighted portfolio
of MA strategies performs even better and represents a unified framework for security selection and market
timing.
Paschal Glabadanidis2
