Investor Myopia and the Momentum Premium across International Equity Markets

The existence of momentum returns has long been established by prior studies, but there has not been a definitive reason for why momentum returns occur.  The authors suggest the reason is that investors are myopic (i.e., nearsighted), and that speculators may overweight public information and underweight private information, which would result in prices taking longer to reach their true fundamental value and for more short-term information to drive prices.  In addition, institutional investor myopia may result from short-term incentives, producing price drifts similar to those found in behavioral models.

The authors took many countries and ranked them according to their level of cultural myopia.  Then they compared that myopia index to the level of momentum returns in each of the countries.  In doing so, they find that countries that tend to be myopic usually have higher momentum returns.

Next, the authors ranked and split the countries into 3 equal groups, then simulated forming equal-weight portfolios of countries for the "Myopic" third, the "Neutral" third, and the "Long-Termist" third.  They find that the myopic portfolio has much higher momentum returns than the long-termist portfolio over the 1988-2015 period.  So we might argue that countries that are culturally more myopic might have higher momentum returns, so the level of myopia of investors might explain momentum returns.

Finally, the authors form regressions of momentum returns and control for other factors that have been found to be related to momentum returns in other research.  The authors find that despite controlling for many other factors, the myopia factor is still significantly related to momentum returns.

Docherty, P., & Hurst, G. (2018). Investor Myopia and the Momentum Premium across International Equity Markets. Journal of Financial & Quantitative Analysis, 53(6), 2465–2490.

Kalok Chan, Hameed, A., & Tong, W. (2000). Profitability of Momentum Strategies in the International Equity Markets.

An academic paper read by Sawyer Investment Management Company regarding the results of using momentum strategies with market indices outside of the US.

Abstract:
This paper examines the profitability of momentum strategies implemented on international stock market indices. Our results indicate statistically significant evidence of momentum profits. The momentum profits arise mainly from time-series predictability in stock market indices--very little profit comes from predictability in the currency markets. We also find higher profits for momentum portfolios implemented on markets with higher volume in the previous period, indicating that return continuation is stronger following an increase in trading volume. This result confirms the informational role of volume and its applicability in technical analysis.

Citation:
Kalok Chan, Hameed, A., & Tong, W. (2000). Profitability of Momentum Strategies in the International Equity Markets. Journal of Financial & Quantitative Analysis, 35(2), 153–172.

Link to Paper:
https://www.jstor.org/stable/2676188?read-now=1&seq=19#metadata_info_tab_contents

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SIMCO is a Texas-registered Investment Adviser with its principal place of business in Dallas, Texas. It was formed on January 1, 2015 and is wholly owned by Ryan Sawyer, who is a CFA Charterholder and a Certified Public Accountant.

SIMCO specializes in the construction of equity portfolios, and is therefore an ideal resource for long-term investors. The firm goes through a rigorous process for selecting each and every holding in the portfolio. Rooted in the empirical research of academia, the portfolios are generally characterized as large-cap value momentum. For more information about how the portfolios are managed, see our website.

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Rational Expectations and the Impact of Money upon Stock Prices

The author notes the prior studies, noting significant relationships between money supply and stock prices; they also note that most recent studies have concluded that the stock market anticipates changes in the money supply and not the other way around.  Their addition to the area is by using the Barro equation, but splitting future changes in money supply into anticipated and unanticipated changes.  Under the efficient market hypothesis, unanticipated changes in the money supply would abruptly affect stock prices; however, expected changes would not.

He first uses the Barro equation to produce a regression with M2 as the dependent variable, and lagged money supply figures, the unemployment rate, and federal expenditures as the independent variables.  He shows these variable to explain 94% of the changes in M2 and to all be significant at a 95% confidence level.  In the second part, the author produces a regression with stock returns as the dependent variable; for the independent variables, he uses the previous money supply equation as the ANTICIPATED money supply changes, and he uses the residuals from this equation as the UNANTICIPATED money supply changes. 

The author found that the unanticipated changes in money supply were significant in changing stock returns; and the anticipated changes in money supply were insignificant.  He then produces the same equation with further lags, and the significance is even more pronounced in support of stock prices anticipating money supply changes.  He proposes that the link between money supply and stock returns found by other studies may in fact be a link between unanticipated changes in money supply and the act of sophisticated investors closing that gap.

Sorensen, E. H. (1982). Rational Expectations and the Impact of Money upon Stock Prices. Journal of Financial & Quantitative Analysis, 17(5), 649–662.

Money Supply and Stock Prices: A Probabilistic Approach

A relationship between money supply and stock prices is fairly recognized in the literature; Sprinkel and Palmer have tried to determine whether the money supply can predict stock prices.  If this could be done, an investor could allocate his capital to and from the market portfolio, or in and out of high and low beta stocks, in an attempt to time the market.

The authors use a probability function to predict when a turning point in the money supply yields a turning point in stock prices; and they boil this down to the combination (i.e., an "efficiency index") of a "reliability index" (i.e., what ratio of predicted turning points were true turning points) and a "opportunity loss index" (i.e., what ratio of true turning points were predicted by the system).

They then used M1 (currency held + demand deposits) and M2 (M1 + time deposits) components of the money supply and the Standard and Poor's 425 over the period January 1948 to December 1970 in their analysis.  Their results show that using a 3% filter for M2 seems to provide the best reliability index; wherein, the trough signals using M2 are 65% accurate and the peak signals using M2 are 59% accurate.  However, using the higher filter of 3% yielded a lower opportunity loss index, meaning there were several true turning points undetected by the system.

Overall, their efficiency index finds that the 2% M1/5% Stocks filter works best for peaks, and the 1% M2/5% Stocks filter works best at troughs; although the 1% M1/5% Stocks is close to the 1% M2/5% Stocks for troughs.  As such, using M1 with relatively sensitive filters seems to provide the best balance of reliability and opportunity loss for predicting turning points in stocks.

Gupta, M. C. (1974). Money Supply and Stock Prices: A Probabilistic Approach. Journal of Financial & Quantitative Analysis, 9(1), 57–68.