Reversal Effect in International Equity ETFs

DeBondt and Thaler in 1985 have found the presence of the winner-loser reversals in the U.S. stock market. The idea is simple; stocks that have been “losers” in a given ranking period are likely to yield higher returns than the corresponding “winner” stocks subsequently. Since the first study, the winner-loser reversals in the U.S. stocks have been studied mainly by academics, and the idea was slightly modified in search of even better performance.
Moreover, the winner-loser reversals were also found by the Richards (1995) in national stock market indices. This paper extends his research and explores it even more while using data for the return indices of 16 national markets. The finding of the paper that reversals are strongest around the 3-year horizon during the testing period results in a merely manageable strategy. The results are similar to those of Balvers, Wu, and Gilliland in the “Stock Markets and Parametric Contrarian Investment Strategies”. They have found strong evidence of mean reversion in relative stock index prices. Their findings imply a significantly positive speed of reversion with a half-life of three to three and one-half years (similar to the results of this paper). Additionally, their result is robust to alternative specifications and data.
The results could also be linked with the work of Spierdijk, Bikker and Van den Hoek – “Mean Reversion in International Stock Markets: An Empirical Analysis of the 20th Century“, this paper analyzes mean reversion in international stock markets during the period 1900-2008, using annual data and stock indexes in seventeen developed countries, covering a time span of more than a century. They have documented the half-lives ranging from a minimum of 2.1 years to a maximum of 23.8 years. Their results also suggest that the speed at which stocks revert to their fundamental value is higher in periods of high economic uncertainty, caused by significant economic and political events. Additionally, although the reversion in stock indices is present and profitable, we can say the same about momentum. Balvers and Wu in the “Momentum and mean reversion across national equity markets” explored these effects jointly. Quoting the authors: “Combination momentum-contrarian strategies, used to select from among 18 developed equity markets at a monthly frequency, outperform both pure momentum and pure contrarian strategies”.

Fundamental reason

The paper has explored potential explanations for reversals in the relative performance of national stock markets over periods of several years. However, some factors make it impossible to identify the real explanation surely. The short data sample, the relatively small number of countries, the possibility of imperfect integration of markets, and the lack of a generally accepted asset pricing model combined make it difficult to distinguish between these possible interpretations. Although, the absence of an explanation for the winner-loser reversals in national market indices is not surprising given that researchers still differ in their assessment of the causes of price-based anomalies in the U.S. market.
Firstly, the major result of the paper is the absence of any support for the hypothesis that the reversals reflect risk differentials. No evidence suggests that returns during the backtesting period of prior losers were significantly riskier than those of previous winners while looking both on their standard deviations and their correlations with the world market return or other known risk factors. Anyway, there is evidence that winner-loser reversals are more significant among the smaller markets than the broader markets, so there may be an element of a “small-country effect” or related to some form of market imperfections. Secondly, a possible interpretation of the results might be that reversals are the result of cross-border equity flows being insufficiently significant to remove mispricing, perhaps due to investors’ fears of expropriation or capital controls. Preliminary evidence for this view might be found in the observation that the contrarian strategy would have yielded below-average returns near the end of the sample period, however as it was previously mentioned, even some more recent papers identify this anomaly. Another possible interpretation could be that it may not even be realistic to expect from arbitrage to remove all price discrepancies given the uncertainty in the valuation of equities, the high volatility of returns, and the long-time required for mispricing to be removed. Last but not least, increases in cross-border flows may add to the degree of mispricing because it implies that there will be more momentum investors to “jump on the bandwagon” of the moment.

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Markets Traded
equities

Financial instruments
ETFs, funds

Confidence in anomaly's validity
Strong

Backtest period from source paper
1969-1995

Notes to Confidence in Anomaly's Validity

Indicative Performance
6.4%

Period of Rebalancing
3 Years

Notes to Indicative Performance

per annum, performance from Table 1 Panel B for holding period 36 months


Notes to Period of Rebalancing

Estimated Volatility
0%

Number of Traded Instruments
8

Notes to Estimated Volatility

not stated


Notes to Number of Traded Instruments

in a sample study, it depends on investor’s need for diversification


Maximum Drawdown
0%

Complexity Evaluation
Simple strategy

Notes to Maximum drawdown

not stated


Notes to Complexity Evaluation

Sharpe Ratio
0

Simple trading strategy

The investment universe consists of 16 ETFs (funds) that invest in individual countries’ equity indexes. Go long on the bottom four countries with the worst 36 – month return and go short on the top 4 countries with the best 36-month return. Rebalance every three years.

Hedge for stocks during bear markets

No - Mean reversion in country equity indexes is again a long-only strategy and, as such, has a strong exposition to equity market risk. Long-term mean reversion factor usually works best after crises but is not the right candidate for hedging equity risk during crises.

Source paper
Strategy's implementation in QuantConnect's framework (chart+statistics+code)
Other papers

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