Market Timing With Moving Averages

I present evidence that a moving average (MA) trading strategy has a greater average return and skewness as well as a lower variance compared to buying and holding the underlying asset using monthly returns of value‐weighted US decile portfolios sorted by market size, book‐to‐market, and momentum, and seven international markets as well as 18,000 individual US stocks. The MA strategy generates risk‐adjusted returns of 3–7% per year after transaction costs. The performance of the MA strategy is driven largely by the volatility of stock returns and resembles the payoffs of an at‐the‐money protective put on the underlying buy‐and‐hold return. Conditional factor models with macroeconomic variables, especially the default premium, can explain some of the abnormal returns. Standard market timing tests reveal ample evidence regarding the timing ability of the MA strategy.     

When Is a Firm's Information Asymmetry Priced? The Role of Institutional Investors

This study reexamines the competing claims that probability of informed trading (PIN) is priced in the cross‐section of stock returns while adjusted PIN (AdjPIN), the component of PIN related to information asymmetry, is not. We find that behind these seemingly contradicting conclusions is the role of institutional investors, and the pricing of PIN and AdjPIN depends on institutional ownership. Only for those stocks with low institutional ownership are both PIN and AdjPIN priced. Our findings imply that investors require compensation for information risk only from stocks with low institutional ownership.     

Foreign Ownership Restriction and Momentum – Evidence from Emerging Markets

This study investigates the impact of foreign investors on stock price efficiency and return predictability in emerging markets. It finds that stocks fully investible for foreign investors exhibit stronger price momentum than non‐investible stocks. The difference in momentum effects between stocks with different levels of investibility cannot be fully explained by world market risk, size, turnover, or country‐specific factors. Further tests show that fully investible stocks have no post‐earnings‐announcement drift (PEAD), and their short‐term momentum reverses over a longer horizon. These results show that the stronger momentum of highly investible stocks does not appear to be driven by foreign investors' underreaction to firm‐specific information, but is more likely to be generated by their positive feedback trading.     

Heterogeneous firm-level responses to trade liberalization: A test using stock price reactions

This paper presents novel empirical evidence on key predictions of heterogeneous firm models by examining stock market reactions to the Canada–United States Free Trade Agreement of 1989 (CUSFTA). I derive testable predictions for a class of models based on Melitz (2003). Using the uncertainty surrounding CUSFTA's ratification, I show that the pattern of abnormal returns of Canadian manufacturing firms was strongly consistent with predictions related to export (U.S.) tariff reductions, but less so with predictions related to import (Canadian) tariff reductions. Lower Canadian tariffs did have an effect through the implied reduction in intermediate input tariffs, however.     

The price effects of index additions: A new explanation

We further explore a new volatility explanation for the permanent price effect of index additions, using a sample of changes in the Nikkei 225. Additions to the index elicit significant price hikes, which tend to be permanent despite temporary price reversals. Meanwhile, investor awareness and demand increase, while price volatility decreases for the added stocks, contrary to the higher price volatility for stocks added to the S&P 500. Moreover, multivariate regression analysis demonstrates that the lower volatility contributes significantly to the permanent price boost, a new explanation; so does the higher investor awareness, consistent with the prior literature.     

Deep order flow imbalance: Extracting alpha at multiple horizons from the limit order book

We employ deep learning in forecasting high-frequency returns at multiple horizons for 115 stocks traded on Nasdaq using order book information at the most granular level. While raw order book states can be used as input to the forecasting models, we achieve state-of-the-art predictive accuracy by training simpler “off-the-shelf” artificial neural networks on stationary inputs derived from the order book. Specifically, models trained on order flow significantly outperform most models trained directly on order books. Using cross-sectional regressions, we link the forecasting performance of a long short-term memory network to stock characteristics at the market microstructure level, suggesting that “information-rich” stocks can be predicted more accurately. Finally, we demonstrate that the effective horizon of stock specific forecasts is approximately two average price changes.     

Information Asymmetry and Quarterly Disclosure Decisions by Firms: Evidence From the Tokyo Stock Exchange

This study investigates whether the new quarterly disclosure reporting requirement issued by the Tokyo Stock Exchange was related to the reduction of the degree of private information‐based trade and the liquidity of listed stocks in Japan, or as a reverse causality, helped dichotomize good firms and bad firms as a separating signaling equilibrium. We use the probability of asymmetric information‐based trade (Adjusted PIN) as a measure of information asymmetry and the probability of symmetric order‐flow shock (PSOS) as a measure of market illiquidity. We use a sample of public firms from 2002 to 2007 that chose to either disclose or not disclose quarterly financial reports. We find that the disclosing firms had lower information asymmetry (Adjusted PIN), lower symmetric order‐flow shocks (PSOS), and lower private information‐based trade (PIN). When we conduct further difference‐in‐differences tests, we find that the firms with lower information asymmetry and higher liquidity had a higher tendency to disclose their financial statements and vice versa. Thus, the new disclosure requirement did not necessarily improve the information asymmetry and liquidity of firms, but instead helped good and bad firms form a case for a separating signaling equilibrium.     

Dispersion in Analysts’ Earnings Forecasts and Market Efficiency

Recent studies show that firms with higher analysts’ earnings forecasts dispersion subsequently have lower returns than firms with lower forecasts dispersion. This paper evaluates alternative explanations for the dispersion–return relation using a stochastic dominance approach. We aim to discriminate between the hypothesis that some asset pricing models can explain the puzzling negative relation between dispersion and stock returns, and the alternative hypothesis that the dispersion effect is mainly driven by investor irrationality and thus is an evidence of a failure of efficient markets. We find that low dispersion stocks dominate high dispersion stocks by second‐ and third‐order stochastic dominance over the period from 1976 to 2012. Our results imply that any investor who is risk‐averse and prefers positive skewness would unambiguously prefer low dispersion stocks to high dispersion stocks. We conclude that the dispersion effect is more likely evidence of market inefficiency, rather than a result of omitted risk factors.     

The Market Timing Power of Moving Averages: Evidence from US REITs and REIT Indexes

I present evidence that a moving average (MA) trading strategy dominates buying and holding the underlying asset in a mean‐variance sense using monthly returns of value‐weighted and equal‐weighted US REIT indexes over the period January 1980 until December 2010. The abnormal returns are largely insensitive to the four Carhart 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 MA 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. 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. The lagged signal to switch has substantial predictive power over the subsequent return of the REIT index. The MA strategy avoids the sharp downturn at the beginning of 2008 and substantially outperforms the cumulative returns of the buy‐and‐hold strategy using all of the 20 REIT indexes. The results from applying the MA strategy with 274 individual REITs largely corroborate the findings for the REIT indexes.     

Momentum Strategies and Investor Sentiment in the REIT Market

Comparing across three momentum measures, we empirically find that the 52‐week high strategy plays a dominant role in generating momentum profits in the Real Estate Investment Trust (REIT) market. The profitability of the 52‐week high strategy, however, varies with the state of investor sentiment. Specifically, we find that the 52‐week high momentum earns significantly positive returns following optimistic periods and significantly negative returns following pessimistic periods. Further evidence indicates that investor sentiment serves as a better predictive variable in explaining the REIT momentum than market states, business cycles, legislation changes, and monetary policy changes. Overall, our findings are in line with behavioral theories in explaining the REIT momentum.     

How Reliable Are the Findings of ‘Foreign’ Investor Studies That Use TIC Data? A Look from the Host Market

Empirical literature on foreign investors' trading in stock markets heavily relies on US Treasury International Capital (TIC) data. Biases in TIC data and the fact that it represents only one source country raise questions on how reliable the conclusions based on TIC data are. Employing novel data of complete foreign flows compiled at destination, we answer these questions. Although the correlations between net flows derived from TIC and destination‐compiled data are low, and visible differences exist in some individual country results, TIC findings are not far off in central tendency. Notably, however, net foreign flows' persistence, positive response to world returns and positive contemporaneous correlation with local returns are more significant than TIC data suggest. Measurement noise in TIC data appears to result in underestimation of these key features.     

Price and Earnings Momentum,Transaction Costs,and an Innovative Practitioner Technique

We use an innovative practitioner technique to investigate the interplay between the ex post performance of momentum strategies and transaction costs, rebalancing frequency, turnover constraints, and fund size. We have three interrelated main results: first, the level of and correlation between active returns to price momentum and earnings momentum strategies vary dramatically with these factors; second, strategies that are fearful of ex ante transaction costs generate returns net of transaction costs that are far superior to the net returns of naive strategies; and third, obtaining better traction with the unique elements of each strategy yields a more profitable combined strategy.     

Option trading and the cross-listed stock returns: Evidence from Chinese A–H shares

We empirically investigate the effects of option trading on the cross-listed stock returns. Using dual-listed stocks in mainland China (A) and Hong Kong (H) stock exchanges, we show that option order imbalance (OI) positively and significantly predicts daily stock returns for both markets, controlling for risk factors and firm characteristics. Informed trading rather than price pressure better explain the predictability. High OI stocks have higher trading volume and present lottery-like properties. Three important events significantly affect the predictive power of OI, consistent with the improved market quality and the episode of speculative trading. Robustness checks support the main findings.     

Non‐Tradable Share Reform,Liquidity, and Stock Returns in China

This article studies the influence of the non‐tradable share reform in the cross‐section of stock returns in China. Prior research has generally neglected this important development in the Chinese stock market. We find that the firm‐specific illiquidity measures that reflect direct transaction costs, price impact and difficulties in trading immediacy, exhibit a positive and significant relationship with stock returns. These effects are particularly pronounced after the non‐tradable share reform. Furthermore, in the post‐reform era, portfolios with high illiquidity (i.e. high relative bid–ask spread, high Amihud illiquidity, low Amivest liquidity ratio) significantly outperform portfolios with low illiquidity, controlling for size, and book‐to‐market effects.     

Bidder's Gain: Evidence from Termination Returns

In most cases, bidder's stock returns around merger announcement convey more information than the synergy created from the acquisition. To overcome the interpretation problem, I study the bidder's return from the perspective of deal termination. Using a hand‐collected dataset on terminated merger proposals, I investigate termination returns in deals canceled for reasons unrelated to the bidder's stand‐alone valuation. I find that bidder's gain varies significantly with the type of target acquired. Further evidence suggests that the liquidity need of private target significantly contributes to the positive gain to the bidder.     

Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market

We investigate the use of machine learning (ML) to forecast stock returns in the Brazilian market using a rich proprietary dataset. While ML portfolios can easily outperform the local market, the performance of long-short strategies using ML is hampered by the high volatility of the short portfolios. We show that an Equal Risk Contribution (ERC) approach significantly improves risk-adjusted returns. We further develop an ERC approach that combines multiple long-short strategies obtained with ML models, equalizing risk contributions across ML models, which outperforms, on a risk-adjusted basis, all individual ML long-short strategies, as well as alternative combinations of ML strategies.     

Are stocks dumped or neglected by analysts' inferior investments to covered stocks?

We compare the long-term stock price and operating performance of firms that are followed by analysts to those that are not over the period of 1994-2005. While analysts are skillful in identifying quality firms for coverage, the market is efficient in pricing both covered and neglected stocks such that risk-adjusted stock returns are compatible between the two groups. However, dumped stocks consistently outperform covered stocks with significant risk-adjusted returns across different market conditions and regulatory environments. Hence, investors might earn better returns by investing in dumped stocks, but the higher returns may represent compensation for greater search costs and information risk associated with investing in these stocks.     

Realized Volatility Forecast: Structural Breaks,Long Memory,Asymmetry, and Day‐of‐the‐Week Effect

We investigate the properties of the realized volatility in Chinese stock markets by employing the high‐frequency data of Shanghai Stock Exchange Composite Index and four individual stocks from Shanghai Stock Exchange and Shenzhen Stock Exchange, and find that the volatility exhibits the properties of long‐term memory, structural breaks, asymmetry, and day‐of‐the‐week effect. In addition, the structural breaks only partially explain the long memory. To capture these properties simultaneously, we derive an adaptive asymmetry heterogeneous autoregressive model with day‐of‐the‐week effect and fractionally integrated generalized autoregressive conditional heteroskedasticity errors (HAR‐D‐FIGARCH) and use it to conduct a forecast of realized volatility. Compared with other heterogeneous autoregressive realized volatility models, the proposed model improves the in‐sample fit significantly. The proposed model is the best model for the day‐ahead realized volatility forecasts among the six models based on various loss functions by utilizing the superior predictive ability test.     

Further evidence on Asian stock return behavior

This paper examines the relationship between expected stock returns and size, and market-to-book ratio in five Asian emerging markets: India, Korea, Malaysia, Taiwan and Thailand. Overall, we find a strong size effect in all markets and a significant market-to-book effect in Korea, Malaysia and Thailand. When the tests allow for both variables, the negative relationship between size and average return is less robust; the inclusion of market-to-book equity seems to absorb the role of size in Asian stock returns. Our finding for the Asian market applies to the post-1984 period, thus questioning the assertion of Black [J. Portfolio Manage. 20 (1993) 8] and MacKinlay (1995) that “the value premium is sample-specific”. Although small firms have—to a certain extent—higher average returns than large firms in Asian markets, the market-to-book variable seems to have a consistently stronger role in average returns and would suggest that value stocks have higher average returns than growth stocks. Thus, the higher average return on value stocks in the Asian emerging markets can be considered as a local manifestation of a global phenomenon.     

Dividend‐Rollover Effect and the Ad Hoc Black‐Scholes Model

One of the most widely used option‐valuation models among practitioners is the ad hoc Black‐Scholes (AHBS) model. The main contribution of this study is methodological. We carefully consider three dividend strategies (No dividend, Implied‐forward dividend, and Actual dividend) for the AHBS model to investigate their effect on pricing errors. We suggest a new dividend strategy, implied‐forward dividend, which incorporates expectational information on dividends embedded in option prices. We demonstrate that our implied‐forward dividend strategy produces more consistent estimates between in‐sample market and model option prices. More importantly our new implied‐forward dividend strategy makes more accurate out‐of‐sample forecasts for one‐day or one‐week ahead prices. Second, we document that both a “Return‐volatility” Smile and a “Return‐pricing Error” Smile exist. From these return characteristics, we make two conclusions: (1) the return dependency of implied volatility is an important explanatory variable and should be controlled to reduce the pricing error of an AHBS model, and (2) it is important for the hedging horizon to be based on return size, that is, the larger the contemporaneous return, the more frequent an option issuer must rebalance the option's hedge. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 32:742‐772, 2012