The output gap and stock returns: Do cyclical fluctuations predict portfolio returns?

This study examines whether the output gap leads portfolio stock returns. The paper conducts in-sample and out-of-sample forecasting of US stock portfolios formed on the basis of size and value. First, the paper finds cross-sectional portfolios are predictable in-sample by the output gap. Out-of-sample evidence is weaker but still generally supports the finding that the historical average benchmark can be beaten. Secondly and most importantly, we find mixed evidence that the Fama–French factor mimicking portfolios can be forecasted by the output gap. In particular, there is some out-of-sample predictability of the size effect (SMB) suggesting this lags the output gap. However, the output gap, a key business cycle indicator, cannot predict the value effect (HML) either in-sample or out-of-sample. Our results add to the prior literature which finds that the factor mimicking returns are related contemporaneously (Petkova and Zhang, 2005) or lead (Liew and Vassalou, 2000) economic indicators.     

Are investors moonstruck? Further international evidence on lunar phases and stock returns

This study uses an alternative model specification to re-examine the influences of the new moon and the full moon on the daily returns of 62 international stock indices for the period 1988 to 2008. The fixed effects panel model incorporates the prior day effect and two calendar anomalies, i.e., the Monday effect and the turn-of-the-month effect, to assess variations in the lunar influences. A covariate, based on per capita gross domestic product (GDP), examines how the results vary between countries. The prior day effect is greater for less developed countries. The overall enhanced new moon effect is independent of GDP. An overall full moon effect is absent. These lunar effects are weakly influenced by the calendar anomalies.     

Do fear indices help predict stock returns?

This study investigates the forecasting power of implied volatility indices on forward looking returns. Prior studies document that negative innovations to returns are associated with increasing implied volatility of the underlying indices; thus, suggesting a possible relationship between extremely high levels of implied volatility and positive short term returns. We investigate this issue by examining the predictive power of three implied volatility indices, VIX, VXN and VDAX, on the underlying index returns. We extend previous research by also focusing on characterised selected stocks and examine the relationship between implied volatility indices and future returns across different sectors and classified portfolios. Our findings suggest that implied volatility indices are good predictors of 20-days and 60-days forward looking returns and illustrate insignificant predictive power for very short term (1-day and 5-days) returns.     

Do oil futures prices predict stock returns?

This paper explores stock return predictability by exploiting the cross-section of oil futures prices. Motivated by the principal component analysis, we find the curvature factor of the oil futures curve predicts monthly stock returns: a 1% per month increase in the curvature factor predicts 0.4% per month decrease in stock market index return. This predictive pattern is prevailing in non-oil industry portfolios, but is absent for oil-related portfolios. The in- and out-of-sample predictive power of the curvature factor for non-oil stocks is robust and outperforms many other predictors, including oil spot prices. The predictive power of the curvature factor comes from its ability to forecast supply-side oil shocks, which only affect non-oil stocks and are hedged by oil-related stocks.     

Do industries matter in explaining stock returns and asset-pricing anomalies?

Industry returns cannot be explained fully by well-known asset pricing models. This study reveals that common factors extracted from industry returns carry significant risk premiums that go beyond the explanatory power of size, book-to-market (BM) ratios, and momentum. In particular, this study shows that (1) the small-firm effect is significant only for firms whose market capitalization is below their industry average; (2) the BM effect is an intra-industry phenomenon; (3) a one-year momentum effect is significant only for firms whose BM ratio is smaller than the industry average and limited to non-January months; and (4) there is seasonality in all effects that cannot be explained by risk-based asset-pricing models. Neither rational nor behavioral theories alone can explain industry returns, and it is perhaps too hasty to attribute asset pricing anomalies to a single driving force.     

An encyclopedia for stock markets? Wikipedia searches and stock returns

We present empirical evidence that collective investor behavior can be inferred from large-scale Wikipedia search data for individual-level stocks. Drawing upon Shannon transfer entropy, a model-free measure that considers any kind of statistical dependence between two time series, we quantify the statistical information flow between daily company-specific Wikipedia searches and stock returns for a sample of 447 stocks from 2008 to 2017. The resulting stock-wise measures on information transmission are then used as a signal within a hypothetical trading strategy. The results evidence the predictive power of Wikipedia searches and are in line with the previously documented notion of buying pressure revealed by online investor attention and the trading patterns of retail investors.     

Do political factors affect stock returns during presidential elections?

This study investigates whether or not political factors such as government policy and political connections affected stock returns during the 2008 Taiwanese presidential election. We find that firms that benefitted from (were threatened by) the proposed Three-Links policy of the winning party experienced positive (negative) stock returns during the election. We use the sensitivities of firms’ returns to bilateral trade flows between Taiwan and China to measure the government-policy effect. Our results show that the effects of political connections weakly exist, but they become more significant when the support ratio of the winning party increased in polling data. We also find that only the government-policy effect holds for different crash-risk and corporate-governance levels. Finally, investment strategies based on both political factors can generate positive abnormal returns with respect to the Fama-French Three-factor Model.     

Do institutional investors have superior stock selection ability in China?

This paper uses unique data on the shareholdings of both institutional and individual investors to directly investigate whether institutional investors have better stock selection ability than individual investors in China. Controlling for other factors, we find that institutional investors increase (decrease) their shareholdings in stocks that subsequently exhibit positive (negative) short- and long-term cumulative abnormal returns. In contrast, individual investors decrease (increase) their shareholdings in stocks that subsequently exhibit positive (negative) short- and long-term cumulative abnormal returns. These findings indicate that institutional investors have superior stock selection ability in China.     

Do investors prefer round stock prices? Evidence from Israeli IPO auctions

We find round number clustering in orders submitted by investors in Israeli IPO auctions. Explanations offered for price clustering, such as dealer collusion or implicit agreement to simplify negotiations, cannot explain price clustering in this market. Therefore, this is direct evidence that investors prefer round numbers.     

Funding conditions and insurance stock returns: Do insurance stocks really benefit from rising interest rate regimes?

We examine funding conditions and U.S. insurance company stock returns. Although constrained funding conditions, signaled by restrictive Federal Reserve monetary policy, correspond with increases in the future payouts of fixed‐income securities held by insurance firms and potentially provide value through the liability side of insurer balance sheets, they also decrease the values of securities currently held in insurer portfolios. Prior research finds that restrictive policy has a negative effect on equity returns in general. Our results suggest the negative impacts of constrained funding environments outweigh the potential positives, as insurance company stock returns are significantly lower during periods of constrained funding. This effect varies within a given funding state and also across insurer type. The effect is strongest during the first 3 months of a constrained funding environment and for life and health insurers—insurer types with longer portfolio durations. For property and liability (P&L) insurers, lower stock return performance only exists in the first 3 months of a constrained funding environment. In the subsequent months, P&L insurers actually have higher stock returns during constrained periods, consistent with their typically shorter duration asset portfolios, which are more quickly rolled over into new higher‐yielding securities.     

Do the size,value, and momentum factors drive stock returns in emerging markets?

This paper investigates the size, value, and momentum effects in 18 emerging stock markets during the period 1990–2013. We find that size and momentum strategies generally fail to generate superior returns in emerging markets. The value effect exists in all markets except Brazil, and it is robust to different periods and market conditions. Value premiums tend to move positively together across different markets, and such inter-market comovements increase overtime and during the global financial crisis.     

Do individual investors’ stock recommendations in online communities contain investment value?

This paper investigates the investment value of individual investors’ stock recommendations within online communities. We find that aggregated recommendations contain no explicit investment value and that following these recommendations may have a negative impact on investment performance. Our results suggest that recommendations are mostly based on simple heuristics and concentrate on a small number of stocks. When restricting the set of recommendations to those made by the most experienced or successful recommenders, results marginally improve but still preclude profitable investment strategies. Experienced and successful recommenders seem more likely to avoid the most expensive pitfalls rather than actually exhibit superior investment performance.     

What drives stock returns in Japan?

Financial Markets and Portfolio Management - We investigate systematic factors driving stock returns and stock return predictability in Japan. We find that dividend yield, cash-flow yield, and...     

US stock returns: are there seasons of excesses?

This article explores the existence of seasonality in the tails of stock returns. We use a parametric model to describe the returns, and obtain a proxy of the innovation distribution via a pre-processing model. Then, we develop a change-point algorithm capturing changes in the tails of the innovations. We confirm the good performance of the procedure through extensive Monte Carlo experiments. An empirical investigation using US stocks data shows that while the lower tail of the innovations is approximately constant over the year, the upper tail is larger in Winter than in Summer, in 9 out of 12 industries.     

Extreme dependence in investor attention and stock returns – consequences for forecasting stock returns and measuring systemic risk

We characterize co-movements in investor attention by modeling multivariate internet search volume data. Using a variety of copula models that can capture both asymmetric and skewed dependence, we find empirical evidence of strong non-linear and asymmetric dependence in the attention investors give to companies. Modeling three years of daily stock returns and search volumes from Google Trends for 29 bank names, we find a striking similarity between the dependence structure inherent in stock returns and the dependence in the corresponding time series of search queries. We then document the existence of significant asymmetric and skewed tail dependence in the joint distribution of stock returns and investor attention. Finally, stock returns and internet search volumes appear to evolve concurrently in real time with neither one leading the other. Our findings have important implications, e.g. for the analysis of banks' interconnectedness based on equity data and the pricing of investor attention in the cross-section of stock returns.     

When does investor sentiment predict stock returns?

We examine the asymmetry in the predictive power of investor sentiment in the cross-section of stock returns across economic expansion and recession states. We test the implication of behavioral theories and evidence that the return predictability of sentiment should be most pronounced in an expansion state when investors' optimism increases. We segregate economic states according to the NBER business cycles and further implement a multivariate Markov-switching model to capture the unobservable dynamics of the changes in the economic regime. The evidence suggests that only in the expansion state does sentiment perform both in-sample and out-of-sample predictive power for the returns of portfolio formed on size, book-to-market equity ratio, dividend yield, earnings-to-price ratio, age, return volatility, asset tangibility, growth opportunities, and 11 widely documented anomalies. In a recession state, however, the predictive power of sentiment is generally insignificant.     

Conversions of mutual savings institutions: Do initial returns from these IPOS provide investors with windfall profits?

We examine initial returns of fully underwritten IPOs of converting thrifts for evidence that managers and depositors of conversion-related offers earn significantly greater returns than investors in IPOs of other financial institutions. Regulators have suggested that new guidelines for conversion from a mutual to a stock thrift are designed to curb “windfall profits” earned by insiders investing in conversion-related IPOs. While there are reports of average initial returns of more than 20% for conversion-related IPOs, our results suggest that investors earn average initial returns of about 7%, which is not significantly different than returns from IPOs of other thrifts and commercial banks.     

Do extreme returns matter in emerging markets? Evidence from the Chinese stock market

Recent evidence in the U.S. and Europe indicates that stocks with high maximum daily returns in the previous month, perform poorly in the current month. We investigate the presence of a similar effect in the emerging Chinese stock markets with portfolio-level analysis and firm-level Fama–MacBeth cross-sectional regressions. We find evidence of a MAX effect similar to the U.S. and European markets. However, contrary to U.S. and European evidence, the MAX effect in China does not weaken much less reverse the anomalous idiosyncratic volatility (IV) effect. Both the MAX and IV effects appear to independently coexist in the Chinese stock markets. Interpreted together with the strong evidence of risk-seeking behaviour among Chinese investors, our results partially support the suggestion that the negative MAX effect is driven by investor preference for stocks with lottery-like features.     

Do investors value smooth performance?

This paper presents empirical evidence that cash-flow volatility is negatively valued by investors. The magnitude of the effect is substantial with a 1% increase in cash-flow volatility, resulting in approximately a 0.15% decrease in firm value. We show that this increase, however, is not associated with earnings smoothing resulting from managers’ accrual estimates. Our results are consistent with a preference by the market for less volatile cash flows and suggest that managers’ efforts to produce smooth financial statements add value, but only via the cash component of earnings.