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Abstract:
This paper examines the returns to investment strategies based on the interactions between value-to-market indicators and corporate financing transactions that increase or decrease the firm's outstanding equity, i.e., equity issues and repurchases. Portfolio-level analyses and firm-level cross-sectional regressions indicate that the well-documented contrarian profits soar when value stocks which repurchase shares (value repurchasers) and growth stocks which issue shares (growth issuers) are considered. The results also show that value-to-market ratios cannot capture the cross-sectional variation in expected stock returns when value issuers and growth repurchasers are considered. Based on various risk measures, we find that value repurchasers are not riskier than growth issuers. Furthermore, value repurchasers (growth issuers) experience the highest increase (decrease) in future growth rates. Our findings are consistent with the misvaluation explanation for the superior returns of value stocks.

Share issues, share repurchases, contrarian investment, expected stock returns, value-to-market ratios

Abstract:
This paper presents a comprehensive study of continuous time GARCH modeling with the thin-tailed normal and the fat-tailed Student-t and generalized error distributions. The paper measures the degree of mean reversion in stock return volatility based on the relationship between discrete time GARCH and continuous time diffusion models. The convergence results based on the aforementioned distribution functions are shown to have similar implications for testing mean reversion in stochastic volatility. Alternative models are compared in terms of their ability to capture mean-reverting behavior of stock return volatility. The empirical evidence obtained from several stock market indices indicates that the conditional variance, log-variance, and standard deviation of stock market returns are pulled back to some long-run average level over time.

reversion, fat-tailed distributions, diffusion, GARCH, stochastic volatility

Abstract:
This paper examines the proportion of wealth invested in stock and bond portfolios as a function of the investors' age, i.e., investment horizon. It has become increasingly popular to advice investors to relocate their funds from a primarily stock portfolio to a primarily bond portfolio as they get older. However, the existing theory does not support this advice: the well-known decision rules such as Mean-Variance (MV) or Stochastic Dominance (SD) rules are unable to explain this common practice. In this paper, we utilize the recently developed Almost Stochastic Dominance (ASD) and Almost Mean Variance (AMV) approaches and employ various datasets to examine the dominance of stock and bond portfolios as a function of the investment horizon. We find that, for short investment horizons, all portfolios are efficient. However, for medium and longer horizons, only the portfolios with higher stock proportions are efficient. The results indicate that ASD and AMV rules unambiguously support the popular practice of advising higher stock to bond ratio for long investment horizons. Hence, we provide an explanation to the practitioners' recommendation within the expected utility paradigm.

Asset Allocation, Life-Cycle Funds, Almost Stochastic Dominance, Almost Mean-Variance

Abstract:
This paper examines the intertemporal relation between downside risk and expected stock returns. Value at risk (VaR), expected shortfall, and tail risk are used as measures of downside risk to determine the existence and significance of a risk-return tradeoff. We find a positive and significant relation between downside risk and the portfolio returns on NYSE/AMEX/Nasdaq stocks. VaR remains a superior measure of risk when compared to the traditional risk measures. These results are robust across different stock market indices, different measures of downside risk, loss probability levels, and after controlling for macroeconomic variables and volatility over different holding periods as originally proposed by Harrison and Zhang (1999).

Downside risk, skewed fat-tail distributions, extreme stock returns, tail risk.

Abstract:
This paper uncovers several new empirical regularities in the historical returns of small stocks. First, within the sample of firms that have low market capitalizations, stocks with low past profitability ("laggers") bring returns significantly higher than those of stocks with high past profitability ("leaders"). Second, the well-documented size premium (i.e., the risk-adjusted returns to small stocks) is generated largely by small laggers. Moreover, both patterns are particularly pronounced at earnings-announcement dates, suggesting that unexpected earnings growth can explain a portion of the abnormal returns to small stocks.

Small-firm effect, Anomalies, Overreaction, Profitability

Abstract:
This paper provides an analysis of the predictability of stock returns using market, industry, and firm-level earnings. Contrary to Lamont (1998), we find that neither dividend payout ratio nor the level of aggregate earnings can forecast the excess market return. We show that these variables do not have robust predictive power across different stock portfolios and sample periods. In contrast to the aggregate-level findings, earnings yield has significant explanatory power for the time-series and cross-sectional variation in firm-level stock returns and 48-industry portfolio returns. It is the mean-reversion of stock prices as well as the earnings' correlation with expected stock returns that are responsible for the forecasting power of earnings yield. These results are robust after controlling for book-to-market, size, price momentum and post-earnings announcement drift. At the aggregate-level, the information content of firm-level earnings about future cash flows is diversified away and higher aggregate earnings do not forecast higher returns.

earnings, dividends, stock returns, market returns, predictability, business cycle

Abstract:
This paper uncovers several new empirical regularities in the historical returns of small stocks. First, within the sample of firms that have low market capitalizations, stocks with low past profitability (laggers) bring returns significantly higher than those of stocks with high past profitability (leaders). Second, the well-documented size premium (i.e., the risk-adjusted returns to small stocks) is generated largely by small laggers. Moreover, both patterns are particularly pronounced at earnings-announcement dates, suggesting that unexpected earnings growth can explain a portion of the abnormal returns to small stocks. There is little institutional ownership of small stocks, pointing to individual investors as the culprits of suboptimal trading. Institutional avoidance of small stocks therefore can explain the persistence of the mispricing. The analysis indicates that the documented effects are driven consistently by those small stocks that have had a prior decrease in institutional ownership ratio.

Small-firm effect, Return anomalies, Overreaction

Abstract:
This paper provides new evidence on the time-series predictability of stock market returns by introducing a test of nonlinear mean reversion. The performance of extreme daily returns is evaluated in terms of their power to predict short- and long-horizon returns on various stock market indices and size portfolios. The paper shows that the speed of mean reversion is significantly higher during the large falls of the market. The parameter estimates indicate a negative and significant relation between the monthly portfolio returns and the extreme daily returns observed over the past one to eight months. Specifically, in a quarter in which the minimum daily return is -2% the expected excess return is 37 basis points higher than in a month in which the minimum return is only -1%. This result holds for the value-weighted and equal-weighted stock market indices and for each of the size decile portfolios. The findings are also robust to different sample periods, different indices, and investment horizons.

mean reversion, extreme returns, time-varying risk aversion, stock market returns, market efficiency

Abstract:
This paper investigates the risk versus mispricing explanation of superior returns to contrarian strategies using the interactions between value-to-market indicators and corporate financing transactions that increase or decrease a firm's outstanding equity. Portfolio-level analyses and firm-level cross-sectional regressions indicate that the well-documented contrarian profits soar when value stocks which repurchase shares (value repurchasers) and growth stocks which issue shares (growth issuers) are considered. Various risk measures indicate that value repurchasers are not riskier than growth issuers. Furthermore, time-series of realized growth rates, analysts' long-term growth estimates, and sensitivity of portfolio returns to investor sentiment support the misvaluation explanation.

Abstract:
Investment bankers focus on narrow, industry-based peer groups for individual stock valuation. And some market-neutral equity hedge fund managers restrict their portfolios to be sector-neutral as well. Yet, academic research into contrarian strategy investment performance has typically invoked full universe valuation and ignored industry effects. Here, we find in favor of the bankers’ and hedge fund managers’ approach. Industry effects matter. Narrow industry-based peer groups improve stock valuation precision for three key valuation ratios. While our analysis of the dynamics of these ratios indicates substantial inertia in relative value rankings, we find that average returns to industry-based contrarian portfolio strategies are positive, statistically significant, and persistent. And over a sample that extends through the “new economy/old economy” and boom/bust period of the late 1990s, contrarian strategies were particularly profitable for NASDAQ-listed stocks. Most importantly, using our full sample of stocks, we show that an industry-neutral strategy is far superior to an industry-exposed, full universe strategy in Sharpe ratio terms over every horizon for each valuation ratio. Thus, contrarian strategy portfolio performance is significantly improved in risk-adjusted terms when implemented in its industry-neutral hedging form.

Abstract:
This paper introduces a generalized discrete time framework to evaluate the empirical performance of a wide variety of well-known models in capturing the dynamic behavior of short term interest rates. A new class of models which displays nonlinearity and asymmetry in the drift, and incorporates the level effect and stochastic volatility in the diffusion function is introduced in discrete time and tested against the popular diffusion, GARCH, and Level-GARCH models. Based on the statistical test results, the existing models are strongly rejected in favor of the newly proposed models because of the nonlinear asymmetric drift of the short rate, and the presence of nonlinearity, GARCH, and level effects in its volatility. The empirical results indicate that the nonlinear asymmetric models are better than the existing models in forecasting the future level and volatility of interest rate changes.

rates, volatility, nonlinearity, asymmetry, GARCH, diffusions

Abstract:
This paper investigates the significance of an intertemporal relation between expected return and risk for the futures markets. The paper not only takes a look at the domestic futures, but the relationship between conditional risk and return is examined in international futures markets as well. We test the significance of a daily risk-return tradeoff in stock index futures for G8 countries (US, Canada, UK, Germany, France, Italy, Japan, and Australia). We use GARCH modeling with the thin-tailed normal and the fat-tailed Student t, generalized error, and generalized t distributions to simultaneously generate risk measures and forecast expected futures returns. The maximum likelihood parameter estimates indicate that the relation between risk and return is flat in futures markets. This result is robust across eight different countries.

stock index futures, international futures markets, risk-return tradeoff, GARCH-in-mean.

Abstract:
This paper investigates the intertemporal relation between conditional skewness and expected returns on the aggregate stock market. The results show a significantly negative link between expected future returns and the risk-neutral skewness measured by the spread between out-of-the-money put and at-the-money call options' implied volatilities of the S&P 500 index. The intertemporal relation is robust across different market portfolios and different measures of risk-neutral skewness, and it remains strongly negative after controlling for various measures of conditional volatility, a large set of macroeconomic variables, non-synchronicity between the options and stock markets, small sample biases, and distributional assumptions. The results also indicate that it is not just the average skewness preference, but also the time-varying skewness preference that is an important determinant of future market returns.

skewness, implied volatility, expected market return, intertemporal risk-return relation

Abstract:
There exists a small sample bias in predictive regressions, when a rate of return is regressed on a lagged stochastic regressor, and the regression disturbance is correlated with the regressors’ innovations. Although this bias can be a serious concern in time-series predictive regressions, it is not significant in panel data setting. By using simulations and stock level data, we document that as the number of cross sections used in the panel data increases the bias in coefficient estimates becomes negligible.

Abstract:
This paper investigates the predictability of variance and value at-risk (VaR) measures in international stock markets. We use daily stock market returns for G7 countries (the United States, the United Kingdom, Germany, Japan, Canada, France, Italy) and generate the realized variance and VaR estimates. We then compute the proportion of the one month ahead variance and VaR that can be explained by the variance and VaR obtained from the past one month to six months of daily data to determine the persistency of these risk measures. We find that for all G7 countries considered in the paper persistency in variance is significantly higher than that in VaR. Variance of the stock market indices for Germany and Italy has the highest persistence, whereas the persistence is low for the US and Canada. However, different than the case of variance, the strongest predictability of VaR is obtained for Japan. We conclude that although the second moment of stock return distributions is highly predictable for Germany and Italy, tails of the distribution are more persistent for Japan.