Predictor Of Future Returns Research Articles

Designing volatility indices for Austria, Finland and Spain

The volatility index of the Chicago Board Options Exchange (VIX) was the first to be established, and it has given rise to international imitations worldwide as it is considered to be a barometer of investor fear. Starting from this volatility index, the aim of this paper is threefold. By adopting the VIX methodology, we construct a volatility index for three European countries (Austria, Finland and Spain) which currently do not provide this kind of market information for investors. Second, we investigate the properties of various volatility indices. In particular, we test their ability to act as fear indicators and as predictors of future returns. Moreover, we seek to cast light on the term structure of the proposed volatility indices, by computing spot and forward implied volatility indices for different times to maturity (30, 60 and 90 days). Our results indicate that volatility indices are useful not only for investors to improve their trading decisions, but also for policy-makers to choose the appropriate economic measures to promote stability in the market.

The Admissible Multiperiod Mean Variance Portfolio Selection Problem with Cardinality Constraints

Uncertain factors in finical markets make the prediction of future returns and risk of asset much difficult. In this paper, a model,assuming the admissible errors on expected returns and risks of assets, assisted in the multiperiod mean variance portfolio selection problem is built. The model considers transaction costs, upper bound on borrowing risk-free asset constraints, cardinality constraints and threshold constraints. Cardinality constraints limit the number of assets to be held in an efficient portfolio. At the same time, threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Because of these limitations, the proposed model is a mix integer dynamic optimization problem with path dependence. The forward dynamic programming method is designed to obtain the optimal portfolio strategy. Finally, to evaluate the model, our result of a meaning example is compared to the terminal wealth under different constraints.

Continuing Overreaction and Stock Return Predictability

We study the return predictability of a measure of continuing overreaction based on the weighted average of signed volumes. We find that the strategies of buying stocks with upward continuing overreaction and selling stocks with downward continuing overreaction generate significant positive returns and that our measure of continuing overreaction is a better predictor of future returns than past returns. The results are stronger among stocks primarily held by investors more prone to biased self-attribution. Our results provide direct support for the model of return predictability based on overconfidence and biased self-attribution.

Predictability in bond returns using technical trading rules

The predictability of future returns on bond portfolios at daily frequency is investigated using a large universe of mechanical trading rules that have been popularized in literature on equity and currency markets. The predictability in returns is inversely related to interest rate risk but positively related to default risk. The return predictability is more sensitive to fluctuations in the economic business cycle rather than changes in the Federal Reserve's monetary policy. Returns on portfolios of Treasury bonds are more predictable during the restrictive monetary policy regime, whereas returns on both Treasury bonds and corporate bonds exhibit much better predictability during the economic expansions rather than recessions. The predictability of returns in various segments of the U.S. bond market has declined over time. Findings for the predictability in the highly liquid bond exchange-traded funds are largely in line with the original results of the predictability in bond portfolio returns.

Wavelets Analysis on Structural Model for Default Prediction

In recent years, to improve predictive ability of corporate defaults has become an important problem. In this paper, regarding on characteristics of listed companies, we sampled 100 companies according to industry types, constructed wavelet structural model, experimented with wavelet decomposition proceeds to get low frequency and high frequency sequence, built the prediction model for both sequences, and then using the prediction of future returns to reconstruct predictive returns, thus avoiding accumulated prediction process with earnings volatility of time series model, therefore enhanced the precision of default prediction. Finally we compared wavelet structural model with time series structural model based on the predictive default distance of China’s listed companies.

Tree-Based Conditional Portfolio Sorts: The Relation between Past and Future Stock Returns

Which variables provide independent information about the cross-section of future returns? Portfolio sorts and Fama-MacBeth regressions cannot easily answer this question when the number of candidate variables is large and when cross-terms might be important. We introduce a new method based on ideas from the machine learning literature that can be used in this context. Applying the method to past-return-based prediction of future returns, short-term returns become the most important predictors. A trading strategy based on our findings has an information ratio twice as high as a Fama-MacBeth regression accounting for two-way interactions. Transaction costs do not explain the results.

On the performance of simple trading rules derived from the fractal dynamics of gold and silver price fluctuations

In a recent study of the fractal dynamics of gold-silver spreads, Batten et al. (2013) suggest that the Hurst coefficient (a simple measure of long-range dependence) may be a promising tool for the development of profitable trading rules in precious metals markets. In this note, we put this proposal to the test and significantly extend their preliminary evidence by (i) implementing more sophisticated Hurst coefficient estimators, (ii) modelling a simple trading rule in the spirit of De Souza and Gokcan (2004) and (iii) explicitly considering the role of transaction costs. For the period from 1979 to 2015, an analysis of gold, silver and the gold-silver spread shows that our Hurst coefficient strategy tends to outperform passive buy-and-hold approaches. In other words, we find that Hurst coefficients are predictors of future returns and thus contain important investment information. Interestingly, this result holds regardless of the choice of Hurst coefficient estimator and is robust to transaction costs, different holding period lengths and a series of other sensitivity checks.

Have Domestic Institutional Investors Become as Market Savvy as Foreign Investors? Evidence from the Taiwan Options Market

Chiu, Lee, and Wang also explore trading by informed investors in TAIEX index derivatives, in this case by looking at put/call ratios. Options on TAIEX are among the most actively traded options in the world. There is sizable participation by individuals, who trade about 50% of all contracts, and also by foreign institutions, which are widely regarded as having better information than domestic Taiwanese investors. The authors also consider domestic institutions and market makers. Excluding market makers, who are assumed to be liquidity providers rather than information traders, each group’s put/call ratio for trades that open a new position is computed daily and used as a predictor of future returns in a vector autoregression, along with a set of control variables. The sample period covers 2007 and 2008, allowing the authors to contrast calm and crisis conditions. The overall tenor of the results reported here will be comforting to believers in efficient markets: There is very little evidence that any group has much power to predict returns in the Taiwan stock market, either from one day to the next, or over shorter intraday intervals. If anything, in this study, domestic individual traders seem to have a little better information than foreign investors.

A Study of Volatility Risk

Time variations of market volatility considerably affect investments risk evaluation and prediction of future returns. They are presented as a source of systemic risk to which is added a risk related to stocks’ sensitivity to volatility shocks. Analysis of the relationship between stocks volatility and market volatility allows for determining whether stocks’ sensitivities to volatility shocks may estimate market’s future risk price. Volatility shocks are defined in terms of volatility risk hedging factors, when market volatility risk price is high and for stocks that are positively correlated to these hedging factors, the value of returns is expected to be low. Idiosyncratic volatility is on the other hand a variable omitted from volatility total risk. If market volatility risk is a missing component of systematic risk, standard models should mis-price portfolios sorted by idiosyncratic volatility because these models do not include factor loadings measuring exposure to market volatility risk.

Conditioning information and cross-sectional anomalies

Recent empirical work suggests that predictability of future returns is related to a time-varying component that expected returns exhibit. In this paper, I use conditional asset pricing models to investigate whether return anomalies exhibit common dynamic patterns in returns. The prediction of a model might hinge on the specific interaction between its underlying state variables and considered portfolios. Using well known anomalies and alternative state variables I study such interaction. I document that different state variables identify similar time-varying behavior for the anomalies in extreme economic conditions, but such anomalies show no commonalities in their overall patterns.

The Effect of Bank-firm Relationships on Sell-side Research

In this paper, I examine how the lending relationships between banks and their borrowers affect the quality of analysts’ earnings forecasts after financial deregulation in Japan. My findings show that short-term lending relationships improve the quality of analysts’ earnings forecasts and that these earnings forecasts are useful for predicting future returns. In contrast, long-term lending relationships decay the quality of forecast and are not valuable for the prediction of future returns. These empirical results indicate that the informational advantage that commercial banks acquire is short-term and that the costs of lending relationships surpass the informational benefits in the long run.

On the Risk and Return of the Carry Trade

DeMiguel, Garlappi, and Uppal (Review of Financial Studies, 22 (2009), 1915-1953) showed that in the stock market, it is difficult for an optimized portfolio constructed using mean-variance analysis to outperform a simple equally-weighted portfolio because of estimation error. In this paper, we demonstrate that portfolio optimization can be made to work in currency markets. The key difference between the two settings is that in currency markets interest rates provide a predictor of future returns that is free of estimation error, which permits the application of mean-variance analysis. We show that over the last 26 years, a mean-variance efficient portfolio constructed in this fashion has a Sharpe ratio of 0.91, versus only 0.15 for the equally-weighted portfolio. We also consider the practical implementation of this strategy.

The Conditional CAPM Explains the Value Premium

This paper proposes alternative specifications of the conditional CAPM with dynamic conditional beta and tests the models' performance in explaining the value premium for the period 1963-2011. The conditional alphas on the value-minus-growth portfolio are estimated to be economically and statistically insignificant, indicating superior performance of the conditional CAPM in explaining the value premium. The results also show that the dynamic conditional covariances of book-to-market portfolios with default spread, dividend yield, and unemployment rate are significant predictors of future returns, implying that default risk, dividend and unemployment related shocks contain systematic risks rewarded in the stock market and they can be viewed as state variables proxying for consumption and investment opportunities. Hence, the superior returns to value stocks represent compensation for bearing the risk of unfavorable shifts in the investment opportunity set along the lines of Merton's (1973) ICAPM.

Illusion of Growth: Merger-Related Transitory Growth and Its Implications for Growth and Accrual Mispricing

Prior literature in accounting and financial economics measures asset growth as year-over-year growth in total assets. Such growth estimates are upward biased when firms engage in mergers and acquisitions. We decompose asset growth into merger-related and organic growth components, and find that merger-related growth is less persistent than organic growth. The merger-related growth is positively associated with analysts’ optimism in earnings forecasts and stock recommendations, and is a strong predictor of future returns. Furthermore, such return predictability is exhibited by firms that do not transparently disclose the merger-related and organic growth components. This finding is consistent with investors with limited attention playing a role in mispricing. Portfolio asset pricing tests reveal that priced risk factors do not explain this growth pricing anomaly. Stocks with high merger-related growth tend to be associated with higher trading costs and arbitrage risk, which contributes to the persistence of this mispricing over time.

The Impact of Asymmetry on Expected Stock Returns: An Investigation of Alternative Risk Measures

We investigate the relation between various alternative risk measures and future daily returns using a sample of firms over the 1988-2009 time period. Previous research indicates that returns are not normally distributed and that investors seem to care more about downside risk than total risk. Motivated by these findings and mixed empirical evidence supporting theoretical positive risk-return relationship, we model the relation between future returns and risk measures and investigate the following questions: (1) Are investors compensated for total risk and/or asymmetric measures of risk? (2) How does the degree of risk aversion in the lower tail of the return distribution impact the predictability of future returns? (3) Is upside risk or downside risk a better predictor of future returns? We find that, although investors seem to be compensated for total risk, measures of downside risk, such as the lower partial moment, are better at explaining future returns. Further, when comparing downside risk to upside risk, we find that investors are more concerned about downside risk. That is, downside risk is a better predictor of future returns. Our results are robust to the addition of traditional control variables, including size, book-to-market ratio of equity (B/M), leverage, and market risk measures, including beta, downside beta and co-skewness. Our findings are an important contribution to the literature as we document a positive risk-return relationship, using both total and asymmetric measures of risk.

Investor Continuing Overreaction and the Cross-Section of Stock Returns

Prior studies argue that overconfidence-driven overreaction leads to return predictability and high trading volume. Motivated by these studies, we propose a measure of continuing overreaction using weighted signed volumes. We find that the strategies of buying stocks with upward continuing overreaction and selling stocks with downward continuing overreaction generate significant positive returns, and our measure of continuing overreaction is a better predictor of future returns than past returns. The results are stronger among stocks primarily held by investors more prone to biased self-attribution. Our results provide direct support for the model of return predictability based on overconfidence and biased self-attribution.

Predicting dividends in log-linear present value models

In a present value model, high dividend yields imply that either future dividend growth must be low, or future discount rates must be high, or both. While previous studies have largely focused on the predictability of future returns from dividend yields, dividend yields also strongly predict future dividends, and the predictability of dividend growth is much stronger than the predictability of returns at a one-year horizon. Inference from annual regressions over the 1927–2000 sample imputes over 85% of the variation of log dividend yields to variations in dividend growth. Point estimates of the predictability of both dividend growth and discount rates are stronger when the 1990–2000 decade is omitted.

Une analyse temps-fréquences des cycles financiers

Résumé Cet article s’intéresse aux fluctuations des cours boursiers aux États-Unis à différentes échelles temporelles. Nous examinons dans quelle mesure les variations à différentes fréquences du ratio cours-bénéfice s’expliquent par des révisions des bénéfices et/ou des rendements espérés. Nous montrons que les mouvements conjoncturels du ratio cours-bénéfice permettent de prévoir les rendements réels des actions. L’information contenue dans ces fluctuations apparaît même supérieure aux autres variables prédictives identifiées dans la littérature. Ces fluctuations conjoncturelles du ratio cours-bénéfice sont extraites à l’aide d’une analyse par ondelettes qui permet de décomposer une série temporelle à différents niveaux de résolution.

APLICAÇÃO DE METODOLOGIAS ALTERNATIVAS DO CAPM EM DIVERSOS CENÁRIOS NO MERCADO DE CAPITAIS BRASILEIRO

<p>Inúmeros estudos têm sido feitos procurando mensurar o componente de risco envolvido no retorno esperado em investimentos de capital. O objetivo deste trabalho é o de comparar os resultados obtidos nas diversas metodologias de cálculo do Capital Asset Princing Model (CAPM) com os resultados efetivos apresentados pelas ações de empresas do mercado brasileiro no período de 2000 a 2004. Esses cálculos utilizam quatro metodologias de determinação do índice beta e três metodologias de cálculo do CAPM, em oito cenários macroeconômicos distintos. A pesquisa buscou determinar relações de igualdade entre o conjunto dos<br />diversos retornos esperados obtidos e o efetivo comportamento de retornos dos ativos estudados em diversos cenários. O estudo utilizou o método estatístico Teste de Hipóteses de Diferença de Médias de duas Populações para comparar as diversas séries de retornos esperados obtidos, com os respectivos retornos efetivos. Os resultados obtidos sugerem a indicação de algumas metodologias e cenários como ferramentas válidas na predição de retornos futuros desses ativos, notadamente quando introduzidas variáveis que considerem o risco-país na sua mensuração.</p>

The 52-week high momentum strategy in international stock markets

We study the 52-week high momentum strategy in international stock markets proposed by George and Hwang [George, T., Hwang, C.Y., 2004. The 52-week high and momentum investing. Journal of Finance 59, 2145–2176.]. This strategy produces profits in 18 of the 20 markets studied, and the profits are significant in 10 markets. The 52-week high momentum profits exist independently from the Jegadeesh and Titman [Jegadeesh, N., Titman, S., 1993. Returns to buying winners and selling losers: implications for market efficiency. Journal of Finance 48, 65–91.] individual stock and Moskowitz and Grinblatt [Moskowitz, T.J., Grinblatt, M., 1999. Do industries explain momentum? Journal of Finance 54, 1249–1290] industry momentum strategies. These profits do not show reversals in the long run. We find that the 52-week high is a better predictor of future returns than macroeconomic risk factors or the acquisition price. The individualism index, a proxy to the level of overconfidence, has no explanatory power to the variations of the 52-week high momentum profits across different markets. However, the profits are no longer significant in most markets once transaction costs are taken into account.