Monthly Returns Research Articles

The Effect of Economic Policy Uncertainty in the US on the Stock Market Performance in Canada and Mexico

This paper investigates the effect of economic policy uncertainty in the United States on stock market performance in Canada and Mexico. Using monthly returns of the Canada S&P/TSX-300 Total Return Index from 1985:2 to 2012:5 and Mexico SE Total Return Index from 1988:1 to 2012:5, this study shows that the increased changes in economic policy uncertainty in the US negatively affect stock market performance in Canada and Mexico. Although the changes in the U.S. trade balance do not influence the effect of the changes in economic policy uncertainty in the US on the stock market performance in Canada and Mexico, the returns on the S&P 500 do have an impact on this effect. The findings suggest that stock market performance in Canada and Mexico is linked to the economic policy conditions and stock performance in the US. The implication of this finding is that market participants in Canada and Mexico do pay attention to the economic policy conditions and stock performance in the US.

Seasonal Effects in the Turkish Stock Market

We test for seasonality in returns of various industry indices in the Istanbul Stock Exchange. The residual returns for all the industry indices in the Turkish stock market are computed and analyzed using the CAPM model. The empirical evidence based on monthly return data from MATRIKS points out to weak evidence of return seasonality in some industries, especially in IT, leasing, holding and tourism. Interestingly, the timing of these returns confirms prior work done in developed markets, where returns are generally positive during the first half of the year and negative during the 3rd and 4th quarters. For robustness, we repeat the same procedure with the Fama – French 3 factor model and obtain similar results. Other industry indices show no evidence of seasonality.

Empirical Asset Pricing for Tactical Asset Allocation

Tactical Asset Allocation is short-term deviation from a long-term portfolio allocation. Portfolio managers typically combine tactical asset allocation with their period rebalancing in order to add additional return that can justify management fees. Unfortunately, the frequency of tactical asset allocation prohibits the manager from using fundamental values since these characteristics change little from month to month. This paper proposes and tests a methodology for determining a pair of asset classes to overweight and underweight that will produce a positive return spread in the next period. The model utilizes investors’ preferences for certain return distribution characteristics and the short-term persistence of these characteristics to select the best spread. Twenty years of monthly return data from five asset classes (domestic equity, international equity, fixed income, REITs, and alternative investments) were selected to represent the asset allocation opportunities of midsize institutional investors.

Predictive regressions with time-varying coefficients

We evaluate predictive regressions that explicitly consider the time-variation of coefficients in a comprehensive Bayesian framework. For monthly returns of the S&P 500 index, we demonstrate statistical as well as economic evidence of out-of-sample predictability: relative to an investor using the historic mean, an investor using our methodology could have earned consistently positive utility gains (between 1.8% and 5.8% per year over different time periods). We also find that predictive models with constant coefficients are dominated by models with time-varying coefficients. Finally, we show a strong link between out-of-sample predictability and the business cycle.

Asymmetric Effects and the Herd Behavior in the Australian Equity Market

The purpose of this paper is to investigate whether Australian stock investors do herd. A sample of the largest251 Australian listed firms is employed from the beginning of 2003 until the end of 2010 on daily and monthlybasis. When the CH approach is used, no evidence of herd behavior for the daily and the monthly return series ofAOI and S&P300 indices is reported. However, the application of the CCK provides better results than thoseobtained by the cross-sectional stock price’s model developed by CH. According to CCK, in normal conditions,the conditional CAPM specifies a linear relationship between CSAD and market returns. However, if herdingoccurs during periods of market stress, then a nonlinear relationship will also exist. To accommodate for thepossibility that the degree of herding may be asymmetric in the up and the down markets, the CCK approach isapplied by examining the nonlinear relationship between CSAD and market returns. Evidence of herding isfound in the up and the down markets for both indices. This indicates that Australian investors exhibitasymmetric herding with respect to financial crisis, while they do not exhibit asymmetric herding in terms offundamentals. Findings show evidence of herding asymmetry created by trading volume only in high volumestate for both indices returns. However, in high volatility state, evidence of asymmetric herding is found for onlythe AOI monthly returns. This suggests that Australian investors remain in showing herding activities on dailyand monthly basis and are affected by the decisions of investors in foreign markets of the US, the UK and China.

The impact of institutional ownership on risk-taking behaviors

One of the major factors influencing a company’s performance is undoubtedly the level of risk-taking. As owners of a great deal of company stock, institutional investors can play an important role in determining this level. Therefore, this study has investigated the influence of institutional ownership on the risk-taking behavior of companies that are listed in the Tehran stock exchange. The study has used the standard deviation of monthly return and systematic risk (β) as market risk criteria, and research and development expense and capital expenditure as company risk criteria. This research includes 58 companies from 2004 to 2008, in which ordinary least squares regression models (panel data) and a tobit model have been used. The results show that no meaningful relationship exists between the percentage and concentration of institutional ownership by stockholders and risk-taking behavior. Key words: Institutional ownership, risk-taking behavior, market risk, company risk.

Evidence and implications of the predictability of high yield bond returns

This study demonstrates that roughly one quarter to one-third of the monthly returns of the Merrill Lynch High Yield Bond Indexes from September 1988 through June 2009 can be explained by predetermined variables. The study also shows that out of sample forecasts of Sharpe ratios from GARCH models are able to predict favorable and unfavorable times to invest in high yield bonds and would have allowed investors to avoid most of the months in which high yield bonds suffered substantial losses. These out of sample results are robust when applied to Vanguard and Fidelity high yield bond mutual funds. Overall, the results support the case for allocating funds to high yield bonds only when favorable risk-return tradeoffs are forecast, particularly in light of the modest risk adjusted high yield bond returns from passive strategies over the sample period and the recent introduction of high yield bond exchange traded funds that have substantially reduced transactions costs.

Momentum and behavioral finance

Purpose – The purpose of this paper is to re‐examine the sources of momentum profits by focusing on momentum in monthly returns.Design/methodology/approach – The paper utilizes a decomposition method proposed by Du and Watkins.Findings – Different from previous studies, it is found that momentum may have multiple sources, and that risk or behavioral biases in isolation may not be sufficient to explain momentum.Practical implications – The paper's finding that momentum may be at least partly due to risk is important for investors to understand the risk of momentum investing.Originality/value – This paper focuses on the sources of momentum profits in monthly returns. The findings that momentum has multiple sources call for new explanations for momentum because all existing theories of momentum are either rational or behavioral. Furthermore, the finding that lead‐lag relationship plays an important role in momentum suggests that researchers should focus on mis‐reaction to common (market‐wide) information to ...

Empirical Evidence on Weak Form of Efficiency in Indian Stock Market

The article is an empirical study to examine the validity of weak form of efficient market hypothesis in two most popular indices of Indian stock market. For examining the hypothesis whether Indian stock markets are efficient in the weak form, two kinds of tests are conducted. These are parametric and non-parametric tests for randomness, that is, unit root test, autocorrelation test, runs test and variance ratio test. The results suggest that the Indian stock market does not show the characteristics of random walk and as such, is not efficient in the weak form in daily and weekly returns. However, the monthly returns are found to be inefficient only as per variance ratio test. Thus, the investors can avail excess returns by predicting the future returns as all return series present an opportunity to investors to gain from the pattern.

Understanding Foreign Exchange Option Returns: The Information Content of Volatility

According to general asset pricing theory, options should reward their holders for the systematic risk they are bearing. In this paper, we study the returns of foreign exchange options. We find that, by sorting options according to the distance of their implied volatility from the historical volatility, we obtain portfolios with positive average monthly returns. These returns are not explained by standard aggregate risk factors, which suggest either that additional risk factors should be accounted for, or that investors behavior differs from the traditional paradigm of rational agents.

Econometric measures of connectedness and systemic risk in the finance and insurance sectors

We propose several econometric measures of connectedness based on principal-components analysis and Granger-causality networks, and apply them to the monthly returns of hedge funds, banks, broker/dealers, and insurance companies. We find that all four sectors have become highly interrelated over the past decade, likely increasing the level of systemic risk in the finance and insurance industries through a complex and time-varying network of relationships. These measures can also identify and quantify financial crisis periods, and seem to contain predictive power in out-of-sample tests. Our results show an asymmetry in the degree of connectedness among the four sectors, with banks playing a much more important role in transmitting shocks than other financial institutions.

Monthly variation in litterfall and the amount of nutrients in an Aleurites montana plantation

In this study, the dynamics of monthly variation in litterfall and the amount of nutrients, i.e., organic C, N, P and K, in an Aleurites montana plantation were analyzed, based on a field study and experiments over one year. The results show that the litterfall mass of A. montana collected generally presents an ascending trend with maximum defoliation occurring in the autumn and winter (October–December), accounting for 75.67% of the total amount of annual litterfall. The sequence in the amount of nutrients in A. montana litter was as follows: organic C > N > K > P; their monthly amounts show various dynamic curves. Similar to the dynamics of the mass of monthly litterfall, the monthly returns of C, N, P and K generally show an ascending trend with their peak values all occurring in December. The mass of A. montana litterfall and the dynamics of its monthly nutrient return provide, to a certain degree, a scientific reference for planting and fertilizing A. montana.

Market Timing with Moving Averages

I present evidence that a moving average (MA) trading strategy third order stochastically dominates buying and holding the underlying asset in a mean-variance-skewness sense using monthly returns of value-weighted decile portfolios sorted by market size, book-to-market cash-flow-to-price, earnings-to-price, dividend-price, short-term reversal, medium-term momentum, long-term reversal and industry. The abnormal returns are largely insensitive to the four Carhart (1997) 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 moving average 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. I also report evidence regarding the profitability of the MA strategy in seven international stock markets. The performance of the MA strategies also holds for more than 18,000 individual stocks from the CRSP database. 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. Furthermore, combining several MA strategies into a value/equal-weighted portfolio of MA strategies performs even better and represents a unified framework for security selection and market timing.

Markov Switching Dynamics in REIT Returns: Univariate and Multivariate Evidence on Forecasting Performance

The fact that REIT returns display rich dynamic time series properties, such as conditional heteroskedasticity and time-varying risk premia, has recently come to the forefront of the real estate finance literature. In this paper we document the presence of Markov switching regimes in expected returns, variances, and in the implied reward-to-risk ratio of REIT returns and compare them to properties of non-REIT stock and bond returns. In a Markov switching model conditional means, variances, and covariances depend on an unobservable Markov state variable that can assume a finite number of values characterizing the state of the financial market at each point in time. We analyze the relative in-sample descriptive performance of regime switching and alternative time series models such as multivariate GARCH. Interestingly, our evidence suggests that regime switching techniques may more successfully fit the monthly return series for REITs, stocks, and bonds over the period 1972-2008.When this evidence is extended to a multivariate setting in which REIT, stock, and bond returns are modeled jointly, we find that the data call for the specification of rich structures with as many as four separate states. This results from the absence of complete synchronicity among the regimes that characterize univariate REIT, stock, and bond returns. This finding may have considerable importance as it implies that for REITs there may exist an important de-coupling between the standard notion of (linear) correlation and of “association,” in the sense that REIT returns may co-move with the returns of other asset classes much less than commonly believed on the basis of their correlation coefficients.

Does Tax Deferral Enhance Firm Value?

Recent research provides evidence that corporate tax departments and tax directors have incentives to reduce financial statement effective tax rates, but little or no incentive to reduce cash taxes paid. The lack of managerial incentives to reduce cash taxes paid provides a stark contrast to the benefits of tax deferral espoused by tax professionals and academics, raising the question: Does tax deferral actually enhance firm value? We examine whether the difference between financial statement tax expense and current taxes paid (i.e., current year tax deferral) is associated with a firm’s change in future profitability and market returns. We find positive associations between current year tax deferral and both the change in next period profitability and stock returns in months around the Form 10-K release date. We also find that these associations increase for firms with greater investment opportunities, financial constraints, and, to a lesser extent, strong corporate governance. These results suggest both profitability and market return benefits associated with tax deferral, consistent with tax deferral enhancing firm value.

Constant versus Time‐Varying Beta Models: Further Forecast Evaluation

ABSTRACTRecent advances in the measurement of beta (systematic return risk) and volatility (total return risk) demonstrate substantial advantages in utilizing high‐frequency return data in a variety of settings. These advances in the measurement of beta and volatility have resulted in improvements in the evaluation of alternative beta and volatility forecasting approaches. In addition, more precise measurement has also led to direct modeling of the time variation of beta and volatility. Both the realized beta and volatility literature have most commonly been modeled with an autoregressive process. In this paper we evaluate constant beta models against autoregressive models of time‐varying realized beta. We find that a constant beta model computed from daily returns over the last 12 months generates the most accurate quarterly forecast of beta and dominates the autoregressive time series forecasts. It also dominates (dramatically) the popular Fama–MacBeth constant beta model, which uses 5 years of monthly returns. Copyright © 2011 John Wiley & Sons, Ltd.

New Belgian Stock Market Returns: 1832–1914

The limited availability of high quality and computer readable data seriously impedes research in history and finance. We introduce a new monthly return series for Belgian owned equity based on Brussels Stock Market data for the period 1832–1914 as an improvement to the popular Drappier index. Over this period, our dataset includes 446,374 prices, 23,976 dividends, 371 stock and reverse splits (or other capital operations) on 2037 stocks of 1387 (foreign and Belgian) companies. Our dataset includes all shares and bonds but also high-quality information on prices, dividends, shares outstanding and market capitalization. In addition, company, country and sector information is available. We construct value weighted, price weighted and equally weighted indices as well as dividend yields. We find three important results. First, total nominal returns hover between 3.29% and 5.35% per annum, depending on how individual stocks are aggregated into the index. Second, dividend income constitutes the major part of total return and dividend distributions have a clear seasonal pattern. Third, the results highlight several drawbacks of the Drappier indices, especially an upward bias in expected equity performance.

The Stock-Bond Comovements in the Paris Bourse: Historical Evidence

Using some recently developed Paris Bourse 19th century price indexes; we study the stock-bond monthly return comovement for a 76 years long period. The comovements of stocks not only with government bonds, like majority of studies on this subject, but also with corporate bonds have been considered in this paper. A multivariate Dynamic conditional correlation GARCH(DCC GARCH) model has been implemented to assess the stock-bond return time varying correlation. The model succeeds to capture well enough the behavior of stocks and bonds returns. We do obtain variable but always highly positive conditional stock-bond correlations. The Granger causality tests which we have conducted per sub periods shows as we approach to the end of the 19th century the corporate bond market becomes more and more dominant in term of price adjustment and therefore more efficient.

The Dividend Month Premium

We document an asset-pricing anomaly whereby companies have positive abnormal returns in months when a dividend is predicted. Abnormal returns in predicted dividend months are high relative to other companies, and relative to dividend-paying companies in months without a predicted dividend, making risk-based explanations unlikely. The anomaly is as large as the value premium, but less volatile. The premium is consistent with price pressure from dividend-seeking investors. Measures of liquidity and demand for dividends are associated with larger price increases in the period before the ex-day (when there is no news about the dividend), and larger reversals afterwards.

Data envelopment analysis models of investment funds

This paper develops theory missing in the sizable literature that uses data envelopment analysis to construct return–risk ratios for investment funds. It explores the production possibility set of the investment funds to identify an appropriate form of returns to scale. It discusses what risk and return measures can justifiably be combined and how to deal with negative risks, and identifies suitable sets of measures. It identifies the problems of failing to deal with diversification and develops an iterative approximation procedure to deal with it. It identifies relationships between diversification, coherent measures of risk and stochastic dominance. It shows how the iterative procedure makes a practical difference using monthly returns of 30 hedge funds over the same time period. It discusses possible shortcomings of the procedure and offers directions for future research.