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Several studies have observed that stocks tend to drop by an amount that is less than the dividend on the ex-dividend day, the so-called ex-dividend day anomaly. However, there still remains a lack of consensus for a single explanation of this anomaly. Different from other studies, this dissertation attempts to answer the primary research question: how can investors make trading profits from the ex-dividend day anomaly and how much can they earn? With this goal, I examine the economic motivations of equity investors through four main hypotheses identified in the anomaly's literature: the tax differential hypothesis, the short-term trading hypothesis, the tick size hypothesis, and the leverage hypothesis.

While the U.S. ex-dividend anomaly is well studied, I examine a long data window (1975–2010) of Thailand data. The unique structure of the Thai stock market allows me to assess all four main hypotheses proposed in the literature simultaneously. Although I extract the sample data from two data sources, I demonstrate that the combined data are consistently sampled. I further construct three trading strategies – “daily return,” “lag one daily return,” and “weekly return” – to alleviate the potential effect of irregular data observation.

I find that the ex-dividend day anomaly exists in Thailand, is governed by the tax differential, and is driven by short-term trading activities. That is, investors trade heavily around the ex-dividend day to reap the benefits of the tax differential. I find mixed results for the predictions of the tick size hypothesis and results that are inconsistent with the predictions of the leverage hypothesis.

I conclude that, on the Stock Exchange of Thailand, juristic and foreign investors can profitably buy stocks cum-dividend and sell them ex-dividend while local investors should engage in short sale transactions. On average, investors who employ the daily return strategy have earned significant abnormal return up to 0.15% (45.66% annualized rate) and up to 0.17% (50.99% annualized rate) for the lag one daily return strategy. Investors can also make a trading profit by conducting the weekly return strategy and earn up to 0.59% (35.67% annualized rate), on average.

This study aims to draw on a less explored predictor – the average correlation of pairwise returns on industry portfolios – to predict stock market returns (SMRs) in the USA.

This study uses the average correlation approach of Pollet and Wilson (2010) and predicts the SMRs in the USA. The model is estimated using monthly data for a long time horizon, from July 1963 to December 2018, for the portfolios comprising 48 Fama-French industries. The model is extended to examine the effects of a longer lag structure of one-month to four-month lags and to control for the effects of a number of variables – average variance (AV), cyclically adjusted price-to-earnings ratio (CAPE), term spread (TS), default spread (DS), risk-free rate returns (R_f) and lagged excess market returns (R_s).

The study finds that the two-month lagged average correlation of returns on individual industry portfolios, used individually and collectively with financial predictors and economic factors, predicts excess returns on the stock market in an effective manner.

The methodology and results are of interest to academics as they could further explore the use of average correlation to improve the predictive powers of their models.

Market practitioners could include the average correlation in their asset pricing models to improve the predictions for the future trend in stock market returns. Investors could consider including average correlation in their forecasting models, along with the traditional financial ratios and economic indicators. They could adjust their expected returns to a lower level when the average correlation increases during a recession.

The finding that recession periods have effects on the SMRs would be useful for the policymakers. The understanding of the co-movement of returns on industry portfolios during a recession would be useful for the formulation of policies aimed at ensuring the stability of the financial markets.

The study contributes to the literature on three counts. First, the study uses industry portfolio returns – as compared to individual stock returns used in Pollet and Wilson (2010) – in constructing average correlation. When stock market becomes more volatile on returns, the individual stocks are more diverse on their performance; the comovement between individual stock returns might be dominated by the idiosyncratic component, which may not have any implications for future SMRs. Using the industry portfolio returns can potentially reduce such an effect by a large extent, and thus, can provide more reliable estimates. Second, the effects of business cycles could be better identified in a long sample period and through several sub-sample tests. This study uses a data set, which spans the period from July 1963 to December 2018. This long sample period covers multiple phases of business cycles. The daily data are used to compute the monthly and equally-weighted average correlation of returns on 48 Fama-French industry portfolios. Third, previous studies have often ignored the use of investors’ sentiments in their prediction models, while investors’ irrational decisions could have an important impact on expected returns (Huang et al., 2015). This study extends the analysis and incorporates investors’ sentiments in the model.

In this paper, it is argued that previous estimates of the expected cost of equity and the expected arithmetic risk premium in the UK show a degree of upward bias. Given the importance of the risk premium in regulatory cost of capital in the UK, this has important policy implications. There are three reasons why previous estimates could be upward biased. The first two arise from the comparison of estimates of the realised returns on government bond (‘gilt’) with those of the realised and expected returns on equities. These estimates are frequently used to infer a risk premium relative to either the current yield on index‐linked gilts or an ‘adjusted’ current yield measure. This is incorrect on two counts; first, inconsistent estimates of the risk‐free rate are implied on the right hand side of the capital asset pricing model; second, they compare the realised returns from a bond that carried inflation risk with the realised and expected returns from equities that may be expected to have at least some protection from inflation risk. The third, and most important, source of bias arises from uplifts to expected returns. If markets exhibit ‘excess volatility’, or f part of the historical return arises because of revisions to expected future cash flows, then estimates of variance derived from the historical returns or the price growth must be used with great care when uplifting average expected returns to derive simple discount rates. Adjusting expected returns for the effect of such biases leads to lower expected cost of equity and risk premia than those that are typically quoted.

The purpose of this paper is to examine operating characteristics, risk and performance measures of all available vehicles for index investing in US bond funds during the 15‐year period from April, 1994 to March, 2009. The results shed light on the important issue of bond index mutual funds (BIMFs) and bond exchange‐traded funds (BETFs) performance compared with average of all bond mutual funds.

Data were obtained from Morningstar Principia. Operating characteristics include expense ratios, annual turnover rates, and tax cost ratios. Performance measures include average annual returns and return percentile rank in category, risks (measured by standard deviation) and risk‐adjusted returns (measured by the Sharpe ratio).

BIMFs and BETFs have significantly lower expense ratios and annual turnover rates than category averages. Their returns and risk‐adjusted returns are significantly higher than bond category averages.

Future studies will be able to benefit from a larger sample size, longer performance records, and the strength of bond index funds in foreign markets.

Both BIMFs and bond exchange‐traded mutual funds have significantly lower expense and annual turnover rates, making them preferred investment choices.

Efforts by active bond mutual fund managers to beat index benchmarks have largely failed. Investors should be wary of bond mutual fund managers touting their ability to beat the average or a bond index.

The advantage of investment in BIMFs and BETFs is clear.

The objective of this paper is to empirically evaluate alternative multifactor explanations of cash‐flows and earnings momentum portfolios. It aims to examine whether the common risk factors, which are related to firm level accounting characteristics, can reflect the behavior of average portfolio returns based on such measures as cash‐flows and earnings momentum in the presence of each other's systematic components and time‐varying measures of volatility.

The paper uses monthly stock returns for all NYSE firms on CRSP database and constructs average portfolio returns between July 1951 and June 2008. It investigates the interdependence of stock returns for cash‐flows and earnings momentum portfolios using their systematic components. The methodology is implemented by extending various characteristic‐based factor models of returns.

The main finding of the study suggests that there is strong information transmission – both in the temporal variation and risk sensitivities of the average returns of cash‐flows and earnings momentum portfolios. Also, there is compelling empirical evidence that the associated systematic components well complement the ability of common risk factors to explain the temporal behavior of all NYSE stocks.

While the results are statistically significant, the effect of aggregate risk in factor model is dubious. An integration of other accruals based accounting characteristics would be an interesting issue to explore.

The goal of the paper is to examine how different combinations of empirically determined variables that are instrumental in the creation of style‐specific benchmarks can capture the time‐series variation of average portfolio returns. It will provide added value to scholars and investment professionals in making effective portfolio management decisions.

Compared to the existing literature, in the evaluation of earnings and cash‐flows based measures, the paper focuses on the predictive power of the systematic components. It shows that paying close attention to the systematic components clearly provides additional information about the time‐varying behavior of average stock returns. The findings that the economic characteristics of the firm can complement the comparative role of the systematic components of cash‐flows and earnings add significantly to the literature.

The purpose of this paper is to determine whether self‐managed superannuation fund (SMSF) trustees earn: the equity risk premium or any premium to the riskless rate of interest.

Using a sample of 100 SMSFs, the average annual returns since inception of the funds in the sample are compared with: the average annual equity risk premium since that time and the average yield of Commonwealth Government Securities since that time.

The investigation reveals: the SMSFs in the sample do not earn the equity risk premium and the SMSFs in the sample did not earn a premium to riskless rate of interest. This leads to the conclusion that the SMSFs have borne risk without commensurate reward. Research limitations/implications – The trustees' rationale for making particular investment decisions and the consistency of the portfolio structures with the risk profiles of the trustees are two areas that may be fruitfully explored in future research.

For SMSF trustees, a simple portfolio that divides assets between (unmanaged) index funds and risk‐free securities on the basis of trustees' risk aversion may generate better results than the existing portfolios. For policy makers, the relatively poor performance of SMSFs implies that the superannuation system as currently structured may not be generating returns that will maximize retirement incomes.

The paper provides the first comparison of SMSF returns with the equity risk premium and the riskless rate of interest measured at appropriate horizons.

We examine the incremental cross-sectional role of several common risk factors related to size, book-to-market, and momentum in size-and-momentum-sorted portfolios. Unlike the existing literature, which focuses on the conditional mean specification only, we evaluate the common risk factors’ incremental explanatory power in the cross-sectional characterization of both average return and conditional volatility. We also investigate the role of ex-ante market risk in the cross-section. The empirical results demonstrate that the size-and-momentum-based risk factors explain a significant portion of the cross-sectional average returns and cross-sectional conditional volatility of the benchmark equity portfolios. We find that the Fama–French (1993) factors and the ex-ante market risk are priced in the cross-sectional conditional volatility. We conclude that the size-and-momentum-based factors provide a source of risk that is independent of the Fama–French factors as well as ex-post and ex-ante market risk. Our results bolster the risk-based explanation of the size and momentum effects.

Investors are inattentive to continuous information as opposed to discrete information, resulting in underreaction to continuous information. This paper aims to examine if the well-documented return predictability of the strategies based on the ratio of short-term to long-term moving averages can be enhanced by conditioning on information discreteness. Anchoring bias has been the popular explanation for the source of underreaction in the context of moving averages-based strategies. This paper proposes and studies another possible source based on investor inattention that can potentially result in superior performance of these strategies.

The paper uses portfolio sorting as well as Fama-MacBeth cross-sectional regressions. For examining the role of information discreteness in the return predictability of the moving average ratio, the sample stocks are double-sorted based on the moving average ratio and information discreteness measure. The returns to these portfolios are computed using standard approaches in the literature. The regression approach controls for various well-known return predictors.

This study finds that the equally-weighted monthly returns to the long-short moving average ratio quintile portfolios increase monotonically from 0.54% for the discrete information portfolio to 1.37% for the continuous information portfolio over the 3-month holding period. This study observes a similar pattern in risk-adjusted returns, value-weighted portfolios, non-January returns, large and small stocks, for alternative holding periods and the ratio of 50-day to 200-day moving average. The results are robust to control for well-known return predictors in cross-sectional regressions.

To the best of the authors’ knowledge, this is the first paper to document the significant role of investor inattention to continuous information in the return predictability of strategies based on the moving average ratios. There are many underreaction anomalies that have been reported in the literature, and the paper's results can be extended to those anomalies in subsequent research.

The findings of this paper have important practical implications. Strategies based on moving averages are an extremely popular component of a technical analyst's toolkit. Their profitability has been well-documented in the prior literature that attributes the performance to investors' anchoring bias. This paper offers a readily implementable approach to enhancing the performance of these strategies by conditioning on a straightforward measure of information discreteness. In doing so, this study extends the literature on the role of investor inattention to continuous information in anomaly profits.

While there is considerable literature on technical analysis, and especially on the performance of moving averages-based strategies, the novelty of this paper is the analysis of the role of information discreteness in strategy performance. Not only does the paper document robust evidence, but the findings suggest that the investor’s inattention to continuous information is a more dominant source of underreaction compared to anchoring. This is an important result, given that anchoring has so far been considered the source of return predictability in the literature.

Sees the objective of teaching financial management to be to help managers and potential managers to make sensible investment and financing decisions. Acknowledges that financial theory teaches that investment and financing decisions should be based on cash flow and risk. Provides information on payback period; return on capital employed, earnings per share effect, working capital, profit planning, standard costing, financial statement planning and ratio analysis. Seeks to combine the practical rules of thumb of the traditionalists with the ideas of the financial theorists to form a balanced approach to practical financial management for MBA students, financial managers and undergraduates.

Corporate social responsibility (CSR) and corporate sustainability have gained prominence in the major capital markets. In Brazil, the São Paulo Stock Exchange (BM&FBovespa) has created the Corporate Sustainability Index (ISE) and the Carbon Efficient Index (ICO2), responsible for indicating the performance of sustainable companies. Therefore, this study proposes to examine and compare the stock returns of the sustainability index member companies with the returns of companies out of these indexes. In this methodology we selected the two principal negotiability indexes of that market (IBOV and IBrX50), which are indexes that meet the most traded stocks of BM&FBovespa, and calculated the average daily returns of the four indexes in order to make performance comparisons over the period 2005–2014, based on nonparametric statistical tests. Our findings indicate that the average returns of sustainability indexes were higher, but these differences were not statistically significant, confirming previous evidence. Additionally, by means of a cointegration test, we found that the indexes are cointegrated in the long term. These findings are limited to the analyzed emerging market and are also subject to the limitations of the estimated models. Thus, we can infer that presence in the sustainability indexes does not indicate statistically significant higher returns, which means that companies with sustainable practices in Brazil are not only concerned with economic performance, but also with social, cultural, and environmental issues. The main findings are aligned with the concept of triple bottom line, even in the case of an emerging market.