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This chapter introduces dividend smoothing, presents theories to explain dividend smoothing behavior, and analyzes how different levels of business environment affect dividend smoothing. First, dividend smoothing describes a mechanism in which a firm is reluctant to reduce dividends and only increases dividends when its earnings increase permanently. In practice, dividend smoothing behavior is found in both developed and developing countries. Firms in developed countries are more likely to smooth dividends than those in developing countries. Second, although Miller and Modigliani (1961) posit that investors are indifferent between stable and unstable dividend payments in a perfect environment, market frictions in the real world make stable and unstable dividends have different effects on firm value. Three common frictions are information asymmetry, agency problem, and investors' demand for income smoothing. Due to information asymmetry between insiders and outsiders, firms tend to smooth their dividends to signal outside investors about their quality. In addition, dividend smoothing may be the substitute for weak corporate governance and/or the outcome of free cash absorption behavior. Besides, dividends are more convenient for investors' consumption; therefore, firms are more likely to smooth dividends in order to satisfy investors' demand for smooth income. Finally, as a special dividend decision, dividend smoothing is also affected by an internal micro (industry) and macro-environment. Dividend smoothing theories are the behind mechanisms to explain these effects.

This chapter seeks to analyze the development across the length and breadth of the Indian financial system in the post-reform period, based on the “flow of funds” accounts estimates by RBI. Besides, this chapter also analyzes the integration of the Indian capital market with the stock markets of the United States, the United Kingdom, Japan, China, Hong Kong, and Singapore using the movements in their stock prices during 1998–2015. Moreover, this chapter is intended for examining the potential implication financial integration, particularly the financial openness of India, on volatility spillover and financial contagion in as much as these two issues have emphatic significance in the determination of the relevant policy roadmap. Our findings broadly confirms the expectations by revealing significantly positive correlations in stock prices, in returns to investments in stock markets, and in mean returns and risk. The integration of the capital markets is also manifested in the cyclical fluctuations of the stock price indices, signifying the underlying sensitivity to random shocks.

In the build-up of an investment decision, the existence of both active and passive investment vehicles triggers a puzzle for investors. Indeed the confrontation between active and index replication equity funds in terms of risk-adjusted performance and alpha generation has been a bone of contention since the inception of these investment structures. Accordingly, the objective of this chapter is to distinctly underscore whether an investor should be concerned in choosing between active and diverse passive investment structures.

The survivorship bias-free dataset consists of 776 equity funds which are domiciled either in America or Europe, and are likewise exposed to the equity markets of the same regions. In addition to geographical segmentation, equity funds are also categorised by structure and management type, specifically actively managed mutual funds, index mutual funds and passive exchange traded funds (‘ETFs’). This classification leads to the analysis of monthly net asset values (‘NAV’) of 12 distinct equally weighted portfolios, with a time horizon ranging from January 2004 to December 2014. Accordingly, the risk-adjusted performance of the equally weighted equity funds’ portfolios is examined by the application of mainstream single-factor and multi-factor asset pricing models namely Capital Asset Pricing Model (Fama, 1968; Fama & Macbeth, 1973; Lintner, 1965; Mossin, 1966; Sharpe, 1964; Treynor, 1961), Fama French Three-Factor (1993) and Carhart Four-Factor (1997).

Solely examination of monthly NAVs for a 10-year horizon suggests that active management is equivalent to index replication in terms of risk-adjusted returns. This prompts investors to be neutral gross of fees, yet when considering all transaction costs it is a distinct story. The relatively heftier fees charged by active management, predominantly initial fees, appear to revoke any outperformance in excess of the market portfolio, ensuing in a Fool’s Errand Hypothesis. Moreover, both active and index mutual funds’ performance may indeed be lower if financial advisors or distributors of equity funds charge additional fees over and above the fund houses’ expense ratios, putting the latter investment vehicles at a significant handicap vis-à-vis passive low-cost ETFs. This chapter urges investors to concentrate on expense ratios and other transaction costs rather than solely past returns, by accessing the cheapest available vehicle for each investment objective. Put simply, the general investor should retreat from portfolio management and instead access the market portfolio using low-cost index replication structures via an execution-only approach.

The battle among actively managed and index replication equity funds in terms of risk-adjusted performance and alpha generation has been a grey area since the inception of mutual funds. The interest in the subject constantly lightens up as fresh instruments infiltrate financial markets. Indeed the mutual fund puzzle (Gruber, 1996) together with the enhanced growth of ETFs has again rejuvenated the active versus passive debate, making it worth a detailed analysis especially for the benefit of investors who confront a dilemma in choosing between the two management styles.

Purpose – The purpose of this chapter is to examine whether or not the Capital Asset Pricing Model (CAPM) reasonably describes the return generating process on the Ghanaian Stock Exchange using monthly return data of 19 individual companies listed on the Exchange during the period January 2000 to December 2009.

Methodology/approach – We follow a methodology similar to Jensen (1968) time series approach. Parameters are estimated using OLS. This study is designed to measure beta risk across different times by following the time series approach. The betas of the individual securities are estimated using time series data of the excess return version of the CAPM.

Findings – Our test results show that although market beta contributes to the variation in equity returns in Ghana, its contribution is not as significant as predicted by the CAPM, and in some cases very weak. Our results also reject the strictest form of the Sharpe–Lintner CAPM, but we found positive linear relationship between equity risk premium and market beta. Instead, our evidence uphold the Jensen (1968) and Jensen, Black, and Scholes (1972) versions of the CAPM.

Research limitations/implications – This study is limited to the single-factor CAPM. Future studies will extend the test to include both size and BE/ME fundamentals and factors relating to P/E ratio, momentum and liquidity.

Practical implications – Our results will make corporate managers to be cautious when using CAPM as a basis to determine cost of equity for investment appraisal purposes, and fund managers when evaluating asset and portfolio performance.

Originality/value – The CAPM is applied to individual securities instead of portfolios, since the model was developed using information on a single security.

The internal factors that influence the decision to change dividend growth rates include two competing models: the earnings and free cash flow models. As far as each of the components of each model is considered, the informative and efficient dividend payout decisions require that managers have to focus on the significant component(s) only. This study examines the cointegration, significance, and explanatory power of those components empirically. The expected outcomes serve two objectives. First, on an academic level, it is interesting to examine the extent to which payout practices meet the premises of the earnings and free cash flow models. The latter considers dividends and financing decisions as two faces of the same coin. Second, on a professional level, the outcomes help focus the management’s efforts on the activities that can be performed when considering a change in dividend growth rates.

This study uses data for the firms listed in two indexes: Dow Jones Industrial Average (DJIA30) and NASDAQ100. The data cover quarterly periods from 30 June 1989 to 31 March 2011. The methodology includes (a) cointegration analysis in order to test for model specification and (b) classical regression in order to examine the explanatory power of the components of earnings and free cash flow models.

The results conclude that: (a) Dividends growth rates are cointegrated with the two models significantly; (b) Dividend growth rates are significantly and positively associated with growth in sales and cost of goods sold only. Accordingly, these are the two activities that firms’ management need to focus on when considering a decision to change dividend growth rates, (c) The components of the earnings and free cash flow models explain very little of the variations in dividends growth rates. The results are to be considered a call for further research on the external (market-level) determinants that explain the variations in dividends growth rates. Forthcoming research must separate the effects of firm-level and market-level in order to reach clear judgments on the determinants of dividends growth rates.

This study contributes to the related literature in terms of offering updated robust empirical evidence that the decision to change dividend growth rate is discretionary to a large extent. That is, dividend decisions do not match the propositions of the earnings and free cash flow models entirely. In addition, the results offer solid evidence that financing trends in the period 1989–2011 showed heavy dependence on debt financing compared to other related studies that showed heavy dependence on equity financing during the previous period 1974–1984.

This chapter re-examines the Fama–French (FF) five-factor asset pricing model proposed by Fama and French (2015), since this model has a failure to capture the lower average returns on small stocks and its performance could not fully satisfy the original definitions of those considered factors. From the viewpoint of the econometrics analysis, we consider the inferior performance could be potentially caused by the spurious effect in the five-factor model, which could mislead the statistical inference and yield biased empirical results. We thus employ the CO-AR estimation by Wang and Hafner (2018) to prove the usefulness of the FF five-factor model. Empirical results demonstrate with the CO-AR estimation, the five-factor model indeed properly captures the lower average returns on small stocks and illustrate the sustainability of efficiency of the market, which is in contrast to the findings of Fama and French (2015). However, we propose a new perspective on the seminal five-factor model.

This chapter provides an overview of the explanations and factors affecting dividend policy. This study employs a systematic literature review approach to review a large sample of studies related to the dividend puzzle. Although the analysis reveals mixed evidence involving the theories and determinants of dividend policy, some determinants appear in numerous studies. However, no consensus exists on an optimal dividend to resolve the dividend puzzle, and the authors propose a model to deal with the same. When examining dividend policy, researchers should consider the firm, market, behavior, and other determinants. When making significant dividend or stock decisions, managers and shareholders should also contemplate the factors, interactions, inadequacies, and consequences. Future researchers should strive to take a more comprehensive view when resolving the dividend puzzle. This study provides a current and complete picture of dividend policy's available theories and empirical determinants. Its significant contribution is identifying some of the more consistently essential determinants of dividend policy while proposing a holistic model to address the prevailing dividend dilemma.