Estimates Of Expected Returns Research Articles

Forecasting the cross-sectional stock returns: Evidence from the United Kingdom

The study provides the forecasts of expected returns based on cross-sectional estimates from the Fama-Macbeth regressions in the United Kingdom. We collected the data of listed firms on the London Stock Exchange on the DataStream from January 1980 to December 2020. We analyze the data sample by employing three cross-sectional models' ten-year rolling estimates of Fama-Macbeth slopes. The empirical findings demonstrate that an investor can derive a composite estimate of the expected return by integrating various company-specific variables in real-time. Model 1 indicates that the expected-return estimates have a predictive slope for future monthly returns of 95.07%, with a standard error of 0.1981. Moreover, model 2 and model 3 report the predictability of returns are 77.57% and 76.94%. In short, our empirical evidence suggests that investors and stakeholders may consider using model 1 to estimate the cost of equity due to its simplicity and effective prediction capability. Our findings are consistent with trade-off theory and prior literature.

Gains from Markowitz Optimization: Evidence from Reoptimization of Mutual Fund Holdings

Prior studies have challenged the practical usefulness of Markowitz portfolio optimization in improving the return–risk trade-off in portfolio management. The authors approach this question from a unique angle by examining whether one can improve the performance of a large sample of actual mutual fund portfolios by reoptimizing the holdings using simple mean–variance optimization methods. The analyses produce compelling evidence of the benefits of Markowitz optimization. Simple portfolio optimization improves mutual fund portfolios’ risk-adjusted performance despite noisy expected return estimates inferred from mutual fund portfolio weights. Several alternative optimization strategies, including the risk-parity portfolio, minimum variance portfolio, mean–variance portfolio, and Sharpe ratio maximization portfolio, all outperform actual mutual fund portfolios in terms of the Sharpe ratio and other risk-adjusted performance measures. Moreover, the results are robust to subsamples partitioned on various dimensions. In contrast to the findings of DeMiguel et al. (2009), the authors find that the 1/N portfolio performs the worst.

A Modified Ohlson (1995) Model and Its Applications

In this paper, I explore a modified Ohlson (1995) model, which incorporates future positive net present value (NPV) investments. I first utilize an approach to simultaneously estimate the parameters in the linear information dynamic alongside the cost of equity capital, then evaluate the model’s performance in equity valuation and return prediction. Contrary to the systematic undervaluation of the Ohlson (1995) model reported in prior literature, I find that there is no systematic undervaluation of stock prices by using the modified Ohlson (1995) model. The out-of-sample median valuation bias estimated with this new approach is only 3.3% compared with 34.8% achieved when carrying out the estimation using existing methods. I also find that using a time-varying cost of equity capital reduces valuation bias and improves valuation accuracy. Furthermore, the expected return estimates developed from the model generate a monotonic decile ranking of future realized stock returns.

Portfolio diversification and model uncertainty: A robust dynamic mean‐variance approach

AbstractThis paper focuses on a dynamic multi‐asset mean‐variance portfolio selection problem under model uncertainty. We develop a continuous time framework for taking into account ambiguity aversion about both expected return rates and correlation matrix of the assets, and for studying the join effects on portfolio diversification. The dynamic setting allows us to consider time varying ambiguity sets, which include the cases where the drift and correlation are estimated on a rolling window of historical data or when the investor takes into account learning on the ambiguity. In this context, we prove a general separation principle for the associated robust control problem, which allows us to reduce the determination of the optimal dynamic strategy to the parametric computation of the minimal risk premium function. Our results provide a justification for under‐diversification, as documented in empirical studies and in the static models. Furthermore, we explicitly quantify the degree of under‐diversification in terms of correlation bounds and Sharpe ratios proximities, and emphasize the different features induced by drift and correlation ambiguity. In particular, we show that an investor with a poor confidence in the expected return estimation does not hold any risky asset, and on the other hand, trades only one risky asset when the level of ambiguity on correlation matrix is large. We also provide a complete picture of the diversification for the optimal robust portfolio in the three‐asset case.

The Performance of Characteristic-Sorted Portfolios: Evaluating the Past and Predicting the Future

The expected returns of most portfolios are likely to fluctuate over time. We present a statistical model that allows for such fluctuations and apply the model to analyze the returns of characteristic-sorted portfolios, such as value minus growth. We find that accounting for plausible magnitudes of persistent variation in returns doubles the standard errors of these portfolios' expected return estimates. We also analyze characteristic-sorted portfolios from the perspective of Bayesian investors and show that investors' posterior beliefs about expected returns are highly dependent on their priors about persistence.

Application of semi-deviation as a proxy for the expected return estimation in the Croatian equity market

Abstract In the field of portfolio management the focus has been on the out-of-sample estimation of the covariance matrix mainly because the estimation of expected return is much more challenging. However, recent research efforts have not only tried to improve the estimation of risk parameters by expanding the analysis beyond the mean-variance setting but also by testing whether risk measures can be used as proxies for the expected return in the stock market. In this research, we test the standard deviation (measure of total volatility) and the semi-deviation (measure of downside risk) as proxies for the expected market return in the illiquid and undeveloped Croatian stock market in the period from January 2005 until November 2017. In such an environment, the application of the proposed methodology yielded poor results, which helps explain the failure of the out-of-sample estimation of the maximum Sharpe ratio portfolio in earlier research in the Croatian equity market.

Gains from Markowitz Optimization: Evidence from Re-Optimization of Mutual Fund Holdings

Prior studies challenge the practical usefulness of Markowitz portfolio optimization in improving the return-risk tradeoff in portfolio management. We approach this question from a unique angle by examining whether one can improve the performance of a large sample of actual mutual fund portfolios by re-optimizing the holdings using simple mean-variance optimization methods. Our analyses produce compelling evidence of the benefits from Markowitz optimization. Simple portfolio optimization improves mutual fund portfolios’ risk-adjusted performance despite noisy expected return estimates inferred from mutual fund portfolio weights. Several alternative optimization strategies, including the risk-parity portfolio, minimum variance portfolio, mean-variance portfolio and Sharpe ratio maximization portfolio all outperform actual mutual fund portfolios in terms of the Sharpe ratio and other risk-adjusted performance measures. Moreover, the results are robust to subsamples partitioned on various dimensions. In contrast to DeMiguel et al. (2009), we find that the 1/N portfolio performs the worst.

Estimating the implied risk premium of U.S.-listed shipping firms

ABSTRACTWhile the water transportation industry is perceived as risk-laden, expected return estimates for shipping firms, based on the capital asset pricing model (CAPM), are found to be ‘remarkably low.’ We apply the implied cost of capital (ICC), defined as the constant discount rate that equates share prices and future cash flows, as an alternative means of shipping expected returns and use these estimates instead, as well as in conjunction with the CAPM to provide fresh evidence on the risk and return characteristics of the shipping industry. An aggregate measure of ICC reveals that the median risk premium of shipping firms between 1983 and 2013 is in the range of 0.94% to 0.08%. The expected return of shipping firms tracks a long-term moving average of the S&P 500 index; nevertheless, shipping returns are below the index return at similar, and at times lower, levels with the 10-year treasury yield. The expected equity premium of the shipping industry implied in the cross-section of ICC estimates and CAPM betas ranges between 1.4% and 0.2%. The persistence of a ‘shipping return paradox’ against a variant of expected return methodologies may indicate the pricing of higher moments in the return distribution of shipping firms beyond the mean-variance framework.

Gaussian Process Priors for Bayesian Portfolio Selection

This article shows how asset characteristics can be incorporated into the Bayesian portfolio selection framework. We use Gaussian process priors to model the belief that assets with similar characteristics are likely to have similar expected returns. The resulting Bayesian shrinkage estimator biases expected return estimates of assets with similar characteristics towards each other. A closed-form solution of the optimal portfolio weights in the Gaussian process prior framework is derived. Our simulation results and our empirical analysis suggest that portfolio selection with Gaussian process priors is a competitive alternative to benchmark portfolio selection approaches from the literature.

Enhancing Risk Parity by Including Views

Within the finance literature, there is an apparent gap between the inherent ignorance of expected returns of a risk parity approach on the one hand, and the assumed certainty of expected returns in a mean–variance approach on the other. The authors propose a portfolio selection framework that allows an investor to position herself between these two extremes. Depending on the confidence in one’s expected return estimates, the optimal portfolio will be tilted more toward the risk parity portfolio or the mean–variance portfolio. The authors illustrate the framework for an investor in an asset allocation context.

PENETAPAN RASIO BAGI HASIL AKAD MUDHARABAH DAN MUSYARAKAH (STUDI KASUS DI BNI SYARIAH)

This study is a descriptive case study analysis in PT. Bank BNI Syariah using primary data and secondary data. This study rejects the results of research Mawardi (2005) and Vustany (2006) which states that the granting of a return to the Islamic banking results are influenced by interest rates. The interest rate is only a reference in determining the level of expected return for the customer to determine the ratio of the results. Calculation of profit sharing between users and customers BNI Syariah funds made by the actual return earned business profits, and distribution of the proceeds among the owners BNI Syariah customer funds carried with the actual return earned by the bank. Determination of the ratio between BNI Syariah results with user customer funds made by setting the level of expected return and the bank’s expected return rate of user client funds. Bank’s expected return level is calculated based customer’s of fund provider’s expected return estimation, the estimated overhead cost, estimation of risk level, and the expected net profit of the bank. While the level of expected return customers entrepreneur is the difference between the projected benefit the customer’s business and the expected return rate of the bank.Keywords: Profit Sharing Ratio, Mudaraba Agreement, Musharaka Agreement, Expected Return, Islamic Banking.

An Analysis of Theories on Stock Returns

Objective in writing this article is to provide an overview of the theories that has been developed for stock returns which is an important area of financial markets’ researches. Since the researches in this field are very active for the past quarter, it is not possible to describe all works that has been done in this area. Most important researches will be discussed without going deeper in mathematical tools and theories.Empirical works have been showing that stock returns are predictable cross-sectional and by time. The discussions about prediction of stock price behavior started with Markowitz with his article –Portfolio Selection-. Markowitz won Nobel Prize in 1990 for his research about portfolio theory. However he criticized by many economists since implementation of the theory requires lots of effort to evaluate data and since it uses historical data the prediction will not be accurate. In addition the assumption that stock returns are normally distributed is not true in reality. Sharpe, Lintner, and Mossin independently developed a model which has come to be known CAPM (capital asset pricing model) in 1964, 1965, and 1966 respectively. Beta coefficient is a key parameter in CAPM world. Beta measures risk of an asset in relation to the market such as S&P500 or an alternative factor. Actually the CAPM is a simple model which is based on sound reasoning and some of the assumptions -all investors have the same information, information is costless, and there are no taxes transactions costs- are unrealistic in market. APT (arbitrage pricing theory) presented for a better estimation for stock returns than CAPM. CAPM is a modified theory while APT is a completely different model. APT’s multiple factors provide a better indication of asset risk and a better estimate of expected return. There are n-factors effecting stock returns in APT but the number of factors are unknown. Furthermore CAPM and APT are single-period models. To get multi-period aspects of market ICAPM was developed. After that CCAPM (consumption-oriented capital asset pricing model) was introduced. It tried to explain behavior of stock returns by a logical extension of APT. A long literature exist on prediction of stock market returns but especially after the latest financial crisis these theories must be analyzed and suggested new ideas for forecasting behavior of stock returns. Keywords: Stock Returns, Markowitz, CAPM, APT, ICAPM, CCAPM, Fama-French 3-factor model.

The Beta Coefficient of an Unlisted Bank

Abstract The problem that we set ourselves in this work is related to the determination of capital return invested in an unlisted bank, particularly, in a credit cooperative bank. The model that we use is the Capital Asset Pricing Model (CAPM) equation, with its various difficulties in applying it to a category of unlisted activities. The biggest obstacle in using CAPM is given by the Beta determination representing the systematic risk of the units under examination. Therefore, to determine this risk coefficient, we assumed a first step in which we consider a similar sector sample, consists of a portfolio of listed banks, from which we obtain a Business Risk Index (BRI), that we use to go back to unlisted bank Beta under consideration. In a second case, it is thought of a target market constituted by the whole unlisted banks sample of the same sector under analysis, then relating the returns of individual observed banks with average returns provided by this market, we obtain the Regression Beta. A third step, provides the Business Risk Index determination of the sector, in this case obtained from the unlisted banks market, and then to reach to our banks Beta under observation. Comparing the results obtained from this analysis allows us to suggest a quite satisfying line for determining the Beta of an unlisted bank and consequently for its expected return estimation.

A look at the actual cost of capital of US firms

The capital asset pricing model (CAPM) receives both criticism and widespread adoption by practitioners and academics as the weighted average cost of capital (WACC) equity component. This study introduces two new costs of equity measures to address CAPM criticisms and provide new perspective on WACC estimates. The firm-based measure focuses on firm–investor cash flows while the market-based measure focuses solely on actual market returns. This study applies its firm and market-based WACC measures, along with the traditional CAPM-based WACC measure, to a broad sector-based cross section from 1972 to 2015. Results show that traditional CAPM-based WACC estimates consistently lie between the new firm and market-based WACC estimates. The central positioning of CAPM WACC supports its use as a conservative hurdle rate estimate for firms and a conservative expected return estimate for investors relative to actual returns.

The method of stock selection with the intention of portfolio formation

The purpose of this study is comparing the method of selecting and forming portfolios. The methods are Capital Assets Pricing Model, Fama and French Model and Excess return model. The methods are transacted in four steps: expected return estimation, stock valuation, selecting portfolios and estimating all kinds of portfolios’ returns and risk. In the point of forming portfolios, the decision variables were estimated to compare the methods. There are two questions: are the portfolio forming methods significant at Tehran Security Exchange? And, are there significant differences between methods with the view of generating Expected Rate of Return, Real Return, Risk, Differential Extents of market return and risk-free return? Multivariate Regression, One Way ANOVA and Correlations Tests are used to analyze and test models. The research finding shows that the models have the ability to perform significantly in Tehran Security Exchange. The models were significantly different in five important measures. They are risk, the future actual return, expected return in short and long terms. Finally, it was evidenced that not only there are significant differences between the three models, but also Excess return method was more efficient than the other models. Keywords: expected return, intrinsic value, book value, market value, firms’ size. JEL Classification: D46, G12, G14, G30, G32

The Cross Section of Long-Term Expected Returns

Effective capital budgeting decisions require reliable estimates of long-term expected returns. I extract a predictor for long-term returns from the book-to-market ratio by controlling for its variation associated with long-term expected profitability. The resulting predictor reliably describes the cross section of returns out-of-sample for at least five years, even when focusing exclusively on large-cap stocks and controlling for expected-return estimates generated by implied cost of capital models, factor models, and characteristic-based models. My results have important implications for improving our cost of equity estimates.

The Cross Section of Expected Stock Returns

This paper studies the cross-sectional properties of return forecasts derived from Fama-MacBeth regressions. These forecasts mimic how an investor could, in real time, combine many firm characteristics to obtain a composite estimate of a stock’s expected return. Empirically, the forecasts vary substantially across stocks and have strong predictive power for actual returns. For example, using ten-year rolling estimates of Fama- MacBeth slopes and a cross-sectional model with 15 firm characteristics (all based on low-frequency data), the expected-return estimates have a cross-sectional standard deviation of 0.87% monthly and a predictive slope for future monthly returns of 0.74, with a standard error of 0.07.

Alternative Investments in Defined-Contribution Retirement Plans: Opportunities and Concerns

Alternative assets—those other than stocks, bonds, and cash—are starting to play a role in defined-contribution (DC) retirement plans and particularly in target-date funds, which are marketed to most retirees as complete investment solutions. The authors ask whether this is a good idea and outline the conditions under which alternatives can sensibly be used as a component of DC plans. They conclude first that risk estimates for alternative assets need to be adjusted upward and expected return estimates downward. Second, the liquidity needs of the fund and of the plan participants should be carefully considered when investing some of the participants’ money in alternatives. Third, the total invested in alternatives on behalf of plan participants should not be large.

Should a Skeptical Portfolio Insurer Use an Optimal or a Risk-Based Multiplier?

Following recent evidence of out-of-sample stock market return predictability, the authors aim to evaluate whether the potential benefits suggested by asset allocation theory can actually be captured in the real world using expected return estimates from a predictive system. The question is addressed in the context of an investor maximizing the long-term growth rate of wealth under a maximum drawdown constraint, and compare the optimal strategy using the predictive system with a similar risk-based allocation strategy independent of expected return estimates. The authors find that the risk-based strategy implies nonetheless very variable and relatively high expected returns, and report important potential benefits in using the expected return estimates of the predictive system they used.

Book-to-Market and the Cross-Section ofExpected Returns in International Stock Markets

Individual stocks’ expected return estimates are a key input for equity selection models. A 2008 study by Eugene Fama and Kenneth French found evidence that past changes in book equity and price contain independent information about expected cash flows that can be used to improve estimates of expected returns. This study focuses on international stock markets and re-examines whether the origins of the book-to-market ratio (BM), in terms of past changes in book equity and price, enhance the estimates of expected returns provided by BM alone. Examining all stocks, as well as subcategories of microcap, small, large, and all-butmicrocap stocks trading in the United Kingdom, Germany, France, Italy, Canada, and Japan, the authors find that recent changes in book equity and price are more relevant than more distant changes in enhancing estimates of expected future cash flows and expected future returns. Their tests also show that changes in book equity say much more about expected stock returns than price changes do. <b>TOPICS:</b>Global, exchanges/markets/clearinghouses, statistical methods