Security Returns Research Articles

Empirical scaling laws and the aggregation of non-stationary data

Widely cited evidence for scaling (self-similarity) of the returns of stocks and other securities is inconsistent with virtually all currently-used models for price movements. In particular, state-of-the-art models provide for ubiquitous, irregular, and oftentimes high-frequency fluctuations in volatility (“stochastic volatility”), both intraday and across the days, weeks, and years over which data is aggregated in demonstrations of self-similarity of returns. Stochastic volatility renders these models, which are based on variants and generalizations of random walks, incompatible with self-similarity. We show here that empirical evidence for self-similarity does not actually contradict the analytic lack of self-similarity in these models. The resolution of the mismatch between models and data can be traced to a statistical consequence of aggregating large amounts of non-stationary data.

MEAN-SEMIVARIANCE MODELS FOR PORTFOLIO OPTIMIZATION PROBLEM WITH MIXED UNCERTAINTY OF FUZZINESS AND RANDOMNESS

In practice, security returns cannot be accurately predicted due to lack of historical data. Therefore, statistical methods and experts' experience are always integrated to estimate future security returns, which are hereinafter regarded as random fuzzy variables. Random fuzzy variable is a powerful tool to deal with the portfolio optimization problem including stochastic parameters with ambiguous expected returns. In this paper, we first define the semivariance of random fuzzy variable and prove its several properties. By considering the semivariance as a risk measure, we establish the mean-semivariance models for portfolio optimization problem with random fuzzy returns. We design a hybrid algorithm with random fuzzy simulation to solve the proposed models in general cases. Finally, we present a numerical example and compare the results to illustrate the mean-semivariance model and the effectiveness of the algorithm.

Integrated alpha modelling

Alpha modelling typically refers to the selection and weighting of various information sources, which when combined are used by active portfolio managers to forecast security returns. It is traditionally seen as an exogenous input in the construction of the investment portfolio. Instead, a growing number of authors have recently argued that alpha modelling should be integrated within the portfolio-construction process, to account for the active manager’s objective, constraints and transaction costs. Building in particular upon the frameworks of Sneddon (2008) and Qian et al (2007), we present a parsimonious and analytically tractable alpha modelling approach that aims at maximising the typical objective function of an active manager. Our modelling scheme combines several salient features of previous methodologies and explicitly identifies three critical components necessary in achieving the manager’s portfolio objectives: (i) the predictability of alpha factors as captured by their information decay; (ii) the contribution of alpha factors to portfolio risk; and (iii) the autocorrelations of alpha factors in their contribution to portfolio turnover. Our methodology is able to provide various prescriptions relevant to the portfolio manager. For instance, as transaction costs increase, allocating more weight to signals with lower information decay is shown to improve portfolio value added. Factors with higher return-to-risk ratios are also given a higher prominence as they help allocate strategy risk more efficiently.

Relevância da informação contábil para o mercado de capitais: evidências no mercado brasileiro

According to Fama (1970) the Capital Markets are fundamental for the economic development of a country because they allocate the resources that are available for investment, a feature that when developed, provides important signals for the formation of stock prices, which should reflect the existing information in the economic system at any time. According to Hendriksen and Van Breda (1999, p.117), the financial statements present the financial, patrimonial and economic situations of the organizations to the external user. Considering the importance of the information for the development of the Capital Market and also, the relevance of financial statements, this paper proposes a study about the efficiency of the Brazilian Market and the impact of the disclosure of financial statements in the price of the stocks. The Study of Events technique was used, being regarded as event, the date of the disclosure of the quarterly and annual financial statements for the period of 2007/2009 of 42 papers of companies listed in the Bovespa Index (Ibovespa) consecutively in the analyzed period. The results reinforced the efficiency hypotheses in its semi-strong form, because the financial statement, for the most part, did not significantly affect the bond prices, except in the period of 2009, when a significant effect was observed, in the cumulative returns of securities after the publication.

On interval portfolio selection problem

The future returns of each securities cannot be correctly reflected by the data in the past, therefore the expert's judgements and experiences should be considered to estimate the security returns for the future. In this paper, we propose an interval portfolio selection model in which both the returns and the risks of assets are defined as intervals. By using interval and convex analysis, we solve this model and get the noninferior solution. Finally, an example is given to illustrate our results. The interval portfolio selection model improves and generalizes the Markowitz's mean-variance model and the results of Deng et al. (Eur J Oper Res 166(1):278---292, 2005).

Predicting Returns: Runs Test for Financial Time Series

Market efficiency theory posits that stock returns are not predictable. One of the common test of this hypothesis is the runs test. It is a test of random walk similar to the Stata's already existing runtest. However, runs_test is specific to daily returns of financial securities (i.e. stocks). runs_test provides the likelihood of a run for all possible lengths of runs. Likelihood is statistically tested against a distribution created with a Monte Carlo experiment. Likelihood of continued run is also provided. runs_test can be used to test whether a trading strategy that is based on runs can be profitable following an included example.

The impact of the Law on Strengthening the Security of Financial Relations on the value relevance of accounting information in Tunisian Stock Exchange

This paper empirically investigates the value relevance of accounting earnings measures in the emerging capital market of Tunisia. The issue is tested by estimating the regression of annual security returns on different earnings measures extracted from income statements. In Tunisia, firms prepare their financial statements in accordance with Tunisian Accounting Standards (TAS) which are inspired from International Financial Reporting Standards (IFRS). Based on a sample of 389 firm years for firms listed on the Tunis Stock Exchange (TSE) during the period 1997-2008 and using pooled regressions, we find that accounting earnings measures are weakly related to security returns. However, we find that earnings before taxes has the higher explanatory power for stock returns. This is perhaps due to the fact that financial statements are often influenced by taxation rules (ROSC, 2006; section 42). Further, we find that cash flow from operations and Total accruals are not value relevant for valuation. We tested whether the value relevance of each measure of performance improved after the adoption in October 2005 of the Law on Strengthening the Security of Financial Relations (LSSFR). Consistent with prior US and other international findings, results show that the explanatory power and the magnitude of the slope coefficient of each measure increased when we take into account for the impact of this enactment. However, the increase is not statistically significant. This is perhaps due to the employed specification of the relation between security returns and accounting information.

Applying an alternative test of herding behavior: A case study of the Indian stock market

The paper presents an alternative approach to test herding behavior in the Indian equity market. In contrast to the conventional test methodologies, based on return dispersions among a group of securities, this paper uses symmetric properties of the cross-sectional return distribution to identify herding. Using this alternative approach, we find evidence of herding in the Indian equity market during the sample period which tends to be more pronounced during the 2007 crash. The paper also finds that the rate of increase in security return dispersion is relatively lower in the up market compared to down market days. This finding is contrary to the directional asymmetry documented by McQueen et al. (1996).

Country-Specific Attention and Security Returns

Country-Specific Attention and Security Returns

Parameters that Provide Higher Explanation Estimating Betas in the Portuguese Stock Market¹

During decades, tests have been developed to verify whether the beta is the best tool to explain the returns of securities on the stock market. Moreover, the value of the beta and its coefficient of determination (R-squared) vary with different parameters used for estimating the beta. In this paper, we investigate for the parameters that provide a higher explanation when we estimate the beta on the Portuguese stock market. We use all nine economic groups listed on the Euronext Lisbon and, for each of those groups, determine which company has the highest market capitalization and highest turnover at the same time, measured in millions of Euros and thousands of Euros, respectively. The linear regression and correlation coefficient between each of the companies can be calculated by studying two national indexes (PSI20 and PSI General) to determine if they get better results with respect to a given period, frequency data or index.We conclude that the explanatory power of R-squared in the Portuguese stock market is very low, independent of the parameters used. When analyzing the year 2008 using linear regression, it remains unclear whether it is preferable to use daily returns or weekly returns, since half of the surveyed companies report the highest yield using either method. The explanatory power of R-squared is higher when using extended time periods and monthly returns, and the results become more accurate when doing the regressions with the PSI20 Index.

Investor Overconfidence and Stock Returns: Evidence from Pakistan

The study investigates investor overconfidence in Pakistan stock market. By taking daily stock prices of 27 leading companies representing all sectors of Karachi stock exchange we found that return of the securities have impact on securities' trading volumes. While trading volumes failed to impact returns in short term horizon. Further returns volatility had impact on the returns but failed to impact trading volume. This indicates that despite return volatility, overconfident Pakistani investor continue to trade in the security. Impulse response analysis exhibits that trading are impacted by one standard deviation of security return but they still remain positive and mostly stay above zero. The study was conducted in vector auto regressive environment.

Universal Access to Health Services Through the Digital Terrestrial Television

The Western World has almost completed the transition toward the Digital Television (DTV), and in particular toward the Digital Terrestrial Television (DTT). In every home there is at least one decoder for the DTT. Some of them have a modem, to connect to a telephonic return line, and a Smart Card reader, both required by the “Pay TV” channels. Since those readers are compatible with the Governmental Smart Cards, a new access for the masses to secure and confidential digital services is nowadays available in our Information Society. “T-Government” defines the set of services provided by Governments or private entities via DTT. “Multimedia Home Platform” is the standard for DTT applications. A Local Health will be no more justified for offering services only through the Web disregarding both the broadcast and the return channels of the DTT since by doing so it would contribute to deepen the “digital divide” between skilled (young) people and unskilled (elder) people. The author defines a scenario for providing such T-Health Services both for patients (T-monitoring health parameters) and healthy citizens. These latter will have a bunch of services over DTT, not only informative or interactive applications on the Set top Box, but also transactional services through the secure return channel. However, much effort has to be spent to guarantee the usability of that new interface which is quite different from that of a Web application. The author designed, tested and redesigned a suite of DTT applications as a “proof of concept” to show the potential of this new platform for health information services. DTT may represent a real contribution to bring social healthcare and wellness.

What to expect when you’re electing

Purpose– The purpose of this paper is to analyze security-market returns relative to the political party of the president, the Federal Reserve’s monetary policy, the year of the president’s term, and the state of political gridlock. Contrary to prior studies, which evaluated the influences separately, the authors jointly evaluate these variables.Design/methodology/approach– The analysis supports the notion that security returns are significantly related to shifts in Fed monetary policy, political gridlock, and the year of the presidential term; however, returns are generally invariant to the president’s political party affiliation. Overall, the findings suggest that investors should focus less attention on the party of the president and instead more closely monitor Fed actions.Findings– It appears that political harmony should be welcomed by equity investors, but not debt investors. Finally, regardless of the political outcome, if the past serves as a guide, investors may have to wait until year three of the next presidential term to enjoy the fruits of the current political season.Originality/value– The academic literature is rich with studies that consider the aforementioned political effects and the influence that monetary policy have on the markets. To date, however, these factors have not been jointly considered when examining returns. This paper considers several dimensions of the political landscape – the party of the president, the presence or absence of political gridlock, and the presidential term cycle effect – in conjunction with Fed monetary policy in examining long-term security returns. By examining the relationship between security returns and both political and monetary conditions, the authors provide robust evidence regarding the relationships.

Risk index based models for portfolio adjusting problem with returns subject to experts' evaluations

This paper discusses a portfolio adjusting problem with additional risk assets and a riskless asset in the situation where security returns are given by experts' evaluations rather than historical data. Uncertain variables are employed to describe the security returns. Using expected value and risk index as measurements of portfolio return and risk respectively, we propose two portfolio optimization models for an existing portfolio in two cases, taking minimum transaction lot, transaction cost, and lower and upper bound constraints into account. In one case the riskless asset can be both borrowed and lent freely, and in another case the riskless asset can only be lent and the borrowing of riskless asset is not allowed. The adjusting models are converted into their crisp equivalents, enabling the users to solve them with currently available programming solvers. For the sake of illustration, numerical examples in two cases are also provided. The results show that under the same predetermined maximum tolerable risk level the expected return of the optimal portfolio is smaller when the riskless asset can only be lent than when the riskless asset can be both borrowed and lent freely.

What to Expect When You're Electing

This paper analyzes security-market returns relative to the political party of the president, the Federal Reserve’s monetary policy, the year of the president’s term, and the state of political gridlock. Contrary to prior studies, which evaluated the influences separately, we jointly evaluate these variables. Our analysis supports the notion that security returns are significantly related to shifts in Fed monetary policy, political gridlock and the year of the presidential term; however, returns are generally invariant to the president’s political party affiliation. Overall, our findings suggest that investors should focus less attention on the party of the president and instead more closely monitor Fed actions. Furthermore, it appears that political harmony should be welcomed by equity investors, but not debt investors. Finally, regardless of the political outcome, if the past serves as a guide, investors may have to wait until year three of the next presidential term to enjoy the fruits of the current political season.

Wealth effects of convertible-bond and warrant-bond offerings: a meta-analysis

The literature on wealth effects associated with the announcements of convertible-bond and warrant-bond offerings is reviewed. The findings of 35 event studies, which include 84 sub-samples and 6310 announcements, are analysed using meta-analysis. We find a mean cumulative abnormal return of−1.14% for convertibles compared with−0.02% for warrant bonds, the significant difference confirming a relative advantage for warrant bonds. Abnormal returns for hybrid securities issued in the USA are significantly more negative than those issued in other countries. In addition, issuing hybrid securities to refund debt does not seem to be favoured by investors. Finally, several factors identified as important by theory or in prior research are not significant within our cross-study models, suggesting that more evidence is needed to confirm whether they are robust.

A risk index model for multi-period uncertain portfolio selection

This paper discusses a multi-period portfolio selection problem when security returns are given by experts’ evaluations. The security return rates are regarded as uncertain variables and an uncertain risk index adjustment model is proposed. Optimal portfolio adjustments are determined with the objective of maximizing the total incremental wealth within the constraints of controlling the cumulative risk index value over the investment horizon and satisfying self-financing at each period. To enable the users to solve the model problem with currently available programming tools, an equivalent of the model is provided. In addition, a method of obtaining the uncertainty distributions of the security returns is given based on experts’ evaluations, and a selection example is presented.

A Krylov subspace approach to large portfolio optimization

With a large number of securities (N) and fewer observations (T), deriving the global minimum variance portfolio requires the inversion of the singular sample covariance matrix of security returns. We introduce the Break-Down Free Generalized Minimum RESidual (BFGMRES), a Krylov subspaces method, as a fully automated approach for deriving the minimum variance portfolio. BFGMRES is a numerical algorithm that provides solutions to singular linear systems without requiring ex-ante assumptions on the covariance structure. Moreover, it is robust to illiquidity and potentially faulty data. US and international stock data are used to demonstrate the relative robustness of BFGMRES to illiquidity when compared to the “shrinkage to market” methodology developed by Ledoit and Wolf (2003). The two methods have similar performance as assessed by the Sharpe ratios and standard deviations for filtered data. In a simulation study, we show that BFGMRES is more robust than shrinkage to market in the presence of data irregularities. Indeed, when there is an illiquid stock shrinkage to market allocates almost 100% of the portfolio weights to this stock, whereas BFGMRES does not. In further simulations, we also show that when there is no illiquidity, BFGMRES exhibits superior performance than shrinkage to market when the number of stocks is high and the sample covariance matrix is highly singular.

A two‐pass model study of the CAPM: evidence from the UK stock market

PurposeThere has been considerable debate on the linear relationship between systematic risk and return. The purpose of this study is to investigate whether security return can be explained by systematic risk.Design/methodology/approachThis study employs the market model to test the effect of excess return on portfolio returns. The paper divides total risk into systematic and idiosyncratic risk to examine whether the degree of inefficient portfolio diversification impairs the applicability of the capital asset pricing model (CAPM). In the two‐pass cross‐sectional regressions, the paper assesses whether excess return on a security is directly proportional to the security's beta. The paper also incorporates the total variance of securities and the squared value of beta to capture idiosyncratic risk and the nonlinear risk‐return relationship.FindingsThe CAPM is rejected due to positive intercepts in most portfolios and there are large proportions of idiosyncratic risk in these portfolios. Two‐pass regressions show that the security market line theory is valid when additional variables are included in the equation. However, survivorship bias appears to be present in the selected sample.Practical implicationsSince large excess returns are present in the models, the traditional CAPM is rejected and incomplete portfolio diversification can be explained by high levels of idiosyncratic risk.Originality/valueThe authors find that inefficient portfolio diversification is due to the level of idiosyncratic risk in a portfolio. Evidence of the nonlinear beta‐return relationship suggests that the traditional CAPM is misspecified.

Integrated Alpha Modeling

Alpha modelling typically refers to the selection and weighting of various information sources, which when combined are used by active portfolio managers to forecast security returns. It is traditionally seen as an exogenous input in the construction of the investment portfolio. Instead, a growing number of authors have recently argued that alpha modelling should be integrated within the portfolio-construction process, to account for the active manager’s objective, constraints and transaction costs. Building in particular upon the frameworks of Sneddon (2008) and Qian et al (2007), we present a parsimonious and analytically tractable alpha modelling approach that aims at maximising the typical objective function of an active manager. Our modelling scheme combines several salient features of previous methodologies and explicitly identifies three critical components necessary in achieving the manager’s portfolio objectives: (i) the predictability of alpha factors as captured by their information decay; (ii) the contribution of alpha factors to portfolio risk; and (iii) the autocorrelations of alpha factors in their contribution to portfolio turnover. Our methodology is able to provide various prescriptions relevant to the portfolio manager. For instance, as transaction costs increase, allocating more weight to signals with lower information decay is shown to improve portfolio value added. Factors with higher return-to-risk ratios are also given a higher prominence as they help allocate strategy risk more efficiently.