Return attribution analysis of the UK insurance portfolios

We examine the attribution of premium growth rates for the five main insurance sectors of the United Kingdom for the period 1969–2005; in particular, Property, Motor, Pecuniary, Health and Accident, and Liability. In each sector, the growth rates of aggregate insurance premiums are viewed as portfolio returns which we attribute to a number of factors such as realized and expected losses and expenses, their uncertainty and market power, using the Sharpe (Determining the Fund’s Effective Asset Mix. Investment Management Review, November–December, pp. 59–69, 1988; J. Portfolio Manag. 18:7–19, 1992) Style Analysis. Our estimation method differs from the standard least squares practice which does not provide confidence intervals for style betas and adopts a Bayesian approach, resulting in a robust estimate of the entire empirical distribution of each beta coefficients for the full sample. We also perform a rolling analysis of robust estimation for a window of seven overlapping samples. Our empirical findings show that there are some main differences across industries as far as the weights attributed to the underlying factors. Rolling regressions assist us to identify the variability of these weights over time, but also across industries.     

Estimating Systematic Risk with Daily Security Returns: A Note on the Relative Efficiency of Selected Estimators

This paper utilizes asymptotic analysis and daily security returns to examine the estimation efficiency of two unbiased robust estimators compared with ordinary least squares. Our results demonstrate a relative efficiency gain for a nonparametric rank estimator and a relative efficiency loss for the minimum absolute deviation estimator when estimating the systematic risk of securities using daily security returns.     

Do Assumptions About Factor Structure Matter in Empirical Tests of the APT?

The effect of assumptions about factor structure on empirical tests of multifactor models such as the Arbitrage Pricing Policy Theory has received little attention in the literature. Using data on securities traded on the London Stock Exchange, we examine whether returns are best described by an approximate factor structure and whether assumptions about correlations across idiosyncratic returns have a significant impact on estimated prices of risk and their significance. Our findings suggest that returns are best described by an approximate factor structure and, if this is taken into account when empirically testing the APT, six factors carry significant prices of risk. However, if a strict factor structure is imposed, no factors carry significant prices of risk. These findings suggest that assumptions about factor structure matter in empirically testing the APT.     

The Estimation of Systematic Risk under Differentiated Risk Aversion: A Mean-Extended Gini Approach

This paper examines a mean-Gini model of systematic risk estimation that resolves some econometric problems with mean-variance beta estimation and allows for heterogeneous risk aversion across investors. Using the mean-extended Gini (MEG) model, we estimate systematic risks for different degrees of risk aversion. MEG betas are shown to be instrumental variable estimators that provide econometric solutions to biases generated by the estimation of mean-variance (MV) betas. When security returns are not normally distributed, MEG betas are proved to differ from MV betas. We design an econometric test that assesses whether these differences are significant. As an application using daily returns, we estimate MEG and MV betas for U.S. securities.     

Corporate Events,Trading Activity,and the Estimation of Systematic Risk: Evidence From Equity Offerings and Share Repurchases

We investigate the relation between trading activity, the measurement of security returns, and the evolution of security prices by examining estimates of systematic risk surrounding equity offerings and share repurchases. In contrast to prior studies, we find no evidence of changes in systematic risk following either equity offerings or share repurchases after correcting for biases caused by infrequent trading and price adjustment delays. Moreover, changes in ordinary least squares beta estimates are significantly related to contemporaneous changes in trading activity. Our results have implications for studies interested in the properties of security returns, particularly those examining periods in which trading activity changes.     

On Testing the Arbitrage Pricing Theory: Inter-Battery Factor Analysis

This paper tests the Arbitrage Pricing Theory (APT) by estimating the factor loadings that are consistent between two industry groups of securities. One of the pitfalls in the study by Roll and Ross is that the factors estimated in one group may not be the same with the factors estimated in another group. This raises some concerns on the acceptability of their conclusions. For our study, we employ inter-battery factor analysis which enables us to estimate factor loadings by constraining the factors to be the same between two different groups. Our results show that there seem to be five or six inter-group common factors that generate daily returns for two industry groups of securities, and these inter-group common factors do not seem to depend on the size of groups. Also, based on our cross-sectional tests on the risk premia, we conclude that the APT should not be rejected.     

Análise da implementação de uma estratégia de investimento em ações baseada em um instrumento de apoio à decisão

The present study analyzes the interface between two disciplinary fields - finance and operational research. In this sense, it integrates two approaches to investment analysis - fundamental and technical, as well as an investor’s concern at the time of resources allocation in a Buy & Hold investment strategy. The study uses the Multicriteria Decision Aid (MCDA) as an instrument of intervention. As for results, it was evident that the instrument of intervention used, together with a pre-defined investment strategy, was able to support the decision maker at the time of allocation of resources, generating an accumulated return of 25.14 % in the period, compared with a negative return -13.41% of the Bovespa index in the same period. In order to check the robustness of results, regressions were performed with both the CAPM model as daily and weekly data, and the t test performed on the coefficients of the regression was significant at 1% for the abnormal return of weekly data and 0.1% for the return of abnormal daily data; in addition, the t-statistic was positive in both cases, indicating the presence of abnormal positive feedback, i.e., the portfolio proposed here outperformed its benchmark.     

The Robustness of the APT to Alternative Estimators

We test the robustness of the APT to two alternative estimation procedures: the Fama and MacBeth (1973) two-step methodology; and the one-step procedure due to Burmeister and McElroy (1988). We find that the APT is indeed sensitive to the chosen estimator and assumptions about the factor structure of stock returns. We believe that our findings have implications for the estimation of asset pricing models in general.     

Aggregate Earnings and Asset Prices

A principal-components analysis demonstrates that common earnings factors explain a substantial portion of firm-level earnings variation, implying earnings shocks have substantial systematic components and are not almost fully diversifiable as prior literature has concluded. Furthermore, the principal components of earnings and returns are highly correlated, implying aggregate earnings risks and return risks are related. In contrast to previous studies, the correlation we report between the systematic components of earnings and returns is stable over time. We also show that the earnings factors are priced, in the sense that the sensitivities of securities' returns to the earnings factors explain a significant portion of the cross-sectional variation in returns, even controlling for return risk. This suggests earnings performance is an underlying source of priced risk. Our evidence that the information sets of returns and earnings are jointly determined implies cash flow risk and return risk are not fully separable, and raises the possibility that it is the common variation of earnings and returns that is priced.     

Dynamic Currency Linkages and Their Determinants: An Empirical Study for East Asian Economic Community Region

In this article, Copula GARCH models have been employed to study the inter-temporal process of currency market co-movements between ASEAN+6 countries (referred to in this study as East Asian Economic Community) and ASEAN+6 currency market index. Empirical results show that the sample countries of the region exhibit varying levels of currency co-movements with the Asian benchmark. Markov regime switching results show that many of the countries which had high dependences with the regional currency index as was found in copula estimations had also overlapping currency market cycles. Using Principal Component Analysis, we find that three statistical factors explain exchange rate co-movements which came out to be trade linkages, economic risk, and currency market openness in our dynamic panel data estimation.     

How does the stock market react to the announcement of green policies?

We investigate the impact of 19 announcements of environmental regulation on the equities listed on the Australian Stock Exchange over the period 2005–2011. Using a well-established event study methodology, we assess whether these announcements are value constructive or destructive for equity investors. Additionally, we estimate the change in systematic risk following the announcements. Our results show that the Australian market was particularly sensitive to the carbon pollution reduction scheme (CPRS) announcement. A cumulative abnormal return of −31% was recorded in the alternative energy sector after Australia submitted its target range to the Copenhagen Accord. We observe that a move towards a greener nation has a mixed effect on abnormal returns with apparent sector-by-sector differences. Green policies appear to affect the long-term systematic risk of industries, leading to the diamond risk phenomenon.     

Unconstrained estimates of the equity risk premium

Estimates of the equity risk premium implied by analyst forecasts—generally 2–4 %—are often significantly below realized equity returns of 6 %. Measurement error could result from conservative assumptions, reliance upon consensus rather than detailed forecasts, the use of market rather than target prices, and regression analysis, which can be influenced by a small number of observations. We address these potential sources of measurement error. Our estimates are consistent with subsequently realized returns and capture systematic risk exposure. Alternative techniques could capture another form of priced risk or identify firm characteristics associated with systematic mispricing. From 1999 to 2008, we estimate an average equity risk premium in the United States of 5.3 %. The estimate increases from 3.1 % for 1999–2000 to 5.9 % from 2001 to 2008, comparable to the historical average of realized equity returns.     

Arbitrage Pricing Theory and Utility Stock Returns

This paper presents some new evidence that Arbitrage Pricing Theory may lead to different and better estimates of expected return than the Capital Asset Pricing Model, particularly in the case of utility stock returns. Results for monthly portfolio returns for 1971–1979 lead to the conclusion that regulators should not adopt the single-factor risk approach of the CAPM as the principal measure of risk, but give greater weight to APT, whose multiple factors provide a better indication of asset risk and a better estimate of expected return.     

How common are common return factors across the NYSE and Nasdaq?

We entertain the possibility of pervasive factors that are not common across two (or more) groups of securities. We propose and implement a general procedure to estimate the space spanned by common and group-specific pervasive factors. In our empirical analysis, we study the factor structure of excess returns on stocks traded on the NYSE and Nasdaq using our methodology. We find that there are only two common pervasive factors that govern the returns for both NYSE and Nasdaq. At the same time, the NYSE and Nasdaq each have one more group-specific factor that is not the same across the two exchanges. Our results point to the absence of complete similarity between the factors driving the returns on these exchanges.     

The volatility effect of futures trading: Evidence from LSE traded stocks listed as individual equity futures contracts on LIFFE

This study investigates the impact of LIFFE's introduction of individual equity futures contracts on the risk characteristics of the underlying stocks trading on the LSE. We employ the Fama and French three-factor model (TFM) to measure the change in the systematic risk of the underlying stocks which arises subsequent to the introduction of futures contracts. A GJR-GARCH(1,1) specification is used to test whether the futures contract listing affects the permanent and/or the transitory component of the residual variance of returns, and a control sample methodology isolates changes in the risk components that may be caused by factors other than futures contract innovation. The observed increase (decrease) in the impact of current (old) news on the residual variance implies that futures contract listing enhances stock market efficiency. There is no evidence that futures innovation impacts on either the systematic risk or the permanent component of the residual variance of returns.     

Stock Return Anomalies and the Tests of the APT

This paper shows that the empirical tests of the Arbitrage Pricing Theory (APT) model are very sensitive to the anomalies observed in January in the stock returns data. There is a strong seasonal pattern in the estimates of the risk premia from the APT model. The most important implication of the findings in this paper is that the APT model can explain the risk-return relation mostly for January. Once the January returns are excluded from the data, there is no significant relation between the expected stock returns and the risk measures predicted by the APT model.     

Arbitrage Asset Pricing under Exchange Risk

This paper extends the APT to an international setting. Specifying a linear factor return-generating model in local currency terms, we show that the usual risk-diversification rule in the APT does not yield a riskless portfolio unless currency fluctuations obey the same factor model as asset returns. We then consider an arbitrage portfolio whose exchange risk is hedged by foreign riskless bonds. Under the resulting no-arbitrage conditions, the expected returns are not on the same hyperplane, unlike the closed-economy APT, unless they are adjusted by the cost of exchange risk hedging.     

Do we need higher-order comoments to enhance mean-variance portfolios? Evidence from a simplified jump process

We consider a joint distribution that decomposes asset returns into two independent components: an elliptical innovation (Gaussian) and a systematic non-elliptical latent process. The paper provides a tractable approach to estimate the underlying parameters and, hence, the assets’ exposures to the latent non-elliptical factor. Additionally, the framework incorporates higher-order moments, such as skewness and kurtosis, for portfolio selection. Taking into account estimation risk, we investigate the economic contribution of the non-elliptical term. Overall, we find weak empirical evidence to support the inclusion of the non-elliptical term and, hence, the higher-order comoments. Nonetheless, our findings support the mean–variance (MV) decision rule that incorporates the elliptical term alone. Excluding the non-elliptical term results in more robust mean–variance estimates and, thus, enhanced out-of-sample performance. This evidence is significant among stocks that exhibit a strong deviation from the Gaussian property. Moreover, it is most pronounced during market turmoils, when exposures to the latent factor are highest.     

A Semiautoregression Approach to the Arbitrage Pricing Theory

This paper developes a semiautoregression (SAR) approach to estimate factors of the arbitrage pricing theory (APT) that has the advantage of providing a simple asymptotic variance-covariance matrix for the factor estimates, which makes it easy to adjust for measurement errors. Using the extracted factors, I confirm the finding that the APT describes asset returns slightly better than the CAPM, although there is still some mispricing in the APT model. I find that not only are the factors “priced” by the market, but the factor premiums move over time in relation to business cycle variables.     

No Arbitrage and Arbitrage Pricing: A New Approach

We argue that arbitrage-pricing theories (APT) imply the existence of a low-dimensional nonnegative nonlinear pricing kernel. In contrast to standard constructs of the APT, we do not assume a linear factor structure on the payoffs. This allows us to price both primitive and derivative securities. Semi-nonparametric techniques are used to estimate the pricing kernel and test the theory. Empirical results using size-based portfolio returns and yields on bonds reject the nested capital asset-pricing model and linear APT and support the nonlinear APT. Diagnostics show that the nonlinear model is more capable of explaining variations in small firm returns.