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Portfolio Returns (portfolio + return)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	100%

Selected Abstracts

Attribution of investment performance: an analysis of Australian pooled superannuation funds*

ACCOUNTING & FINANCE, Issue 1-2 2001
David R. Gallagher
This paper evaluates the market timing and security selection capabilities of Australian pooled superannuation funds over the eight-year period from January 1991 to December 1998. Evaluation of both components of investment performance is surprisingly scarce in the Australian literature despite active investment managers engaging in both market timing and security selection. The paper also evaluates performance for the three largest asset classes within diversified superannuation funds and their contribution to overall portfolio return. The importance of an accurately specified market portfolio proxy in the measurement of investment performance is demonstrated. This paper employs performance benchmarks that account for the multi-sector investment decisions of active investment managers in a manner that is consistent with their unique investment strategy. Consistent with U.S. literature, the empirical results indicate that Australian pooled superannuation funds do not exhibit significantly positive security selection or market timing skill. [source]

Mean Reversion in the Short Horizon Returns of UK Portfolios

JOURNAL OF BUSINESS FINANCE & ACCOUNTING, Issue 1-2 2001
Patricia Chelley-Steeley
This paper will show that short horizon stock returns for UK portfolios are more predictable than suggested by sample autocorrelation co-efficients. Four capitalisation based portfolios are constructed for the period 1976,1991. It is shown that the first order autocorrelation coefficient of monthly returns can explain no more than 10% of the variation in monthly portfolio returns. Monthly autocorrelation coefficients assume that each weekly return of the previous month contains the same amount of information. However, this will not be the case if short horizon returns contain predictable components which dissipate rapidly. In this case, the return of the most recent week would say a lot more about the future monthly portfolio return than other weeks. This suggests that when predicting future monthly portfolio returns more weight should be given to the most recent weeks of the previous month, because, the most recent weekly returns provide the most information about the subsequent months' performance. We construct a model which exploits the mean reverting characteristics of monthly portfolio returns. Using this model we forecast future monthly portfolio returns. When compared to forecasts that utilise the autocorrelation statistic the model which exploits the mean reverting characteristics of monthlyportfolio returns can forecast future returns better than the autocorrelation statistic, both in and out of sample. [source]

An Intertemporal Capital Asset Pricing Model with Owner-Occupied Housing

REAL ESTATE ECONOMICS, Issue 3 2010
Yongqiang Chu
This article studies portfolio choice and asset pricing in the presence of owner-occupied housing in a continuous time framework. The unique feature of the model is that housing is a consumption good as well as a risky asset. Under general conditions, that is, when the utility function is not Cobb,Douglas and the covariance matrix is not block-diagonal, the model shows that the market portfolio is not mean-variance efficient, and the traditional capital asset pricing model fails. Nonetheless, a conditional linear factor pricing model holds with housing return and market portfolio return as two risk factors. The model also predicts that the nondurable consumption-to-housing ratio (ch) can forecast financial asset returns. The two factor pricing model conditioning on,ch,yields a good cross-sectional fit for Fama,French 25 portfolios. [source]

Estimating Systematic Risk Using Time Varying Distributions

EUROPEAN FINANCIAL MANAGEMENT, Issue 1 2002
Gregory Koutmos
This article proposes a dynamic vector GARCH model for the estimation of time-varying betas. The model allows the conditional variances and the conditional covariance between individual portfolio returns and market portfolio returns to respond asymmetrically to past innovations depending on their sign. Covariances tend to be higher during market declines. There is substantial time variation in betas but the evidence on beta asymmetry is mixed. Specifically, in 50% of the cases betas are higher during market declines and for the remaining 50% the opposite is true. A time series analysis of estimated time varying betas reveals that they follow stationary mean-reverting processes. The average degree of persistence is approximately four days. It is also found that the static market model overstates non-market or, unsystematic risk by more than 10%. On the basis of an array of diagnostics it is confirmed that the vector GARCH model provides a richer framework for the analysis of the dynamics of systematic risk. [source]

Mean Reversion in the Short Horizon Returns of UK Portfolios

Does Idiosyncratic Risk Really Matter?

THE JOURNAL OF FINANCE, Issue 2 2005
TURAN G. BALI
ABSTRACT Goyal and Santa-Clara (2003) find a significantly positive relation between the equal-weighted average stock volatility and the value-weighted portfolio returns on the NYSE/AMEX/Nasdaq stocks for the period of 1963:08 to 1999:12. We show that this result is driven by small stocks traded on the Nasdaq, and is in part due to a liquidity premium. In addition, their result does not hold for the extended sample of 1963:08 to 2001:12 and for the NYSE/AMEX and NYSE stocks. More importantly, we find no evidence of a significant link between the value-weighted portfolio returns and the median and value-weighted average stock volatility. [source]

INTANGIBLE ASSETS, BOOK-TO-MARKET, AND COMMON STOCK RETURNS

THE JOURNAL OF FINANCIAL RESEARCH, Issue 1 2006
James M. Nelson
Abstract I examine two anomalies where the Fama and French three-factor model fails to adequately explain monthly industry and index returns. Both anomalies are consistent with a bad model problem where the book-to-market factor introduces a negative bias in the intercepts. I propose the intangibles model as an alternative where the three-factor model is known to have difficulty. This alternative model, which replaces the book-to-market factor with zero investment portfolio returns based on prior investments in intangible assets, is well specified in random samples, has comparable power, and fully explains both anomalies. [source]

Hedging and value at risk: A semi-parametric approach

THE JOURNAL OF FUTURES MARKETS, Issue 8 2010
Zhiguang Cao
The non-normality of financial asset returns has important implications for hedging. In particular, in contrast with the unambiguous effect that minimum-variance hedging has on the standard deviation, it can actually increase the negative skewness and kurtosis of hedge portfolio returns. Thus, the reduction in Value at Risk (VaR) and Conditional Value at Risk (CVaR) that minimum-variance hedging generates can be significantly lower than the reduction in standard deviation. In this study, we provide a new, semi-parametric method of estimating minimum-VaR and minimum-CVaR hedge ratios based on the Cornish-Fisher expansion of the quantile of the hedged portfolio return distribution. Using spot and futures returns for the FTSE 100, FTSE 250, and FTSE Small Cap equity indices, the Euro/US Dollar exchange rate, and Brent crude oil, we find that the semiparametric approach is superior to the standard minimum-variance approach, and to the nonparametric approach of Harris and Shen (2006). In particular, it provides a greater reduction in both negative skewness and excess kurtosis, and consequently generates hedge portfolios that in most cases have lower VaR and CVaR. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:780,794, 2010 [source]

Hedging and value at risk

THE JOURNAL OF FUTURES MARKETS, Issue 4 2006
Richard D. F. Harris
In this article, it is shown that although minimum-variance hedging unambiguously reduces the standard deviation of portfolio returns, it can increase both left skewness and kurtosis; consequently the effectiveness of hedging in terms of value at risk (VaR) and conditional value at risk (CVaR) is uncertain. The reduction in daily standard deviation is compared with the reduction in 1-day 99% VaR and CVaR for 20 cross-hedged currency portfolios with the use of historical simulation. On average, minimum-variance hedging reduces both VaR and CVaR by about 80% of the reduction in standard deviation. Also investigated, as an alternative to minimum-variance hedging, are minimum-VaR and minimum-CVaR hedging strategies that minimize the historical-simulation VaR and CVaR of the hedge portfolio, respectively. The in-sample results suggest that in terms of VaR and CVaR reduction, minimum-VaR and minimum-CVaR hedging can potentially yield small but consistent improvements over minimum-variance hedging. The out-of-sample results are more mixed, although there is a small improvement for minimum-VaR hedging for the majority of the currencies considered. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:369,390, 2006 [source]

A note on the relationships between some risk-adjusted performance measures

THE JOURNAL OF FUTURES MARKETS, Issue 5 2002
Donald Lien
Assuming portfolio returns are normally distributed, it is shown that both Sortino ratio (SR) and upside potential ratio (UPR) are monotonically increasing functions of the Sharpe ratio. As a result, all three risk-adjusted performance measures provide identical ranking among investment alternatives. The effects of skewness and kurtosis are then evaluated within the Edgeworth-Sargan density family. For the Sortino ratio, the above conclusion remains valid in the presence of negative skewness or excessive kurtosis. Similar results apply to the UPR with modifications. For all other cases, both SR and UPR provide exactly opposite ranking among investment alternatives to that suggested by the Sharpe ratio when the Sharpe ratio is large. Applications to futures hedging are discussed. Specifically, it is found that the Sharpe ratio may frequently lead to a smaller futures position than the other two ratios. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:483,495, 2002 [source]