Monthly Returns Research Articles

Hedge Fund Performance Evaluation Using The Sharpe And Omega Ratios

The Sharpe ratio is widely used as a performance evaluation measure for traditional (i.e., long only) investment funds as well as less-conventional funds such as hedge funds. Based on mean-variance theory, the Sharpe ratio only considers the first two moments of return distributions, so hedge funds characterised by asymmetric, highly-skewed returns with non-negligible higher moments may be misdiagnosed in terms of performance. The Sharpe ratio is also susceptible to manipulation and estimation error. These drawbacks have demonstrated the need for augmented measures, or, in some cases, replacement fund performance metrics. Over the period January 2000 to December 2011 the monthly returns of 184 international long/short (equity) hedge funds with geographical investment mandates spanning North America, Europe, and Asia were examined. This study compares results obtained using the Sharpe ratio (in which returns are assumed to be serially uncorrelated) with those obtained using a technique which does account for serial return correlation. Standard techniques for annualising Sharpe ratios, based on monthly estimators, do not account for this effect. In addition, this study assesses whether the Omega ratio supplements the Sharpe Ratio in the evaluation of hedge fund risk and thus in the investment decision-making process. The Omega and Sharpe ratios were estimated on a rolling basis to ascertain whether the Omega ratio does indeed provide useful additional information to investors to that provided by the Sharpe ratio alone.

Forecasting market turbulence using regime-switching models

We propose an early warning system to timely forecast turbulence in the US stock market. In a first step, a Markov-switching model with two regimes (a calm market and a turbulent market) is developed. Based on the time series of the monthly returns of the S&P 500 price index, the corresponding filtered probabilities are successively estimated. In a second step, the turbulent phase of the model is further specified to distinguish between bullish and bearish trends. For comparison only, a Markov-switching model with three states (a calm market, a turbulent bullish market, and a turbulent bearish market) is examined as well. In a third step, logistic regression models are employed to forecast the filtered probabilities provided by the Markov-switching models. A major advantage of the presented modeling framework is the timely identification of the factors driving the different phases of the capital market. In a fourth step, the early warning system is applied to an asset management case study. The results show that explicit consideration of the models’ signals yields better portfolio performance and lower portfolio risk compared to standard buy-and-hold and constant proportion portfolio insurance strategies.

On the Relation between EGARCH Idiosyncratic Volatility and Expected Stock Returns

AbstractA spurious positive relation between exponential generalized autoregressive conditional heteroskedasticity (EGARCH) estimates of expected monthtidiosyncratic volatility and monthtstock returns arises when the monthtreturn is included in estimation of model parameters. We illustrate via simulations that this look-ahead bias is problematic for empirically observed degrees of stock return skewness and typical monthly return time series lengths. Moreover, the empirical idiosyncratic risk-return relation becomes negligible when expected monthtidiosyncratic volatility is estimated using returns only up to montht− 1.

Relationship between Investors Sentiment Index with Stock Returns in Tehran Stock Exchange (TSE)

In this study, investor’ sentiment on stock returns of sorted portfolios was reviewed based on size and ratio of book to market value from 2001 to 2013. Monthly return of each portfolio was calculated based on monthly return of each firms using equal weight approach and finally, relevant coefficients were estimated using Multivariate Regression Method in the form of time series on the model. For this purpose, four-factorial model of market portfolio, size of firms, ratio of book to market value and investors’ sentiment were used in clarification of return. The results of this study indicate that there is a positive and significant relationship between investors’ sentiment with stock returns of the firms which enjoy the minimum size and ratio of book to market value.

Functional Principal Components Analysis of Shanghai Stock Exchange 50 Index

The main purpose of this paper is to explore the principle components of Shanghai stock exchange 50 index by means of functional principal component analysis (FPCA). Functional data analysis (FDA) deals with random variables (or process) with realizations in the smooth functional space. One of the most popular FDA techniques is functional principal component analysis, which was introduced for the statistical analysis of a set of financial time series from an explorative point of view. FPCA is the functional analogue of the well-known dimension reduction technique in the multivariate statistical analysis, searching for linear transformations of the random vector with the maximal variance. In this paper, we studied the monthly return volatility of Shanghai stock exchange 50 index (SSE50). Using FPCA to reduce dimension to a finite level, we extracted the most significant components of the data and some relevant statistical features of such related datasets. The calculated results show that regarding the samples as random functions is rational. Compared with the ordinary principle component analysis, FPCA can solve the problem of different dimensions in the samples. And FPCA is a convenient approach to extract the main variance factors.

Calendar effects in the Tunisian stock exchange

This paper examines daily returns of the stock market index of Tunisia (Tunindex) to prove whether there is existence of calendar effects related to the day of the week, the month of the year, and the semi–month effects. Using both parametric and nonparametric tests, we find evidence of day of the week and month of the year effects. However, we report no semi–month effect in daily returns of Tunindex in the Tunisian stock exchange (TSE) over the period January 1998 to December 2011. More specifically, we report the Friday effect that Friday returns tend to be positive and higher than returns of the other days. Also, we find an April effect in which we document that the returns are significantly higher in April than the returns in other months.

Performance persistence in socially responsible mutual funds

This paper reports on an examination of the performance persistence of 238 socially responsible (SR) mutual funds using ten-year monthly and annual returns. The method used relative percentile ranks and annual returns and reward-to-variability ratios to examine persistence. No evidence of performance persistence was found. The results suggest that superior past performance of SR funds is no indicator of superior performance in future.

The Market Timing Power of Moving Averages: Evidence from US REITs and REIT Indexes

AbstractI present evidence that a moving average (MA) trading strategy dominates buying and holding the underlying asset in a mean‐variance sense using monthly returns of value‐weighted and equal‐weighted US REIT indexes over the period January 1980 until December 2010. The abnormal returns are largely insensitive to the four Carhart factors and produce economically and statistically significant alphas of between 10 and 15% per year after transaction costs. This performance is robust to different lags of the MA and in subperiods while investor sentiment, liquidity risks, business cycles, up and down markets, and the default spread cannot fully account for its performance. The MA strategy works just as well with randomly generated returns and bootstrapped returns. The substantial market timing ability of the MA strategy appears to be the main driver of the abnormal returns. The returns to the MA strategy resemble the returns of an imperfect at‐the‐money protective put strategy relative to the underlying portfolio. The lagged signal to switch has substantial predictive power over the subsequent return of the REIT index. The MA strategy avoids the sharp downturn at the beginning of 2008 and substantially outperforms the cumulative returns of the buy‐and‐hold strategy using all of the 20 REIT indexes. The results from applying the MA strategy with 274 individual REITs largely corroborate the findings for the REIT indexes.

ROBUST ESTIMATION AND FORECASTING OF THE CAPITAL ASSET PRICING MODEL

In this paper, we develop a modified maximum likelihood (MML) estimator for the multiple linear regression model with underlying student t distribution. We obtain the closed form of the estimators, derive the asymptotic properties, and demonstrate that the MML estimator is more appropriate for estimating the parameters of the Capital Asset Pricing Model (CAPM) by comparing its performance with least squares estimators (LSE) on the monthly returns of US portfolios. The empirical results reveal that the MML estimators are more efficient than LSE in terms of the relative efficiency of one-step-ahead forecast mean square error in small samples.

Hedge fund replication: putting the pieces together

In this paper, we aim to bring together into one common framework various advances in factor-based hedge fund replication. Our replication methodology relies on a set of investable dynamic risk factors extracted from futures contract prices and on an automatic variable and model selection procedure. The methodology is then validated by creating out-of-sample replicating portfolios for the monthly returns of about 7000 hedge funds from 2006 to 2012 and under the assumption of transaction costs. Our results suggest that hedge fund replication is on average possible and works best for liquid strategies.

Order Flow and Cross-Sectional Monthly Returns: Compensation for Market Maker with Inventory Concern

We investigate whether market makers with inventory concerns are compensated with subsequent monthly returns in the cross-section. We find a significant negative relation between order flows and monthly returns, “the order flow effect”, suggesting that market makers lower prices for stocks with sell order flows and demand a reward in the form of higher expected returns. Further, the order flow effect is stronger for high-volatility or high-volume stocks for which market makers have serious inventory concerns. Funding liquidity of market makers also affects the order flow effect. Finally, our finding is independent of existing regularities and robust to the decimalization.

Stable and Efficient Portfolios

DeMiguel et al. (2009a) show that estimation errors lead to mean-variance portfolios that underperform naive diversification (1/N). In response to this finding, new studies have developed more efficient sample-based portfolio strategies that offer higher risk-adjusted returns than 1/N . In this paper, I show that the latter portfolio may still be superior in the presence of transaction costs. This is because sample-based strategies tend to be unstable over time. Instability leads to high transaction costs that significantly reduce portfolio returns. I resolve this issue by introducing a stability penalty to the standard mean-variance objective that controls the deviation from the investor’s portfolio before rebalancing. In contrast to other techniques in the literature that account for transaction costs, the stability penalty offers intuitive analytical solutions to the portfolio choice problem. As such, it allows to treat estimation errors and transactions costs in a joint manner and it can be directly applied to any portfolio strategy. I evaluate the stability approach by applying it to nine sample-based strategies from the literature and study their performance in five data sets of monthly returns. The results confirm that it leads to stable and efficient portfolios that offer higher Sharpe ratio than 1/N and equal or lower turnover.

Summaries of Papers in this Issue

Summaries of Papers in this Issue

Monte Carlo Simulation in Financial Valuation

This paper uses Monte Carlo simulation of a simple equity growth model with resampling of historical financial data to estimate the probability distribution of the future equity, earnings and payouts of companies, which are then used to estimate the probability distribution of the future return on the stock and stock options. The model is used on the S&P 500 stock market index and the Coca-Cola company. The relation between USA government bonds, the S&P 500 index and the Dow Jones Venture Capital index (DJVC) is also studied and it is found that there is no consistent and predictable risk premium between USA government bonds and the S&P 500 and DJVC indices, but there is significant correlation between the monthly returns of the S&P 500 and DJVC indices.

Investor Sentiment for Real Assets: The Case of Dry Bulk Shipping Market*

We investigate the role of sentiment and its implications for real assets. Using shipping sentiment proxies that capture market expectations, valuation, and liquidity, we construct sentiment indices for the dry bulk shipping market. Evidence suggests that sentiment affects the monthly returns of real assets. The empirical findings also show that market sentiment serves as a contrarian indicator for future cycle phases in all sectors. Furthermore, a sentiment-based trading simulation exercise on the sale and purchase of vessels shows that investors can benefit from higher returns compared to the buy-and-hold benchmark, while partially offsetting the highly volatile nature of the shipping industry.

Performance and role of European listed infrastructure in a mixed‐asset portfolio

PurposeThe purpose of this paper is to examine the performance of European listed infrastructure before, during and after the global financial crisis and the significance of European infrastructure in a mixed asset portfolio. The paper examines the level of correlation of European infrastructure with other major assets classes and substantiates the potential diversification benefits of including European infrastructure within a mixed asset portfolio.Design/methodology/approachThe study uses monthly investment return indices obtained from Thomson Reuters DataStream over a ten year period (2001‐2010). The paper analysed the European listed infrastructure investment return characteristics including average annual return, annual risk, Sharpe indices, mean variance portfolio and maximum return portfolio and computes the efficient portfolio frontiers using the risk solver optimization tool.FindingsThis study shows that despite the global financial turmoil, a robust performance was seen by certain infrastructure sub‐sectors particularly European generation utilities, which posted positive annualised returns during the global financial crisis and European “ports” emerged as the overall best performing sub‐asset class during the post‐GFC period. Using the monthly return indices over the ten year period, European infrastructure investment was found to play a significant role in the optimality of multi asset portfolios.Originality/valueThe originality of the paper stems from the analysis of the performance and significance of European listed infrastructure in a multi‐asset portfolio over unique periods which tested the resilience of European listed infrastructure performance over different financial climates including the global financial crisis period. This paper presents European listed infrastructure as an indication of rewarding investment outlets for investors in quest of exposure to the infrastructure industry and for those seeking to enhance investment portfolio performance.

Accelerating prevention of mother-to-child transmission of HIV: Ten-year experience of Universal Antenatal HIV Testing Programme in a low HIV prevalence setting in Hong Kong

Hong Kong has a low prevalence of HIV infection at less than 0.01%. Universal Antenatal HIV Testing Programme (UATP) was launched in all public antenatal units in September 2001. In 2008, voluntary rapid HIV testing was introduced in all public labour units to fill up the gap for pregnant women without HIV testing during the antenatal period. This study evaluated the performance of UATP and rapid HIV testing with indicators. From September 2001 to December 2011, process and outcome indicators for monitoring and evaluation were collected from the service providers in the form of monthly return of workload statistics and case-based statistics of each identified HIV-positive pregnancy via reporting forms. A total of 479,160 antenatal HIV tests and 2,675 rapid tests were performed in the study period. The acceptance rate for UATP and rapid HIV testing was 98% and 80.4% respectively. With the implementation of rapid HIV testing in January 2008, the proportion of pregnant women with HIV status discerned before delivery increased from 84.9% in 2006 to over 99.5% since 2008. The HIV prevalence in UATP and rapid HIV testing was 0.02% and 0.1% respectively. Fifty-three (68%) out of 78 HIV-infected pregnant women identified from the programme have delivered locally. Forty-three (81%) of them delivered by caesarean section and 50 (94%) of them were given antiretrovirals for intervention. Only three children born before the implementation of rapid HIV testing were HIV-infected. In conclusion, UATP and its rapid HIV testing component have been highly accepted and effective in the prevention of perinatal HIV transmission in Hong Kong.

The timing of 52-week high price and momentum

We propose a new momentum strategy based on the timing of a stock’s 52-week high price. We find that the stocks that attained the 52-week high price in the recent past significantly outperform the stocks that attained the 52-week high price in the distant past. In particular, the top 10% of the stocks with the most recent 52-week high price outperform the bottom 10% of the stocks with most distant 52-week high price by 0.70% per month. Further, conditioning on the recency of 52-week high price significantly increases the profitability of momentum strategy based on the nearness of current price to the 52-week high price. Specifically, the average monthly return of this strategy is about twice as large for stocks with recent 52-week high price as compared with stocks with distant 52-week high price.

The impact of the global financial crisis on firm‐level risk of the S&P 500

PurposeThis paper aims to assess the impact of the global financial crisis of 2007‐09 on the risk structure of S&P 500 firms by examining their market, active, and residual risks before and during the crisis.Design/methodology/approachThe classic one‐factor model is estimated for each firm in the S&P 500 to decompose risk into market, active, and residual components. Five sets of regression estimates based on monthly return data are used: 2002‐06, 2003‐07, 2004‐08, 2005‐09, and 2006‐10. The estimates provide insight into the risk structure of S&P 500 firms before and during the crisis.FindingsThe average correlation coefficient between S&P 500 firms rose during the crisis from 0.20 to 0.35, an increase of 75 percent. Although the results indicate that active and residual risks are significant across the firms and across the periods, the impact of the financial crisis was mostly on market risk. The increase in risks was pronounced for financial firms, especially insurance companies, and industrial firms, especially “hard” manufacturing.Research limitations/implicationsBecause the study focuses on the global financial crisis of 2007‐09, researchers should be careful about generalizing the results to the post‐crisis period.Practical implicationsInvestors should be aware that equity portfolio risk reduction during major crises can be hard to achieve because the average correlation coefficient between stock returns may rise significantly, crimping the efficacy of diversification.Originality/valueIt was very difficult for equity investors to shield themselves from the risk associated with the global financial crisis of 2007‐09.

International Real Estate Review

We find that the 3-day window around funds from operations (FFO) announcements drives the momentum profits found in the literature, which deliver an average excess monthly return of 1.22% over the period of 1990-2008 and 1.59% during the post-2000 period. Excluding this announcement window, a momentum strategy does not generate any significant returns. The FFO-surprised-based portfolio formation method produces higher momentum profits than the return-based formation method. There is a significant positive serial correlation between the unexpected FFO for the next two quarters. We contribute to the current literature by documenting that the persistence of momentum profits is due to the underreaction by analysts on public information, the FFO announcement.