Evaluation of investment funds through different performance measures

Purpose - The aim of this study is to examine the evaluation of Brazilian equity funds from different performance measures. Theoretical framework - In the literature, several indexes are available that can be used to evaluate the performance of investment funds. Design/methodology/approach - Monthly return data were collected from 1,901 Brazilian equity funds. Fund performance was estimated using four indexes: the Sharpe ratio, the Sortino ratio, Jensen’s alpha, and the Treynor ratio. Findings - The results showed that all four performance measures are positively associated. This means that there are no significant differences in the ranking of Brazilian equity funds in terms of performance. Research, Practical & Social implications - The comparison of different performance indexes contributes to the literature on the subject by providing further data for researchers to adequately define the indexes considered in studies on the performance of funds. Originality/value - This study fills a gap in the literature regarding the analysis of performance measures of investment funds. Keywords - Mutual funds. Equity funds. Performance.

Application of multilayer perceptron to deep reinforcement learning for stock market trading and analysis

Trading strategies to maximize profits by tracking and responding to dynamic stock market variations is a complex task. This paper proposes to use a multilayer perceptron method (a part of artificial neural networks (ANNs)), that can be used to deploy deep reinforcement strategies to learn the process of predicting and analyzing the stock market products with the aim to maximize profit making. We trained a deep reinforcement agent using the four algorithms: proximal policy optimization (PPO), deep Q-learning (DQN), deep deterministic policy gradient (DDPG) method, and advantage actor critic (A2C). The proposed system, comprising these algorithms, is tested using real time stock data of two products: Dow Jones (DJIA-index), and Qualcomm (shares). The performance of the agent linked to the individual algorithms was evaluated, compared and analyzed using Sharpe ratio, Sortino ratio, Skew and Kurtosis, thus leading to the most effective algorithm being chosen. Based on the parameter values, the algorithm that maximizes profit making for the respective financial product was determined. We also extended the same approach to study and ascertain the predictive performance of the algorithms on trading under highly volatile scenario, such as the pandemic coronavirus disease 2019 (COVID-19).

Taylor’s law of fluctuation scaling for semivariances and higher moments of heavy-tailed data

We generalize Taylor’s law for the variance of light-tailed distributions to many sample statistics of heavy-tailed distributions with tail index α in (0, 1), which have infinite mean. We show that, as the sample size increases, the sample upper and lower semivariances, the sample higher moments, the skewness, and the kurtosis of a random sample from such a law increase asymptotically in direct proportion to a power of the sample mean. Specifically, the lower sample semivariance asymptotically scales in proportion to the sample mean raised to the power 2, while the upper sample semivariance asymptotically scales in proportion to the sample mean raised to the power (2−α)/(1−α)>2. The local upper sample semivariance (counting only observations that exceed the sample mean) asymptotically scales in proportion to the sample mean raised to the power (2−α2)/(1−α). These and additional scaling laws characterize the asymptotic behavior of commonly used measures of the risk-adjusted performance of investments, such as the Sortino ratio, the Sharpe ratio, the Omega index, the upside potential ratio, and the Farinelli–Tibiletti ratio, when returns follow a heavy-tailed nonnegative distribution. Such power-law scaling relationships are known in ecology as Taylor’s law and in physics as fluctuation scaling. We find the asymptotic distribution and moments of the number of observations exceeding the sample mean. We propose estimators of α based on these scaling laws and the number of observations exceeding the sample mean and compare these estimators with some prior estimators of α.

Word Portfolio Optimization in the Environment of Zero Interest Rate

This paper provides a deep analysis of ten globally diversified portfolios, composed of different financial instruments: bonds, shares, ETF’s, commodities, indexes, currencies, constructed applying various optimization techniques. Statistical moments, such as mean, standard deviation, kurtosis and skewness of portfolios are compared and discussed. Moreover, performance of the portfolios within the time horizon of one year estimating Sharpe ratio, Treynor ratio, Sortino ratio is presented. Furthermore, a risk analysis of created portfolios is evaluated in terms of historical VaR and CVaR applying confidence interval 95%. The main results of this paper reveal that the portfolio, which is optimized to minimize VaR produces high expected shortfall. Secondly, the Risk Parity portfolio, despite reducing volatility, has delivered the highest kurtosis of the return, which may indicate the possible tail loss. Furthermore, the maximum Sharpe ratio portfolio has delivered extremely high kurtosis in comparison with the kurtosis of the other portfolios. Finally, it is observed that for the Naïve diversification portfolio it has been typical to have the highest downside deviation.

Performance and Volatility Modelling for Shariah Compliant Stocks in Malaysia Using Exponentially Weighted Moving Average

The diversity of investment in Malaysia provides an excellent platform to gauge volatility. Malaysia as an emerging market with a rich Islamic culture serves as an inspiration to randomly model a portfolio of 50 Shariah compliant stock returns from 2015 to 2020. The systematic risk of a company’s stock returns is measured by computing the volatility and downside volatility for the said period. The Exponentially Weighted Moving Average (EWMA) method is used to outline the risk levels of Shariah compliant stocks for the recent stipulated period. The results indicate a statistical difference between beta and downside beta for Shariah compliant portfolio. This signals investors to be cognisant of the semi-variant characteristics of returns in estimating volatility. Meanwhile, there is no significant difference in performance using the Sharpe and Sortino ratio on the beta and downside beta scores respectively. Consequently, this suggests that investors can always measure performance to a sufficient degree of accuracy regardless of their volatility choice.

Climate Change in the Capital Markets: A Study of Actively Managed Green Bond Funds

In this study, we carried out a performance analysis of green bond portfolios available from public databases for the period between 2017 and 2020. The aim of our research was to obtain empirical proof for the existence of the green premium, which was confirmed by risk-adjusted indicators, i.e. the Sharpe ratio, the M2 ratio and the Sortino ratio. The green premium is the return differential that can be measured between green and conventional financial instruments. According to the literature, investors are willing to forego 1 to 9 basis points of their returns in the interests of financing climate targets, to cover the issuer’s extra costs incurred from green bond ratings and reporting obligations. Our results confirmed that the green bond portfolio underperforms benchmark indices by an average green premium of 2 basis points. We only found a single green bond fund that did not involve a green premium and was capable of achieving a risk-adjusted excess return. Nevertheless, it is noted that all of the indicators used showed that the average performance of green bonds improved steadily each year in the period under review.

PERFORMANCE EVALUATION OF EXCHANGE TRADED FUND IN THE INDONESIA STOCK EXCHANGE

This study evaluates the performance of the Exchange Traded Fund (ETF) index in the Indonesia Stock Exchange by using the Treynor Ratio, Sharpe Ratio, Sortino Ratio, Jensen Alpha, Information Ratio, and Omega Ratio. There are 12 ETFs to be evaluated, R-LQ45X, XIIC, XIIT, XIJI, XISI, XISR, XIIF, XISC, XPLQ, XPDV, XPES, XPLC. The data used in this study are the weekly closing price and risk-free investment that is represented by the BI rate from January 2018 to December 2019. The result of this study shows that there are only two of the ETF that has better performance than risk-free investment, namely XIIT and R-LQ45X if it is calculated by using the Sharpe Ratio, Sortino Ratio, Information Ratio, and Omega Ratio. In contrast, the Treynor Ratio and Jensen Alpha show negative value or worse than risk-free investment.

Cryptocurrencies as an asset class in portfolio optimisation

In this paper, cryptocurrencies are analysed as investment instruments. The study aims to verify whether they can be classified as an asset class and what kind of benefits they may bring to the investor's portfolio. We used 6 indices as proxies for the major asset classes, including the cryptocurrency index CRIX, for all cryptographic assets.Cryptocurrencies relatively fully satisfied 7 asset class requirements, namely stable aggregation, investability, internal homogeneity, external heterogeneity, expected utility, selection skill and cost-effective access. It was found that crypto assets have diversification properties. Portfolio optimisation with the Modern Portfolio Theory showed an increase in the Sharpe ratio of tangency portfolios with the inclusion of CRIX. However, the Post-Modern Portfolio Theory identified significant deterioration of the downside risk and the Sortino ratio.

PERFORMANCE EVALUATION OF LQ45 STOCKS IN THE INDONESIA STOCK EXCHANGE DURING PERIOD OF 2016-2018

Objective: This study investigates the performance evaluation of each LQ45 stock in the Indonesia Stock Exchange conducted by using the Sharpe Index, Treynor Ratio, Jensen Alpha, Sortino Ratio, and Information Ratio. Stocks evaluated are those that consistently listed in the LQ45 index during 2016-2018. Research Design & Methods: The number of samples used in this study was 32 stocks taken using a purposive sampling technique. The data used in this study are the monthly closing price of stocks, the composite stock price index, and the BI 7-day Repo Rate interest rate data. Findings: The results of this study show that not all stocks included in the LQ45 index have good performances. The results of this study show that BBCA stock is the best stocks based on Sharpe Index and Information Ratio. Based on the Jensen Alpha method and the Sortino Ratio, PTBA stock is the best stocks. As for the Treynor Ratio method, the best stock is INCO. Recommendations: There is a blemish in research for further research that is expanding the scope of research, not only companies included in LQ45. Future studies can analyze portfolios consisting of LQ45 stocks and updating periods because stock performance is cyclical. Contribution & Value Added: This research contributes to the analysis of LQ45 stock performance based on five methods including Sortino and Information Ratio that are rarely used and show differences in the results of the five stock performance indices.

Bootstrap Estimation of Expected Risk and Return of Strategy Equity Indices

The aim of this article is to present the results of research associated with the ex-post estimation of expected risk, return and other characteristics of strategy equity indices and capital-weighted equity indices partially and to determine credible methods for a transparent comparison. The data sources are the MSCI and STOXX equity index providers. Suitable statistical methods and a computation-intensive method for estimating selected characteristics have been used and compared to one another.For the measurement of excess return per unit of risk a modified Sortino ratio was used, which takes into account only the downside size and frequency of returns, measuring the return to negative volatility trade-off. Based on our results, it is apparent that some strategic equity indices outperform capital-weighted equity indices in a long-term investment perspective (1997-2018).A suitable combination of strategic equity indices, namely the mix of dividend strategy and momentum strategy may lead to the highest yield / risk ratio expressed by the Sortino ratio. The outperformance path of a mix of dividends and momentum strategy indices is much more stable than either the performance of the individual strategy equity indices or capital-weighted equity indices alone.