Portfolio performance under tracking error and benchmark volatility constraints

Purpose Using a portfolio comprising liquid global stocks and bonds, this study aims to limit absolute risk to that of a standardised benchmark and determine whether this has a significant impact on expected return in both high volatility period (HV) and low volatility period (LV). Design/methodology/approach Using a traditional benchmark comprising 40% equity and 60% bonds, a constant tracking error (TE) frontier was constructed and implemented. Portfolio performance for different TE constraints and different economic periods (expansion and contraction) was explored. Findings Results indicate that during HV, replicating benchmark portfolio risk produces portfolios that outperform both the maximum return (MR) portfolio and the benchmark. MR portfolios outperform those with the same risk as that of the benchmark in LV. The MR portfolio weights assets to obtain the highest return on the TE frontier. During HV, the benchmark replicated risk portfolio obtained a higher absolute risk value than that of the MR portfolio because of an inefficient benchmark. In HV, the benchmark replicated risk portfolio favoured intermediate maturity treasury bills. Originality/value There is a dearth of literature exploring the performance of active portfolios subject to TE constraints. This work addresses this gap and demonstrates, for the first time, the relative portfolio performance of several standard portfolio choices on the frontier.

Evaluation of multi-asset investment strategies with digital assets

The drastic growth of the cryptocurrencies market capitalization boosts investigation of their diversification benefits in portfolio construction. In this paper with a set of classical and modern measurement tools, we assess the out-of-sample performance of eight portfolio allocation strategies relative to the naive 1/N rule applied to traditional and crypto-assets investment universe. Evaluated strategies include a range from classical Markowitz rule to the recently introduced LIBRO approach (Trimborn et al. in Journal of Financial Econometrics 1–27, 2019). Furthermore, we also compare three extensions for strategies with respect to input estimators applied. The results show that in the presence of alternative assets, such as cryptocurrencies, mean–variance strategies underperform the benchmark portfolio. In contrast, CVaR optimization tends to outperform the benchmark as well as geometric optimization, although we find a strong dependence of the former’s success on trading costs. Furthermore, we find evidence that liquidity-bounded strategies tend to perform very well. Thus, our findings underscore the non-normal distribution of returns and the necessity to control for liquidity constraints at alternative asset markets.

Fund Managers Adding Values? Measuring Performance without Benchmark – A Study of Indian Mutual Fund Schemes

This paper calculates the Portfolio Change Measure (PCM) developed by Grinblatt and Titman for a sample of 744 equity schemes of Indian mutual funds over a minimum period of more than 2 years and less than 11 years. PCM, based on holding of assets, is a measure which is free from ‘benchmark’ biases arising out of usage of a ‘benchmark’ portfolio. So by using PCM as a measure, this paper, without using any benchmark, attempts to assess whether the selected mutual fund managers were able to add value and exhibit superior skills on the average and thus making a case for active fund management over a passive buy and hold strategy. Using the monthly holding statement of each individual scheme’s portfolio, rolling PCM has been calculated on a monthly basis with a rolling window of one year. The results of our analysis, supported by robustness checks, which includes time periods of pre-and post-Global Financial Crisis, shows strong evidence of active fund management adding value in the stock selection and hence in return generating process, thus justifying the possession of superior skill or superior information of fund managers at an aggregate level. Finally, using Quantile Regression we identify some characteristics of the scheme like scheme size and ownership category, which influence PCM significantly.

Performance and Risk Aversion of Funds with Benchmarks

This chapter provides a simple method of ranking mutual funds’ probabilities of outperforming a benchmark portfolio. We show that ranking fund performance in this way is identical to ranking each fund’s portfolio with a generalized entropy, equivalent to an expected generalized power utility index that uses a risk-aversion coefficient specific to that fund. When the return differential between fund and benchmark portfolio (log gross) returns follows a Gaussian process, this ranking is equivalent to using a simple modification of the Information Ratio (1998). We develop and apply feasible parametric and nonparametric estimators to rank the performance of the small fraction of mutual funds that (from the results of an hypothesis test) could outperform the S&P 500 Index in the long run, and to estimate the fund-specific risk-aversion coefficients required for the ranking. We also argue that an auxiliary hypothesis that fund managers attempt to maximize the outperformance probability is no less plausible than an extant alternative behavioral hypothesis and is more parsimoneously parametrized.

The Impact of Domestic Mergers and Acquisitions on the Operating Profit Margins of Companies in Russia

This research paper studies the impact of domestic Russian mergers and acquisitions on the operating profit margin of companies participating in deals. The goal of the research is to evaluate the changes in operating profit margin, and to analyse the significance of factors affecting operating profit margin after deals have been concluded. The main scientific contribution of this research is the development of a methodology to analyse the effect of mergers and acquisitions on operating profit margins that takes into account the idiosyncratic features of the Russian market, and which can be used with limited information for analysis of private companies. The proposed methodology is based on benchmarking the operating profit margin of companies participating in a deal against the same variable for a portfolio of similar companies. Based on the analysis of recent studies, several explanatory variables were proposed to explain the changes in operating profit margin after the deal. Among these were included real GDP growth, type and value of the deal, book value of assets of the target company, as well as a number of control variables. A random effects model with robust standard errors was used to test the significance of factors affecting operating profit margin. This methodology was applied to a sample of 73 domestic Russian deals observed in the period 2012-2019. This research makes several practical contributions to the literature. In the studied sample, deals lead to an increase of operating profit margin by 4.6% relative to the period before the deal, and 2.5% relative to the benchmark portfolio. The highest growth of operating profit margin relative to the benchmark portfolio is observed 2 years after the deal. This growth is increased by the purchase of large companies in the same industry. There is a significant negative effect of the deal value and a strong indication that buyers tend to overpay for the target companies relative to their fair value. This research will be of practical use for persons in management positions to estimate the value of prospective deals, and for academic researchers interested in the analysis of mergers and acquisitions in emerging markets.

CAN BRICS’S CURRENCY BE A HEDGE OR A SAFE HAVEN FOR ENERGY PORTFOLIO? AN EVIDENCE FROM VINE COPULA APPROACH

In this paper, we examine the role of Brazil, Russia, India, China and South Africa’s (BRICS) currency in energy market by using vine copula method. The value-at-risk (VaR) and expected shortfall of two portfolios are calculated. One is a benchmark portfolio which is consisted of only energy prices, the other is a portfolio which adding the BRICS’s exchange rate into the benchmark portfolio. The data period is from 24 August 2010 to 29 November 2019. Our results show the BRICS’s currency can reduce the risk in energy investment.

Properties of the beta coefficient of the global minimum variance portfolio

The paper is devoted to the investigation of statistical properties of the sample estimator of the beta coefficient in the case when the weights of benchmark portfolio are constant and for the target portfolio, the global minimum variance portfolio is taken. We provide the asymptotic distribution of the sample estimator of the beta coefficient assuming that the asset returns are multivariate normally distributed. Based on the asymptotic distribution we construct the confidence interval for the beta coefficient. We use the daily returns on the assets included in the DAX index for the period from 01.01.2018 to 30.09.2019 to compare empirical and asymptotic means, variances and densities of the standardized estimator for the beta coefficient. We obtain that the bias of the sample estimator converges to zero very slowly for a large number of assets in the portfolio. We present the adjusted estimator of the beta coefficient for which convergence of the empirical variances to the asymptotic ones is not significantly slower than for a sample estimator but the bias of the adjusted estimator is significantly smaller.

Dantzig Type Optimization Method with Applications to Portfolio Selection

This paper investigates a novel optimization problem motivated by sparse, sustainable and stable portfolio selection. The existing benchmark portfolio via the Dantzig type optimization is used to construct a sparse, sustainable and stable portfolio. Based on the formulations, this paper proposes two portfolio selection methods, west and north portfolio selection, and investigates their empirical properties. Numerical results presented for 12 datasets and various simulated data show that the west selection can reduce risk, and the north selection may outperform the benchmark as to risk-adjusted returns (based on, e.g., information ratio and Sharpe ratio).

Analysis on the Risk Return Profile of Alternative Assets Under Reference Portfolio Concept

This paper provides the methodology of estimating the risk-return relationship of alternative asset investments within the mean-variance framework. While conducting strategic asset allocation, most of the institutional investors do not take into account the risk-return relationship of alternative assets, or use arbitrary policy numbers that do not properly reflect the characteristics of alternative assets. This paper borrows the concept of reference portfolio in developing the methodology of estimating the risk-return relationship of alternative investments. The reference portfolio is the benchmark portfolio used in strategic asset allocation by pension funds. This can serve as the opportunity costs of alternative investments. We use the realized IRR’s from actual investments, and estimate the risk-return characteristics of alternative investments. We find that by properly estimating the mapping relationship between the reference portfolio and alternative asset classes, we can incorporate the risk-return profile of these non-market assets within the mean-variance framework together with the other traditional asset classes.