Сравнительный анализ стратегий хеджирования фьючерсами портфеля ценных бумаг
Hedging is one of the most popular strategies for market risk management. Hedging is aimed at decreasing the volatility, or variability, of portfolio returns. The portfolio usually consists of the spot assets and hedging instruments. The latter can be represented by futures, options and over-the-counter assets such as forwards and swaps. While futures’ hedging is rather simple it’s quite widespread in practice. This paper is aimed at comparison of four hedging strategies, where the spot asset is stock and hedging instrument is futures. For this purpose five Russian stocks from Moscow Exchange are selected and analyzed for the period from the 1st of December 2015 till the 29th of February 2016.
The key element of the hedging strategy is the calculation of the hedging coefficient. The latter shows what part of the stocks’ value in the portfolio should be covered by futures. In this paper the hedging coefficient is computed through internal rate of return, ordinary least squares (OLS) and maximum likelihood. The latter is able to estimate hedging coefficient taking into account heteroskedasticity, because the regression errors follow GARCH model. Further hedging strategies are compared by such criteria as standard deviation of portfolio returns, portfolio Value-at-Risk and hedging efficiency.
According to the results the most efficient strategy is one based on internal rate of returns. The other criteria show that the same strategy together with OLS demonstrates better results. Correction for heteroskedasticity made through maximum likelihood did not allow improving hedging efficiency.
The research can be extended in the several directions, namely considering options’ hedging; adding to the portfolio other spot assets, for example, commodities and currencies; taking into account investors’ risk aversion in the calculations of hedging coefficients; introducing transaction costs in the model.
Internal rate of return IRR is one of the key criteria for justifying and choosing capital investments with conventional cash flows. However, this criterion is not practically used when the rate of return of investment instruments (short sales, options, futures, swaps) is calculated because these instruments create non-conventional cash flows. The author previously showed that IRR problems were observed when the present value of cash flows changed sign from period to period. This paper offers a criterion to evaluate the rate of return of investment instruments with non-conventional cash flows, i.e. General Rate of Return (GRR).
The article describes proposed by the authors methodology of analysis of the Russian mutual funds. The aim of this methodology is to find out how attractive they are to investors and if they are able to provide the possibility of obtaining higher returns with less risk than the market in general. The study determines what type of fund management (active or passive) is more optimal. It also explains the effectiveness of focusing on past performance of the funds for making future investments. In addition, the ability of the management companies to repeat their past results is analyzed. Moreover, it is shown if it makes sense to focus on management companies that achieved the best results in the past while making decisions about future investments. These and other results achieved in this article reveal the features of the Russian market of collective investments and allow investors to form more competent policy of mutual funds’ investments. The methodology proposed by the authors is universal. Its application for the analysis of the other markets of collective investments will allow revealing their features.
The present article is devoted to consideration of investment strategy in stock market. The questions connected with designing of such strategy are systemically considered in it. The emphasis is thus placed on adaptation of the general (managerial) theory of engineering to engineering of investment strategy. Engineering of investment strategy is considered in indissoluble interrelation with the analysis of their typology. The most actual types and directions of engineering of investment strategy are characterized in the conclusion of article.
We develop a model of asset pricing and hedging for interconnected financial markets with frictions – transaction costs and portfolio constraints. The model is based on a control theory for random fields on a directed graph. Market dynamics are described by using von Neumann – Gale dynamical systems first considered in connection with the modelling of economic growth [13,24]. The main results are hedging criteria stated in terms of risk-acceptable portfolios and consistent price systems, extending the classical superreplication criteria formulated in terms of equivalent martingale measures.
Random matrix theory (RMT) is applied to investigate the cross-correlation matrix of a financial time series in four different stock markets: Russian, American, German, and Chinese. The deviations of distribution of eigenvalues of market correlation matrix from RMT global regime are investigated. Specific properties of each market are observed and discussed.
The paper aims at finding the most accurate VaR model for the four most liquid Russian stocks. Among the possible VaR modeling techniques, the estimates considered in this work are based on GARCH models with six different distributions. A back testing analysis is performed to evaluate the accuracy of the alternative models and to find the worst predictable period in terms of the volatility behavior.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.