The main goal of this paper is to investigate the behaviour of stock returns in the case of stock markets from Central and Eastern Europe (CEE), focusing on the relationship between returns and conditional volatility. Since there is relatively little empirical research on the volatility of stock returns in underdeveloped stock markets, with even fewer studies on markets in the transitional economies of the CEE region, this paper is designed to shed some light on the econometric modelling of the conditional mean and volatility of stock returns from this region. The results presented in this paper provide confirmatory evidence that ARIMA and GARCH processes provide parsimonious approximations of mean and volatility dynamics in the case of the selected stock markets. There is overwhelming evidence corroborating the existence of a leverage effect, meaning that negative shocks increase volatility more than positive shocks do. Since financial decisions are generally based upon the trade-off between risk and return, the results presented in this paper will provide valuable information in decision making for those who are planning to invest in stock markets from the CEE region.
Mutual fund fees are extraordinarily high in Poland – almost three times higher than in Western Europe and almost five times higher than in the United States. In fact is that from among 183 Polish open-ended stock mutual funds as many as 81 impose a management fee of 4%, which is the highest value in the sample. The question arises whether it is really worth to invest in funds from the more expensive group. Comparing funds charging the highest fees (4%) with the cheaper ones it seems that there is no statistically significant difference between rate of return, risk and efficiency. However, more expensive funds have on average higher costs, are three years older and have almost 70% bigger assets. This may suggest that a well-established market position – not performance – is the trigger for raising their fees. Interestingly, funds with a relatively high minimal initial contribution level (5,000 PLN) have significantly lower management fees with similar costs, total assets value and performance results. Further analysis has also indicated that the costs level (Total Expense Ratio) is higher for older funds, while it is not related to funds’ size.
Background: Investors on financial markets are interested in finding trading strategies which could enable them to beat the market. They always look for best possibilities to achieve above-average returns and manage risks successfully. MGARCH methodology (Multivariate Generalized Autoregressive Conditional Heteroskedasticity) makes it possible to model changing risks and return dynamics on financial markets on a daily basis. The results could be used in order to enhance portfolio formation and restructuring over time.
Objectives: This study utilizes MGARCH methodology on Croatian financial markets in order to enhance portfolio selection on a daily basis. Methods/Approach: MGARCH methodology is applied to the stock market index CROBEX, the bond market index CROBIS and the kuna/euro exchange rate in order to model the co-movements of returns and risks on a daily basis. The estimation results are then used to form successful portfolios.
Results: Results indicate that using MGARCH methodology (the CCC and the DCC model) as guidance when forming and rebalancing a portfolio contributes to less portfolio volatility and greater cumulated returns compared to strategies which do not take this methodology into account.
Conclusions: It is advisable to use MGARCH methodology when forming and rebalancing portfolios in terms of portfolio selection.
This study employs the recently developed Lagrange multiplier-based causality-in-variance test by Hafner and Herwartz (2006), to determine the volatility spillovers between interest rates and stock returns for the US, the euro area, the UK, and Japan. The investigation pays careful attention to volatility transmissions between stock returns and interest rates before and after these economies reached the Zero Lower Bound (ZLB), which is permitted via the use of Shadow Short Rates (SSR), used as a proxy for monetary policy decisions. The results based on daily data imply that while bidirectional causality is observed, the volatility spillover from interest rates to stock markets are more prominent for the full-sample, as well as the sub-samples covering the pre- and during-ZLB periods.
Kamaldeen Ibraheem Nageri and Rihanat Idowu Abdulkadir
Efficient market hypothesis asserts movements in asset prices are due to significant changes in information. The financial crisis of 2007-2009 originated from subprime mortgages in the United States and affected African countries through local stock markets. This study evaluates the Nigerian stock market efficiency in the pre and post financial meltdown of 2007-2009. GARCH models under three error distributional assumptions were used. The data covers January 2010 to December 2016 divided into pre and post meltdown. Findings indicate that in the pre and post meltdown, the Nigerian stock market is inefficient in the weak form while using the meltdown as event window, the market is efficient in the semi-strong form. It was recommended that prompt release of financial information by quoted firms should be on-line real time and mandatory to discourage rumour and speculative activities. Authority should not only spell out punishments but should be strict and firm about it.
Investors are interested in sector diversification on stock markets among other important portfolio topics. This paper looks at five sector indices on Croatian capital market as an example of a small, relatively illiquid market. Sector indices have been constructed at the beginning of 2013 and since then there is a lack of studies, which focus on sector diversification on Zagreb Stock Exchange (ZSE). Thus, the purpose of this paper is to evaluate the recent dynamics of risk and performance of five sector indices on ZSE by employing MGARCH (Multivariate Generalized Autoregressive Conditional Heteroskedasticity) models empirically. Output from the analysis is used to form guidance for investors on Croatian capital market. The results indicate that in the observed period from February 4th 2013 to October 13th 2015 portfolios based on MGARCH methodology outperform other portfolios in terms return and risk. Thus, it is advisable to use this methodology when making portfolio selection.
The beta parameter is a popular tool for the evaluation of portfolio performance. The Sharpe single-index model is a simple regression model in which the stock’s returns are regressed against the returns of a broader index. The beta parameter is a measure of the strength of this relation. Extensive recent research has proved that the beta is not constant in time and should be modelled as a time-variant coefficient. One of the most popular methods of the estimation of a time-varying beta is the Kalman filter. As the output of the Kalman filter, one obtains a sequence of the estimates of a time-varying beta. This sequence shows the historical dynamics of sensitivity of a company’s returns to the variations of market returns. The article proposes a method of clustering companies listed on the Warsaw Stock Exchange according to time-varying betas.
Ana Pavković, Mihovil Anđelinović and Ivan Pavković
Background: Cryptocurrencies represent a specific technological innovation in financial markets that keeps getting more and more popular among investors around the world. Given the specific characteristics of the cryptocurrencies, this paper examines the possibility of their use as a diversification instrument.
Objectives: This paper examines the direction and strength of the relationship between the selected cryptocurrencies and important financial indicators on the European Union market. Since cryptocurrencies are a novelty in the financial system, the empirical literature in this area is rather scarce.
Methods/Approach: In order to assess diversification properties of cryptocurrencies for European traders, a comprehensive econometric analysis was carried out. The first part of the analysis refers to the estimation of the multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, whereas the second part focuses on wavelet transforms.
Results: Bitcoin and Ripple proved as a possible diversification instrument on most of the observed European markets since corresponding coefficients of unconditional correlation are negative.
Conclusions: The relationship between the value of the cryptocurrencies and selected indices is generally very weak and slightly negative, indicating that some cryptocurrencies can serve as a means of diversification. However, investors need to take into account the extreme volatility, exhibited in all existing cryptocurrencies.
This paper investigates changes in the nature of REITs by estimating the time-varying long-run relationship among securitized real estate, direct real estate, and stock performance. The informational environment of U.S. REITs has matured gradually since their introduction. As more information on this asset class has become available, the “true” nature of REITs has thus become more apparent. We find that the long-term elasticity of direct real estate total returns on REIT total returns has increased since 1980, and became significant at the beginning of the 1990s, while the elasticity of general equity total returns remained insignificant. During the 2000s, the underlying property market was able to predict nearly 30% of REIT variance in the long term. Consequently, ignoring changes in the “nature” of REITs may lead to an underestimation of the influence from the underlying property market, and misspecification of the optimal weights in the long-term inter-asset portfolio.
In Croatia and other countries of Central and Eastern Europe, as a consequence of deep financial integration and abolition of capital controls, considerable loans to households indexed to the Swiss franc have emerged. Although all of researchers of the Swiss franc do not agree entirely on whether the Swiss franc is a safe haven currency, its property of continuous appreciation is commonly accepted. There was a continuous appreciation of the Swiss franc over the Croatian kuna. This paper examines the performance of several ARCH-based models for Swiss franc against the Croatian kuna on daily data sets within time period from 1997 to 2010. Evaluating the models through standard information criteria Component ARCH (1,1) is found to be the best-fitting model.