nep-rmg New Economics Papers
on Risk Management
Issue of 2008‒03‒15
eight papers chosen by
Stan Miles
Thompson Rivers University

  1. Forecasting VaR and Expected shortfall using dynamical Systems : a risk Management Strategy, By Dominique Guegan; Cyril Caillault
  2. Estimating Regime Dependent Switches in Emerging Equity Markets By Turk, Mehmet; Ozun, Alper
  3. Market Returns and Weak-Form Efficiency: the case of the Ghana Stock Exchange By Frimpong, Joseph Magnus; Oteng-Abayie, Eric Fosu
  4. Some Empirical Notes on Recent Perspectives in International Portfolio Management By Turk, Mehmet; Ozun, Alper; Cetkin, Umit
  5. Risks and Regulation of Insurance Companies. Is Solvency II the Right Answer? By Benjamin Lorent
  6. Stochastic Volatility Models in Estimation of Exchange Rates By Turk, Mehmet; Ozun, Alper
  7. A multi-horizon scale for volatility By Alexander Subbotin
  8. Changing regime volatility: A fractionally integrated SETAR model By Gilles Dufrenot; Dominique Guegan; Anne Peguin-Feissolle

  1. By: Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I); Cyril Caillault (FORTIS Investments - Fortis investments)
    Abstract: Using non-parametric (copulas) and parametric models, we show that the bivariate distribution of an Asian portfolio is not stable along all the period under study. We suggest several dynamic models to compute two market risk measures, the Value at Risk and the Expected Shortfall: the RiskMetric methodology, the Multivariate GARCH models, the Multivariate Markov-Switching models, the empirical histogram and the dynamic copulas. We discuss the choice of the best method with respect to the policy management of bank supervisors. The copula approach seems to be a good compromise between all these models. It permits taking financial crises into account and obtaining a low capital requirement during the most important crises.
    Keywords: Value at Risk - Expected Shortfall - Copula - RiskMetrics - Risk management -<br />GARCH models - Switching models.
    Date: 2008–03–06
  2. By: Turk, Mehmet; Ozun, Alper
    Abstract: High and sudden volatility in the financial markets might cause unexpected losses. Increasing volatility in the prices of financial securities follows regime shifts in the markets. In general, there exist two regimes in the financial markets, namely, “stable” and “volatile” regimes. Therefore, estimating regime shifts in financial time series is crucial for the efficient risk management. From that perspective, the regime switching probabilities in emerging stock markets are examined with one of the regime switching models called Two State MSH(2)-AR, Autoregressive Markov Switching Heteroscedasticity Model. In the empirical analysis, we use daily time series data between 09/01/2004 and 13/09/2007 from i) emerging markets including Turkey, Russia, Ukraine, Brazil and Lebanon; ii) an advanced market, namely Dow Jones Industrial Average, iii) a world stock index, MSCI (Morgan Stanley Composite Index). Using data from different markets gives us to chance of evaluating the model’s performance with different time series. In addition, finding different regimes in the indexes within the same time period means that the investor have chance to diversify their portfolios.
    Keywords: Emerging markets; Regime switches; Markov chains; Volatility ; stock exchanges
    JEL: E32 G15 F21 F36
    Date: 2008
  3. By: Frimpong, Joseph Magnus; Oteng-Abayie, Eric Fosu
    Abstract: This paper examines the weak-form efficient market hypothesis (EMH) in the case of the Ghana Stock Exchange (GSE) an emerging market. Daily returns from the Databank Stock Index (DSI) over a 5-year period 1999-2004 were used for the exercise. Random walk (RW) and GARCH(1,1) models are used as the basis for our analysis. The GSE DSI returns series exhibit volatility clustering, an indication of inefficiency on the GSE. The weak-form efficient market (random walk) hypothesis was rejected for the GSE, meaning that the market is inefficient. The inefficient market has important implications for investors, both domestic and international. Knowledge of profitable arbitrage opportunities due to market predictability serves to attract investors to diversify from more efficient markets to invest on the GSE bourse to increase their returns.
    Keywords: Ghana Stock Exchange; FINSAP; efficient market hypothesis; nonlinearity test
    JEL: G14 C12 C22
    Date: 2007–08–08
  4. By: Turk, Mehmet; Ozun, Alper; Cetkin, Umit
    Abstract: This paper examines the impacts of volatility in high yield US corporate bond prices on US, non-US and emerging market returns within a multivariate GARCH model framework. By using daily closing values of various financial instruments in different clusters, it is empirically pointed out that the volatility spillovers from the high yield US corporate bonds to different instruments in the world markets are quite high. Furthermore, different time spans are taken into consideration to examine if these affects have been changed recently. A multivariate GARCH analysis shows that the repricing in credit has propagated largely to major fixed income markets, overnight rates, and more recently to FX. In equities however, the impact has been relatively small so far. The empirical findings show that achieving portfolio diversification is not as easy as it was in the past by using some financial instruments.
    Keywords: multivariate garch; portfolio diversification; US corporate spreads; emerging markets; volatility spillover
    JEL: C51 G15
    Date: 2008–01–01
  5. By: Benjamin Lorent (Centre Emile Bernheim, Solvay Business School, Université Libre de Bruxelles, Brussels.)
    Abstract: The role of insurance sector has grown in importance. While there is a plethora of academic literature on the needs for a banking regulation, literature on insurance regulation is scarce and mainly focused on asymmetry issues. In this paper, we describe the reasons for an insurance regulation. Recent developments faced by insurers modified the risks encountered by the sector, especially liquidity risk and systemic risk. The purpose of the discussion presented here is also to outline the specificities of the new framework for the regulation of European insurance undertakings, Solvency II, as it is currently discussed to provide an appropriate response to the changing needs of insurance regulation. Our analysis leads us to conclude that Solvency II answers well to the developing insurance sector. However, caution is warranted for some areas such as evaluation of embedded options and guarantees, risk transfer and financial conglomerates.
    Keywords: Insurance, Regulation, Solvency II, Liquidity risk, Systemic risk
    JEL: G20 G22 G28
    Date: 2008–02
  6. By: Turk, Mehmet; Ozun, Alper
    Abstract: Volatility in financial markets should be correctly estimated for an efficient risk management. In emerging markets, due to relatively low trade volume, economic and political instability, and regulatory changes, higher volatility persists in financial asset prices as compared to those in advanced markets. In highly volatile markets, unexpected shifts in financial asset prices can be predicted by using flexible models enabling data filtering. In this research article, we use logarithmic normal stochastic volatility with Kalman filter and two regime switching stochastic volatility with Hamilton filter to estimate volatilities of exchange rates. In a comparative way, we examine the success of the two models in volatility estimation using time series from the Turkish markets. By employing daily USD/TRY exchange rates from 01/01/2004 to 25/07/2007, we empirically examine if the models are successful in predicting exchange rates in short-term and long-term. The article has originality in being first research article, as much as the authors know, which examines stochastic volatility models in a comparative perspective using data from Turkish exchange rate markets.
    Keywords: Regime Switching models; stochastic volatility; Hamilton filters; Kalman filters; exchange rate; Turkish lira
    JEL: G14 C14 F31
    Date: 2008
  7. By: Alexander Subbotin (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, Higher School of Economics - State University)
    Abstract: We decompose volatility of a stock market index both in time and scale using wavelet filters and design a probabilistic indicator for valatilities, analogous to the Richter scale in geophysics. The peak-over-threshold method is used to fit the generalized Pareto probability distribution for the extreme values in the realized variances of wavelet coefficients. The indicator is computed for the daily Dow Jones Industrial Averages index data from 1986 to 2007 and for the intraday CAC 40 data from 1995 to 2006. The results are used for comparison and structural multi-resolution analysis of extreme events on the stock market and for the detection of financial crises.
    Keywords: Stock market, volatility, wavelets, multi-resolution analysis, financial crisis.
    Date: 2008–03
  8. By: Gilles Dufrenot (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille II - Université Paul Cézanne - Aix-Marseille III - Ecole des Hautes Etudes en Sciences Sociales - CNRS : UMR6579); Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I); Anne Peguin-Feissolle (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille II - Université Paul Cézanne - Aix-Marseille III - Ecole des Hautes Etudes en Sciences Sociales - CNRS : UMR6579)
    Abstract: This paper presents a 2-regime SETAR model with different long-memory processes in both regimes. We briefly present the memory properties of this model and propose an estimation method. Such a process is applied to the absolute and squared returns of five stock indices. A comparison with simple FARIMA models is made using some forecastibility criteria. Our empirical results suggest that our model offers an interesting alternative competing framework to describe the persistent dynamics in modeling the returns.
    Keywords: SETAR - Long-memory - Stock indices - Forecasting
    Date: 2008–03–06

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