New Economics Papers
on Risk Management
Issue of 2013‒10‒02
nine papers chosen by

  1. A Conditional Value-at-Risk Based Portfolio Selection With Dynamic Tail Dependence Clustering By De Luca, Giovanni; Zuccolotto, Paola
  2. Gauging the Safehavenness of Currencies By Alfred Wong; Tom Fong
  3. Belgium: Technical Note on Crisis Management and Bank Resolution Framework By International Monetary Fund. European Dept.
  4. A financial systemic stress index for Greece By Dimitrios P. Louzis; Angelos T. Vouldis
  5. Testing for the Systemically Important Financial Institutions: a Conditional Approach By Sessi Tokpavi
  6. Fuel Hedging, Operational Hedging and Risk Exposure– Evidence from the Global Airline Industry By Brian Lucey; Britta Berghöfer
  7. Probabilistic aspects of finance By Hans F\"ollmer; Alexander Schied
  8. Minimum Variance Portfolio Optimisation under Parameter Uncertainty: A Robust Control Approach By Bertrand Maillet; Sessi Tokpavi; Benoit Vaucher
  9. Pricing and Hedging Derivative Securities with Unknown Local Volatilities By Kerry W. Fendick

  1. By: De Luca, Giovanni; Zuccolotto, Paola
    Abstract: In this paper we propose a portfolio selection procedure specifically designed to protect investments during financial crisis periods. To this aim, we focus attention on the lower tails of the returns distributions and use a combination of statistical tools able to take into account the joint behavior of stocks in event of high losses. In detail, we propose to firstly cluster time series of stock returns on the basis of their lower tail dependence coefficients, estimated with copula functions, and secondly to use the obtained clustering solution to build an optimal minimum CVaR portfolio. In addition, the procedure is defined in a time-varying context, in order to model the possible contagion between stocks when volatility increases. This results in a dynamic portfolio selection procedure, which is shown to be able to outperform classical strategies.
    Keywords: Copula functions, Tail dependence, Time series clustering.
    JEL: C38 C58 G11
    Date: 2013–08
  2. By: Alfred Wong (Hong Kong Monetary Authority); Tom Fong (Hong Kong Monetary Authority)
    Abstract: This study assesses the 'safehavenness' of a number of currencies with a view to providing a better understanding of how capital flows tend to react to sharp increases in global risk aversion during periods of financial crisis. It focuses on how currencies are perceived by dollar-based international investors or, more specifically, whether they are seen as safe-haven or risky currencies. To assess the 'safehavenness' of a currency, we use a measure of risk reversal, which is the price difference between a call and put option of a currency. This measures how disproportionately market participants are willing to pay to hedge against appreciation or depreciation of the currency. The relationship between the risk reversal of a currency and global risk aversion is estimated by means of both parametric and non-parametric regressions which allow us to capture the relationship in times of extreme adversity, i.e., tail risk. Our empirical results suggest that the Japanese yen and, to a lesser extent, the Hong Kong dollar are the only safe haven currencies under stressful conditions out of 34 currencies vis-a-vis the US dollar.
    Keywords: Safe Haven Currency, Risk Reversal, Quantile Regression, Mixture Vector Autoregressive Models, Tail Risk, Crash Risk
    Date: 2013–09
  3. By: International Monetary Fund. European Dept.
    Keywords: Bank resolution;Bank supervision;Banking sector;Deposit insurance;Risk management;Crisis prevention;Financial Sector Assessment Program;Belgium;
    Date: 2013–05–24
  4. By: Dimitrios P. Louzis (Bank of Greece); Angelos T. Vouldis (Bank of Greece)
    Abstract: The paper develops a financial systemic stress index (FSSI) for Greece. We present a methodology for constructing and evaluating a systemic stress index which: i) adopts the suggestion of Hollo et al. (2012) [Hollo, Kremer, and Duca (2012) “CISS – A ‘Composite Indicator of Systemic Stress’ in the Financial System” ECB Working Paper 1426] to incorporate time-varying correlations between different market segments, and uses a multivariate GARCH approach which is able to capture abrupt changes in correlations; ii) utilizes both market and balance sheet data; and iii) evaluates the FSSI utilizing the results of a survey, conducted among financial experts, in order to construct a benchmark chronology of financial crises for Greece, which in turn is used to investigate whether changes in the FSSI are good indicators for financial crises. The results show that the FSSI is able to provide a precise periodization of crises.
    Keywords: Financial crisis; systemic stress; stress index; multivariate GARCH.
    JEL: G01 G10 G20 E44
    Date: 2013–03
  5. By: Sessi Tokpavi
    Abstract: We introduce in this paper a testing approach that allows checking whether two financial institutions are systemically equivalent, with systemic risk measured by CoVaR (Adrian and Brunnermeier, 2011). The test compares the difference in CoVaR forecasts for two financial institutions via a suitable loss function that has an economic content. Our testing approach differs from those in the literature in the sense that it is conditional, and helps evaluating in a forward-looking manner, the extent to which statistically significant differences in CoVaR forecasts can be attributed to lag values of market state variables. Moreover, the test can be used to identify systemically important financial institutions (SIFIs). Extensive Monte Carlo simulations show that the test has desirable small sample properties. With an application on a sample including 70 large U.S. financial institutions, our conditional test using market state variables such as VIX and various yield spreads, reveals more (resp. less) heterogeneity in the systemic profiles of these institutions compared to its unconditional version, in crisis (resp. non-crisis) period. It also emerges that the systemic ranking provided by our testing approach is a good forecast of a financial institution's sensitivity to a crisis. This is in contrast to the ranking obtained directly using CoVaR forecasts which has less predictive power because of estimation uncertainty.
    Keywords: Systemic Risk, SIFIs, CoVaR, Estimation Uncertainty, Conditional Predictive Ability Test.
    JEL: G32 C53 C58
    Date: 2013
  6. By: Brian Lucey (Institute for International Integration Studies, Trinity College Dublin); Britta Berghöfer (Institute for International Integration Studies, Trinity College Dublin)
    Abstract: The aviation industry is characterized by low profit margins and a constant struggle with skyrocketing fuel costs. Financial and operational hedging strategies serve aviation managers as a tool to counteract high and volatile fuel prices. While most research on fuel hedging has concentrated on the U.S. airline market, this paper is the first study to include airlines from Asia and Europe. We analyze 64 airlines over 10 years and find that Asian carriers are more negatively exposed than European airlines but less exposed than North American airlines. In contrast to Treanor, Simkins, Rogers and Carter (2012), this study finds less significant negative exposure coefficients among U.S. carriers. Using a fixed effects model we reject the hypothesis that financial hedging decreases risk exposure. One possibility is that the decreased volatility in jet fuel prices over the past few years has perhaps made airlines less exposed to fuel prices and hence, financial hedging less effective. However, operational hedging, defined by two proxies for fleet diversity, reduces exposure significantly. A one percent increase in fleet diversity, calculated with a dispersion index using different aircraft types, reduces the risk exposure coefficient by 2.99 percent. On the other hand, fleet diversity, calculated with different aircraft families, reduces exposure by 1.45 percent. Thus, aviation managers have to balance the fleet diversity between operational flexibility and entailed costs.
    Keywords: Airline, hedging, operational hedging, financial hedging
    JEL: G3
  7. By: Hans F\"ollmer; Alexander Schied
    Abstract: In the past decades, advanced probabilistic methods have had significant impact on the field of finance, both in academia and in the financial industry. Conversely, financial questions have stimulated new research directions in probability. In this survey paper, we review some of these developments and point to some areas that might deserve further investigation. We start by reviewing the basics of arbitrage pricing theory, with special emphasis on incomplete markets and on the different roles played by the "real-world" probability measure and its equivalent martingale measures. We then focus on the issue of model ambiguity, also called Knightian uncertainty. We present two case studies in which it is possible to deal with Knightian uncertainty in mathematical terms. The first case study concerns the hedging of derivatives, such as variance swaps, in a strictly pathwise sense. The second one deals with capital requirements and preferences specified by convex and coherent risk measures. In the final two sections we discuss mathematical issues arising from the dramatic increase of algorithmic trading in modern financial markets.
    Date: 2013–09
  8. By: Bertrand Maillet; Sessi Tokpavi; Benoit Vaucher
    Abstract: The global minimum variance portfolio computed using the sample covariance matrix is known to be negatively affected by parameter uncertainty. Using a robust control approach, we introduce a portfolio rule for investors who wish to invest in the global minimum variance portfolio due to its strong historical track record but seek a rule that is robust to parameter uncertainty. Our robust portfolio theoretically corresponds to the global minimum variance portfolio in the worst-case scenario, with respect to a set of plausible alternative estimators of the covariance matrix, in the neighbourhood of the sample covariance matrix. Hence, it provides protection against errors in the reference sample covariance matrix. Monte Carlo simulations illustrate the dominance of the robust portfolio over its non-robust counterpart, in terms of portfolio stability, variance and risk-adjusted returns. Empirically, we compare the out-of-sample performance of the robust portfolio to various competing minimum variance portfolio rules in the literature. We observe that the robust portfolio often has lower turnover and variance and higher Sharpe ratios than the competing minimum variance portfolios.
    Keywords: Global minimum variance portfolio, Parameter uncertainty, Robust control approach, Robust portfolio.
    JEL: G11 D81 C44
    Date: 2013
  9. By: Kerry W. Fendick
    Abstract: A common assumption in financial engineering is that the market price for any derivative coincides with an objectively defined risk-neutral price - a plausible assumption only if traders collectively possess objective knowledge about the price dynamics of the underlying security over short time scales. Here we assume that traders have an objective knowledge about the underlying security's price trajectories only for large time scales. We show that avoidance of arbitrage that is still feasible uniquely determines the prices of options with large expiration times, and we derive limit theorems useful for estimation of model parameters and present-value analysis of derivative portfolios.
    Date: 2013–09

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