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on Risk Management |
| By: | Boudt, Kris; Peterson, Brian; Croux, Christophe |
| Abstract: | Modified Value at Risk (VaR) is an estimator of VaR based on the Cornish-Fisher expansion. It is fast to compute and reliable for non-normal returns. In this paper, we introduce modified Expected Shortfall as a new analytical estimator for Expected Shortfall (ES), another popular measure of downside risk. We give all the necessary formulas for computing portfolio modified VaR and ES and for decomposing these risk measures into the contributions made by each of the portfolio holdings. This new methodology is shown to be very useful for analyzing the risk properties of portfolios of alternative investments. |
| Keywords: | Alternative investments; Component Value at Risk; Cornish-Fisher expansion; downside risk; expected shortfall; portfolio; risk contribution; Value at Risk. |
| JEL: | C13 C22 G11 |
| Date: | 2007–08–17 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:5108&r=rmg |
| By: | Pospisil, Libor; Vecer, Jan; Xu, Mingxin |
| Abstract: | The main idea of this paper is to introduce Tradeable Measures of Risk as an objective and model independent way of measuring risk. The present methods of risk measurement, such as the standard Value-at-Risk supported by BASEL II, are based on subjective assumptions of future returns. Therefore two different models applied to the same portfolio can lead to different values of a risk measure. In order to achieve an objective measurement of risk, we introduce a concept of {\em Realized Risk} which we define as a directly observable function of realized returns. Predictive assessment of the future risk is given by {\em Tradeable Measure of Risk} -- the price of a financial contract which pays its holder the Realized Risk for a certain period. Our definition of the Realized Risk payoff involves a Weighted Average of Ordered Returns, with the following special cases: the worst return, the empirical Value-at-Risk, and the empirical mean shortfall. When Tradeable Measures of Risk of this type are priced and quoted by the market (even of an experimental type), one does not need a model to calculate values of a risk measure since it will be observed directly from the market. We use an option pricing approach to obtain dynamic pricing formulas for these contracts, where we make an assumption about the distribution of the returns. We also discuss the connection between Tradeable Measures of Risk and the axiomatic definition of Coherent Measures of Risk. |
| Keywords: | dynamic risk measure; conditional value-at-risk; shortfall |
| JEL: | G13 G28 |
| Date: | 2007–09–27 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:5059&r=rmg |
| By: | Marco S. Matsumura |
| Abstract: | We use macro finance models to study the interaction between macro variables and the Brazilian sovereign yield curve using daily data. We calculate the model implied default probabilities and a measure of the impact of macro shocks on the probabilities. An extension of the Dai-Singleton identification strategy for Gaussian models with latent and observable factors is described in order to estimate our models. Among the tested variables, VIX is the most important macro factor affecting short term bonds and default probabilities and the Fed short rate is the most important factor affecting the long term default probabilities. |
| Date: | 2006–12 |
| URL: | http://d.repec.org/n?u=RePEc:ipe:ipetds:1241&r=rmg |
| By: | Leo de Haan; Jan Kakes |
| Abstract: | We investigate the capital structure of 350 Dutch insurers during the period 1995-2005. Our main findings are: (1) a small company size, a mutual organisation, high profitability, large equity investments, and being a fire insurer, all contribute to higher solvency margins; (2) minimum solvency requirements from the supervisor are less easy to explain by firm characteristics and do not correlate positively with risk; (3) neither do insurers follow solvency requirements closely; (4) most insurers have surplus capital which, together with a large company size and high profitability, reduces the risk of insolvency. |
| Keywords: | Insurance companies; Capital structure; Solvency requirements |
| JEL: | G22 G32 |
| Date: | 2007–08 |
| URL: | http://d.repec.org/n?u=RePEc:dnb:dnbwpp:145&r=rmg |
| By: | Ilya, Gikhman |
| Abstract: | In this article we discuss fundamentals of the debt securities pricing. We begin with a generalization of the present value concept. Though the present value is the base valuation method in the modern finance we will illustrate that this concept does not sufficiently accurate in producing instrument pricing. The incompleteness of the unique present value approach stems from variability of the interest rates. Admitting variability of the interest rates we define two present values one for buyer other for seller. Therefore future buyer and seller cash payments can be described by the correspondent present values. Usually used assumption that future interest on investment over a specified time period would be the same as before specified period is a theoretical simplification that might be admitted or not. Admitting such assumption leads to eliminating an important component of the market risk. Recall that the assumption that a future payment can be invested with the same constant interest rate equal to the one used in the past is a component of the group conditions that specify frictionless of the market. We use this new concept that splits present value within two counterparties to outline details of the new valuation method of the fixed income securities. The primary goal of this paper is a credit derivative pricing method of the risky debt instruments. First we introduce a formal definition of the default. It somewhat close but does not coincide with the reduced form of the default setting. |
| Keywords: | default; risky bond; reduced form model; credit risk; |
| JEL: | G13 G12 |
| Date: | 2007–10–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:1450&r=rmg |
| By: | Torben G. Andersen; Oleg Bondarenko |
| Abstract: | The notion of model-free implied volatility (MFIV), constituting the basis for the highly publicized VIX volatility index, can be hard to measure with accuracy due to the lack of precise prices for options with strikes in the tails of the return distribution. This is reflected in practice as the VIX index is computed through a tail-truncation which renders it more compatible with the related concept of corridor implied volatility (CIV). We provide a comprehensive derivation of the CIV measure and relate it to MFIV under general assumptions. In addition, we price the various volatility contracts, and hence estimate the corresponding volatility measures, under the standard Black-Scholes model. Finally, we undertake the first empirical exploration of the CIV measures in the literature. Our results indicate that the measure can help us refine and systematize the information embedded in the derivatives markets. As such, the CIV measure may serve as a tool to facilitate empirical analysis of both volatility forecasting and volatility risk pricing across distinct future states of the world for diverse asset categories and time horizons. |
| JEL: | C51 C52 G12 G13 |
| Date: | 2007–09 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:13449&r=rmg |
| By: | S. Boragan Aruoba; Francis X. Diebold; Chiara Scotti |
| Abstract: | We construct a framework for measuring economic activity in real time (e.g., minute-by-minute), using a variety of stock and flow data observed at mixed frequencies. Specifically, we propose a dynamic factor model that permits exact filtering, and we explore the efficacy of our methods both in a simulation study and in a detailed empirical example. |
| Date: | 2007 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgif:901&r=rmg |
| By: | Jokipii, Terhi (Stockholm School of Economics); Milne, Alistair (Bank of Finland and Cass Business School) |
| Abstract: | Using an unbalanced panel of accounting data from 1997 to 2004 and controlling for individual bank costs and risk, we find capital buffers of the banks in the EU15 have a significant negative co-movement with the cycle. For banks in the accession countries there is significant positive co-movement. Capital buffers of commercial and savings banks, and of large banks, exhibit negative co-movement. Those of co-operative and smaller banks exhibit positive co-movement. Speeds of adjustment are fairly slow. We interpret these results and discuss policy implications, noting that negative co-movement of capital buffers will exacerbate the procyclical impact of Basel II. |
| Keywords: | Bank capital; bank regulation; business cycle fluctuations |
| JEL: | G21 G28 |
| Date: | 2007–07–15 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:sifrwp:0056&r=rmg |
| By: | Hasseltoft, Henrik (Swedish Institute for Financial Research) |
| Abstract: | This paper shows that the long-run risk model of Bansal and Yaron (2004) is able to simultaneously explain the dynamics and cyclical properties of interest rates and the level and volatility of equity returns. Specifically, the model accounts for deviations from the expectations hypothesis of interest rates, the upward sloping nominal yield curve, the downward sloping term structure of volatility and the predictive power of the yield spread. Real (nominal) rates are positively (negatively) correlated with consumption growth and the nominal yield spread predicts future real consumption growth, excess stock returns and inflation. The cyclical properties of nominal interest rates are shown to critically depend on the value of the elasticity of intertemporal substitution and on the correlation between consumption and inflation. The driving forces of the model are uncertainty about expected consumption growth, time-varying volatility of consumption growth and deviations from the Fisher hypothesis. |
| Keywords: | long run risk; cyclicality; interest rates |
| JEL: | E43 G12 |
| Date: | 2007–07–15 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:sifrwp:0058&r=rmg |
| By: | Athanasios Bolmatis; Evan G. Sekeris |
| Abstract: | In this paper we develop information based factors which outperform other popular factors used in the multifactor pricing literature such as the Fama and French size and book-to-market factors. The first factor is based on the age of an asset, measured by the number of months since the asset’s IPO, while the second factor is based on the percentage of trading days an asset does not trade in a given year. Both factors attempt to capture the quality and speed of information diffusion on the market. Our information factors perform particularly well on momentum portfolios, which, Hong et al (2000) have shown to result from gradual-information diffusion. This gradual information diffusion explanation is consistent with the information argument underlying our factors, namely that, assets plagued with information problems can be miss-priced for sustained periods of time. Furthermore, our multifactor model successfully prices most industry portfolios and performs as well as the Fama and French model when pricing the 25 size/book-to-market sorted portfolios. |
| Keywords: | Investments ; Stock market ; Asset pricing ; Capital assets pricing model |
| Date: | 2007 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedbqu:qau07-6&r=rmg |