Ali Boloorforoosh Contact Information John Molson School of Business Concordia University 1455 de Maisonnuve Blvd. W Montr´eal, QC, H3G 1M8 Phone: (514) 296 5877 e-mail: [email protected] Webpage: http://aliboloor.com Appointments Chief Analyst, Risk Quantification Nov. 2014 - present National Bank of Canada (Market Risk Division) Affiliate Assistant Professor John Molson School of Business, Concordia University Apr. 2015 - present Research Interests Theoretical and Empirical Asset Pricing, Derivative Pricing in Incomplete Markets and Markets with Friction, and Numerical Methods. Education Ph.D. Finance 2014 John Molson School of Business, Concordia University · Dissertation: “Thee Essays in Theoretical and Empirical Derivative Pricing” · Advisor: Stylianos Perrakis M.Sc. Finance Coursework 2006–2007 John Molson School of Business, Concordia University M.B.A. 2006 Sprott School of Business, Carleton University B.Sc. Mechanical Engineering 2003 School of Engineering (Fanni), University of Tehran Publication “Valuing Catastrophe Derivatives under Limited Diversification: A Stochastic Dominance Approach”, with S. Perrakis. Journal of Banking & Finance, 2013, 37, 3157-3168. Working Papers “Is Idiosyncratic Volatility Risk Priced? Evidence from the Physical and Risk-Neutral Distributions”, · Northern Finance Association Best PhD Paper Award, 2014 “Catastrophe Derivatives and Reinsurance Contracts: An Incomplete Markets Approach”, with S. Perrakis, 2014. Under review at the Journal of Risk and Insurance Works in progress “The Dynamics of Equity Correlations”, with P. Christoffersen, M. Fournier, and C. Gourieroux “Can Multifactor Volatility Market Models Capture the Structure in Idiosyncratic Volatilities?” “Volatility Risk and the Pricing Kernel in the Heston and Heston-Nandi Models”, with S. Perrakis and Q. Sun “Stochastic Dominance Evaluation of Stock Options with and without Transaction Costs”, with S. Perrakis 1 Ali Boloorforoosh Teaching Experience Lecturer John Molson School of Business, Concordia University · Options and Futures (FINA 412) · Introduction to Finance (COMM 308) 2011, 2013, 2014 2012 Fellowships and Awards Best PhD Paper Award, Northern Finance Association Doctoral Fellowship, Institut de Finance Math´ematique de Montr´eal Doctoral Fellowship, Social Sciences and Humanities Research Council Doctoral Fellowship, National Bank of Canada Fellowship, University of Tehran 2014 2011–2012 2010–2011 2007–2010 1998–2003 Computer skills Programming: Matlab, R, SAS, Stata, LATEX, Linux, Parallel Computing Database: OptoinMetrics, CRSP, Compustat Conference Presentation “Valuing Catastrophe Derivatives under Limited Diversification: A Stochastic Dominance Approach” · Mathematical Finance Days, Montr´eal (2011) · Multinational Finance Society, Rome (2011) - Discussant · Midwest Finance Association, New Orleans (2012) - Discussant “Catastrophe Derivatives and Reinsurance Contracts: An Incomplete Markets Approach” · Canadian Operational Research Society, Ottawa, 2014 “Is Idiosyncratic Volatility Risk Priced? Evidence from the Physical and Risk-Neutral Distributions” · Northern Finance Association, Ottawa, 2014 Work Experience Purchasing Manager Shob Tech., Tehran, Iran 1999–2003 Mechanical Engineer, Piping Core Sazeh Consultants, Tehran, Iran 2003–2004 Personal Married; One child Citizenship: Iran/Canada Languages: Persian (Native), English (Fluent) References Stylianos Perrakis Professor of Finance John Molson School of Business (514) 848-2424 ext 2963 [email protected] Peter Christoffersen Professor of Finance Rotman School of Management (416) 946-5511 [email protected] Lawrence Kryzanowski Professor of Finance John Molson School of Business (514) 848-2424 ext 2782 [email protected] Sergei Isaenko Associate Professor of Finance John Molson School of Business (514) 848-2424 ext 2797 [email protected] 2 Ali Boloorforoosh Abstracts Is Idiosyncratic Volatility Risk Priced? Evidence from the Physical and RiskNeutral Distributions (Job Market Paper ) We use simultaneous data from equity, index and option markets in order to estimate a single factor market model in which idiosyncratic volatility is allowed to be priced. We model the index dynamics’ P-distribution as a mean-reverting stochastic volatility model as in Heston (1993), and the equity returns as single factor models with stochastic idiosyncratic volatility terms. We derive theoretically the underlying assets’ Q-distributions and estimate the parameters of both P- and Q-distributions using a joint likelihood function. We document the existence of a common factor structure in option implied idiosyncratic variances. We show that the average idiosyncratic variance, which proxies for the common factor, is priced in the cross section of equity returns, and that it reduces the pricing error when added to the Fama-French model. We find that the idiosyncratic volatilities differ under P- and Qmeasures, and we estimate the price of this idiosyncratic volatility risk, which turns out to be always significantly different from zero for all the stocks in our sample. Further, we show that the idiosyncratic volatility risk premiums are not explained by the usually equity risk factors. Finally, we explore the implications of our results for the estimates of the conditional equity betas. Valuing Catastrophe Derivatives under Limited Diversification: a Stochastic Dominance Approach We present a new approach to the pricing of catastrophe event derivatives that does not assume a fully diversifiable event risk. Instead, we assume that the event occurrence and intensity affect the return of the market portfolio of an agent that trades in the event derivatives. Based on this approach, we derive values for a CAT option and a reinsurance contract on an insurers assets using recent results from the option pricing literature. We show that the assumption of unsystematic event risk seriously underprices the CAT option. Last, we present numerical results for our derivatives using real data from hurricane landings in Florida. Catastrophe Derivatives and Reinsurance Contracts: An Incomplete Markets Approach We apply a recently developed new approach to the pricing of catastrophe derivatives to the valuation of a reinsurance contract. Since the payoff of that contract has the form of a vertical spread, our methodology is also applicable to the valuation of such spreads in other markets. We do not assume a fully diversifiable CAT event risk. Instead, we assume that there exists a class of investors whose diversified portfolios return is negatively affected by the occurrence of the CAT event. We derive bounds for a reinsurance contract with a non-convex payoff using recent results from the option pricing literature; we also show that these bounds are tighter than the ones arising from a combination of the bounds of the options forming the spread. We also present the derivation of the same bounds based on stochastic dominance criteria, and the trading strategies exploiting the mispricings. We adopt a recursive discrete time approach as more realistic for the class of problems that we examine, and we value numerically the reinsurance contract with real data from hurricane landings in Florida. Last, we show that the limiting pricing kernels defining the bounds for derivative assets of this type are crucially dependent on the shape of the derivatives payoff function and do not have a closed form expression. 3
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