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
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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]
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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.
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