Dan Pirjol (dpirjol)

Dan Pirjol

Teaching Associate Professor

School of Business

Education

  • PhD (1995) University of Mainz (Theoretical Physics)
  • MS (1992) University of Bucharest (Physics)

Research

My research is in financial engineering, focusing on derivatives pricing, hedging and risk management, using methods from asymptotic analysis and applied probability.

I am also interested in problems of applied mathematics motivated by simulation and implementation of industry models.

Focus areas:

​Financial mathematics
Financial risk management
Applied mathematics and numerical methods

General Information

Industry experience:

2006-2008: Merrill Lynch, Bank of America, modeling and model risk management
2008-2010: Markit Partners, quant developer
2009-2019: JP Morgan, Model risk management

Experience

My industry experience is in modeling of financial markets, derivatives pricing and risk measurement, including model risk.

Interest rates and FX markets. Stochastic modeling of the yield curve.
Equity modeling. Local volatility and stochastic volatility models.
Exotic derivatives: Asian options on equities and commodity futures.
Counterparty credit risk. XVA credit risk measures.

Institutional Service

  • FE PhD Committee Member
  • Financial Engineering seminar Member
  • Financial Engineering Seminar Member

Professional Service

  • Risks Co-Editor for a special issue: Emerging topics in finance and risk engineering. In memory of Peter Carr
  • AMMCS 2023 Conference Sesssion organizer
  • Risk Magazine Referee for Risk magazine
  • Referee for SIAM Journal on Financial Engineering (SIFIN) Referee
  • Referee for Probability in Engineering and Informational Sciences Referee for Probability in Engineering and Informational Sciences

Professional Societies

  • AMS – American Mathematical Society Member
  • INFORMS – The Institute for Operations Research and the Management Sciences Member

Selected Publications

Book

  1. Pirjol, D.; Zhu, L. (2024). Emerging topics in finance and risk engineering. Basel: MDPI.
    https://www.mdpi.com/journal/risks/special_issues/emerging_topics_in_finance_and_risk_engineering_in_memory_of_Peter_Carr.

Journal Article

  1. Pirjol, D.; Zhu, L. (2024). Asymptotics for short maturity Asian options in jump-diffusion models with local volatility. Quantitative Finance (3-4 ed., vol. 24, pp. 433-449). London: Taylor and Francis.
    https://www.tandfonline.com/doi/full/10.1080/14697688.2024.2326114.
  2. Glasserman, P.; Pirjol, D.; Wu, Q. (2024). Tail risk monotonicity under temporal aggregation in GARCH(1,1) models. International Journal of Theoretical and Applied Finance (2-3 ed., vol. 26, pp. 2350005). Singapore: World Scientific.
    https://www.worldscientific.com/doi/abs/10.1142/S0219024923500292.
  3. Pirjol, D.; Zhu, L. (2023). Short maturity asymptotics for option prices with interest rates effects. International Journal of Theoretical and Applied Finance (vol. 26, pp. 2350023). Singapore: World Scientific.
    https://www.worldscientific.com/doi/10.1142/S0219024923500231.
  4. Pirjol, D. (2023). Subleading corrections to the implied volatility of an Asian option in the Black-Scholes model. International Journal of Theoretical and Applied Finance (2 ed., vol. 26, pp. 2350005). Singapore: World Scientific.
    https://www.worldscientific.com/doi/10.1142/S021902492350005X.
  5. Pirjol, D.; Zhu, L. (2023). Asymptotics of the Laplace transform of the time integral of the geometric Brownian motion. Operations Research Letters (3 ed., vol. 51, pp. 346-352). Elsevier.
    https://www.sciencedirect.com/science/article/pii/S0167637723000597.
  6. Glasserman, P.; Pirjol, D. (2023). Total Positivity and Relative Convexity of Option Prices. Frontiers in Mathematical Finance (1 ed., vol. 2, pp. 1-32). American Institute of Mathematical Sciences.
    https://www.aimsciences.org/article/doi/10.3934/fmf.2023001.
  7. , P. G.; Pirjol, D. (2023). W-shaped implied volatility curves and the Gaussian mixture model. Quantitative Finance (4 ed., vol. 23, pp. 557-577). London.
    https://www.tandfonline.com/doi/full/10.1080/14697688.2023.2165448.
  8. Pirjol, D.; Lewis, A. (2022). Proof of non-convergence of the short-maturity for the SABR model. Quantitative FInance (9 ed., vol. 22, pp. 1747-1757). London: Taylor & Francis.
    https://www.tandfonline.com/doi/abs/10.1080/14697688.2022.2071759?journalCode=rquf20.
  9. Nandori, P.; Pirjol, D. (2021). On the distribution of the time-integral of the geometric Brownian motion. Journal of Computational and Applied Mathematics (1 March 2022 ed., vol. 402, pp. 113818). Amsterdam: Elsevier Publishers.
    https://www.sciencedirect.com/science/article/abs/pii/S0377042721004404?via%3Dihub.
  10. PIRJOL, D. (2020). Small-t expansion for the Hartman-Watson distribution. Methodology and Computing in Applied Probability (vol. to be announced). New York City: Springer.
  11. Pirjol, D.; Zhu, L.. Asymptotics of the time-discretized log-normal SABR model: The volatility surface. Probability in Engineering and Informational Sciences (vol. volume pending - article published online, pp. 1-33). Cambridge: Cambridge University Press.
    http://journals.cambridge.org/action/displayJournal?jid=PES.

Magazine/Trade Publication

  1. Pirjol, D.; Zhu, L. (2021). What is the volatility of an Asian option?. Risk (May 2021 ed., pp. 74-79). London: risk.net.
    https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3875929.

Courses

FE 620: Pricing and Hedging
FE 570: Market Microstructure
FE 670: Algorithmic Trading
FE 535: Introduction to Financial Risk Management
QF 302: Introduction to Market Microstructure
QF 435: Financial Risk Management for Capital Markets