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Jonathan Schachter, PhD

Jon is a Project Associate in Quantitative Modeling. He has over 21 years of experience in the Financial Services industry. He has deep market and credit valuation and risk experience including corporate bonds, credit-default swaps, CDOs, CLOs, ABSs, CVA, loan loss modeling, loan indemnification, and security-based loans.


  • Ph.D., Physics, University of California at Berkeley
  • M.A., Mathematical Finance, Columbia University
  • Postdoctoral Researcher, Astronomy Department, Harvard University
  • Series 7 and 63 (Lapsed due to leaving a FINRA member firm)  


  • LIBOR transition: impact on cash and derivative products denominated in USD and EUR, fallbacks, RFR modeling (especially near 0)

  • Analyzed temporal correlation properties of commodities futures time series as a prelude for inclusion in the VaR model: criteria were a low auto-correlation in each contract, and a high cross-correlation with the benchmark contract (generally 2nd nearby).

  • Tested algorithm for the determination of stressed VaR historical intervals. Recomputed VaR in spreadsheets and compared with values computed in the risk backbone.  

  • Computed CVA for client’s swaps book as year-end work for auditors.Used EAD/LGD/PD framework for ALLL. Critiqued client choice of loss distributions vs. available data.  Led team producing daily full revaluation historical VaR reports for clients, where products included vol skew risk and prepayment risk. Judicious choices were made for time series to ensure stationarity.

  • Built transaction-based return tool (with Modified Dietz method) for mutual fund portfolio managers. Takes into account day trading, dividends paid, withholding, and redemptions.

  • Developed prototype for proprietary liquid bond index — since Barclay’s Aggregate is the entire market, not just liquid issues. Index constituents were redefined monthly, but the index was priced daily, and could be used for desk’s clients to benchmark against.

Model Focus and Techniques

  • Valuation models for financial instruments: vanilla,
  • first order exotics, structured products
  • Volatility models: Local vol (Dupire), Heston, SABR.
  • Rates models: Hull-White, Black-Karasinski, LMM
  • Monte Carlo Simulation/PDEs/Trees
  • Principal Component Analysis
  • Generalized Linear ModelsPD/LGD

Programming Skills

  • R, Python, Matlab, C++, Java


Jonathan Schachter, PhD