David Shimko Financial Executive Professor

Professor David Shimko is the founder and principal consultant of Wall Street Scholars. He currently teaches valuation, financial engineering and risk management in the FRE Department of New York University's Tandon School of Engineering.

At Wall Street Scholars, David works with clients globally in evaluating, designing and implementing risk management policies, strategies, programs and evaluation tools. He worked first with Risk Capital (1999-2007) and then independently (2007-2017) to provide high-level strategic risk advice, expert witness testimony, analytical systems, and tools in the fields of valuation, risk management and risk governance. From 1999-2004, he was also an Adjunct Professor of Finance at the Harvard Business School.

Before co-founding Risk Capital, David worked with Bankers Trust as principal and head of risk management advisory group. He patented and co-developed CoVar, an initiative of Bankers Trust designed to provide credit risk management services to the energy industry.

Prior to Bankers Trust, he was Vice President and head of Risk Management Research at J.P. Morgan Securities , responsible for ongoing research into strategic and analytical commodity derivatives research on Morgan's trading desk.

• Doctorate (Finance)
  1982-1987, Northwestern University

Finance in Continuous Time: A Primer

We begin with the assumption that the reader either is familiar with stochastic processes in discrete time or has experience in time series analysis. We use the discrete-time processes to motivate intuition for the continuous-time processes; the reader then discovers how these processes might be applied to variables of financial interest. The properties of arithmetic Brownian motion (random walk), geometric Brownian motion (proportional random walk), and the Ornstein-Uhlenbeck processes (mean-reverting) are presented so that the reader may check the formulation of financial models for economic meaningfulness. An elementary form of the famous Itô's Lemma is presented in Section 3, along with its multivariate extensions and extension to jump processes. This section motivates the intuition behind Itô's Lemma and facilitates student understanding. The chapter ends with financial applications of Itô's Lemma and by showing how to derive some elementary asset prices. The chapter should be read in its entirety, since later sections depend critically upon developments in earlier sections. Students should attempt all problems at the end of the chapter.

Financial Executive David Shimko Aug 2025 Data and Statistics 790

Dynamic Implied Probability: An Application to 0DTE Options

We take the current market pricing of an option chain for any maturity as given and propose a robust method for simulating and predicting its value at future points in time. The model bypasses traditional option valuation approaches, directly focusing on changes in the implied (risk-neutral) probability distributions of future underlying values. It eliminates the need for differential implied volatilities across strikes, offering a simplified framework. These insights can be used for forecasting option prices, assessing risk, and optimizing trading strategies. The Dynamic Implied Probability (DIP) model is particularly well-suited for 0DTE options, which expire on the same day they are bought or sold.

Financial Executive David Shimko Apr 2025 Derivatives 1,452

Finance in Continuous Time: A Primer (out of print)

This textbook introduces students to the basics of stochastic calculus while inviting them to solve cash flow valuation problems. This provides a useful foundation for the further study of derivatives pricing. Numerous exercises are provided with solutions.

Financial Executive David Shimko Feb 2024 Derivatives 1,321

A Structural Model for Capital Asset Prices

Reframing modern portfolio theory with Gaussian cash flows rather than percentage returns, the CFPM (cash flow portfolio model) sets a structural foundation for valuing both traditional capital assets and derivatives. Asset prices are shown to be decreasing functions of both cash flow covariances and variances. The usual single-period CAPM formulas can be derived, but the expected returns are determined endogenously. All risk is implicitly priced in expected returns, leading to reinterpreted rules for portfolio selection and capital budgeting. Derivatives obey the same total covariance-based pricing relationships as cash flows, except that they exist in zero net supply. Together with a single no-arbitrage convexity constraint, the Bachelier and Black-Scholes/Merton option pricing models are derived in a discrete time setting without continuous trading. The closed-form CFPM extends to multiple periods. The resulting model aspires to replace multiperiod discounting of cash flows at constant single-period CAPM discount rates.

Financial Executive David Shimko Feb 2024 Asset Valuation 1,473