Krishna Ramaswamy

Krishna Ramaswamy
  • Edward Hopkinson, Jr. Professor of Investment Banking
  • Professor of Finance

Contact Information

  • office Address:

    3259 Steinberg-Dietrich Hall
    3620 Locust Walk
    Philadelphia, PA 19104

Research Interests: investment management in equity and bond markets, options and futures

Links: CV

Overview

Education

PhD, Stanford University, 1978; MBA, Duke University, 1973; BTech, Indian Institute of Technology, Kharagpur, India, 1971

Recent Consulting

Investment Management, Bankers Trust, International Monetary Fund

Academic Positions Held

Wharton: 1985-present (named Edward Hopkinson, Jr. Professor of investment Banking, 1998; Bankers Trust Term Associate Professor of Finance, 1985-90). Previous appointment: Columbia University. Visiting appointment: University of Chicago

Other Positions

Research Coordinator, Institute for Quantitative Research in Finance, 1979-89; Technical Staff Member, Economics Department, Bell Telephone Laboratories, 1977-79

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Research

  • Chua, C.T. Krishna Ramaswamy, Robert A. Stine (2009), Predicting Short-Term Eurodollar futures, Journal of Fixed Income, 18, 47–61.

  • Choong Tze Chua, Dean P. Foster, Krishna Ramaswamy, Robert A. Stine (2007), A Dynamic Model for the Forward Curve, Review of Financial Studies, 21, 265-310.

    Abstract: This article develops and estimates a dynamic arbitrage-free model of the current forward curve as the sum of (i) an unconditional component, (ii) a maturity-specific component and (iii) a date-specific component. The model combines features of the Preferred Habitat model, the Expectations Hypothesis (ET) and affine yield curve models; it permits a class of low-parameter, multiple state variable dynamic models for the forward curve. We show how to construct alternative parametric examples of the three components from a sum of exponential functions, verify that the resulting forward curves satisfy the Heath-Jarrow-Morton (HJM) conditions, and derive the risk-neutral dynamics for the purpose of pricing interest rate derivatives. We select a model from alternative affine examples that are fitted to the Fama-Bliss Treasury data over an initial training period and use it to generate out-of-sample forecasts for forward rates and yields. For forecast horizons of 6 months or longer, the forecasts of this model significantly outperform those from common benchmark models.

Teaching

All Courses

  • FNCE1000 - Corporate Finance

    This course provides an introduction to the theory, the methods, and the concerns of corporate finance. The concepts developed in FNCE 1000 form the foundation for all elective finance courses. The main topics include: 1) the time value of money and capital budgeting techniques; 2) uncertainty and the trade-off between risk and return; 3) security market efficiency; 4) optimal capital structure, and 5) dividend policy decisions. ACCT 1010 + STAT 1010 may be taken concurrently.

  • FNCE1008 - Corporate Finance (Honors)

    This course provides an introduction to the theory, the methods, and the concerns of corporate finance. The concepts developed in FNCE 1000 form the foundation for all elective finance courses. The main topics include: 1) the time value of money and capital budgeting techniques; 2) uncertainty and the trade-off between risk and return; 3) security market efficiency; 4) optimal capital structure, and 5) dividend policy decisions. ACCT 1010 + STAT 1010 may be taken concurrently. Honors sections require MATH 1400 or MATH 1070 as a prerequisite. Application process.

  • FNCE2170 - Financial Derivatives

    This course covers one of the most exciting and fundamental areas in finance. Financial derivatives serve as building blocks to understand broad classes of financial problems, such as complex asset portfolios, strategic corporate decisions, and stages in venture capital investing. The main objective of this course is build intuition and skills on (1) pricing and hedging of derivative securities, and (2) using them for investment and risk management. In terms of methodologies, we apply the non-arbitrage principle and the law of one price to dynamic models through three different approaches: the binomial tree model, the Black-Scholes-Merton option pricing model, and the simulation-based risk neutral pricing approach. The course covers a wide range of applications, including the use of derivatives in asset management, the valuation of corporate securities such as stocks and corporate bonds with embedded options, interest rate and credit derivatives, as well as crude oil derivatives. We emphasize practical considerations of implementing strategies using derivatives as tools, especially when no-arbitrage conditions do not hold. STAT 1020 may be taken concurrently.

  • FNCE7170 - Financial Derivatives

    This course covers one of the most exciting and fundamental areas in finance. Financial derivatives serve as building blocks to understand broad classes of financial problems, such as complex asset portfolios, strategic corporate decisions, and stages in venture capital investing. The main objective of this course is build intuition and skills on (1) pricing and hedging of derivative securities, and (2) using them for investment and risk management. In terms of methodologies, we apply the non-arbitrage principle and the law of one price to dynamic models through three different approaches: the binomial tree model, the Black-Scholes-Merton option pricing model, and the simulation-based risk neutral pricing approach. The course covers a wide range of applications, including the use of derivatives in asset management, the valuation of corporate securities such as stocks and corporate bonds with embedded options, interest rate and credit derivatives, as well as crude oil derivatives. We emphasize practical considerations of implementing strategies using derivatives as tools, especially when no-arbitrage conditions do not hold.

  • FNCE8920 - Financial Engineering

    This class covers advanced pricing models for equity, fixed income and credit derivatives. It aims at: 1) Introducing the main models used in practical applications to price and hedge derivatives; 2) Understanding their comparative advantages and limitations, as well as how they are calibrated and applied. As part of team assignments, students will be asked to calibrate and implement the models introduced in the class using software of their choice.

  • FNCE8990 - Independent Study

    Independent Study Projects require extensive independent work and a considerable amount of writing. ISP in Finance are intended to give students the opportunity to study a particular topic in Finance in greater depth than is covered in the curriculum. The application for ISP's should outline a plan of study that requires at least as much work as a typical course in the Finance Department that meets twice a week. Applications for FNCE 8990 ISP's will not be accepted after the THIRD WEEK OF THE SEMESTER. ISP's must be supervised by a Standing Faculty member of the Finance Department.

In the News

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Activity

Latest Research

Chua, C.T. Krishna Ramaswamy, Robert A. Stine (2009), Predicting Short-Term Eurodollar futures, Journal of Fixed Income, 18, 47–61.
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