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

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

Current Courses

  • FNCE100 - Corporate Finance

    This course provides an introduction to the theory, the methods, and the concerns of corporate finance. The concepts developed in FNCE 100 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. During the Fall semester there are honors sections of FNCE 100 offered. The seats in the honors sections are awarded through an application process. Please go to: https://fnce.wharton.upenn.edu/programs/course-applications for additional information. Corporate Finance is a Core course and must be taken for a grade.

    FNCE100301 ( Syllabus )

Past Courses

  • FNCE100 - Corporate Finance

    This course provides an introduction to the theory, the methods, and the concerns of corporate finance. The concepts developed in FNCE 100 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. During the Fall semester there are honors sections of FNCE 100 offered. The seats in the honors sections are awarded through an application process. Please go to: https://fnce.wharton.upenn.edu/programs/course-applications for additional information. Corporate Finance is a Core course and must be taken for a grade.

  • FNCE206 - Financial Derivatives

    This course covers one of the most exciting yet fundamental areas in finance: derivative securities. In the modern financial architecture, financial derivatives can be the most challenging and exotic securities traded by institutional specialists, while at the same time, they can also be the basic securities commonly traded by retail investors such as S&P Index Options, Beyond trading, the basic ideas of financial derivatives serve as building blocks to understand a much broader class of financial problems, such as complex asset portfolios, strategic corporate decisions, and stages in venture capital investing. The golobal derivatives market is one of the most fast-growing markets, with over $600 trillion notional value in total. It is important as ever to understand both the strategic opportunities offered by these derivative instruments and risks they imply. The main objective of this course is to help students gain the intuition and skills on (1) pricing and hedging of derivative securities, and (2) using them for investment and risk management. In terms of metholologies, 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. We discuss 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 derivatives, credit derivatives, as well as crude oil derivatives. In addition to theoretical disucssions, we also emphasize practical considerations of implementing strategies using derivatives as tools, especially when no-arbitrage conditions do not hold.

  • FNCE399 - Supervised Study in Finance

    Integrates the work of the various courses and familiarizes the student with the tools and techniques of research.

  • FNCE717 - Financial Derivatives

    This course covers one of the most exciting yet fundamental areas in finance: derivative securities. In the modern financial architecture, financial derivatives can be the most challenging and exotic securities traded by institutional specialists, while at the same time, they can also be the basic securities commonly traded by retail investors such as S&P Index Options, Beyond trading, the basic ideas of financial derivatives serve as building blocks to understand a much broader class of financial problems, such as complex asset portfolos, strategic corporate decisions, and stages in venture capital investing. The golobal derivatives market is one of the most fast-growing markets, with over $600 trillion notional value in total. It is important as ever to understand both the strategic opportunities offered by these derivative instruments and risks they imply. The main objective of this course is to help students gain the intuition and skills on (1) pricing and hedging of derivative securities, and (2) using them for investment and risk management. In terms of metholologies, 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. We discuss 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 derivatives, credit derivatives, as well as crude oil derivatives. In addition to theoretical disucssions, we also emphasize practical considerations of implementing strategies using derivatives as tools, especially when no-arbitrage conditions do not hold.

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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In the News

Wells Fargo: What It Will Take to Clean Up the Mess

A series of scandals at Wells Fargo is tainting its reputation. Wharton experts weigh in on what the bank must do to recover.

Knowledge @ Wharton - 2017/08/8
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