Akash Bandyopadhyay
Akash Bandyopadhyay

FINANCE
Clinical Assistant Professor of Finance

Print Overview

Akash Bandyopadhyay is a Senior Lecturer in the Finance Department. Before joining the Kellogg faculty, he was a faculty member of Finance at the Graduate School of Business of the University of Chicago (now known as Booth School of Business). He also served as a Visiting Assistant Professor of Finance at the University of Illinois at Urbana-Champaign.

While finishing his PhD, Bandyopadhyay made a leap to Wall Street through his research on equity derivatives pricing models for Banc of America Securities and seminar presentation of his models at Goldman Sachs. After graduation, he continued working as a research quant in the investment banks (at the equity derivatives risk management group of Deutsche Bank, at the derivative analytics group for the corporate and institutional clients of Merrill Lynch, and at the market risk management group of Société Générale) before returning to academia.

Akash Bandyopadhyay’s research interests are in the areas of asset pricing theory, models, and empirical tests. His current focus is incomplete markets and markets with differential information and/or partial liquidity, and financial economics beyond standard models.

Students of the University of Chicago’s Graduate School of Business (now Booth School of Business) rated Akash Bandyopadhyay as the school's "most enthusiastic finance professor" when he taught there. His finance classes were among the most popular and demanding courses at Chicago GSB (Booth). He received numerous citations and awards for teaching excellence.

Bandyopadhyay received his PhD in Theoretical Physics from the University of Illinois at Urbana-Champaign in 2001.

Print Vita
Education
PhD, 2001, Theoretical Physics, University of Illinois at Urbana-Champaign
MS, 1996, Theoretical Physics, University of Notre Dame
MSc, 1992, Physics, University of Calcutta, India
BSc, 1989, Physics, Mathematics and Statistics, Presidency College, University of Calcutta, India

Academic Positions
Senior Lecturer, Finance, Kellogg School of Management, Northwestern University, 2009-present
Adjunct Assistant Professor, Finance, Booth School of Business, University of Chicago, 2003-2008
Visiting Assistant Professor, Finance, College of Business, University of Illinois at Urbana-Champaign, 2001-2003

 
Print Research
Research Interests
Asset Pricing Theory, Models, and Empirical Tests
Derivative Securities and Markets
Equity Valuation, Investments and Portfolio Choice
Financial Econometrics
Financial Engineering
Financial Risk Management
Fixed Income Securities and Markets


 
Print Teaching
Full-Time / Part-Time MBA
Investments (FINC-460-0)

This course counts toward the following majors: Analytical Finance, Finance.

This course aims at developing key concepts in investment theory from the perspective of a portfolio manager rather than an individual investor. The goal of this class is to provide you with a structure for thinking about investment theory and show you how to address practical investment problems in a systematic manner. Instead of focusing on pure theoretical models, the emphasis is given on the empirical facts observed in asset prices in worldwide capital markets, understanding whether they manifest new dimension of systematic risk, and how to design smart portfolios to take advantage of multiple sources of systematic risk.

Topics include capital allocation and optimal portfolio selection; diversification, risk, and various models linking risks with returns, such as, the CAPM, the Fama-French 3-Factor Model (‘value’ and ‘size’ investing), ‘momentum investing’ and the Carhart’s 4-Factor Model, and Ross’s multifactor APT to account for multiple sources of systematic risk; risk-adjusted returns, measures of fund performance, and various trading strategies used by Hedge Funds; market efficiency (including empirical anomalies and behavioral finance). Among other topics, impact of borrowing constraint and transaction costs and illiquidity; risk management issues, such as, portfolio insurance; Bond valuation and the term structure of interest rates; the Black-Scholes/Merton option pricing model; etc. may be covered as time permits.

This is a quantitative course. We discuss many cases, but case studies will require ability to do statistical analysis similar to what might be applied in practice. The course develops an applied analytical framework of financial investments. Therefore students interested in this course are expected to have sound knowledge of Statistics and Regression Analysis.

Empirical Methods in Finance (FINC-970-0)

This course counts toward the following majors: Analytical Finance, Finance

This advanced course is designed for students with strong quantitative skill who want to learn modern disruptive discoveries in investments research and state-of-the-art statistical techniques of portfolio management. You will learn cutting-edge econometric methods for analyzing financial markets and programming techniques to implement them. We cover financial models from up-to-date research literature and examine ‘how’ and ‘when’ markets are beat-able. Students who plan to work in financial industry under a technical capacity, such as, as a quantitative portfolio manager (or, as a risk manager) in hedge funds or investment banks, are expected to find this course immensely rewarding.

Topics include (but not limited to): (1) multifactor models, such as the Fama-French factors, momentum strategies, and liquidity factors, (2) return predictability, (3) stochastic nature of volatility and structuring options portfolio to receive variance risk premium, (4) term structure of riskfree rates, yield curve modeling and risk-factors in bond premium, and (5) effects of illiquidity or transaction costs. Necessary statistical methods, such as, the Fama-MacBeth regression, GRS test, GMM, factor extraction via principal component analysis, Itô’s lemma and stochastic calculus (including jumps), bootstrapping of yield curve, and the techniques of Monte Carlo simulation will be developed within the course.

Expertise in running regression and doing statistical analysis in Excel (or in another platform, such as, MATLAB) is required. We will organize tutorial sessions on MATLAB. MATLAB tutorial sessions will meet throughout the quarter on Mondays 6:30PM – 8:00PM at Jacobs 4214 starting from the second week. Hedge funds seem highly impressed with MATLAB abilities. Therefore attendance in the tutorial sessions is expected and very strongly recommended.

Course grade will be based on five bi-weekly assignments (these assignments will require extensive statistical analysis of investment models and financial data, either in MATLAB or in Excel or in your choice of software) and a final comprehensive take-home project. Students will have unrestricted access to the WRDS database of financial data for working on the assignments and test.

Course Prerequisites: Finance/Economics at the level of FINC 460-0, and ideally, students must be comfortable with handling statistics and algebra in paper-and-pencil at the level of hypotheses testing, linear regression analysis, elementary matrix algebra, and basic differential and integral calculus (including Taylor series expansion). Knowledge of the prerequisite courses is necessary to succeed in this class. But hard-working well-motivated students may request waiver from the prerequisite courses by contacting the instructor via e-mail. Auditors (definition: any un-registered attendance, inside or outside of Kellogg) are not allowed in this course.



Doctoral
Special Topics in Finance: Empirical Methods in Finance (FINC-530-0)

This is an introductory course on Empirical Asset Pricing with a focus on topics of current research interest and dynamic models in continuous-time. We will examine empirical evidence of existing theory and provide a roadmap of ideas for future theoretical inquiry. Since intriguing empirical work is always guided by theory, we will cover the necessary asset pricing theory along the way.

The course has a broad coverage and a long reading list of papers. The emphasis will be on studying the current literature. Necessary econometric methods, such as, Fama-MacBeth procedure, GRS test, GMM, time-series processes, methods for continuous-time processes, such as, Itô calculus (including jumps), martingales and changes-of-measure, and techniques of Monte Carlo simulation will be developed within the course. Topics include (but not limited to): (1) linear unconditional and conditional beta pricing models (including empirical factors, such as, Fama-French model, momentum factor, models of liquidity and illiquidity risk premia, etc. and rational vs behavioral debate on robust empirical anomalies, such as, the disposition effect), (2) return predictability, (3) consumption based models of stochastic discount factor, (4) stochastic nature of volatility and existence of variance risk premium, and (5) models for term-structure of riskfree rates and factors affecting bond risk premia. Time permit, we will also discuss current state of research on long-standing empirical puzzles confronting canonical theory, such as, the equity premium puzzle.

This course is intended for first or second year PhD students in finance and economics who have successfully completed at least one quarter of econometrics and have general knowledge in basic financial economics. Expertise in running regression and doing statistical analysis in MATLAB (or in another platform) is a plus (tutorial sessions on MATLAB will be held). Review sessions will meet on Tuesdays 3:00PM – 5:00PM at Jacobs 4214 starting from the second week. Attendance in lectures and reviews are required. Course grade will be based on weekly assignments, writing referee report(s), and class presentation of a research paper.

Auditors (definition: any un-registered attendance, inside or outside of Kellogg) are not allowed in this course. Well prepared students may request waiver from the prerequisite courses by contacting the instructor via e-mail.

Course Prerequisites: ECON-480-1 AND ECON-480-2