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Akash Bandyopadhyay
Akash Bandyopadhyay

FINANCE
Senior Lecturer 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 comprehensive study of financial investments will cover active portfolio strategies in stocks and bonds, optimal portfolio selection from the perspective of individual and institutional investors, and the role of style and performance benchmarks in portfolio management. Special topics such as performance evaluation, role of options and futures, liquidity and trading costs, and potential investment strategies to exploit mispricing in financial assets (such as, those used by the hedge funds) will also be covered. 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 dimensions of systematic risk. This is a quantitative course. The course develops an applied analytical framework of financial investments. Therefore students interested in this course are expected to have sound knowledge of basic statistics and regression analysis.

Empirical Methods in Finance (FINC-970-0)
This course is an introduction to the models and techniques required to do empirical analysis in finance. The aim is to familiarize students with the important empirical facts observed in the asset markets and the essential quantitative tools to analyze them. Students will learn the statistical methodologies for analyzing financial markets, study the classic literature that characterize observed movements in security prices, and examine statistical tests to determine whether markets are efficient. Topics include but not limited to (1)multifactor models for understanding the cross-sectional pattern of average returns, such as value-growth and momentum effects, (2)time variation in asset returns and return predictability, (3)robust optimal portfolio selection, (4)stochastic nature of volatility and volatility risk premium, (4)performance evaluation of hedge funds, (5)term structure of interest rates, and (6)effects of market imperfections, such as, illiquidity, transaction costs, and short-sell restrictions. Necessary econometric methods, such as, the panel and time-series regressions, various time-series processes, the models for continuous-time processes, and techniques of Monte Carlo simulation will be developed within the course.

This course is intended for MBA and PhD students in finance. We will read a selection of classic research articles and attempt to replicate those studies by using up-to-date actual asset price data. MBA students who plan to work in the asset management industry under a technical capacity (such as, managing portfolios in hedge funds) are expected to find this course immensely beneficial. This is a quantitative course, but we will keep the formal technical requirements at the minimal level. Students must be comfortable with basic calculus, elementary matrix algebra, regression analysis, and statistics at the level of hypotheses testing. Expertise in running regression and doing statistical analysis in EXCEL or STATA or MATLAB (or in another platform) is required. Hedge funds seem impressed with MATLAB abilities. We will organize tutorial sessions on MATLAB.

Prerequisites: MBA Students: FINC-460 or DECS-434 or IEMS 401 or permission of instructor. PhD Students: None.

Doctoral
Special Topics in Finance (FINC-530-0)
This course is an introduction to the models and techniques required to do empirical research in asset pricing focusing on current empirical work in finance. The aim is to familiarize students with the important empirical facts observed in the asset markets and the essential quantitative tools to analyze them. Students will learn the statistical methodologies for analyzing financial markets, study the classic literature that characterize observed movements in security prices, and examine statistical tests to determine whether markets are efficient. Topics include but not limited to (1)multifactor models for understanding the cross-sectional pattern of average returns, such as value-growth and momentum effects, (2)time variation in asset returns and return predictability, (3)robust optimal portfolio selection, (4)stochastic nature of volatility and volatility risk premium, (4)performance evaluation of hedge funds, (5)term structure of interest rates, and (6)effects of market imperfections, such as, illiquidity, transaction costs, and short-sell restrictions. Necessary econometric methods, such as, the panel and time-series regressions, various time-series processes, the models for continuous-time processes, and techniques of Monte Carlo simulation will be developed within the course. This course is intended for PhD as well as MBA students in finance. We will read a selection of classic research articles and attempt to replicate those studies by using up-to-date actual asset price data. Familiarity with MATLAB (or in another statistical platform, such as STATA) is a plus. We will organize tutorial sessions on MATLAB. Course grade will be based on writing a referee report and a class presentation on a current research paper (AFA discussant style).