Department of Management Studies
Indian Institute of Science, Bangalore-560012
Venue: Seminar hall
Date & Time: 28/07/2023 at 11:30 AM
SPEAKER:
Dr Thomas K Philips,
Adjunct Faculty at the Department of Finance and Risk Engineering, Tandon School of Engineering,
NYU
Entitled:
“Cyclically Adjusted Price/Earnings Ratio (CAPE) as a Predictor of Long -Term Equity Returns”.
Abstract:
Professor Robert Shiller’s cyclically adjusted price/earnings ratio (CAPE) has proven to be a powerful descriptor, as well as a useful predictor, of long-term equity returns in the United States and many global markets. CAPE uses a 10-year average of real earnings to simultaneously filter noise in earnings and to estimate corporate profitability over a business cycle.
In this talk, Dr Thomas will explain CAPE’s theoretical underpinnings and simplify its methodology by separating the filtering of noise from the detection of cyclicality in earnings. In addition, he accounts for an empirical nonlinearity in the relationship between valuation ratios and equity market returns and combines two robust non-linear forecasts to create an improved forecast of the 10-year forward returns of the S&P 500. He will also explain why robust estimators are of particular importance in finance, and why so many predictive models perform poorly out-of-sample.
About the Speaker:
Dr Thomas K Philips is an accomplished senior investment professional, researcher, educator, author, and subject matter expert on risk management, portfolio management, performance measurement, and valuation. He currently teaches Quantitative Portfolio Management and Valuation Theory in the Department of Finance and Risk Engineering at NYU’s Tandon School of Engineering.
Thomas is the former Global Head of Front Office Risk for the Institutional Division of BNP Paribas Asset Management. In that role, he directly oversaw and led the organisation in many crucial areas including risk management, risk systems, risk budgeting, and client advisory, and was a member of the senior management team. Prior to this, he completed his PhD in Computer Science at the University of Massachusetts, Amherst, MA.