hero image
Robert Novy-Marx - University of Rochester. Rochester, NY, US

Robert Novy-Marx Robert Novy-Marx

Lori and Alan S. Zekelman Distinguished Professor of Finance | University of Rochester

Rochester, NY, UNITED STATES

Robert Novy-Marx is an award-winning expert on empirical asset pricing, empirical methods, and public finance.

Areas of Expertise (3)

Public Finance

Empirical Asset Pricing

Empirical Methods

Media

Publications:

Documents:

Photos:

Videos:

Professor Robert Novy-Marx on the Basis for a Value Premium Government Pensions Getting Worse by the Day Testing Strategies Based on Multiple Signals

Audio:

Biography

Novy-Marx earned the Fama/DFA Prize for the best capital markets/asset pricing paper in the Journal of Financial Economics (2012 and 2013), the Smith-Breeden Prize for the best capital markets paper in the Journal of Finance (2011), the Spängler IQAM Prize for the best paper in the Review of Finance (2011), and the Mill's Prize for the best paper in Real Estate Economics. Novy-Marx is also a former professional triathlete, a member of the National Bureau of Economic Research and taught at the Booth School of Business before coming to the Simon School.

Education (2)

University of California, Berkeley: PhD, Finance 2003

Swarthmore College: BA, Physics 1991

Selected Media Appearances (2)

Detroit the beginning of the end of public-sector pensions?

Fox Business  tv

2013-12-12

Simon Business School Professor Robert Novy-Marx on what Detroit’s bankruptcy means for public-sector workers across the country.

Media Appearance Image

view more

The NEXT 10 City Pensions That Will Run Out Of Money

Insider  online

2010-12-27

Projections by Robert Novy-Marx and Joshua Rauh show the average city has $15,000 per household in unfunded pension liabilities. These massive liabilities are ignored by common government accounting.

Media Appearance Image

view more

Selected Articles (4)

Comparing Cost-Mitigation Techniques

Financial Analysts Journal

Robert Novy-Marx and Mihail Velikov

2018-10-21

This paper compares the efficacy of three common transaction cost mitigation techniques: limiting a strategy to cheap-to-trade securities, rebalancing a strategy less frequently, and “banding,” which imposes a higher hurdle for actively trading into a position than for maintaining an established position. All three strategies significantly reduce transaction costs, but the techniques that reduce turnover have less negative impact on strategy gross performance than limiting trade to low cost securities. Banding is more effective than simply reducing rebalancing frequencies, because banding yields similar trading cost reductions while maintaining a better exposure to the underlying signal used to select stocks.

view more

A Taxonomy of Anomalies and their Trading Costs

Review of Financial Studies

Robert Novy-Marx and Mihail Velikov

2015-01-29

This paper studies the performance of a large number of anomalies after accounting for transaction costs, and the effectiveness of several transaction cost mitigation strategies. It finds that introducing a buy/hold spread, which allows investors to continue to hold stocks that they would not actively trade into, is the single most effective simple cost mitigation strategy. Most of the anomalies that we consider with one-sided monthly turnover lower than 50% continue to generate statistically significant net spreads, at least when designed to mitigate transaction costs. Few of the strategies with higher turnover do. In all cases transaction costs reduce the strategies’ profitability and its associated statistical significance, increasing concerns related to data snooping.

view more

Economic and financial approaches to valuing pension liabilities

Journal of Pension Economics and Finance

Robert Novy-Marx

2015-01-29

Financial economics holds that payment streams should be valued using discount rates that reflect the cash flows’ risks. In the case of pension liabilities, the appropriate discount rate for a pension fund's liabilities is the expected rate of return on a portfolio that would be held under a liability-driven investment policy. The valuation of defined benefit pension obligations involves choices revolving around deciding: (1) what future benefit payments to recognize today (i.e., which liability concept to use); and (2) from whose point of view to value the liabilities. Moving towards modeling, the distribution of future liabilities using a ‘risk-neutral’ framework, would allow for calculating the present value of the future liabilities more accurately. This would provide policymakers with information more relevant for the decision-making, and it would also permit easier communication of the risks facing the Pension Benefit Guaranty Corporation's PIMS model via a single univariate statistic.

view more

Linking Benefits to Investment Performance in US Public Pension Systems

Journal of Public Economics

Robert Novy-Marx and Joshua Rauh

2014-08-01

This paper calculates the effect that introducing risk-sharing during either retirement or the working life would have on public sector pension liabilities. We begin by considering the introduction of a variable annuity for the retirement phase in which positive benefit adjustments are granted each year only if asset returns surpass 5%. This change would reduce unfunded accrued liabilities by over half, and would lower the annual contribution increases required to target full funding in 30 years by 44%. Alternative measures that have similar effects on costs include increasing employee contributions by 10.3% of pay while keeping benefits unchanged; or giving employees a collective DC plan with an employer contribution of 10% of pay for future service. If there is a minimum guarantee that benefits cannot fall below their initial levels, the impact of introducing variable annuities is substantially smaller. We discuss these results in the context of models of lifecycle portfolio choice, and analyze the conditions under which lifecycle agents might receive utility gains from the implementation of variable annuities.

view more