When Opportunity Knocks: Cross-Sectional Return Dispersion and Active Fund Performance Anna von Reibnitz (ANU) 2016 CIFR/UBS Investment Management and Markets Conference

Motivation Active managers are paid to add value On average, active funds underperform after fees Which managers outperform? The managers who pursue the most active strategies (e.g. Wermers, 2003; Kacperczyk, Sialm, and Zheng, 2005; Brands, Brown, and Gallagher, 2005; Cremers and Petajisto, 2009; Amihud and Goyenko, 2013) This paper: When will they outperform?

Dispersion as Active Opportunity Cross-sectional return dispersion (RD): contemporaneous divergence of individual constituent returns from the return of the benchmark index Low dispersion: low impact of active bets High dispersion: high impact of active bets Main findings: Alpha produced by the most active funds is greatest when RD is highest The outperformance of the most active funds over the least active funds is concentrated in times of high RD A strategy of switching between highly active and passive funds based on the RD environment produces alpha of over 2.7% p.a. after all fees.

Data Fund sample: Active, U.S. equity mutual funds (CRSP) Sample period: Jan 1972 – Dec 2013 (3,048 funds) Fund activeness measure: Amihud and Goyenko (2013) “Selectivity” measure (1-R2t-1) Sort funds each month into quintiles from “High Activeness” (high 1-R2t-1) to “Low Activeness” (low 1-R2t-1) Primary performance measure: Carhart (1997) alpha Return dispersion measure: Persistence in high RD months: enables use of lags Sort months into quintiles based on RDt-1

Results Figure 2 Fund Activeness: S1 = Least active fund portfolio Most Active Figure 2 Fund Activeness: S1 = Least active fund portfolio S5 = Most active fund portfolio Return Dispersion: Q1 = Lowest return dispersion quintile Q5 = Highest return dispersion quintile Least Active High RD

Table 3: Excess Returns Note: Excess returns are the annualised raw returns of the fund portfolio in excess of the market of all NYSE, Amex and Nasdaq stocks. t-statistics are in parentheses. ***, ** and * denote significance at the 1%, 5% and 10% level.

Table 4: Carhart Alpha Note: Carhart alphas are annualised and expressed in percentage points. t-statistics are in parentheses. ***, ** and * denote significance at the 1%, 5% and 10% level.

Robustness Checks Results hold using: Additional robustness: In-sample and indicator regressions allowing for time-varying factor loadings Multivariate regressions controlling for fund-level characteristics Additional robustness: Fund portfolio sorts: quintiles, deciles Performance estimates: Carhart, CPZ, Fama-French, CAPM, raw returns Dispersion Measures: Equal-weighted, value-weighted, S&P500 stocks, all NYSE/NASDAQ/Amex stocks Measures of Activeness: R2 and Active Share Fees: Both net and gross returns Sub-Period analysis Controlling for economic recessions (NBER)

Table 14: Switching Strategy Strategy: Invest in active funds if the previous month’s dispersion is in the top 20% of the past 10 years, and otherwise invest passively in S&P500 index funds Time period: 1977-2013 for Carhart (FFC) alpha, 1981-2013 for Cremers, Petajisto and Zitzewitz (CPZ) alpha Key active portfolios: S5 (most active funds), S5/α5 (subset of most active funds with the 20% highest alpha in the previous month) Note: t-statistics based on heteroskedasticity and autocorrelation consistent standard errors clustered by fund are reported in parentheses. ***, ** and * denote significance at the 1%, 5% and 10% level.

Table 15: No-load funds Issue: Switching between funds may incur significant front-end and back-end load fees Response: Isolate switching strategy to no-load funds Strategy remains profitable: In sub-periods (pre and post 1995) With rebalancing frequencies up to six months With a one month implementation delay

Through dispersion, opportunity really can knock! Summary Cross-sectional return dispersion provides valuable insights Ex post: fund performance evaluation Ex ante: formation of active bets and signal for investors Through dispersion, opportunity really can knock!

References Amihud, Y., Goyenko, R., 2013. Mutual fund’s R2 as predictor of performance. Review of Financial Studies 26, 667-694. Brands, S., Brown, S., Gallagher, D., 2005. Portfolio concentration and investment manager performance. International Review of Finance 5, 149-174. Carhart, M., 1997. On persistence in mutual fund performance. Journal of Finance 52, 57-82. Cremers, M., Petajisto, A., 2009. How active is your fund manager? A new measure that predicts performance. Review of Financial Studies 22, 3329-3365. Cremers, M., Petajisto, A., Zitzewitz, E., 2013. Should benchmark indices have alpha? Revisiting performance evaluation. Critical Finance Review 2, 1-48. Kacperczyk, M., Sialm, C., Zheng, L., 2005. On the industry concentration of actively managed equity mutual funds. Journal of Finance 60, 1983-2011. Wermers, R., 2003. Are mutual fund shareholders compensated for active management “bets”? Working paper. University of Maryland.

When opportunity knocks: Cross-sectional return dispersion and active fund performance DISCUSSANT Paul Winter UBS @CIFRMedia