Camille Schmidt

Portfolio Quality and Mutual Fund Performance

This study investigates how the quality of stocks owned by mutual funds affects the performance of those funds during 2000–2009. The quality of a stock is positively related to its size, while quality is inversely related to volatility. Evidently, stocks in the lowest quality decile perform particularly poorly amidst volatile market conditions with a mean monthly Daniel, Grinblatt, Titman and Wermers (DGTW) alpha 1.93% [25.73% per annum (pa)] less than high-quality stocks. Furthermore, funds which hold the lowest quality stocks exhibit substantial underperformance, particularly during market downturns, with funds in the lowest decile of quality incurring a mean monthly DGTW alpha 0.96% (12.14% pa) lower than their higher quality counterparts. Interestingly, we discover a trend to funds investing in higher quality stocks over time.

Quality Investing in an Australian Context

This study extends an examination of Quality investing in the US to the Australian market. Specifically, a Quality score is computed as the aggregate of eight fundamental accounting metrics. An investment strategy investing in the highest (lowest) quality stock quintile, that is, Quintile 5 (1) generates an average annual Daniel, Grinblatt, Titman and Wermers (DGTW)-adjusted alpha of 6.37% (−7.98%), which is significant at the 5% level over April 2000–March 2010. A two-way segmentation based on size first, and quality second, reveals that the strong positive quality effect is primarily driven by small stocks, as the average DGTW-alpha for the top-quality tercile of small stocks is 14.02%, significant at the 5% level. Statistically significant positive DGTW-alphas are also determined for quality micro and large stocks. The quality analysis is also applied to a sample of Active Equity Mutual Funds’ stock holdings. Weak evidence of the quality return premium is detected at the fund level.

Capacity Analysis for Equity Funds

This article discusses the definition and determinants of capacity and outlines a practical approach for analyzing the capacity of equity funds. It is argued that capacity analysis should focus on effective capacity, defined as the level of assets under management at which any additional investments would generate alpha below a minimum threshold at the margin, for the active component of a portfolio. The approach combines potential drivers into an integrated analysis and generates insight into the critical factors for the capacity of the strategy being analyzed. The approach is illustrated for a factor-based momentum strategy and an actual equity fund.

Global Equity Fund Performance: An Attribution Approach

We use portfolio holdings data to examine the performance of 143 global equity funds over the period 2002 to 2012. We find that the average global equity manager outperforms their benchmark by 1.2% to 1.4% per annum before fees. Attribution analysis reveals that the prime source of excess return relates to selecting stocks that beat their local markets. Modest contributions arise from country selection, most notably in emerging markets; while currency effects are mixed. Our findings support giving consideration to active management in global equity markets, at least for institutional investors who pay fees below 1% per annum.

Are funds true to label? A note on matching qualitative and quantitative information

Our contribution to funds management research is in matching qualitative information sourced from the fund manager with their own quantitative data concerning what assets they own, how they trade and how their portfolios are managed. We find that survey responses are informative of characteristic values relative to other funds, for example funds that declare higher maximum tracking errors tend to have higher tracking errors. Furthermore, self-declared number of stocks held and turnover are less indicative of future fund characteristics than actual past measures. Overall, our study suggests that the questionnaire responses do contain some information value when used by asset consultants to compare funds.

Are Funds True to Label? Matching Qualitative and Quantitative Information

Our contribution to funds management research is in matching qualitative information sourced from the fund manager with their own quantitative data concerning what assets they own, how they trade, and how their portfolios are managed. We find that survey responses are informative of characteristic values relative to other funds e.g. funds that declare higher maximum tracking errors tend to have higher tracking errors. Furthermore, self-declared number of stocks held and turnover are less indicative of future fund characteristics than actual past measures. Overall, our study suggests that the Questionnaire responses do contain some information value when used by asset consultants to compare funds.The appendices for this paper are available at the following URL: http://ssrn.com/abstract=2666818

Style factor timing: An application to the portfolio holdings of US fund managers

This study develops a style rotation model based on quarterly forecasts of style factor (SF) returns, across four style categories, generated using market and macroeconomic data. The prescriptions from this model are tested on a sample of US active equity mutual funds’ portfolio holdings. An annual buy-and-hold style timing strategy investing in the factor with the highest forecast return each quarter achieves an average annual excess return of 7.26%, significant at the 1% level during 1981–2011. However, a fund-of-fund (FoF) timing strategy investing in the funds with the greatest exposure (i.e. the preferred funds) to the style predicted to outperform over the following year does not generate statistically significant Daniel, Grinblatt, Titman and Wermers (DGTW)-adjusted performance. The lack of performance is primarily because the long-only funds are by nature unable to fully exploit the long-short SF returns. This highlights the issue of using long-short portfolio returns, particularly when evaluating fund performance.