Broker Recommendations and Mutual Fund Trades

We investigate the alignment of mutual fund trades with brokers’ recommendations and their associated performance. Using 2,730 funds with 44,315 fund-periods between 1994 and 2005, we find that more than 20% of funds adjust their portfolios in line with brokers’ recommendations. However, funds that trade counter to these recommendations, on average, earn superior excess returns. This superior performance is most pronounced in small funds holding less-liquid stocks that trade more actively, and we attribute this to their private information having greater incremental value

Mutual fund risk: Mean reversion or gaming?

The issue of whether mutual fund managers behave as though they are competing in a tournament has been the focus of several recent studies. Tournament behavior may be influenced by managers’ interim relative performance and whether they adjust their fund’s risk by their trades to win the tournament, improve their ranking, or prevent deterioration in their present ranking. It is an empirical issue as to whether a change in intertemporal risk is intentional or simply arises from risk mean reversion. Our methodology differentiates funds that actively trade to change risk from those whose risk is changed by trades with alternative motivations. Funds that are statistically identified as trading to change return variance or tracking error variance do not exhibit risk mean reversion. Rather, funds more commonly trade to reduce tracking error variance, particularly those with already low tracking error variances. We find weak evidence that underperforming funds intentionally trade to reduce return variance, and that trades designed to change tracking error variance are not associated with prior performance

Investor Sentiment and the Performance of Mutual Funds Pursuing Momentum and Contrarian Trading Strategies

The success of mutual funds engaging in momentum and contrarian trading strategies is predicated on the identification of mispriced stocks. Stock investor sentiment betas capture salient characteristics that predispose stocks to mispricing. Funds engage in momentum and contrarian trading in equal proportions, but differ in the sentiment betas of the stocks in their portfolios. Momentum funds hold stocks with higher sentiment betas, and with a wider spread of betas compared to contrarian funds. Fund excess returns are strongly related to Baker and Wurgler’s (2007) change in sentiment index, and the mean and spread of the sentiment betas of their stocks

Investor sentiment and momentum and contrarian trading strategies: Mutual fund evidence

Stocks with high sentiment betas are more sensitive to investor sentiment, with more subjective valuations. We contend that sentiment beta also captures the duration of mispricing. Accordingly, stocks with high (low) sentiment betas provide opportunities for momentum (contrarian) traders. We form hypothetical zero investment portfolios of high (low) sentiment betas stocks, and show that momentum profits decompose to reveal positive (negative) serial correlation of idiosyncratic returns, that contribute to momentum (contrarian) profits. Furthermore, actual mutual funds identified as momentum (contrarian) traders hold stocks with higher (lower) sentiment betas. Additionally, funds adjust sentiment betas to enhance performance as sentiment changes

Systematic risk and the performance of mutual funds pursuing momentum and contrarian trades

We examine mutual fund trading activity to determine whether they rebalance their portfolios towards stocks that were recent superior performers (a momentum strategy) or towards stocks that recently underperformed (a contrarian strategy). Using 2,829 funds with 49,661 fund-periods between 1991 and 2005, we find that around 15% of the funds exhibit contrarian trading behavior with a similar percentage following a momentum strategy. We highlight the importance of a stock’s risk to traders adopting momentum and contrarian strategies. Mutual funds that follow a momentum strategy and acquire high-risk stocks improve their performance, while those following a contrarian strategy in these stocks diminish their performance. Both contrarian and momentum trading behavior by funds persists

Comparative Value-relevance of GAAP, IBES, S&P Core, Cash Earnings and Cash Flows

This study examines the impact the global financial crisis had on the value relevance of GAAP and non-GAAP earnings. We adopt the Ohlson (1995) valuation and CAR models to test the value relevance and information content of alternative earnings measures. We use six different earnings measures comprising IBES earnings, Standard & Poor’s (S&P) core earnings, cash earnings, cash flows from operations, earnings from operations adjusted to exclude special items under GAAP and income before extraordinary items under GAAP. We draw our sample from US publicly traded firms between 2002 and 2010. Our sample is partitioned into Financial and non-Financial firms, and S&P 500 and non-S&P 500 firms. The results show that investors place greater value relevance on GAAP earnings during the GFC period relative to the pre-GFC period

Mutual Fund Trades: Timing Sentiment and Managing Tracking Error Variance

We use portfolio holdings to show that mutual funds preferentially trade stocks according to the stocks‟ sentiment betas. Stocks with high sentiment betas are more responsive to investor sentiment and increase (decrease) in value as sentiment increases (decreases). Sentiment-based trades may be motivated by the opportunity to increase fund returns through timing predictability in sentiment, or by management of portfolio risk. Sentiment is mean-reverting, but its level and recent change only partially explain these trades. In contrast, 30 percent of sentiment-based trades are explained by the initial sentiment beta of funds that trade to reduce their tracking error variance

Loan loss reserves and bank stock returns: Evidence from Asian banks

This study examines the effects of the loan-loss-reserves-to-gross-loans ratio, a proxy for credit risk, on bank stock returns for a sample of 42 listed Asian banks during the period 1999-2007. By applying a panel data analysis that includes a control for market returns, book-to-market ratio, size, and country-specific factors, the results show that the ratio has a negative and significant influence on bank stock returns. Overall, the results suggest that credit risk remains a major threat to Asian banks. In addition, while loan loss reserves are needed for mitigating credit risk, investors do not consider them as good news or a credible signal concerning bank intentions to resolve problem loans

Assessing sentiment timing ability and mutual fund manager skill

We develop a method that can statistically identify fund managers that exhibit selectivity in their trades, and find that occurrences of good and bad selectivity exceed random expectation. Mutual funds exhibit selectivity by tilting their portfolios towards the better performing stocks when they buy (sell) stocks with high sentiment betas preceding an increase (decrease) in investor sentiment. Conversely, funds that incorrectly time investor sentiment exhibit bad stock selection, explaining the above random incidence of this behavior. Our method can distinguish skill from fortuitous stock selection, and provides a practical tool for evaluating the performance of fund managers

Does selectivity in mutual fund trades exploit sentiment timing?

In this study, we develop a method that can statistically identify fund managers that exhibit selectivity in their trades and find that occurrences of good and bad selectivity exceed random expectation. Mutual fund managers exhibit selectivity by tilting their portfolios toward better performing stocks when they buy (sell) stocks with high sentiment betas preceding an increase (decrease) in investor sentiment. Conversely, funds that incorrectly time investor sentiment exhibit bad stock selection, explaining the above random incidence of this behavior. Our method distinguishes skill from fortuitous stock selection and provides a practical tool for evaluating the performance of fund managers