Can the Chinese volatility index reflect investor sentiment?

The volatility index is the implied volatility calculated inversely from the option prices. This study investigates whether the official Chinese volatility index, iVX, can represent investor sentiment. In order to describe investor sentiment comprehensively, we build a three-dimensional investor sentiment measurement system composed of macro, meso and micro level, and decompose iVX into three components to obtain short-term, medium-term fluctuations and long-term trend by EEMD method. The relationships between iVX, its components and sentiment indexes at each level have been analyzed separately, and the empirical results reveal all components of iVX can reflect the investor sentiment at the corresponding level but to which extent they can reflect are not the same. Further we introduce the mixed-frequency dynamic factor analysis to extract the common sentiment factor, which shows stronger correlation with contemporaneous iVX, compared with the sentiment indexes at each level. The ADL model in robustness check also demonstrates the results. Our findings confirm iVX can represent the common sentiment and expectations of Chinese investors in different time scales.     

Can hedge funds time market liquidity?

We explore a new dimension of fund managers' timing ability by examining whether they can time market liquidity through adjusting their portfolios' market exposure as aggregate liquidity conditions change. Using a large sample of hedge funds, we find strong evidence of liquidity timing. A bootstrap analysis suggests that top-ranked liquidity timers cannot be attributed to pure luck. In out-of-sample tests, top liquidity timers outperform bottom timers by 4.0–5.5% annually on a risk-adjusted basis. We also find that it is important to distinguish liquidity timing from liquidity reaction, which primarily relies on public information. Our results are robust to alternative explanations, hedge fund data biases, and the use of alternative timing models, risk factors, and liquidity measures. The findings highlight the importance of understanding and incorporating market liquidity conditions in investment decision making.     

Does investor sentiment really matter?

We examine the role sentiment plays and its manifestation in the trading behavior of investors in the U.S. stock market. Our findings support the notion that sentiment-induced buying and selling is an important determinant of stock price variation. While ‘classical’ asset pricing categorizes investors who trade in ways not consistent with mean-variance optimization as ‘irrational,’ we show that this traditional view should not hastily be evoked to characterize sentiment-driven investing. We instead show that sentiment-driven investors can trade against the herd and sell when prices are overinflated as a result of over-bullishness and vice versa. The asset pricing implications of this paper are that sentiment is linked to shifts in risk tolerance and this triggers contrarian-type behavior. In sum, we uncover the following regarding the behavior of sentiment-driven investors; firstly, they are more apt to trade on survey-based indicators rather than market-based indicators. Secondly, they trade on the basis of information extracted from individual, rather than institutional, investor surveys. Thirdly, they respond asymmetrically to shifts in sentiment and trade more aggressively during periods of declining sentiment. Finally, there is asymmetry in the role of sentiment with respect to business conditions whereby such buying and selling is more pronounced during bear markets.     

Are mutual funds sitting ducks?

We find that patient traders profit from the predictable, flow-induced trades of mutual funds. In anticipation of a 1%-of-volume change in mutual fund flows into a stock next quarter, the institutions in the same 13F category as hedge funds trade 0.29–0.45% of volume in the current quarter. A third of the trading is associated with the subset of 504 identified hedge funds. The effect is stronger when quarterly mutual fund portfolio disclosure is required and among hedge funds with more patient capital. A one standard deviation higher measure of anticipatory trading by a hedge fund is associated with a 0.9% higher annualized four-factor alpha. A one standard deviation higher measure of anticipation of a mutual fund's trades by institutions is associated with a 0.07–0.15% lower annualized four-factor alpha. The effect is stronger for more constrained mutual funds.     

When does investor sentiment predict stock returns?

We examine the asymmetry in the predictive power of investor sentiment in the cross-section of stock returns across economic expansion and recession states. We test the implication of behavioral theories and evidence that the return predictability of sentiment should be most pronounced in an expansion state when investors' optimism increases. We segregate economic states according to the NBER business cycles and further implement a multivariate Markov-switching model to capture the unobservable dynamics of the changes in the economic regime. The evidence suggests that only in the expansion state does sentiment perform both in-sample and out-of-sample predictive power for the returns of portfolio formed on size, book-to-market equity ratio, dividend yield, earnings-to-price ratio, age, return volatility, asset tangibility, growth opportunities, and 11 widely documented anomalies. In a recession state, however, the predictive power of sentiment is generally insignificant.     

Multi-asset class mutual funds: Can they time the market? Evidence from the US,UK and Canada

The importance of asset allocation decisions in wealth management is well established. However, given its importance it is perhaps surprising that so little attention has been paid to the question of whether professional fund managers are skilful at timing market movement across asset classes over time. The timing literature has tended to concentrate on the timing skill of single asset class funds. Using data on US, UK and Canadian multi-asset class funds, we apply two alternative methodologies to identify the asset class timing abilities of managers. Overall, whether we apply a returns-based method or a holdings-based testing approach, we find evidence of only a tiny minority of funds with asset class timing ability.     

Why does stock-market investor sentiment influence corporate investment?

Review of Quantitative Finance and Accounting - We examine the relationship between corporate investment and investor sentiment at the firm level with the predicted change in investor sentiment....     

Can hedge funds time global equity markets? Evidence from emerging markets

This paper examines the ability of global hedge funds to time a particularly volatile asset class — emerging market equities. In particular, we study whether or not these funds can either time emerging markets as a whole, or time their exposures to different regions. Using both pooled and calendar-time approaches, we generally find no evidence of overall timing ability. However, we do find some evidence of period-specific timing ability during the financial crisis and subsequent recovery.     

Do sentiment trades explain investor overconfidence around analyst recommendation revisions?

This study examines irrational stock market reactions to analyst recommendation revisions depending on investor sentiment levels prior to analyst report announcements. We construct a firm-specific sentiment indicator by extending Huang et al. (2015, Review of Financial Studies, 28, pp.791–837). Analyst recommendation revisions have more pronounced effects for downgrades, which is attributable to sentiment effects. Domestic investors tend to react less to upgrades (downgrades) news when their prior beliefs are pessimistic (optimistic), implying that they are overconfident. The domestic investors drive sentiment trades, whereas foreign investors are not biased.     

Why are some mutual funds closed to new investors?

Fund families typically claim that closing a fund protects the fund's superior performance by preventing it from growing too large to be managed efficiently. Even though funds with better performance and larger size are more likely to be closed, there is no evidence that closing a fund can indeed protect its performance. Instead, fund closing decisions are more likely to be motivated by spillover effects – by closing a star fund, the fund family signals its superior performance and also brings investors' attention and investments to other funds in the family. Some evidence exists to suggest that the closing strategy is effective in generating higher inflows into the rest of the family, at least in the short run.     

Does favorable investor sentiment lead to costly decisions to go public?

We investigate the real effects of decisions to undertake an initial public offering of stock in periods of favorable investor sentiment. Specifically, we examine potential effects of favorable investor sentiment on investment expenditures and how effects on investment affect firm operating performance and value as well as the likelihood of survival. We find that firms going public during periods of favorable sentiment, on average, spend substantially more on investments, especially acquisitions, than firms going public in other periods. The effect of favorable investor sentiment on investment is more pronounced for younger firms. We do not find, however, that the higher investment spending in the wake of favorable sentiment leads to worse operating or stock performance. Stock returns around acquisitions announcements are also positive for firms going public in favorable sentiment periods. The preponderance of our findings indicate that decisions to go public in favorable investor sentiment periods do not lead to corporate investment decisions that harm firm performance and value.     

How well do investor sentiment and ensemble learning predict Bitcoin prices?

Investor sentiment is widely recognized as the major determinant of cryptocurrency prices. Although earlier research has revealed the influence of investor sentiment on cryptocurrency prices, it has not yet generated cohesive empirical findings on an important question: How effective is investor sentiment in predicting cryptocurrency prices? To address this gap, we propose a novel prediction model based on the Bitcoin Misery Index, using trading data for cryptocurrency rather than judgments from individuals who are not Bitcoin investors, as well as bagged support vector regression (BSVR), to forecast Bitcoin prices. The empirical analysis is performed for the period between March 2018 and May 2022. The results of this study suggest that the addition of the sentiment index enhances the predictive performance of BSVR significantly. Moreover, the proposed prediction system, enhanced with an automatic feature selection component, outperforms state-of-the-art methods for predicting cryptocurrency for the next 30 days.     

The performance of precious-metal mutual funds: Does uncertainty matter?

We studied the relative risk-adjusted returns and downside risk performance of precious-metal mutual funds (PMFs) in different uncertainty periods (pre-crisis, crisis and post-crisis) using propensity score matching techniques and difference-in-differences matching regression. For a sample of PMFs and global corporate funds quoted in USD over the period January 2005 to June 2015, we found that the relative performance of PMFs differed across uncertainty periods. Thus, they performed similarly to corporate funds in the pre-crisis period, they outperformed corporate funds regarding risk-adjusted returns but underperformed in terms of downside risk in the crisis period and they displayed a similar risk-return performance to corporate funds in the post-crisis period. Difference-in-difference estimates indicate that a shift from low to high uncertainty had a positive impact on risk-adjusted returns for PMFs, whereas this advantage dissipated when uncertainty was reduced. However, fluctuations in uncertainty had mixed effects on the relative downside risk associated with PMFs. This evidence has implications for investors who seek to gain exposure to precious metals using PMFs.     

Do mutual fund managers time market liquidity?

This paper examines mutual fund managers' ability to time market-wide liquidity. Using the CRSP mutual fund database, we find strong evidence that over the 1974–2009 period, mutual fund managers demonstrate the ability to time market liquidity at both the portfolio level and the individual fund level. Liquidity timing predicts future fund performance and the difference in the risk-adjusted returns between top and bottom liquidity-timing funds is approximately 2% per year. Funds exhibiting liquidity-timing ability tend to have longer histories, higher expense ratios, and higher turnover rates.     

Missing the marks? Dispersion in corporate bond valuations across mutual funds

We study the dispersion of month-end valuations placed on identical corporate bonds by different mutual funds. Such dispersion is related to bond-specific characteristics associated with liquidity and market volatility. The Trade Reporting and Compliance Engine (TRACE) could have contributed to the general decline in dispersion over our sample period, though other factors most likely played roles. Further tests reveal marking patterns to be consistent with returns smoothing behavior by managers. Funds with ambiguous marking policies and those holding “hard-to-mark” bonds appear more prone to smooth reported returns. From a regulatory perspective, we see little downside to requiring funds to explicitly state their marking standards.     

Bank affiliation and mutual funds’ trading strategy distinctiveness

This study investigates the effect of commercial bank affiliation on mutual fund trading strategy distinctiveness. We find that bank affiliation has a significantly positive relationship with mutual funds’ unique investment strategies, and this phenomenon exhibits better performance, supporting the benefits of bank affiliation. This association is most pronounced around macroeconomic releases, during high economic policy uncertainty periods, and among funds located within a close distance from their parent bank headquarters. Further analysis indicates that the more talented affiliated fund managers tend to pursue the distinctive strategy. Therefore, our evidence reveals that the underlying mechanisms are that affiliated funds own information advantages or hire more skilled fund managers due to the unique position of commercial banks in the economy. Finally, our results suggest that affiliated funds with a higher Strategy Distinctiveness Index attract stronger net inflows and are less exposed to risks. Our findings remain unchanged after several robustness tests.     

Does concurrent management of mutual and hedge funds create conflicts of interest?

This paper shows that conflicts of interest may exist in cases where a hedge fund manager starts a mutual fund but not in the opposite case. We compare performance, asset flows, and risk incentives to establish several key differences between these two scenarios: First, prior to concurrent management, hedge fund managers experience worse performance while mutual fund managers achieve better performance relative to their full-time peers. Second, hedge fund managers who choose concurrent management are disproportionately the ones with less experience. Their hedge funds tend to suffer a decline in performance after the event. By contrast, mutual fund managers who choose concurrent management tend to outperform their full-time peers. Based on our findings, we make important recommendations for policy makers and companies. The relevance of our recommendations extends beyond the small share of companies presently engaged in concurrent management.     

Actively managed mutual funds holding passive investments: What do ETF positions tell us about mutual fund ability?

We provide the first in-depth examination of exchange-traded funds (ETFs) within actively managed mutual fund (AMMF) portfolios to better understand why AMMFs make substantial investments in passive ETFs. We examine the association between holding ETF positions and AMMF performance, as well as indirect measures of performance, including market timing, flow management, and cash holdings. We find that over one-third of AMMFs take an ETF position between 2004 and 2015. Our results indicate that AMMFs allocating large portions of their portfolio to ETFs perform worse, by between 0.41% and 1.63% annually using various performance measures. These AMMFs also exhibit worse market timing and hold more cash. In contrast, AMMFs that hold ETFs in small amounts have similar characteristics to non-user AMMFs. Therefore, the act of holding an ETF does not signal inferior ability, however, taking large ETF positions does.