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Most investors' retirement portfolios have inter‐period cash inflows. The standard time‐weighted mean return (or geometric mean return) is generally used to report returns on investors' retirement portfolios. The purpose of this paper is to examine the standard time‐weighted mean return and point out additional deficiencies in the time‐weighted mean in this situation, which have not been addressed in the literature.

The paper provides examples that point out additional deficiencies that arise using geometric mean returns as estimates of an individual investor's performance.

With inter‐period cash flows the dollar‐weighted return can be affected by both timing and the sequence of the asset return series even if the investor has constant inflows or outflows of capital. In contrast for these same asset return arrays, the time‐weighted mean return measure may be unaffected by these important variations in the return arrays, and thus may misrepresent actual investor results. This is an important point that has not been addressed in the literature.

With inter‐period cash flows the dollar‐weighted return can be affected by both timing and the sequence of the asset return series even if the investor has constant inflows or outflows of capital. In contrast for these same asset return arrays, the time‐weighted mean return measure may be unaffected by these important variations in the return arrays, and thus may misrepresent actual investor results. This is an important point that has not been addressed in the literature.

When one talks of the return performance one typically refers to an average buy‐and‐hold return, also known as time‐weighted return. However, the returns of investors can be quite different. Investor returns are determined not only by the returns on the underlying assets but also by the timing and magnitude of their capital flows into and out of these assets. To account for the annual‐to‐annual variation in assets under management, a dollar‐weighted return has to be calculated. The difference between time‐weighted returns and dollar‐weighted returns is known as the performance gap. The purpose of this paper will be to investigate this in the UK property market.

Using an approach similar to that of Dichev the authors examine the performance gap in the UK direct property market using historical return data for 45 market‐segments over the time period 1981‐2009.

The results show that the performance gap was negative, i.e. investor returns were greater than asset returns. That is, UK direct property investors have shown greater returns than their underlying investments. This implies that estimates of the performance of the UK property market based on property returns do not reflect the experience of investors as a group.

This study provides the first evidence of the performance gap in the UK direct real estate market.

The purpose of this paper is to investigate whether mutual fund investors can make effective cash flow timing decisions and examine the sensitivity of these decisions to past fund performance using cash flow data at the individual fund level.

This study examines performance persistence and investor timing ability of 200 domestic equity mutual funds in Taiwan between 1996 and 2009. In particular, a performance gap measuring the difference between dollar‐weighted average monthly returns and geometric average monthly returns is used to evaluate investors' timing ability.

The empirical results show that funds that have performed well (poorly) in the previous year tend to continue performing well (poorly) in the following year, and investors' timing performance is negatively related to fund performance. The results also show that investors' timing performance is significantly and negatively related to fund size, length of fund history, and momentum‐style of funds, but positively related to value‐style funds. These results suggest that mutual fund investors are loss‐averse and demonstrate return‐chasing behavior in well‐performing funds.

The paper contributes to the mutual fund performance literature by proposing an integrated framework that jointly tests fund performance and how it affects investors' cash flow timing decisions. Furthermore, the paper individually measures investors' timing sensitivity for the current best (worst) performance funds and consecutive two‐year best (worst) performance funds, and contributes to a growing body of research on the behavior of mutual fund investors.

Introduction: According to the effective market hypothesis, investors act rationally when making an investment decision. The hypothesis assumes that investors invest in a way that maximizes their returns, taking into account the new information received. If the information released on the market is interpreted in the same way by all investors, no investor would be able to earn above the market. This hypothesis is valid in case of efficient markets. In the event that investors show irrational behavior to the information released on the market, the markets move away from efficiency. Overreaction behavior is one of the non-rational behaviors of investors. Overreaction behavior involves investors overreacting by misinterpreting the new information released to the market. According to De Bondt and Thaler’s (1985), overreaction hypothesis in the event that investors overreact to the news coming to the market, after a period the false evaluation, the price of the security is corrected with the reversal movement, without the need of any positive or negative information. Aim: The purpose of this study is to examine investors’ overreaction behavior in mergers and acquisitions. For this purpose, overreaction behavior was analyzed for companies whose stocks are traded on the Borsa Istanbul, which were involved in mergers or acquisitions. Method: In the study, companies that made mergers and acquisitions for the period 2007–2017 were determined, and abnormal returns and cumulative abnormal returns were calculated by using monthly closing price data of these companies. Moreover, whether investors overreact to the merger and acquisition decision is examined separately for one-, three- and five-year periods. Findings: As a result of the research, it has been observed that there is a reverse return for one-, three-, and five-year periods. However, it has been determined that the overreaction hypothesis is valid for only one year.

The purpose of this paper is to analyze the trading behaviors of retail investors and investigate their impacts on stock returns.

As retail investors are considered as the main noise traders in the capital market, using the trading records of Chinese retail investors from 2005 to 2009, the authors study their trading preferences and the correlation of their trades. Then, they use a multifactor model to test whether the co‐movement of stock returns could be explained by individual sentiment.

The authors' results show that the small‐cap stocks are obviously preferred by retail investors. Meanwhile, the net stock demands of retail investors are systematically correlated, even when the effect of market risk is excluded. In the perspective of the net stock demands, the authors use BSI to measure the individual sentiment, finding that individual sentiment plays an important role in the formation of the cross‐section of stock returns. However, the authors' results imply that BSI is a reverse indicator to predict the future returns, which implies that the trading behaviors of retail investors are irrational.

Consistent with behavioral theory, the authors' findings support the viewpoint that stock returns could be affected by the systematic correlated trading of retail investors. To some extent, their findings highlight the need to know more details of individual investors' trading behaviors through which the fluctuations of asset prices can be better understood.

Considering the unique data of the gold investor sentiment index in Thailand, the purpose of this paper is to investigate the bivariate dynamic relationship between the gold investor sentiment index and stock market return, as well as that between the gold investor sentiment index and stock market volatility, using the panel vector autoregression (PVAR) methodology. The author presents and discusses the findings both for the full sample and at the industry level. The results support prior literature that stocks in different industries do not react similarly to investor sentiment.

The PVAR methodology with the GMM estimation is found to be superior to other static panel methodologies due to considering both unobservable time-invariant and time-variant factors, as well as being suitable for relatively short time periods. The panel data approach improves the statistical power of the tests and ensures more reliable results.

In general, a negative and unidirectional association from gold investor sentiment to stock returns is observed. However, the gold sentiment-stock realized volatility relationship is negative and bidirectional, and there exists a greater impact of a stock’s realized volatility on gold investor sentiment. Importantly, evidence at the industry level is stronger than that at the aggregate level in both return and volatility cases, confirming the role of gold investor sentiment in the Thai stock market. The capital flow effect and the contagion effect explain the gold sentiment-stock return relationship and the gold sentiment-stock volatility relationship, respectively.

The gold price sentiment index can be used as a factor for stock return predictability and stock realized volatility predictability in the Thai equity market.

Practitioners and traders can employ the gold price sentiment index to make a profit in the stock market in Thailand.

This is the first paper to use panel data to investigate the relationships between the gold investor sentiment and stock returns and between the gold investor sentiment and stocks’ realized volatility, respectively.

The purpose of this paper is to investigate the impact of investor confidence on mutual fund performance in two relatively vulnerable but leading emerging markets, India and Pakistan.

A pooled ordinary least squared (OLS) model is used to look at two alternative measures of investor confidence and test for the relationship between investor confidence and mutual fund returns. To check the robustness of the findings, the authors also implement two-stage least squares and generalized method of moments techniques to control for unobserved heterogeneity, simultaneity and dynamic endogeneity problems in the regressors.

The paper finds that the returns of mutual funds are positively associated with investor confidence and an interaction effect exists between investor confidence and persistence in performance. The paper also confirms that returns from mutual funds are associated with different fund characteristics such as fund size, turnover, expense, liquidity, performance persistence and the fund’s age. These findings remain robust to alternative model specifications and measures of investor confidence.

While the previous literature mainly focuses on mutual fund characteristics and the macroeconomic determinants of mutual fund returns, this paper demonstrates that investor confidence plays an important role in determining mutual fund performance. The authors attribute this finding to two relatively unique features of the emerging markets in the study. A lack of awareness of mutual funds as being a low-cost investment vehicle and the interplay of cultural and behavioral changes have prevented investor’s savings from being channeled into investment products, away from gold or property.

This paper aims to analyze the effects of investors’ sentiment, return and risk series on one to another of selected exchange rates. The empirical analysis consists of a time-varying inter-dependence between the observed variables, with the focus on spillovers between the variables.

Monthly data on the index Sentix, exchange rates EUR–USD, EUR–CHF and EUR–JPY are analyzed from February 2003 to December 2019. The applied methodology consists of vector autoregression models (VAR) with Diebold and Yilmaz (2009, 2011) spillover indices.

The results of the empirical research indicate that using static analysis could result in misleading conclusions, with dynamic analysis indicating that the financial of 2007-2008 and specific negative events increase the spillovers of shock between the observed variables for all three exchange rates. The sources of shocks in the model change over time because of variables changing their positions being net emitters and net receivers of shocks.

The shortfalls of this study include using the monthly data frequency, as this was available for the authors, namely, investors are interested to obtain new information on a weekly and daily basis, not only monthly. However, at the time of writing this research, we could obtain only monthly data.

As the obtained results are in line with previous literature and were found to be robust, there exists the potential to use such analysis in the future when forecasting risk and return series for portfolio management purposes. Thus, a basic comparison was made regarding the investment strategies, which were based on the results from the estimation. It was shown that using information about shock spillovers could result in strategies that can obtain better portfolio value over time compared to basic benchmark strategies.

First, this paper allows for the spillovers of shocks in variables within the VAR models in all directions. Second, a dynamic analysis is included in the study. Third, the mentioned spillover indices are included in the study as well.

This study disentangles the investor-base effect and the information effect of investor attention. The former leads to a larger investor base and higher stock returns, while the latter facilitates the dissemination of information among investors and impacts informational trading.

Using positive volume shocks as a proxy for increased investor attention, this study evaluates the impacts of the investor-base effect and the information effect of investor attention on market correction following extreme daily returns in the US stock market from 1966 to 2018.

This study finds that the investor-base effect increases subsequent returns of both daily winner and daily loser stocks. The information effect leads to economically less significant return reversals for both the daily winner and daily loser stocks. These two effects tend to have economically more significant impacts on the daily loser stocks. The economic significance of these two effects is also related to firm size and the state of the stock market.

This study is the first to disentangle the investor-base effect and the information effect of increased investor attention. The evidence that the information effect facilitates the dissemination of new information and impacts stock returns contributes to the strand of studies on the impact of investor attention on market efficiency. This evidence also contributes to the strand of studies analyzing the impact of informational trading on stock returns. In addition, this study provides evidence for market overreaction and the subsequent correction. The results for up and down markets contribute to the literature on the investors' trading behavior.

Previous studies have found that trusting and sociable individuals are more likely to participate in the stock market and hold risky assets. The purpose of this paper is to explore if trust and sociability also are related to individual investors' stock-portfolio returns.

The authors study the questions in the paper by linking survey measures of trust and sociability to investors' actual stock portfolios.

The authors find that trusting investors acquire higher raw and risk-adjusted stock-portfolio returns, but that the returns do not differ depending on how sociable investors are. These results suggest that trust is important for investors' stock-portfolio decisions, and that trusting investors tend to perform better in the stock market than less-trusting investors.

This is, to the best of the authors’ knowledge, the first paper that relates survey measures of trust and sociability to investors' actual stock-portfolio holdings. This is important to increase the understanding for how trust and sociability are related to the financial decisions individuals makes.