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The purpose of this study is to examine the market‐timing ability of mutual fund flows and how fund investors conduct asset allocation in response to market volatility.

The paper compares the abnormal returns of net inflow funds with those of net outflow funds, and it explores the performance gap between them based on a model that incorporates both market return timing and market volatility timing. The asset allocation pattern of fund investors and its relation to market volatility are also investigated.

This study finds that funds that receive net money inflows fail to earn risk‐adjusted abnormal returns, while funds with net outflows earn statistically significant negative abnormal returns. Neither the net inflow funds nor the net outflow funds show any ability to time the market return, but there is some evidence that net inflow funds exhibit an ability to time market volatility. Because cash holdings of the net outflow funds are much lower than that of the net inflow funds, it is concluded that the underperformance of net outflow funds is to an extent an asset fire sale.

The study results show that fund investors on the whole are driven by market volatility, and they do not have an ability to time the market return. The results do not exclude the possibility that a small number of investors possess market timing skills.

The study demonstrates the importance of funds' liquidity management through investor reaction to dynamic market conditions.

The current and ongoing controversy that has come to be known as the “Mutual Fund Scandal of 2003” was based in large part on abusive market timing activities that were allowed to occur in select mutual funds. There are many ways in which amarket timer can steal profits through short‐term trading activities but the primary opportunity arises in those mutual funds that invest in foreign shares of stock. This 2004 article looks at a sampling of those mutual funds that invest in companies based in the United Kingdom and evaluates the potential for abusive market‐timing activities.

This is the first article to apply a machine learning approach to the analysis of time on market on real estate markets.

The random survival forest approach is introduced to the real estate market. The most important predictors of time on market are revealed and it is analyzed how the survival probability of residential rental apartments responds to these major characteristics.

Results show that price, living area, construction year, year of listing and the distances to the next hairdresser, bakery and city center have the greatest impact on the marketing time of residential apartments. The time on market for an apartment in Munich is lowest at a price of 750 € per month, an area of 60 m2, built in 1985 and is in a range of 200–400 meters from the important amenities.

The findings might be interesting for private and institutional investors to derive real estate investment decisions and implications for portfolio management strategies and ultimately to minimize cash-flow failure.

Although machine learning algorithms have been applied frequently on the real estate market for the analysis of prices, its application for examining time on market is completely novel. This is the first paper to apply a machine learning approach to survival analysis on the real estate market.

The study assess the selection ability and market timing skills of mutual fund and unit trust managers in Ghana.

The study uses an improved survivorship bias-free dataset of yearly after-fee returns of all mutual funds and unit trusts operating in Ghana from January 2011 to December 2019, cumulating in nine years of quantitative fund data. The authors assess Mutual funds and Unit trusts that ever existed, “alive” or “dead,” over the sample period in the study. The authors construct factor loadings to enable the application of multifactor models in the analysis. The authors apply the unconditional versions of the Jensen alpha, Fama-French three-factor, and Carhart four-factor models to determine the selection ability and market timing skills of 32 mutual funds and 17 unit trusts. The authors deploy HAC-consistent robust standard errors to the OLS estimations to subdue the effect of heterogeneity and autocorrelation.

The results indicate that, on average, mutual funds and unit trust managers possess market timing skills but no selection ability. When the results are decomposed into fund types, fixed-income and balanced mutual fund managers possess selection ability and market timing skills.

To the authors' best knowledge, this study is the earliest to examine the selection ability and market timing skills of both mutual fund and unit trust managers in Sub-Saharan Africa (SSA). It is also the earliest to construct factor loadings for the Ghana stock market.

This study aims to explore how brands use brand personification techniques in real-time marketing on social media, particularly Twitter, and examine how these techniques impact consumer engagement, moderated by brand-event congruence levels.

Data included 464 tweets posted by 95 brands around three large events in 2019. The types of brand personification techniques and the level of brand-event congruence applied by the tweets were content-analyzed, and regression analyses were conducted to examine their linkages to consumer engagement metrics.

Results confirmed the use of diverse personification techniques in brands’ real-time marketing tweets as in the previous literature. The study also revealed a new personification technique, tacit expression, not reported in previous literature. The study also showed that the overall effectiveness of multimedia-based (vs caption-based) personification techniques in increasing consumer engagement on social media was greater, but their relative effectiveness varied depending on whether or not the event was functionally congruent with the brand.

The findings offer valuable suggestions to brand managers regarding prioritizing brand personification techniques and aligning brands’ social media marketing with real-time events to maximize the effectiveness of real-time marketing in boosting consumer engagement.

This research offers insights into the dynamic effects of different brand personification techniques in the new context of real-time marketing, extending the scope of literature on brand personification and anthropomorphism. The revelation of a new type of brand personification not captured in the extant literature is also a significant contribution.

The purpose of this paper is to examine the market timing and stock selection abilities of socially responsible (SR) mutual funds. Some high-profile SR fund managers try to embrace market timing and security selection plans to add value to the performance. Market timing relies on forecasting the equity market and shifting assets into or out of the market in anticipation of market movements. The selectivity measure assesses fund managers ability to select undervalued securities. Furthermore, the authors examine whether fund characteristics play any role in market timing and security selection ability.

The authors use Treynor and Mazuy's’ (1966) and Henriksson and Mertons’ (1981) model to examine the market timing and security selection ability. The study uses a decade of monthly returns to examine the skills of fund managers in the SR industry for the period from July 2002 to June 2012.

The main findings are that the managers – though not very successful – do indulge in stock selection and market timing activities. It was found that 48 funds have positive statistically significant stock selectivity coefficients and only a very small number of five funds with positive statistically significant market timing coefficients. Results suggest that there is a trade-off between the two activities. It was found that aggressive funds, funds with higher growth rate and riskier funds are more likely to engage in market timing rather than stock selection.

The implication is that SR managers cannot achieve superior stock selection and market timing ability simultaneously. Risk-averting investors in SR funds expect SR behavior from the managers. This means that managers of SR funds, with very little evidence of market timing ability, may have to refrain from market timing of SR funds.

Using a Morningstar dataset comprising almost all SR funds in existence as of June 2012, this is probably the most exhaustive long-term study to date on market timing and stock selection abilities of SR fund managers.

The purpose of this paper is to examine the impact of market timing and pseudo market timing on equity issuance decisions of IPOs in an emerging economy – India. Indian new issues market provides a perfect setting to test market timing against pseudo market timing due to two reasons. First, the US literature shows that most underpriced IPOs are highly overvalued and in India, the authors have the evidence of underpricing of IPOs. But whether Indian IPOs are overvalued or not it is yet to be tested. Second, majority of IPOs were issued in India only after the 1991 economic reforms which may signal the evidence for pseudo market timing hypothesis.

The authors use direct test to examine the impact of market timing and pseudo market timing variables on the IPO activity. The direct tests of market timing and pseudo market timing hypotheses are based on the positive relation of market timing variables and market conditions variables with IPO activity. The authors examine the long-run performance of IPOs by using the calendar-time regression approach to test market timing against pseudo market timing. This serves as indirect test of market timing and pseudo market timing. Evidence of market timing using indirect test shows that there is a decline in the long-run stock performance of IPOs.

The results show that in India, firms issue equity not just due to market conditions but they also issue equity in order to time the market. The results of market timing are also supported by the calendar-time approach results. However, the authors find that the evidence of market timing is stronger for hot issue markets as compared to cold issue markets.

This is the first study to comprehensively examine market timing and pseudo market timing using direct and indirect tests for an emerging market context.

The Treynor and Mazuy framework is a widely used return-based model of market timing. However, existing corrections to the regression intercept can be manipulated through derivatives trading. Because they are conceptually flawed, these corrections produce biased performance measures. This paper aims to get back to Henriksson and Merton’s initial idea of option replication to overcome this issue and adapt the market timing model to various kinds of trading strategies and return-generating processes.

This paper proposes a theoretical adjustment based on Merton’s option replication approach adapted to the Treynor and Mazuy specification. The linear and quadratic coefficients of the regression are exploited to assess the cost of the replicating option that yields similar convexity for a passive portfolio. A similar reasoning applies for various timing patterns and in multi-factor models.

The proposed framework induces a potential rebalancing risk and involves the delicate issue of choosing the cheapest option. This paper shows that these issues can be overcome for reasonable tolerance levels. The option replication approach is a workable approach for practical applications.

The adaptation of Merton’s reasoning to the Treynor and Mazuy model has surprisingly never been proposed so far. This paper has the potential to correct for a pervasive bias in the estimation of the performance of a market timer in the context of this very popular quadratic regression setup. Because of the power of the option replication approach, the reasoning is shown to be applicable to multi-factor models, negative timing and market neutral strategies. This paper could fuel empirical studies that would shed new light on the genuine market timing skills of active portfolio managers.

This study aims to investigate how the timing behavior affects the capital structure decisions of South Asian family firms. A strand of literature is available based on the capital structure of firms in general but inconsistent with family businesses framework and not from market timing outlook. This study looks at the issues from the market timing perspectives of both equity and debt market timing.

The sample of the study is the listed family firms of India, Pakistan and Bangladesh. The firm-level data are collected from Thomson Reuters' DataStream and the ownership data collected from the countries' stock exchanges and financial statements of the family firms.

The results show that there is strong support for the market timing in the family firms' capital structure. Moreover, the financial crisis of 2007–2009 surprisingly had a positive effect on the capital structure of South Asian family business.

This study looks at the issues from the market timing perspectives of both equity and debt market timing. It provides evidence for supporting the equity and debt market timing effect on the capital structure and financing decision of family firms. It also addresses the impact of the 2007–2009 financial crisis on the capital structure of family firms.

The purpose of the study is applying and comparing models that predict optimal time for new product exit based on its demand pattern and survivability. This is to decide whether or not to continue investing in new product development (NPD).

The study investigates the optimal time for new product exit within the hi-tech sector by applying three models: the dynamic learning demand model (DLDM), the generalized Bass model (GBM) and the hazard model (HM). Further, for inter- and intra-model comparison, the authors conducted a simulation, considering Weiner and exponential price functions to enhance generalizability.

While higher price volatility signifies an unstable technology, greater investment into research and development (R&D) and marketing results in higher product adoption rates. Imitators have a more prominent role than innovators in determining the longevity of hi-tech products.

The study conducts a comparison of three different models considering time-varying parameters. There are four scenarios, considering variations in advertising intensity and content, word-of-mouth (WOM) effect, price volatility effect and sunk cost effect.