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The authors examine cryptocurrency market behavior using a hidden Markov model (HMM). Under the assumption that the cryptocurrency market has unobserved heterogeneity, an HMM allows us to study (1) the extent to which cryptocurrency markets shift due to interactions with social sentiment during a bull or bear market and (2) the heterogeneous pattern of cryptocurrency market behavior under these two market conditions.

The authors advance the HMM model based on two six-month datasets (from November 2017 to April 2018 for a bull market and from December 2018 to May 2019 for a bear market) collected from Google, Twitter, the stock market and cryptocurrency trading platforms in South Korea. Social sentiment data were collected by crawling Bitcoin-related posts on Twitter.

The authors highlight the reaction of the cryptocurrency market to social sentiment under a bull and a bear market and in two hidden states (an upward and a downward trend). They find: (1) social sentiment is relatively relevant during a bull compared to a bear market. (2) The cryptocurrency market in a downward state, that is, with a local decreasing trend, tends to be more responsive to positive social sentiment. (3) The market in an upward state, that is, with a local increasing trend, tends to better interact with negative social sentiment.

The proposed HMM model contributes to a theoretically grounded understanding of how cryptocurrency markets respond to social sentiment in bull and bear markets through varied sequences adjusted for cryptocurrency market heterogeneity.

The purpose of this paper is to examine semi-strong market efficiency by observing the behavioral finance implications of Jim Cramer’s recommendations in bull vs bear markets. The authors extend the literature by analyzing investor reaction through the lenses of prospect theory, overreaction, and herding.

The authors test for abnormal returns in response to Mad Money buy and sell recommendations. The authors use a sample of buy and sell recommendations from MadMoneyRecap.com from July 28, 2005 through February 9, 2009. The 3.5-year time period is the most recent and comprehensive set of Mad Money recommendations that has been tested to date.

The results indicate market inefficiency at the semi-strong level. Furthermore, the findings highlight the loss aversion tendencies of investors in regards to prospect theory of Kahneman and Tversky (1979) as well as the disposition effect of Shefrin and Statman (1985). Evidence also exists consistent with the herding and overreaction hypotheses.

The evidence suggests contrarian behavior in which investors respond positively to good news in bad times – perhaps, in effort to stay the course and at least break even. This behavior may suggest that losers tend to hold on to losses in hopes of recouping them. Thus, positive information in bad times could further persuade market participants to hang on to or buy more of losers, while also persuading non-shareholders to buy in as well.

Though other studies including Kenny and Johnson (2010) have estimated abnormal returns in response to analyst recommendations, to the knowledge, none has examined behavioral implications of investor reaction to buy and sell recommendations in both bull and bear markets. Furthermore, the study captures a longer bull and bear market and covers two definitions of such markets.

The purpose of this paper is to study merger momentum and its driving factors in China by sampling 376 listed bidders from 2008 to 2013.

The empirical model captures the dependency of market reaction on recent merger and stock market states. The independent variables are designed from two dimensions, i.e. at the level of market-wide as an integral and bidder-specific as individuals. Furthermore, both the market and bidding firms contain merger momentum and market momentum, respectively.

The empirical results show that there is merger momentum in the market. Particularly, merger momentum is significant both in short run and long run for the mergers with cash payment, which supports the synergy effect. It also implicates the mergers with stock driven by investor sentiment. Besides, investors’ over-optimism is significant in the bull markets while managerial hubris is found in the bear markets.

The driving factors for merger momentum in China are complex. Three impacts with different effects interact with one another. They are investor sentiment and managerial hubris with negative effects resulting in reversal abnormal return in the long run, and synergies with positive shocks resulting in no reverse at all. The limitation of the paper is insufficient analysis of the mergers financed by stocks, which will be the focus for future study.

The conclusions of the study help to intensify the understanding of the immature and unnormalized capital market in China. The empirical analyses give some inspiration and suggestions to three parties in the market, i.e. investors, bidding firms and regulators, respectively.

There are three contributions. The first one is to provide a novel model to identify how these different effects work on the merger momentum. The second one is the measurement of investor sentiment from different perspectives. The last but most important one is the new findings with novel explanations, which proves that the impacts on merger momentum are complex.

The purpose of this study is to examine the performances of liquidity factors in the stock market cycle. It aims to investigate whether the contribution of liquidity factors changes with stock market trends.

Six liquidity proxies and two-factor construction methods are compared in this study. The spanning regression method was applied to examine the contribution of liquidity factors to the asset pricing model, while the Fama and MacBeth regression method was used for examining the pricing power of liquidity factors.

The result shows that liquidity factors are accretive to models explaining returns in bull markets but not accretive to models in bear markets. The most appropriate method of constructing liquidity factors in the Japanese stock market has also been clarified.

In the Japanese stock market, there has never been a comprehensive test of the role of the liquidity risk factor in different market trends using the long-run data. This study helps with identifying the importance of liquidity pricing risk in different market trends. It also fills the gaps by comparing liquidity factors that are constructed through different methods and proxies and provides evidence for further confirming the correct asset pricing model in the future.

This paper aims to empirically indicate the factors influencing stock liquidity premium (i.e. the relationship between liquidity and stock returns) in one of the leading European emerging markets, namely, the Polish one.

Various firms’ characteristics and market states are analysed as potentially affecting liquidity premiums in the Polish stock market. Stock returns are regressed on liquidity measures and panel models are used. Liquidity premium has been estimated in various subsamples.

The findings vividly contradict the common sense that liquidity premium raises during the periods of stress. Liquidity premium does not increase during bear markets, as investors lengthen the investment horizon when market liquidity decreases. Liquidity premium varies with the firm’s size, book-to-market value and stock risk, but these patterns seem to vanish during a bear market.

This is one of the first empirical papers considering conditional stock liquidity premium in an emerging market. Using a unique methodological design it is presented that liquidity premium in emerging markets behaves differently than in developed markets.

The purpose of this paper is to explore the relationship between Dow Jones Islamic Market World Index, Islamic gold-backed cryptocurrencies and halal chain in the presence of state (regime) dynamics.

The authors have used the Markov-switching model to identify bull and bear market regimes. Moreover, the dynamic conditional correlation, the Baba, Engle, Kraft and Kroner- generalized autoregressive conditional heteroskedasticity and the wavelet coherence models are applied to detect the presence of spillover and contagion effects.

The findings indicate various patterns of spillover between halal chain, Dow Jones Islamic Market World Index and Islamic gold-backed cryptocurrencies in high and low volatility regimes, especially during the COVID-19 pandemic. Indeed, the contagion dynamics depend on the bull or bear periods of markets.

These present empirical findings are important for current and potential traders in gold-backed cryptocurrencies in that they facilitate a better understanding of this new type of assets. Indeed, halal chain is a safe haven asset that should be combined with Islamic gold-backed cryptocurrencies for better performance in portfolio optimization and hedging, mainly during the COVID-19 period.

To the best of the authors’ knowledge, this paper is the first research on the impact of the halal chain on the Dow Jones Islamic Market World Index return, Islamic gold-backed cryptocurrencies returns in the bear and bull markets around the global crisis caused by the COVID-19 pandemic.

This study aims to investigate the association of demographic characteristics, market conditions and risk taking with the disposition effect using data on Brazilian individual investors.

This study uses a unique data set with monthly data from June 2007 to February 2017 provided by one of the largest asset management firms in Brazil. This paper computes the proportion of gains realized and the proportion of losses realized to see if investors incur the disposition effect. This paper then performs logistic regressions to verify the association between investors’ disposition effects and demographic and portfolio characteristics. This paper analyses the prevalence of cognitive biases depending on market conditions (bull or bear markets) and include regressions by asset class as robustness checks.

This paper finds evidence that risk averse investors are more prone to the disposition effect, male subjects are less prone to this cognitive bias and age is not associated with the disposition effect. This paper observes that the tendency to incur the disposition effect decreases during bull markets but increases during bear markets. Also, this paper finds that sophisticated investors are more prone to selling winning assets and holding on to losses.

First, paper gains and losses are based on the highest and lowest prices of the month and not on the price at the moment the sale occurred. Second, this paper had access only to end-of-month information, not to actual daily trading records. Third, because the data set relates to individual investors who trade investment funds, this paper cannot determine whether firm size is associated with the disposition effect. Fourth, age may not necessarily be a proxy for investor experience, so one should interpret the lack of significance for age in terms of generational differences.

This paper demonstrates that the disposition effect is prevalent even among wealthier and more educated investors with delegated asset classes. This paper also presents evidence on the association between demographic characteristics and cognitive biases considering a liquidity-constrained, highly volatile and developing market.

This paper demonstrates that gender is an important characteristic to understand cognitive biases and that investor sophistication may not necessarily be an attenuation factor for the disposition effect in a liquidity-constrained market.

This is the first study to analyse the role of demographic characteristics and risk taking to explain the disposition effect using real information at the individual level about Brazilian investors. It is also the first to analyse the intensity of cognitive biases during bull and bear markets in the Brazilian economy.

This study aims to analyze how risk tolerance is influenced by bull and bear market phases, age and professional work experience (PWE) of investors in emerging economies. The authors also analyze how different market phases (bull and bear) influence risk tolerance of investors in emerging economies for different age groups and with varying PWE.

The study uses two quantitative methods, one-way ANOVA and hierarchical regression model (HLM) to analyze individual investors' financial risk tolerance (FRT) in India.

The authors find that age and PWE have positive relationship with FRT behavior. However, interactions of these variables with market phase variable indicate that risk tolerance has nonlinear increasing relationship with investor's age and PWE. The risk tolerance of older investors is consistently high in both bull and bear market conditions, while young investors display a nonlinear risk behavior in different market conditions.

The study suggests that financial planners should include a longitudinal risk profiling of investors based on age groups, PWE and the current market phase to better understand investors' FRT and also to prefer more context-specific advice to investors in emerging economies, which, consequently, result in increasing the retail investors' interest in otherwise sparsely participated equity market.

Interaction effect of bull and bear market phases on relationship between age and PWE and FRT has been scantly studied.

Following behavioral finance and monetary wisdom, the authors theorize: Decision-makers (investors) adopt deep-rooted personal values (the love-of-money attitudes/avaricious financial aspirations) as a lens to frame critical concerns (short-term and long-term investment decisions) in the immediate-proximal (current income) and distal-omnibus (future inheritance) contexts to maximize expected utility and ultimate serenity across context, people and time.

The authors collected data from 277 active equity traders (professional money managers and individual investors) in Pakistan’s two most robust investment hubs—Karachi and Lahore. The authors measured their love-of-money attitude (avaricious monetary aspirations), short-term and long-term investment decisions and demographic variables and collected data during Pakistan's bear markets (Pakistan Stock Exchange, PSX-100).

Investors’ love of money relates to short-term and long-term decisions. However, these relationships are significant for money managers but non-significant for individual investors. Further, investors’ current income moderates this relationship for short-term investment decisions but not long-term decisions. The intensity of the aspirations-to-short-term investment relationship is much higher for investors with low-income levels than those with average and high-income levels. Future inheritance moderates the relationships between aspirations and short-term and long-term decisions. Regardless of their love-of-money orientations, investors with future inheritance have higher magnitudes of short-term and long-term investments than those without future inheritance. The intensity of the aspirations-to-investments relationship is more potent for investors without future inheritance than those with inheritance. Investors with low avaricious monetary aspirations and without inheritance expectations show the lowest short-term and long-term investment decisions. Investors' current income and future inheritance moderate the relationships between their love of money attitude and short-term and long-term decisions differently in Pakistan's bear markets.

The authors help investors make financial decisions and help financial institutions, asset management companies, brokerage houses and investment banks identify marketing strategies and investor segmentation and provide individualized services.

Professional money managers have a stronger short-term orientation than individual investors. Lack of wealth (current income and future inheritance) motivates greedy investors to take more risks and become more vulnerable than non-greedy ones—investors’ financial resources and wealth matter. The Matthew Effect in investment decisions exists in Pakistan’s emerging economy.

The purpose of this paper is to examine the value of active fund management using a sample of hybrid mutual funds.

Instead of using traditional risk‐adjusted measures, the paper employs an alternative attribution return methodology where the actual monthly fund return is compared to the return that would have been earned by the indexing strategy that best reflects the fund's prior month allocation. Value is measured by defining a fund's attribution return as the difference between a fund's actual month t return and the return that would have been generated in month t by the indexing strategy that most closely approximates the fund's month t−1 portfolio allocation.

It is found that hybrid funds as a group do not add value and that this underperformance does not appear to be driven by the poor performance of non‐surviving funds. However, these funds perform significantly better than the style benchmark under weak vs strong stock market conditions. This performance difference between bull and bear market conditions suggests some hedge fund‐like downside protection that may offer a reason why investors choose these funds despite the funds’ average underperformance and despite their higher costs relative to index funds.

The contribution of this paper is twofold. First, it concentrates on hybrid mutual funds, which despite a surge in their interest over the last five years have attracted very little academic study. Second, in the implementation of its non‐traditional performance measure, it employed daily fund returns, stock market indices and bond market indices as opposed to the monthly or quarterly data used in other related studies.