Strategies of portfolio investment with estimates of bull and bear markets

The financial market has non-linear patterns, with different return behavior in bull versus bear markets. This article uses multivariate model estimates to study portfolios in changing conditions, and develops investment strategies for portfolios in light of uncertainty about the bear or bull status of the stock market. Portfolios were optimized for the main stocks listed on the Brazilian market index Ibovespa. The portfolios proposed with estimates of changing market status outperformed others over the analyzed period, with rebalancing adjustments made either weekly or monthly.

Macroeconomic variables for predicting bear stock markets of Taiwan and China

PurposeThis research examines how macroeconomic variables can precisely predict bull/bear stock markets in China and Taiwan.Design/methodology/approachThis paper adopts a two-state Markov switching model to characterize the bull and bear markets spanning from 1994 to 2019 and then conduct a bear stock market predictability test by running regressions between the filtered probabilities of bear markets and a series of macroeconomic variables in turn at different horizons of 1, 3, 6, 12 and 24 months.FindingsThis paper shows that inflation rates, changes in real exchange rates, and foreign currency reserve growth are key predictors of bear markets in China, while term spreads, unemployment rates and foreign reserve growth are major factors that can predict bear markets in Taiwan. Remarkably, industrial production growth does not have predictive power for bear markets, which may suggest emerging markets are driven by fund flows rather than real economic activities. Besides, the impact directions of foreign currency reserve growth are opposite, which may be due to different proportions of the financial accounts in their balance of payments.Practical implicationsIn practical respect, this paper provides market participants the usefulness, impact direction and implications of bear market predictors when building their market-timing strategies in China and Taiwan stock markets. The government institutions may also thereby make appropriate policies to prevent huge stock market downturns and serious drawbacks.Originality/valueIt highlights the “fund-driven market hypothesis” and “foreign currency reserve effects” that commonly dominate Taiwan and China stock markets since both are highly affected by international funds.

Disposition effect, demographics and risk taking

Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Practical implications 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. Social implications 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. Originality/value 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.

Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information Entropy

The interactive effect is significant in the Chinese stock market, exacerbating the abnormal market volatilities and risk contagion. Based on daily stock returns in the Shanghai Stock Exchange (SSE) A-shares, this paper divides the period between 2005 and 2018 into eight bull and bear market stages to investigate interactive patterns in the Chinese financial market. We employ the Least Absolute Shrinkage and Selection Operator (LASSO) method to construct the stock network, compare the heterogeneity of bull and bear markets, and further use the Map Equation method to analyse the evolution of modules in the SSE A-shares market. Empirical results show that (1) the connected effect is more significant in bear markets than bull markets and gives rise to abnormal volatilities in the stock market; (2) a system module can be found in the network during the first four stages, and the industry aggregation effect leads to module differentiation in the last four stages; (3) some stocks have leading effects on others throughout eight periods, and medium- and small-cap stocks with poor financial conditions are more likely to become risk sources, especially in bear markets. Our conclusions are beneficial to improving investment strategies and making regulatory policies.