Jul 2026· Wseas Transactions on Business and Economics· pp. 1098· 0 citations· 9 references
Abstract
The Chinese A-share market, characterized by its unique retail-dominated structure and institutional constraints, exhibits pricing features distinct from mature markets. This study constructs a portfolio management framework adapted to the microstructure of the A-share market and examines how institutional investors can generate excess returns through Bubble Riding and Factor Timing strategies when limited arbitrage and investor irrationality coexist. First, using a synchronization-risk framework and a behavioral overreaction mechanism, we derive that the optimal strategy for rational arbitrageurs under heterogeneous beliefs and short-sale constraints can shift from immediate mean reversion to momentum-following. Subsequently, we integrate a China-localized factor construction and conduct an empirical study using A-share data from 2020 to 2026 collected through Python and the Baostock interface. The results show that: (1) traditional Fama-French factors are weakened in the A-share market when shell-value contamination is ignored, and excluding the bottom 30% of micro-cap stocks improves pricing efficiency; (2) momentum and sentiment factors exhibit nonlinear characteristics across market regimes; and (3) a dynamic risk-control strategy based on market-wide turnover rates—penalizing high-volatility exposure during bubble periods and increasing beta exposure during freezing periods—substantially outperforms the CSI 300 index out of sample.
This paper examines the Post-Earnings Announcement Drift (PEAD) in the Chinese A-share market. As an overview of the researches carried out from 2011 to 2023 for evaluating why this significant anomaly is still economically and theoretically relevant in emerging countries. As a prevalent market anomaly, PEAD refers to the persistent directional deviation of stock prices following corporate earnings releases. Classical models cannot explain PEAD well. Even after continuous improvements in market reform and development of trade infrastructure, the delay in reflected reaction has yet to fully reconcile with established theories. To explain such persistent inefficiency, this paper constructs a framework combining psychology and structure. Investor inattention explains the under-reaction to earnings. Structural constraints, such as short-sale restrictions, prevent the arbitrageurs from correcting mispricing. Furthermore, based on the above analysis results, different kinds of environmental conditions have been identified to cause changes by means of drifts. Empirical evidence indicates that, recent studies have found that institutional investors may not eliminate this anomaly but rather strengthen or amplify it due to momentum herd behavior in a high-transparent situation. Finally, in terms of understanding behavioural finance at multiple angles through this model; thus possessing considerable value for both theory and practice.
This study conducts an empirical re-evaluation of the effectiveness of technical analysis within the framework of the Efficient Market Hypothesis (EMH) in an emerging market setting. Utilizing a comprehensive two-decade daily dataset (2006–2025) of the Indonesian LQ45 Index, the research simulates a mechanical trading strategy based on 20-day and 50-day Exponential Moving Average (EMA) crossovers, contrasting its performance against a passive Buy-and-Hold (B&H) benchmark. To eliminate subjective bias and ensure methodological rigor, the analysis employs continuous log-returns and assumes a frictionless market. Statistical inference, performed using Welch's independent samples t-test, indicates no significant difference in raw returns between the active EMA strategy and the passive benchmark (p-value = 0.959), thereby strongly supporting the weak-form EMH. Notably, the study reveals a sustained negative equity risk premium over the two decades, with both equity strategies yielding lower returns (6.07% and 6.42%, respectively) than the 7.99% risk-free rate of 10-year government bonds. Despite underperforming in absolute returns, the EMA strategy demonstrates exceptional risk mitigation capabilities, drastically reducing total portfolio volatility from 23.65% to 15.39% and compressing downside deviation from 18.72% to 15.05%. Evaluated through the Modified Sharpe and Sortino ratios, these findings redefine the utility of moving averages: while technical analysis fails to maximize profit or generate anomalous returns, it functions as a highly effective portfolio insurance mechanism, capable of mitigating downside risk during market downturns.
Septorian Adhi Nugroho· The International Conference...· 0 citations
This study investigates whether factor-model selection drives the mixed evidence on ESG pricing in China's A-share market, where "green discount" and "green premium" coexist. Taking the Liu–Stambaugh–Yuan (LSY) four-factor model as the benchmark pricing framework and combining Shangdao Ronglv ESG ratings with CSMAR data, it examines model dependence, market capitalization heterogeneity, policy asymmetry, and risk transmission. The results show that ESG pricing conclusions are strongly model-dependent: the estimated ESG premium reverses sign once the local LSY factors and firm fundamentals are controlled, and statistically significant evidence of a premium is concentrated among large-cap stocks. The 2016 green finance policy is associated with dimensionally asymmetric changes in corporate ESG performance, although pre-existing trends limit strict causal identification. The environmental and governance dimensions transmit through opposite stock-price-risk paths, a pattern consistent with a dimensional hedging interpretation. These results imply that credible ESG pricing evidence in the A-share market requires an empirical specification—and above all a pricing benchmark—suited to the Chinese market.
Zize Wei· Journal of Applied Economics...· 0 citations
This study develops an integrated and longitudinal investigation of market microstructure dynamics across four principal ASEAN equity markets—Indonesia, Singapore, Thailand, and Malaysia—over the 2010–2025 period. The analysis concentrates on the structural interaction between liquidity provision, price discovery efficiency, and regulatory architecture within the context of three major global disturbances: the 2013 Taper Tantrum, the COVID-19 systemic shock (2020–2021), and the global monetary tightening cycle (2022–2025). While existing literature largely examines microstructure components in isolation or within single-country settings, this research reconceptualizes regulation as an endogenous moderating mechanism that shapes the dynamic interplay between liquidity and informational efficiency. The central proposition is that institutional robustness determines shock absorption capacity, recovery speed, and long-run market quality. Methodologically, the study applies a quantitative-explanatory longitudinal framework using daily data. Econometric procedures include multivariate GARCH specifications to estimate volatility persistence, Diebold-Yilmaz spillover indices with time-varying parameter VAR extensions to evaluate cross-market transmission, dynamic panel regression for institutional impact assessment, and event-study plus difference-in-differences estimators to isolate crisis effects.
JEL Codes:
Keywords: market microstructure, liquidity multidimensionality, price discovery efficiency, regulatory quality, crisis transmission, ASEAN equity markets, financial integration
Edwin Julianus Sebayang, Dwi Handoko, Bondan Haryono et al.· Global Conference on Busines...· 0 citations
This study develops an agent-based financial market model to explain stock-price momentum and reversal through the joint effects of local herding and delayed information diffusion. Investors form heterogeneous Gaussian beliefs about the next-period price, choose among buying, selling, and remaining inactive, and revise their action probabilities in response to neighboring investors. The local interaction structure is represented by von Neumann and Moore lattices and is later replaced by Erd\H{o}s--R\'enyi and Watts--Strogatz networks for robustness. A separate information process updates investor beliefs through a finite-speed diffusion mechanism, allowing informational adjustment to be distinguished from behavioral imitation. The simulations show that stronger herding produces spatially clustered trading, larger price fluctuations, and more pronounced excess kurtosis in returns. Faster information diffusion reduces the time required for prices to approach the signal-implied value, whereas the combination of information diffusion and social reinforcement generates overshooting and subsequent reversal. An empirical application to China's A-share market compares conventional CSAD and LSV measures with a rolling tail-based herding indicator obtained after Johnson $S_U$ transformation. The indicators display similar time variation and rise during major market disruptions. These findings identify information delay, local social reinforcement, and the eventual decay of herding as complementary mechanisms behind momentum and reversal.
This study examines the relationship between investor overconfidence and dynamic market
volatility in the Vietnamese stock market, a frontier market distinguished by rapid growth and
the dominance of individual investors. Although the overconfidence–volatility framework has
been tested across many developed and emerging markets, Vietnam has remained largely
unexamined despite exhibiting the speculative boom-and-crash cycles and heavy retail
participation that make it a compelling case for behavioral analysis. Drawing on the frameworks
of Chuang and Lee (2006) and Jlassi et al. (2014), we analyze daily VN-Index price and tradingvolume data from the Ho Chi Minh Stock Exchange (HOSE) over 2016–2025, comprising 2,497
observations. Log trading volume is decomposed via OLS regression on five lagged daily returns
into an overconfidence-driven (overreaction) component and a non-overconfidence component,
which are then incorporated into an EGARCH(1,1) model to assess their contributions to
conditional volatility. The results support all three hypotheses. The overconfidence component
has a positive and highly significant effect on conditional volatility (f₃ = 0.136, p < 0.01) that
substantially exceeds that of the non-overconfidence component (f₄ = 0.004), indicating that
behavioral trading is a primary driver of market instability. Volatility is highly persistent (f₂ =
0.950) and asymmetric, with negative shocks generating larger responses than positive shocks of
equal magnitude (K = −0.153, p < 0.01). These findings extend the international
overconfidence-volatility literature to an emerging market and highlight the role of investor
psychology in shaping market risk.
T. Vũ, Mai Uyen, Tú Anh Trần· International Journal of Soc...· 0 citations
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