Sparse portfolio strategy from mutual funds' favorite stocks in China A share market.
problem Building a sparse portfolio from mutual funds' favorite stocks in a market with limited fund information.
method Analyzed mutual fund favorite stocks, used portfolio optimizer with constraints, and compared different methods.
result Sparse portfolios consistently outperform the benchmark index 930950.CSI.
Hierarchical AI multi-agent framework optimizes equity portfolios in China's A-share market.
problem Optimizing equity portfolios in China's A-share market using AI and multi-agent systems.
method A hierarchical multi-agent design integrating macro, firm-level, and reinforcement learning approaches.
result Consistently outperforms benchmarks and state-of-the-art systems on risk-adjusted returns and drawdown control.
The MAXFLAT low-pass filter improves factor adjustment for better portfolio performance in China's stock market.
problem Improving factor adjustment for better portfolio performance in China's stock market.
method Using MAXFLAT low-pass volatility model to adjust factors and construct portfolios.
result Adjusted factors by MAXFLAT volatility model show better performance in both large and small cap universes.
Model explains stock momentum and reversal in China's A-share market.
problem Understanding stock momentum and reversal in China's A-share market.
method Agent-based model with local herding and delayed information diffusion.
result Stronger herding leads to spatially clustered trading and larger price fluctuations.
This paper compares two stock factor models in China's A-share market.
problem Contradicting results in existing research on stock factor models.
method Empirical analysis using China's A-share data from 2005-2020, orthogonalizing redundant factors, and 25-group portfolio returns calculation.
result The five-factor model outperforms the three-factor model in explaining excess return rates.
The study identifies extremal dependence in financial markets using a bootstrap-based testing procedure.
problem Accurately identifying extremal dependence in multivariate heavy-tailed financial data.
method Bootstrap-based testing procedure applied to U.S. and Chinese stock returns.
result The U.S. exhibits more isolated clustering of dependent assets compared to China.
A CNN-based model improves stock price prediction accuracy.
problem Overfitting in image-based stock prediction models.
method SMSFR-CNN combining CNN and image features.
result SMSFR-CNN achieves high predictive accuracy on A-share stocks.
This paper introduces anti-correlation networks to study China's stock market.
problem Previous studies ignored anti-correlation in financial networks.
method Constructed weighted temporal anti-correlation and positive correlation networks.
result Unveiled differences in topological measurements between anti-correlation and positive correlation networks.
This paper uses DRL for long-short portfolio optimization, improving risk-adjusted returns.
problem Traditional portfolio optimization limits diversification by excluding short-selling.
method Developed a DRL framework with a short-selling mechanism for continuous trading.
result DRL model with short-selling achieves superior risk-adjusted returns.
This thesis applies RL to market making in China's commodity market.
problem Leverage RL for market making in China's commodity market.
method Developed an automatic trading system using RL.
result RL is feasible for market making in China's commodity market.
This paper measures financial market resilience in China and identifies key uncertainties.
problem Measuring financial market resilience in China.
method Quantitative analysis of total financial market and sub-markets, Diebold-Yilmaz connectedness approach.
result Financial market resilience in China is event-driven and influenced by geopolitical risks, economic and trade policy uncertainty, and U.S.-China tensions.
Enhances stock market prediction using multi-sourced data.
problem Improving stock market prediction by considering multiple data sources.
method Extended Coupled Hidden Markov Model incorporating historical trading data and news events, with correlations between stocks incorporated.
result Superior performance on China A-share market data in 2016 compared to previous methods.
We propose a new set of stylized facts quantifying the structure of financial markets. The key idea is to study the combined structure of both investment strategies and prices in order to open a qualitatively new level of understanding of financial and economic markets. We study the detailed order flow on the Shenzhen …
Social media features predict stock prices in China's market.
problem Lack of research on stock prediction in China's market.
method Extracted features from Xueqiu tweets, analyzed collective sentiment and perception, used nonlinear models.
result Social media features are effective in predicting stock price movements in China.
Paper proposes a new portfolio model for better investment decisions.
problem Traditional portfolio models fail to adapt to nonstationary markets.
method Developed a mean-detrended cross-correlation portfolio model (M-DCCP model).
result The M-DCCP model outperforms traditional models in constructing optimal portfolios.
Since 2002 when China first introduced QFII (Qualified Foreign Institutional Investors) system, QFII has been developing in China for 14 years, during when RQFII, Shanghai-Hongkong Stock Connect Program, Shanghai-London Stock Connect Program furthur broadened the avenue for foreign capital to invest in Chinese Security…
China's stock market reacts positively to PMI news but not to negative news.
problem Understanding asymmetric responses to PMI announcements in China's stock market.
method Empirical investigation of stock market reactions to PMI announcements.
result China's stock market reacts positively to positive PMI news but not to negative news.
This paper examines how the U.S.--China trade war affects stock markets, finding evidence of financial contagion and changes in risk channels.
problem The impact of the U.S.--China trade war on stock markets and financial contagion.
method Developed a novel jump-diffusion process to account for risk contagion, using high-frequency financial data and quasi-maximum likelihood estimator.
result Evidence of financial contagion from the U.S. to China, with changes in risk contagion channels.
Study reveals holiday effect on China's time-honored brands, especially alcoholic beverages.
problem Understanding holiday impact on China's time-honored brands.
method Event study using listed companies of China's time-honored brands from 2012-2021.
result Time-honored brand stocks show significant post-holiday effect during Chinese New Year, alcoholic beverages more sensitive.
Study shows how China's stock market reflects economic demand changes during COVID-19.
problem Understanding how stock market volatility is influenced by economic demand changes.
method Divided industries into demand-oriented groups and analyzed spillover networks.
result Spillover effects from demand-oriented sectors to consumption-oriented sectors increased during the outbreak.
Study shows COVID-19 increases stock market crash risk in China.
problem Impact of COVID-19 on stock market crash risk in China.
method Estimated conditional skewness using GARCH-S model and constructed fear index from Baidu Index data.
result Conditional skewness reacts negatively to daily growth in total confirmed cases, indicating increased crash risk.
Quantum-enhanced method improves stock return prediction accuracy.
problem Improving precision of stock return forecasting.
method Quantum Gramian Angular Field (QGAF) combining quantum computing and CNNs.
result Significantly improved prediction accuracy (25% MAE, 48% MSE reduction).
Paper uses Ricci curvature to measure and forecast China's stock market stability.
problem Measuring and predicting systemic stability of China's stock market.
method Geometric measure derived from discrete Ricci curvature applied to financial networks.
result Ricci curvature effectively captures market stability and predicts future trends.
Novel framework detects lead-lag relationships in Chinese A-share market.
problem Detecting lead-lag relationships in the Chinese A-share market.
method Two-stage framework: long-term coupling via correlation, dynamic time warping, and rank-based metrics; high-frequency data analysis via cross-correlation, Granger causality, and regression models.
result Strongly coupled stock pairs often exhibit lead-lag effects, especially at finer time scales.
This study finds ESG rating disagreement reduces corporate productivity, especially in certain types of firms.
problem The impact of ESG rating disagreement on corporate productivity.
method Analysis of A-share listed companies data from 2015 to 2022 using XGBoost regression and SHAP.
result ESG rating disagreement reduces corporate productivity, especially in certain types of firms.
Investor-driven information diffusion affects excess comovement in China and the U.S. markets.
problem Investor-driven information diffusion and its impact on excess comovement.
method Cross-sectional analysis of 4,533 Chinese and 4,517 U.S. stocks from 2010 to 2022.
result Retail-driven information diffusion significantly drives excess comovement in China, while institution-driven diffusion is the primary driver in the U.S.
The study finds solar terms significantly impact China's stock market returns and volatility.
problem Investigating the effect of solar terms on China's stock market.
method Regression framework, analyzing multiple solar terms and their impact on return and volatility.
result Solar terms 1, 3, and 4 cause significant positive returns, while 8, 11, and 14 bring high volatility.
Cross-shareholding improves stock price synchronicity in China.
problem Measuring price informativeness in Chinese stock market firms.
method Analyzing cross-shareholding networks and centrality measures.
result Cross-shareholding reduces price delay and enhances price synchronicity.
There are more than eight hundred interest rates published in China bond market every day. Which are the benchmark interest rates that have broad influences on most interest rates is a major concern for economists. In this paper, multi-variable Granger causality test is developed and applied to construct a directed net…
We document a well-developed log-periodic power-law antibubble in China's stock market, which started in August 2001. We argue that the current stock market antibubble is sustained by a contemporary active unsustainable real-estate bubble in China. The characteristic parameters of the antibubble have exhibited remarkab…
Study shows death ratio of COVID-19 deaths increases financial volatility.
problem Impact of COVID-19 deaths on financial markets.
method Analysis of VIX index based on daily case reports and death ratios.
result Death ratio positively influences financial volatility.
Study finds super-efficiency correlates more strongly with stock market valuation than ROA in Chinese banks.
problem Investigating the relationship between bank efficiency and stock market valuation.
method Employed a non-radial, non-oriented slack-based super-efficiency Data Envelopment Analysis (Super-SBM-UND-VRS) model, treating NPLs as undesired output.
result Super-efficiency is more strongly correlated with stock market valuation than ROA, as measured by Tobin's Q.
China Vanke Co. faced a hostile takeover by Baoneng Group, sparking controversy.
problem A hostile takeover of China Vanke Co. by Baoneng Group.
method No specific method mentioned in the abstract.
result National controversy over corporate governance and government role in capital markets.
Develops a new model for measuring extremal dependence in financial markets.
problem Lack of suitable models for studying extremal dependence in financial markets.
method Constructs regular variation models on Rd and develops a bivariate measure for asymmetry in extremal dependence. result Rejects the Efficient Tail Hypothesis for China's futures market and identifies profitable investment opportunities.
Empirical study of CAPM and Fama-French model in Chinese A-share market.
problem Testing and validating CAPM and Fama-French model in Chinese A-share market.
method Used Fama-MacBeth regression and Fama-French three-factor model to analyze Chinese A-share trading data from 2000 to 2019, adjusting for IPO shell value contamination.
result Fama-French model captures most of A-share market returns, with adjusted R-squared > 0.88.
Study compares information flow between Chinese and US stock sectors.
problem Analyzing how information flows between sectors in Chinese and US stock markets.
method Daily sector indices, transfer entropy of daily returns, comparing 2000-2017.
result Most active sectors in information exchange differ between China and US, reflecting market dynamics.
Study shows how COVID-19 pandemic affected China's crude oil futures market efficiency.
problem Impact of COVID-19 on China's crude oil futures market efficiency.
method Multifractal analysis to compare market efficiency before and during the pandemic.
result Market efficiency of SC and its cross-correlations with other assets increased significantly after the outbreak of COVID-19.
This study analyzes factors affecting China's stock market volatility.
problem Investigating factors influencing China's stock market volatility.
method Used ARDL model and principal component analysis on daily data from 2010-2024.
result Exchange rate and bond yields significantly impact stock market volatility.
Study shows investor sentiment boosts intraday trading in Chinese markets.
problem Impact of investor sentiment on intraday overtrading in Chinese A-share markets.
method High-frequency sentiment indices from social media analyzed for intraday overtrading in CSI 300 and CSI 500 constituents.
result Investor sentiment significantly increases intraday overtrading, especially among institutional investors.
We investigate the spatial and temporal structures of four financial markets in Greater China. In particular, we uncover different characteristics of the four markets by analyzing the sector and subsector structures which are detected through the random matrix theory. Meanwhile, we observe that the Taiwan and Hongkong …
The prevalent view in the economics literature is that a high level of infrastructure investment is a precursor to economic growth. China is especially held up as a model to emulate. Based on the largest dataset of its kind, this paper punctures the twin myths that, first, infrastructure creates economic value, and, se…
China uses two Renminbi markets to hedge cross-border risks, leading to a price discrepancy.
problem China's two Renminbi markets (onshore and offshore) create a price discrepancy for currency forwards.
method Joint equilibrium model for spot and forward trading with transaction costs and segmented supply.
result The model explains the observed forward price discrepancy in terms of offshore liquidity stress.
The paper examines market efficiency in China and India post financial crises.
problem Testing market efficiency in emerging markets post crises.
method Examined daily returns using auto correlation tests, runs tests, and unit root tests.
result Both Chinese and Indian stock markets do not exhibit weak form of market efficiency.
There certainly is little or no doubt that politicians, sometimes consciously and sometimes not, exert a significant impact on stock markets. The evolving volatility over the Republican Donald Trump's surprise victory in the US presidential election is a perfect example when politicians, through announced policies, sen…
Paper uses bipartite graph to forecast cross-market returns, revealing asymmetry.
problem Cross-market return predictability and asymmetry between U.S. and Chinese markets.
method Directed bipartite graph capturing time-ordered linkages, hypothesis testing for edge selection, regularized and ensemble machine learning models.
result U.S. returns predict Chinese intraday returns, but not vice versa, revealing asymmetry.
Paper predicts high-frequency futures return directions using mean-uncertainty methods.
problem Data imbalance in short-term price movements of futures markets.
method Employed mean-uncertainty logistic regression and support vector machines under sublinear expectation framework.
result Mean-uncertainty approaches outperform conventional methods in classification metrics and average returns.
Digital transformation boosts corporate financial asset allocation, especially short-term.
problem Understanding how digital transformation affects corporate financial decisions.
method Fixed-effects models and staggered DID design using A-share listed companies data.
result Digital transformation significantly promotes corporate financial asset allocation, more pronounced in short-term.
Study uses Hawkes processes to analyze stock market contagion in China.
problem Understanding contagion in Chinese stock market.
method Fitting Hawkes processes to daily returns and sector indices.
result Identifies long-term dependencies and trending patterns in sector indices.