Study examines trading costs after Hong Kong-Shanghai Connect.
problem Estimating trading costs in China's securities market.
method Developed a novel methodology to compensate for lack of data.
result Trading costs on Shanghai may have increased after Connect.
We have performed detailed multifractal analysis on the minutely volatility of two indexes and 1139 stocks in the Chinese stock markets based on the partition function approach. The partition function χq(s) scales as a power law with respect to box size s. The scaling exponents τ(q) form a nonlinear function of …
There are some statistical anomalies in the Chinese stock market, i.e., positive return skewness, anti-leverage effect (positive returns induce higher volatility than negative returns); and reverse volatility asymmetry (contemporaneous return-volatility correlation is positive). In this paper, we first confirm the exis…
China's QFII and RQFII programs expand foreign investment in Chinese markets.
problem Foreign investment restrictions in China's capital markets.
method Comparative analysis of globalization processes in Taiwan, Korea, and India.
result China's market openness increases as foreign demand grows.
New method selects edges in stock networks using multiple threshold values.
problem Balancing prominent correlations and network connectivity in stock networks.
method Uses multiple distributions in a maximum likelihood estimator for selecting threshold values.
result Proposed method develops networks with appropriate connectivities.
We introduce the Speculative Influence Network (SIN) to decipher the causal relationships between sectors (and/or firms) during financial bubbles. The SIN is constructed in two steps. First, we develop a Hidden Markov Model (HMM) of regime-switching between a normal market phase represented by a geometric Brownian moti…
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.
An active margin system for margin loans is proposed for Chinese margin lending market, which uses cash and randomly selected stock as collateral. The conditional probability of negative return(CPNR) after a forced sale of securities from under-margined account in a falling market is used to measure the risk faced by t…
This study analyzes information flow networks in Chinese stock sectors using transfer entropy.
problem Understanding information transmission and market dynamics in Chinese stock sectors.
method Daily closing price data of 28 sectors from 2000 to 2017, transfer entropy, maximum spanning arborescence (MSA).
result The composite sector is an information source, and the non-bank financial sector is an information sink.
Paper improves Chinese word segmentation using dictionary knowledge.
problem Chinese word segmentation with limited labeled data.
method Two methods: pseudo labeled data generation and multi-task learning.
result Improves Chinese word segmentation performance, especially with scarce training data.
Paper proposes SA-VAE for generating stylized Chinese characters.
problem Automatic generation of stylized Chinese characters is challenging.
method Proposes Style-Aware Variational Auto-Encoder (SA-VAE) to capture content and style components.
result Shows powerful one-shot/low-shot generalization ability.
Paper uses PCA to analyze Chinese sovereign bonds and discusses bond immunization.
problem Analyzing factors affecting Chinese sovereign bond yield changes.
method Applied Principal Component Analysis (PCA) on bond yield data.
result Identified principal factors influencing Chinese sovereign bond yield changes.
Paper proposes neural approach for Chinese named entity recognition.
problem Challenges in Chinese named entity recognition due to context-dependency and lack of word delimiters.
method Introduces a CNN-LSTM-CRF neural architecture and a unified framework for joint training with word segmentation.
result Improves Chinese named entity recognition performance, especially with limited training data.
Study reveals risk transmission channels among Chinese sectors.
problem Understanding risk transmission within Chinese economic sectors.
method Volatility spillovers analysis using VAR model and rolling window approach.
result 17 sectors are risk transmitters and 11 are risk takers.
FGN improves Chinese NER by integrating glyph information and interactive context.
problem Chinese named entity recognition is challenging due to the complexity of characters and their glyphs.
method FGN uses a novel CGS-CNN structure to capture glyph and interactive information, and a sliding window method to fuse BERT and glyph representations.
result FGN achieves state-of-the-art performance on four NER datasets, improving over previous methods.
Deep learning system generates new Chinese fonts via style variables.
problem Efficiently design new Chinese fonts.
method End-to-end deep learning system generating new style fonts via interpolation of latent style-related embedding variables.
result Smooth transition between different font styles achieved.
L. Kauffman conjectured that a particular solution of the Chinese Rings puzzle is the simplest possible. We prove his conjecture by using low-dimensional topology and group theory. We notice also a surprising connection between the Chinese Rings and Habiro moves (related to Vassiliev invariants).
Study shows Chinese stock market returns are predictable over time, especially during market turbulence.
problem Predicting returns in the Chinese stock market is challenging due to market inefficiency.
method Used wild bootstrap automatic variance ratio test and generalized spectral test.
result Return predictability varies over time, with significant predictability during market turmoils.
The paper constructs financial sentiment factors using NLP for the Chinese market.
problem Evaluating sentiment in the Chinese financial market.
method Crawling news and comments, applying NLP techniques, building a finance-specific lexicon, and adjusting the sentiment factor.
result The adjusted sentimental factor has a strong correlation with the Chinese market, especially during crises.
Analysis shows preference for Chinese yuan in global trade network.
problem Analyzing the preference of countries to trade in US dollars or Chinese yuan.
method Mathematical analysis of world trade network using Ising spin interactions.
result Majority of countries prefer trading in Chinese yuan due to network structure.
Study finds key subgraphs in Chinese guarantee networks.
problem Understanding the structure of Chinese guarantee networks.
method Analysis of 2- and 3-node subgraphs considering financial heterogeneity.
result Mutual, 2-out-stars, and triangle sub-patterns are common motifs.
Model predicts Chinese stock market liquidity and customer order behavior.
problem Understanding market liquidity and customer order behavior in the Chinese stock market.
method Dual state-space model using Fourier transform to connect volume-at-price buckets to correlations.
result Customer orders are correlated with market sentiment and stock returns, not with bond returns.
Chinese stock market shows time series momentum and contrarian effects over different periods.
problem Analyzing momentum and contrarian effects in Chinese stock market performance.
method Examined time series momentum and contrarian strategies applied to major indices in China.
result Time series momentum effect in short run, contrarian effect in long run, performance dependent on look-back and holding periods.
BERT improves Chinese word segmentation performance.
problem Chinese word segmentation task.
method Applying BERT to CWS task using benchmark datasets.
result BERT can improve performance even with inconsistent labels.
Study examines volatility-based strategy for Chinese ETF options, improving returns in volatile markets.
problem Lack of effective trading strategies in volatile Chinese equity markets.
method Volatility forecasting using GARCH models to dynamically adjust positions and exposures.
result Dynamic adjustment of positions and exposures enhances returns in volatile markets.
Neural approach for Chinese word segmentation using lexicon and unlabeled data.
problem Efficiently segment Chinese words with limited labeled data.
method Posterior regularization algorithm with indirect supervision from lexicon and unlabeled data.
result Validation of approach on multiple benchmark datasets in in-domain and cross-domain scenarios.
Study evaluates LLMs for predicting Chinese stock movements using financial news sentiments.
problem Evaluating LLMs' ability to predict stock price movements using financial news sentiments.
method Standardized experimental procedure with three LLMs, each with unique performance enhancement methods.
result Developed quantitative trading strategies and conducted back-tests to assess LLMs' performance.
This study uses NLP to predict stock performance based on analyst reports.
problem Predicting stock performance using textual information from analyst reports.
method Natural language processing (NLP) and a customized BERT deep learning model for Chinese text.
result Strong positive sentiment in analyst reports increases excess return and intraday volatility, while strong negative sentiment increases volatility and trading volume but decreases excess return.
This paper analyzes the quantitative relations between stock prices and quantities of tradable stock shares in Chinese stock markets at six time points by means of Exploratory Data Analysis (EDA) method. It is found the resulting formulae have the same structure but different parameters. This paper also uses these rela…
Modeling equity market impact with Chinese data, improving on existing models.
problem Understanding and quantifying market impact in Chinese equity markets.
method Developed a price impact model considering heteroscedasticity and dependency between permanent and temporary impacts using large tick data.
result The model outperforms existing models and suggests a constant impact exponent of around 0.7 across all stocks.
Study predicts 2015 Chinese stock market bubble using LPPLS model.
problem Detecting and predicting the 2015 Chinese stock market bubble.
method Calibrated Log Periodic Power Law Singularity (LPPLS) model, Lomb spectral analysis, Unit-root tests, CMA-ES optimization.
result The LPPLS model can predict the actual critical day (tc) two months before the bubble crash.
Paper develops neural network for Mandarin polyphone disambiguation.
problem Homograph problem in Mandarin Chinese text-to-speech.
method Bidirectional RNN for context, prediction network for mapping embeddings to pronunciations.
result Achieves 94.69% accuracy on polyphonic character dataset.
New framework analyzes pre-stock jump trading behaviors using multivariate time series analysis.
problem Understanding micro-trading behaviors before stock price jumps.
method Multivariate time series analysis considering temporal information.
result Identifies highly informative attributes for predicting price jumps.
A new Chinese Checkers agent combines heuristics, MCTS, and deep RL.
problem Challenging state-space and unbounded depth in Chinese Checkers.
method Combines heuristics, Monte Carlo Tree Search, and deep reinforcement learning.
result Competent agent reaches human player level.
To investigate the universal structure of interactions in financial dynamics, we analyze the cross-correlation matrix C of price returns of the Chinese stock market, in comparison with those of the American and Indian stock markets. As an important emerging market, the Chinese market exhibits much stronger correlations…
Study replicates reference-dependent preferences impact on risk-return trade-off in Chinese stock market.
problem Impact of reference-dependent preferences on risk-return trade-off in Chinese stock market.
method Utilized CGO proxy, econometric techniques (Dependent Double Sorting, Fama-MacBeth regressions), and data from 1995-2024.
result Reference-dependent preferences have a weaker or absent positive risk-return relationship in the Chinese market.
The paper examines how contrarian and momentum effects in Chinese stock markets fluctuate over time.
problem Investigating the time-varying risk-premium relation of Chinese stock markets.
method Using the Capital Asset Pricing Model and French-Fama three factor model, the paper studies the evolving arbitrage opportunities and contrarian profitability in Chinese stock markets.
result Contrarian and momentum effects in Chinese stock markets vary over time, with higher profitability in certain market conditions.
Article proposes a profitable intraday trading strategy for Chinese stocks.
problem Intraday trading opportunities in Chinese stock market.
method Markowitz optimization and Multilayer Perceptron (MLP) for stock price prediction.
result Validation of Markowitz portfolio optimization and MLP for intraday stock price prediction.
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.
FinTech negatively impacts Chinese banks' financial sustainability.
problem Impact of FinTech on financial sustainability of Chinese commercial banks.
method Three-stage network DEA-Malmquist model and two-way fixed effects model.
result FinTech primarily undermines financial sustainability by eroding loan efficiency and profitability.
Study optimizes market making in Chinese stock market with stochastic control and scenario analysis.
problem Limited research on market making in Chinese stock market.
method Optimal market making framework with exponential CARA utility function, accounting for market conditions and risks.
result Impact of volatility and stamp duty on market maker's profit and liquidity.
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.
Paper builds a supervised learning model for Chinese futures price prediction.
problem Predicting the trend of Chinese futures prices accurately.
method Supervised learning model designed for futures price movement classification.
result The model meets accuracy requirements for classifying futures price movements.
Paper finds political networks reduce bond issuance costs in China.
problem The financial value of within-government political networks in China.
method Using municipal leaders' working experience to measure political networks, the study examines the effect on bond issuance yield spreads.
result Political networks reduce bond issuance yield spreads by improving issuer credit ratings, especially in less developed financial markets.
Improved AI patent classifier measures U.S. and China's AI patenting.
problem Measuring AI patents with high precision and generalization.
method Fine-tuning PatentSBERTa on manually labeled data from USPTO's AI Patent Dataset.
result Rapid growth in AI patenting in both countries, but different organizational patterns.
Geography and distance impact financial dynamics in Chinese stock markets.
problem Investigate the impact of geography and distance on financial dynamics in Chinese stock markets.
method Daily data analysis of individual stocks in Shanghai and Shenzhen stock markets, focusing on geographical correlation and distance effect.
result Stock location impacts financial dynamics, except during financial crises. Short distance has higher probability than long distance, and correlation weakly decays with distance in Shanghai but remains stable in Shenzhen.
Directly proves CRP from stick-breaking process without measure theory.
problem Indirect proof of CRP from stick-breaking process is complex.
method Direct proof using stick-breaking process to CRP, avoiding measure theory.
result Direct proof connects stick-breaking process to CRP.
Improved CNN for HCCR with new loss function and ranking method.
problem Loss of inter-class information in traditional CNN models for HCCR.
method Combining cross entropy with a new similarity ranking function (Average variance similarity) as loss function.
result New loss function (SoftMax cross entropy with Average variance similarity) achieves highest accuracy in HCCR.