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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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25.0%50.0%75.0%100.0% · Jun 199319922001200920182026
48 results for Chinese Remainder Theorem

Paper introduces statistical CRT for robust multiple parameter estimation.

problem Ambiguity resolution problem with exponential failure probability.
method Proposes a wrapped Gaussian mixture model and two novel approaches for robust estimation.
result Statistically based scheme achieves stronger robustness, especially in low SNR.

Let MM be a closed Riemannian manifold carrying an effective and isometric action of a compact connected Lie group GG. We derive a refined remainder estimate in the stationary phase approximation of certain oscillatory integrals on TM×GT^\ast M \times G with singular critical sets that were examined previously in order…

2015-07-20abs ↗pdf ↗

Study embeddings between Barron spaces with various activation functions, focusing on RePU.

problem Understanding the influence of activation functions on infinitely wide neural networks.
method Prove embeddings by constructing push-forward maps on measures representing functions.
result Barron spaces with RePU activation have a hierarchical structure similar to Sobolev spaces.

Improved estimate for remainder term in Weyl law for congruence subgroups of Chevalley groups.

problem Improving the remainder term estimate in the Weyl law for congruence subgroups of Chevalley groups.
method Sharpened the Weyl law remainder term estimate for simply connected Chevalley groups.
result Power saving estimate for the remainder term.

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.

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.

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).

2000-07-21abs ↗pdf ↗

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.

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.

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.

In this paper we study minimal and constant mean curvature (cmc) periodic surfaces in H^2 x R. More precisely, we consider quotients of H^2 x R by discrete groups of isometries generated by horizontal hyperbolic translations f and/or a vertical translation T. In the quotient by the Z^2 subgroup of the isometry group ge…

2011-06-29abs ↗pdf ↗

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.

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…

2012-02-02abs ↗pdf ↗

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.

China's stock market is the largest emerging market all over the world. It is widely accepted that the Chinese stock market is far from efficiency and it possesses possible linear and nonlinear dependence. We study the predictability of returns in the Chinese stock market by employing the wild bootstrap automatic varia…

2016-11-13abs ↗pdf ↗

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.

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.

This paper concentrates on the time series momentum or contrarian effects in the Chinese stock market. We evaluate the performance of the time series momentum strategy applied to major stock indices in mainland China and explore the relation between the performance of time series momentum strategies and some firm-speci…

2017-02-07abs ↗pdf ↗

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.

The paper explores how dynamic preconditioning affects the CLT in online averaging.

problem When does dynamic preconditioning preserve the Polyak-Ruppert CLT?
method The authors decompose the averaged error and identify a stabilization-rate threshold for the CLT to hold.
result The CLT holds if the dynamic remainder vanishes in L2L^2 and the stabilization rate exceeds a threshold.

Amid the current financial crisis, there has been one equity index beating all others: the Shanghai Composite. Our analysis of this main Chinese equity index shows clear signatures of a bubble build up and we go on to predict its most likely crash date: July 17-27, 2009 (20%/80% quantile confidence interval).

2009-07-10abs ↗pdf ↗

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.