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.
Study introduces KorFinMTEB for Korean financial texts, revealing model limitations.
Proposes RDASS for better Korean text summarization evaluation.
Study finds financial YouTube channel 3PROTV predicts stock market performance and sentiment changes.
We study the effect of globalization on the Korean market, one of the emerging markets. Some characteristics of the Korean market are different from those of the mature market according to the latest market data, and this is due to the influence of foreign markets or investors. We concentrate on the market network stru…
NMIXX fine-tunes embeddings for finance, outperforming general models in Korean.
Improved sentiment analysis in Korean finance using masked PLMs.
We study the dynamical behavior of high-frequency data from the Korean Stock Price Index (KOSPI) using the movement of returns in Korean financial markets. The dynamical behavior for a binarized series of our models is not completely random. The conditional probability is numerically estimated from a return series of K…
In this paper, we studied the dynamics of the log-return distribution of the Korean Composition Stock Price Index (KOSPI) from 1992 to 2004. Based on the microscopic spin model, we found that while the index during the late 1990s showed a power-law distribution, the distribution in the early 2000s was exponential. This…
We apply the formalism of the continuous time random walk (CTRW) theory to financial tick data of the bond futures transacted in Korean Futures Exchange (KOFEX) market. For our case, the tick dynamical behaviors of the returns and volatility for bond futures are treated particularly at the long-time limit. The volatili…
This study empirically re-examines fat tails in stock return distributions by applying statistical methods to an extensive dataset taken from the Korean stock market. The tails of the return distributions are shown to be much fatter in recent periods than in past periods and much fatter for small-capitalization stocks …
In this study, we establish a network structure of the Korean stock market, one of the emerging markets, with its minimum spanning tree through the correlation matrix. Base on this analysis, it is found that the Korean stock market doesn't form the clusters of the business sectors or of the industry categories. When th…
The multifractal behavior for tick data of prices is investigated in Korean financial market. Using the rescaled range analysis(R/S analysis), we show the multifractal nature of returns for the won-dollar exchange rate and the KOSPI. We also estimate the Hurst exponent and the generalized th-order Hurst exponent in …
We study the evolution of probability distribution functions of returns, from the tick data of the Korean treasury bond (KTB) futures and the S$&$P 500 stock index, which can be described by means of the Fokker-Planck equation. We show that the Fokker-Planck equation and the Langevin equation from the estimated Kramers…
We investigated financial market data to determine which factors affect information flow between stocks. Two factors, the time dependency and the degree of efficiency, were considered in the analysis of Korean, the Japanese, the Taiwanese, the Canadian, and US market data. We found that the frequency of the significant…
Modeling financial time series with LSTM and trainable initial states.
ClovaCall introduces a new Korean call speech corpus for contact centers.
The herd behaviors of returns for the won-dollar exchange rate and the KOSPI are analyzed in Korean financial markets. It is shown that the probability distribution of price returns for three values of the herding parameter tends to a power-law behavior with the exponents (the wo…
This paper analyzes text in financial disclosures to improve financial analysis.
Paper uses Transformers to predict intraday volume ratio with high accuracy.
We introduce the minority game theory for two kinds of the Korean treasury bond (KTB) in Korean futures exchange markets. Since we discuss numerically the standard deviation and the global efficiency for an arbitrary strategy, our case is found to be approximate to the majority game. Our result presented will be compar…
We investigate the distribution function and the cumulative probability for Korean household incomes, i.e., the current, labor, and property incomes. For our case, the distribution functions are consistent with a power law. It is also showed that the probability density of income growth rates almost has the form of a e…
We consider returns of two Korean stock market indices, KOSPI and KOSDAQ index. Central parts of the probability distribution function of returns are well fitted by the Lorentzian distribution function. However, tail parts of the probability distribution function follow a power law behavior well. We found that the prob…
New distress dictionary improves bankruptcy prediction from disclosure text.
Mining financial text documents and understanding the sentiments of individual investors, institutions and markets is an important and challenging problem in the literature. Current approaches to mine sentiments from financial texts largely rely on domain specific dictionaries. However, dictionary based methods often f…
Anonymization reduces economic signal extraction from financial texts.
Investor flows in Korean equity market transmit shared information, not private signals.
System detects relevant financial news and predictions from unstructured text.
FINCH dataset enables financial Text-to-SQL tasks, improving model evaluation.
This study uses NLP to detect financial risks from documents.
BioFinBERT analyzes sentiment of biotech press releases and financial text around inflection points.
Enhanced regime shifts detection using unstructured text and financial data.
FinEAS models financial sentiment using BERT embeddings.
German FinBERT improves financial text analysis performance.
Study evaluates if LLMs have company-specific biases in financial sentiment analysis.
Paper introduces NumLLM for better financial text understanding with numeric variables.
Simple feature engineering beats complex models in financial prediction.
We investigated the temporally evolving network structures of the Japanese and Korean stock markets through the minimum spanning trees composed of listed stocks. We tested the validity of conventional grouping by industrial categories, and found a common trend of decrease for Japan and Korea. This phenomenon supports t…
Following the financial crisis of the late 2000s, policy makers have shown considerable interest in monitoring financial stability. Several central banks now publish indices of financial stress, which are essentially based upon market related data. In this paper, we examine the potential for improving the indices by de…
We analyzed cross-correlations between price fluctuations of global financial indices (20 daily stock indices over the world) and local indices (daily indices of 200 companies in the Korean stock market) by using random matrix theory (RMT). We compared eigenvalues and components of the largest and the second largest ei…
UniFinEval benchmarks financial models across text, images, and videos.
BERTopic improves financial text analysis with FinTextSim's contextual embeddings.
FinGPT democratizes financial data for LLMs, enabling innovation.
We consider the effects of the global financial crisis through a local Korean financial market around the 2008 crisis. We analyze 185 individual stock prices belonging to the KOSPI (Korea Composite Stock Price Index), cosidering three time periods: the time before, during, and after the crisis. The complex networks gen…
InvestLM is a financial domain LLM tuned on LLaMA-65B for investment advice.
We investigate a factor that can affect the number of links of a specific stock in a network between stocks created by the minimal spanning tree (MST) method, by using individual stock data listed on the S&P500 and KOSPI. Among the common factors mentioned in the arbitrage pricing model (APM), widely acknowledged in th…
This study uses deep learning to analyze stock market sentiment from financial forums.
We study the tick dynamical behavior of the bond futures in Korean Futures Exchange(KOFEX) market. Since the survival probability in the continuous-time random walk theory is applied to the bond futures transaction, the form of the decay function in our bond futures model is discussed from two kinds of Korean Treasury …
Qwen3-8B outperforms classical models in financial text classification.