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.
Paper breaks down risk contribution into inherent and correlation risk components.
This paper introduces anti-correlation networks to study China's stock market.
The paper finds a surprising positive correlation between upstreamness and downstreamness in global value chains.
Bootstrapping regularizes singular correlation matrices, reducing the need for complex regularization.
A new way to describe correlation matrices makes modeling easier.
Proposes a hierarchical clustering method for positive and negative dissimilarities.
We report evidence of a deep interplay between cross-correlations hierarchical properties and multifractality of New York Stock Exchange daily stock returns. The degree of multifractality displayed by different stocks is found to be positively correlated to their depth in the hierarchy of cross-correlations. We propose…
This article provides the mathematical foundation for stochastically continuous affine processes on the cone of positive semidefinite symmetric matrices. This analysis has been motivated by a large and growing use of matrix-valued affine processes in finance, including multi-asset option pricing with stochastic volatil…
This letter explores the behavior of conditional correlations among main cryptocurrencies, stock and bond indices, and gold, using a generalized DCC class model. From a portfolio management point of view, asset correlation is a key metric in order to construct efficient portfolios. We find that: (i) correlations among …
ChatGPT predicts stock market movements based on Bloomberg headlines, showing a positive correlation over short to medium terms.
Novel trading strategy for generalized lattice markets ensures positive profits.
Proposes a new model to describe positive volatility-price correlation in commodity markets.
A fast method estimates correlations in hybrid systems using observable market data.
Stock correlations is crucial to asset pricing, investor decision-making, and financial risk regulations. However, microscopic explanation based on agent-based modeling is still lacking. We here propose a model derived from minority game for modeling stock correlations, in which an agent's expected return for one stock…
Develops correlation number for specific potentials and Hitchin representations.
Study analyzes factors affecting capital adequacy in Bangladesh's banks.
We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximiz…
The paper examines how small positive dependence can lead to correlated tail risks.
In the recent years, banks have sold structured products such as worst-of options, Everest and Himalayas, resulting in a short correlation exposure. They have hence become interested in offsetting part of this exposure, namely buying back correlation. Two ways have been proposed for such a strategy : either pure correl…
We study the relation between serial correlation of financial returns and volatility at intraday level for the S&P500 stock index. At daily and weekly level, serial correlation and volatility are known to be negatively correlated (LeBaron effect). While confirming that the LeBaron effect holds also at intraday level, w…
Factorial moments are convenient tools in particle physics to characterize the multiplicity distributions when phase-space resolution () becomes small. They include all correlations within the system of particles and represent integral characteristics of any correlation between these particles. In this letter, we sh…
We point out a stunning time asymmetry in the short time cross correlations between intra-day and overnight volatilities (absolute values of log-returns of stock prices). While overnight volatility is significantly (and positively) correlated with the intra-day volatility during the \textit{following} day (allowing thu…
Correlations between asset returns are important in many financial applications. In recent years, multivariate volatility models have been used to describe the time-varying feature of the correlations. However, the curse of dimensionality quickly becomes an issue as the number of correlations is for asse…
The study examines correlations of logarithms of integers at different scalings.
Study examines stock price correlations between Indonesian holding companies and their subsidiaries.
In 2012, JPMorgan accumulated a USD~6.2 billion loss on a credit derivatives portfolio, the so-called `London Whale', partly as a consequence of de-correlations of non-perfectly correlated positions that were supposed to hedge each other. Motivated by this case, we devise a factor model for correlations that allows for…
Identifying homogeneous subgroups of variables can be challenging in high dimensional data analysis with highly correlated predictors. We propose a new method called Hexagonal Operator for Regression with Shrinkage and Equality Selection, HORSES for short, that simultaneously selects positively correlated variables and…
This study uses local Gaussian correlation to analyze stock return tails, revealing more sensitive network properties.
Method estimates sparse inverse covariance and partial correlation matrices efficiently.
We study power-law correlations properties of the Google search queries for Dow Jones Industrial Average (DJIA) component stocks. Examining the daily data of the searched terms with a combination of the rescaled range and rescaled variance tests together with the detrended fluctuation analysis, we show that the searche…
Study sharpens threshold for matching correlated graphs without labels.
Study finds stock selection ability of Chinese mutual funds is better than asset allocation ability.
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…
We develop a theoretical trading conditioning model subject to price volatility and return information in terms of market psychological behavior, based on analytical transaction volume-price probability wave distributions in which we use transaction volume probability to describe price volatility uncertainty and intens…
Bayesian model fuses multiple classifiers with explicit correlation modeling.
This paper sets thresholds for recovering vertex correspondences in partially correlated graphs.
Biclustering is an unsupervised data mining technique that aims to unveil patterns (biclusters) from gene expression data matrices. In the framework of this thesis, we propose new biclustering algorithms for microarray data. The latter is done using data mining techniques. The objective is to identify positively and ne…
We analyse the temporal changes in the cross correlations of returns on the New York Stock Exchange. We show that lead-lag relationships between daily returns of stocks vanished in less than twenty years. We have found that even for high frequency data the asymmetry of time dependent cross-correlation functions has a d…
Paper defines conditions for feasible correlation matrices from factor structures.
Graph Canonical Correlation Analysis improves CCA for multiomics datasets.
The paper studies the correlation of Hilbert lengths for convex projective surfaces.
Study quantizes ropelength and writhe of 12-crossing knots.
Two insurance companies collaborate to maximize the probability of none going bankrupt.
With the random matrix theory, we study the spatial structure of the Chinese stock market, American stock market and global market indices. After taking into account the signs of the components in the eigenvectors of the cross-correlation matrix, we detect the subsector structure of the financial systems. The positive …
We analyze a method to produce pairs of non independent Poisson processes from positively correlated, self-decomposable, exponential renewals. In particular the present paper provides the family of copulas pairing the renewals, along with the closed form for the joint distribution of the pair…
Researchers develop geodesics for a new metric on correlation matrices.
We discovered that past changes in the market correlation structure are significantly related with future changes in the market volatility. By using correlation-based information filtering networks we device a new tool for forecasting the market volatility changes. In particular, we introduce a new measure, the "correl…
Cryptocurrency market becomes more cross-correlated over time.