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.
Model shows triangular arbitrage key to cross-currency correlations in forex markets.
Transformer predicts Ethereum prices using cross-currency correlation and sentiment analysis.
Proposes a new method to assess Wrong-Way Risk in cross-currency swaps.
Develops a new model for cross-currency derivatives pricing.
Paper examines pricing and hedging for cross-currency swaps referencing backward-looking rates.
Abstract framework for cross-currency interest rate contracts.
A method to complete incomplete correlation matrices using maximum entropy.
This paper examines pricing and hedging strategies for cross-currency equity protection swaps.
Study proposes a method to construct copulas using corrected Hermite polynomial expansion for estimating foreign exchange volatility.
The Multi Variate Mixture Dynamics model is a tractable, dynamical, arbitrage-free multivariate model characterized by transparency on the dependence structure, since closed form formulae for terminal correlations, average correlations and copula function are available. It also allows for complete decorrelation between…
Study multi-currency markets with multiple interest rates and collateral.
We revisit the problem of pricing and hedging plain vanilla single-currency interest rate derivatives using multiple distinct yield curves for market coherent estimation of discount factors and forward rates with different underlying rate tenors. Within such double-curve-single-currency framework, adopted by the market…
In the forthcoming ISDA Standard Credit Support Annex (SCSA), the trades denominated in non-G5 currencies as well as those include multiple currencies are expected to be allocated to the USD silo, where the contracts are collateralized by USD cash, or a different currency with an appropriate interest rate overlay to ac…
Collateralization with daily margining has become a new standard in the post-crisis market. Although there appeared vast literature on a so-called multi-curve framework, a complete picture of a multi-currency setup with cross-currency basis can be rarely found since our initial attempts. This work gives its extension r…
A new challenge to quantitative finance after the recent financial crisis is the study of credit valuation adjustment (CVA), which requires modeling of the future values of a portfolio. In this paper, following recent work in [Weinan E(2017), Han(2017)], we apply deep learning to attack this problem. The future values …
This research uses empirical copulas to price quanto options, showing significant differences from traditional models.
It is well known that traded foreign exchange forwards and cross currency swaps (CCS) cannot be priced applying overnight cash and carry arguments as they imply absence of funding advantage of one currency to the other. This paper proposes a heuristic present value concept for multi-currency pricing and hedging which a…
We present a general derivation of the arbitrage-free pricing framework for multiple-currency collateralized products. We include the impact on option pricing of the policy adopted to fund in foreign currency, so that we are able to price contracts with cash flows and/or collateral accounts expressed in foreign currenc…
The financial crisis of 2007/08 caused catastrophic consequences and brought a bunch of changes around the world. Interest rates that were known to follow or behave similarly of each other diverged. Furthermore, the regulation and in particular the counterparty credit risk began to to be considered and quantified. Cons…
The focus of this paper is the efficient computation of counterparty credit risk exposure on portfolio level. Here, the large number of risk factors rules out traditional PDE-based techniques and allows only a relatively small number of paths for nested Monte Carlo simulations, resulting in large variances of estimator…
This work optimizes induced correlation in joint graph embeddings.
In this paper we use wavelet concepts to show that correlation coefficient between two financial data's is not constant but varies with scale from high correlation value to strongly anti-correlation value This studies is important because correlation coefficient is used to quantify degree of independence between two va…
We analyze the daily stock data of the Nasdaq Composite index in the 22-year period 1992-2013 and identify market states as clusters of correlation matrices with similar correlation structures. We investigate the stability of the correlation structure of each state by estimating the statistical fluctuations of correlat…
The study uses DCC for financial market analysis, revealing hidden correlations.
This study uses local Gaussian correlation to analyze stock return tails, revealing more sensitive network properties.
Polynomial time algorithm matches correlated Gaussian matrices without vanishing correlation.
This paper treats the problem of screening for variables with high correlations in high dimensional data in which there can be many fewer samples than variables. We focus on threshold-based correlation screening methods for three related applications: screening for variables with large correlations within a single trea…
This paper introduces anti-correlation networks to study China's stock market.
The study shows how trade uncertainty affects stock-bond correlations over time.
Infinite CNNs lose spatial correlations, but can be restored by correlated weights.
We discuss some methods to quantitatively investigate the properties of correlation matrices. Correlation matrices play an important role in portfolio optimization and in several other quantitative descriptions of asset price dynamics in financial markets. Specifically, we discuss how to define and obtain hierarchical …
This research examines rare spurious correlations in neural networks and their impact on accuracy and privacy.
The study reveals how synaptic correlations promote dimension reduction in neural networks.
Proposes PSCCA for estimating correlations and canonical correlations in sparse count data.
Study examines NFT market dynamics using correlation and noise analysis.
Polynomial-time algorithm matches correlated random graphs with non-vanishing correlation.
Proposes a multi-view VAE for imputing missing data from correlated sources.
Neurons in the visual cortex are correlated in their variability. The presence of correlation impacts cortical processing because noise cannot be averaged out over many neurons. In an effort to understand the functional purpose of correlated variability, we implement and evaluate correlated noise models in deep convolu…
Enhances community detection in correlated networks with node attributes.
New method detects intrinsic cross-correlations in non-stationary time series affected by common factors.
Develops correlation number for specific potentials and Hitchin representations.
The study finds significant power-law cross correlations in Bitcoin's return-volatility dynamics.
Financial markets analyzed by reducing correlation matrix complexity.
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…
Discovering a correlation from one variable to another variable is of fundamental scientific and practical interest. While existing correlation measures are suitable for discovering average correlation, they fail to discover hidden or potential correlations. To bridge this gap, (i) we postulate a set of natural axioms …
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 …
This paper analyzes correlations in patterns of trading of different members of the London Stock Exchange. The collection of strategies associated with a member institution is defined by the sequence of signs of net volume traded by that institution in hour intervals. Using several methods we show that there are signif…
Improved portfolio optimization using Kendall-like correlation coefficients.