English
Related papers

Related papers: Implied Basket Correlation Dynamics

200 papers

The increasing influence of unstructured external information, such as news articles, on stock prices has attracted growing attention in financial markets. Despite recent advances, most existing newsbased forecasting models represent all…

Computational Engineering, Finance, and Science · Computer Science 2025-10-28 Jinwoong Kim , Sangjin Park

Implied volatility IV is a key metric in financial markets, reflecting market expectations of future price fluctuations. Research has explored IV's relationship with moneyness, focusing on its connection to the implied Hurst exponent H. Our…

Computational Finance · Quantitative Finance 2025-02-12 Daniele Angelini , Fabrizio Di Sciorio

It is commonly believed that the correlations between stock returns increase in high volatility periods. We investigate how much of these correlations can be explained within a simple non-Gaussian one-factor description with time…

Disordered Systems and Neural Networks · Physics 2008-12-02 Pierre Cizeau , Marc Potters , Jean-Philippe Bouchaud

Positive feedback trading, which buys when prices rise and sells when prices fall, has long been criticized for being destabilizing as it moves prices away from the fundamentals. Motivated by the relationship between positive feedback…

Mathematical Finance · Quantitative Finance 2021-11-25 Aihua Li

Recent advances in the simulation of frictionally contacting elastodynamics with the Incremental Potential Contact (IPC) model have enabled inversion and intersection-free simulation via the application of mollified barriers, filtered…

Economic models with input-output networks assume that firm or sector (unit) growth is driven by a weighted sum of trade partners' growth and an independently-drawn idiosyncratic shock. I show that the idiosyncratic risk assumption in a…

General Economics · Economics 2022-08-03 Victor Sellemi

We consider the problem of calculating risk-neutral implied volatilities of European options without relying on option mid prices but solely on bid and ask prices. We provide an approach, based on the conic finance paradigm, that allows to…

Mathematical Finance · Quantitative Finance 2021-10-25 Matteo Michielon , Asma Khedher , Peter Spreij

We consider a conditional factor model for a multivariate portfolio of United States equities in the context of analysing a statistical arbitrage trading strategy. A state space framework underlies the factor model whereby asset returns are…

Statistical Finance · Quantitative Finance 2023-09-06 Trent Spears , Stefan Zohren , Stephen Roberts

This paper analyzes how interaction effects can be consistently estimated under economically plausible assumptions in linear panel models with a fixed $T$-dimension. We advocate for a \emph{correlated interaction term estimator} (CITE) and…

Econometrics · Economics 2025-03-18 Chris Muris , Konstantin Wacker

Clustered data are common in biomedical research. Observations in the same cluster are often more similar to each other than to observations from other clusters. The intraclass correlation coefficient (ICC), first introduced by R. A.…

Methodology · Statistics 2024-02-20 Shengxin Tu , Chun Li , Donglin Zeng , Bryan E. Shepherd

In this note, we develop stock option price approximations for a model which takes both the risk o default and the stochastic volatility into account. We also let the intensity of defaults be influenced by the volatility. We show that it…

Computational Engineering, Finance, and Science · Computer Science 2007-12-21 Erhan Bayraktar

The use of intelligent systems for stock market predictions has been widely established. In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well represented using several connectionist paradigms and…

Artificial Intelligence · Computer Science 2007-05-23 Ajith Abraham , Ninan Sajith Philip , P. Saratchandran

Inspired by applications in sports where the skill of players or teams competing against each other varies over time, we propose a probabilistic model of pairwise-comparison outcomes that can capture a wide range of time dynamics. We…

Machine Learning · Statistics 2019-05-20 Lucas Maystre , Victor Kristof , Matthias Grossglauser

This study investigates the application of causal discovery algorithms in equity markets, with a focus on their potential to build investment strategies. An investment strategy was developed based on the causal structures identified by…

Computational Finance · Quantitative Finance 2024-08-30 Ruijie Tang

Financial correlation matrices measure the unsystematic correlations between stocks. Such information is important for risk management. The correlation matrices are known to be ``noise dressed''. We develop a new and alternative method to…

Statistical Mechanics · Physics 2009-11-07 Thomas Guhr , Bernd Kaelber

Computation of observables in discrete stochastic, possibly conditioned, dynamics over large sparse networks is at the basis of a myriad of applications. The Matrix-Product Belief Propagation method allows a semi-analytical estimation of…

Statistical Mechanics · Physics 2026-05-15 Federico Florio , Alfredo Braunstein

We calculate the inelastic scattering probabilities in the wide band limit of a local polaron model with quadratic coupling to bosons. The central object is a two-particle Green function which is calculated exactly using a purely algebraic…

Materials Science · Physics 2010-03-25 Thomas Olsen

The correlation matrix formalism is used to study temporal aspects of the stock market evolution. This formalism allows to decompose the financial dynamics into noise as well as into some coherent repeatable intraday structures. The present…

Soft Condensed Matter · Physics 2009-11-07 J. Kwapien , S. Drozdz , F. Gruemmer , F. Ruf , J. Speth

The value of stocks, indices and other assets, are examples of stochastic processes with unpredictable dynamics. In this paper, we discuss asymmetries in short term price movements that can not be associated with a long term positive trend.…

Data Analysis, Statistics and Probability · Physics 2009-11-13 Ingve Simonsen , Peter Toke Heden Ahlgren , Mogens H. Jensen , Raul Donangelo , Kim Sneppen

Correlations between two variables of a high-dimensional system can be indicative of an underlying interaction, but can also result from indirect effects. Inverse Ising inference is a method to distinguish one from the other. Essentially,…

Populations and Evolution · Quantitative Biology 2014-12-10 Benedikt Obermayer , Erel Levine