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In this study, we predict next-day movements of stock end-of-day implied volatility using random forests. Through an ablation study, we examine the usefulness of different sources of predictors and expose the value of attention and…

Computational Finance · Quantitative Finance 2023-01-03 Thomas Dierckx , Jesse Davis , Wim Schoutens

Implied volatilities form a well-known structure of smile or surface which accommodates the Bachelier model and observed market prices of interest rate options. For the swaptions that we study, three parameters are taken into account for…

Statistical Finance · Quantitative Finance 2017-10-04 Jinglun Yao , Sabine Laurent , Brice Bénaben

Most machine learning models operate under the assumption that the training, testing and deployment data is independent and identically distributed (i.i.d.). This assumption doesn't generally hold true in a natural setting. Usually, the…

Machine Learning · Computer Science 2021-12-14 Kumud Lakara , Akshat Bhandari , Pratinav Seth , Ujjwal Verma

We calculate realized volatility of the Nikkei Stock Average (Nikkei225) Index on the Tokyo Stock Exchange and investigate the return dynamics. To avoid the bias on the realized volatility from the non-trading hours issue we calculate…

Statistical Finance · Quantitative Finance 2017-04-28 Tetsuya Takaishi , Toshiaki Watanabe

We formulate and analyze an inverse problem using derivatives prices to obtain an implied filtering density on volatility's hidden state. Stochastic volatility is the unobserved state in a hidden Markov model (HMM) and can be tracked using…

Pricing of Securities · Quantitative Finance 2017-03-07 Carlos Fuertes , Andrew Papanicolaou

Albeit of crucial interest for both financial practitioners and researchers, market-implied volatility data of European swaptions often exhibit large portions of missing quotes due to illiquidity of the various underlying swaption…

Machine Learning · Computer Science 2022-04-25 Ivo Richert , Robert Buch

This paper introduces a unified parametric modeling approach for time-varying market betas that can accommodate continuous-time diffusion and discrete-time series models based on a continuous-time series regression model to better capture…

Methodology · Statistics 2022-04-15 Donggyu Kim , Minseog Oh , Minjeong Song , Yazhen Wang

We propose a robust hypothesis testing procedure for the predictability of multiple predictors that could be highly persistent. Our method improves the popular extended instrumental variable (IVX) testing (Phillips and Lee, 2013; Kostakis…

Methodology · Statistics 2024-01-03 Xiaosai Liao , Xinjue Li , Qingliang Fan

This paper studies the joint role of long-memory dynamics,rough-volatility behavior, and persistence-based forecasting features in equity volatility modeling. We combine semiparametric long-memory estimation, rough-volatility diagnostics,…

Statistical Finance · Quantitative Finance 2026-05-26 Akash Deep , Nicholas Appiah , Svetlozar T. Rachev

The mathematical properties of a family of generalized beta distribution, including beta-normal, skewed-t, log-F, beta-exponential, beta-Weibull distributions have recently been studied in several publications. This paper applies these…

Methodology · Statistics 2007-10-26 J. H. Sepanski , Lingji Kong

In the first quarter of 2006 Chicago Board Options Exchange (CBOE) introduced, as one of the listed products, options on its implied volatility index (VIX). This created the challenge of developing a pricing framework that can…

Pricing of Securities · Quantitative Finance 2009-05-14 Claudio Albanese , Harry Lo , Aleksandar Mijatović

This paper introduces novel volatility diffusion models to account for the stylized facts of high-frequency financial data such as volatility clustering, intra-day U-shape, and leverage effect. For example, the daily integrated volatility…

Methodology · Statistics 2022-06-01 Donggyu Kim , Minseok Shin

In this paper we consider the simulation-based Bayesian analysis of stochastic volatility in mean (SVM) models. Extending the highly efficient Markov chain Monte Carlo mixture sampler for the SV model proposed in Kim et al. (1998) and Omori…

Econometrics · Economics 2024-11-21 Daichi Hiraki , Siddhartha Chib , Yasuhiro Omori

The stochastic volatility model is one of volatility models which infer latent volatility of asset returns. The Bayesian inference of the stochastic volatility (SV) model is performed by the hybrid Monte Carlo (HMC) algorithm which is…

Computational Finance · Quantitative Finance 2014-08-06 Tetsuya Takaishi

Working on different aspects of algorithmic trading we empirically discovered a new market invariant. It links together the volatility of the instrument with its traded volume, the average spread and the volume in the order book. The…

Trading and Market Microstructure · Quantitative Finance 2019-08-14 Oleh Danyliv , Bruce Bland

A Bayesian procedure is developed for multivariate stochastic volatility, using state space models. An autoregressive model for the log-returns is employed. We generalize the inverted Wishart distribution to allow for different correlation…

Statistical Finance · Quantitative Finance 2008-12-02 K. Triantafyllopoulos

We investigate the variety of a portfolio of stocks in normal and extreme days of market activity. We show that the variety carries information about the market activity which is not present in the single-index model and we observe that the…

Statistical Mechanics · Physics 2009-10-31 Fabrizio Lillo , Rosario N. Mantegna

In a model driven by a multi-dimensional local diffusion, we study the behavior of implied volatility {\sigma} and its derivatives with respect to log-strike k and maturity T near expiry and at the money. We recover explicit limits of these…

Probability · Mathematics 2016-10-06 Stefano Pagliarani , Andrea Pascucci

This paper investigates how realized and option implied volatilities are related to the future quantiles of commodity returns. Whereas realized volatility measures ex-post uncertainty, volatility implied by option prices reveals the…

Risk Management · Quantitative Finance 2018-08-01 František Čech , Jozef Baruník

We discuss a bivariate beta distribution that can model arbitrary beta-distributed marginals with a positive correlation. The distribution is constructed from six independent gamma-distributed random variates. We show how the parameters of…

Statistics Theory · Mathematics 2021-06-03 Susanne Trick , Frank Jäkel , Constantin A. Rothkopf
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