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There are some statistical anomalies in the Chinese stock market, i.e., positive return skewness, anti-leverage effect (positive returns induce higher volatility than negative returns); and reverse volatility asymmetry (contemporaneous…

General Finance · Quantitative Finance 2015-11-06 Liang Wu , Jingyi Luo , Yingkai Tang , Gregory Bardes

This study utilised the dynamics of five time-varying models to estimate six essential features of financial return volatility that are relevant for robust risk management. These features include pronounced persistence, mean reversion,…

Applications · Statistics 2025-03-05 Richard T. A. Samuel , Charles Chimedza , Caston Sigauke

Agents' heterogeneity is recognized as a driver mechanism for the persistence of financial volatility. We focus on the multiplicity of investment strategies' horizons, we embed this concept in a continuous time stochastic volatility…

Statistical Finance · Quantitative Finance 2013-04-04 Danilo Delpini , Giacomo Bormetti

We present a framework for analyzing the near miss effect in lotteries. A decision maker (DM) facing a lottery, falsely interprets losing outcomes that are close to winning ones, as a sign that success is within reach. As a result of this…

Theoretical Economics · Economics 2023-12-18 Michael Crystal

In modern portfolio theory, the balancing of expected returns on investments against uncertainties in those returns is aided by the use of utility functions. The Kelly criterion offers another approach, rooted in information theory, that…

Risk Management · Quantitative Finance 2015-03-13 Ole Peters

Financial time series exhibit a number of interesting properties that are difficult to explain with simple models. These properties include fat-tails in the distribution of price fluctuations (or returns) that are slowly removed at longer…

Statistical Finance · Quantitative Finance 2013-11-19 Raoul Golan , Austin Gerig

Volatility forecasts are key inputs in financial analysis. While lasso based forecasts have shown to perform well in many applications, their use to obtain volatility forecasts has not yet received much attention in the literature. Lasso…

Applications · Statistics 2016-10-11 Ines Wilms , Jeroen Rombouts , Christophe Croux

In this work, we explore the theoretical properties of conditional deep generative models under the statistical framework of distribution regression where the response variable lies in a high-dimensional ambient space but concentrates…

Statistics Theory · Mathematics 2026-02-02 Shivam Kumar , Yun Yang , Lizhen Lin

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

We review the dynamics of the returns of Leveraged Exchange Traded Funds (LETFs) and propose a new measure of realized volatility: Shortfall from Maximum Convexity. We show that SMC has a more intuitive interpretation and provides more…

Statistical Finance · Quantitative Finance 2015-10-06 Matthew Ginley

Leverage is strongly related to liquidity in a market and lack of liquidity is considered a cause and/or consequence of the recent financial crisis. A repurchase agreement is a financial instrument where a security is sold simultaneously…

General Finance · Quantitative Finance 2010-11-05 Wanfeng Yan , Ryan Woodard , Didier Sornette

The scale and terms of aggregate borrowing in an economy depend on the manner in which wealth is distributed across potential creditors with heterogeneous beliefs about the future. This distribution evolves over time as uncertainty is…

General Economics · Economics 2023-04-10 Bikramaditya Datta , Rajiv Sethi

Although stochastic volatility and GARCH (generalized autoregressive conditional heteroscedasticity) models have successfully described the volatility dynamics of univariate asset returns, extending them to the multivariate models with…

Econometrics · Economics 2020-10-09 Yuta Yamauchi , Yasuhiro Omori

We investigate the joint dynamics of spot and implied volatility from an empirical perspective. We focus on the equity market with the SPX Index our underlying of choice. Using only observable quantities, we extract the instantaneous…

Statistical Finance · Quantitative Finance 2015-07-06 Florent Ségonne

We inspect how accurate machine learning (ML) is at forecasting realized variance of the Dow Jones Industrial Average index constituents. We compare several ML algorithms, including regularization, regression trees, and neural networks, to…

Econometrics · Economics 2026-01-21 Kim Christensen , Mathias Siggaard , Bezirgen Veliyev

Dynamical models of cognition play an increasingly important role in driving theoretical and experimental research in psychology. Therefore, parameter estimation, model analysis and comparison of dynamical models are of essential…

By studying all the trades and best bids/asks of ultra high frequency snapshots recorded from the order books of a basket of 10 futures assets, we bring qualitative empirical evidence that the impact of a single trade depends on the…

Trading and Market Microstructure · Quantitative Finance 2010-10-28 Khalil al Dayri , Emmanuel Bacry , Jean-Francois Muzy

In many countries life expectancy gains have been substantially higher than predicted by even recent forecasts. This is primarily due to increasing rates of improvement in old-age mortality not captured by existing models. In this paper we…

Methodology · Statistics 2021-09-07 Søren Fiig Jarner

This paper characterizes the equilibrium in a continuous time financial market populated by heterogeneous agents who differ in their rate of relative risk aversion and face convex portfolio constraints. The model is studied in an…

General Finance · Quantitative Finance 2018-06-19 Tyler Abbot

Stock market volatility forecasting is a task relevant to assessing market risk. We investigate the interaction between news and prices for the one-day-ahead volatility prediction using state-of-the-art deep learning approaches. The…

Statistical Finance · Quantitative Finance 2018-12-31 Marcelo Sardelich , Suresh Manandhar