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This paper introduces a novel methodology for index return forecasting, blending highly correlated stock prices, advanced deep learning techniques, and intricate factor integration. Departing from conventional cap-weighted approaches, our…

General Finance · Quantitative Finance 2024-05-06 Tian Tian , Ricky Cooper , Jiahao Deng , Qingquan Zhang

The random values and volumes of consecutive trades made at the exchange with shares of security determine its mean, variance, and higher statistical moments. The volume weighted average price (VWAP) is the simplest example of such a…

General Economics · Economics 2026-01-21 Victor Olkhov

A method for quantile-based, semi-parametric historical simulation estimation of multiple step ahead Value-at-Risk (VaR) and Expected Shortfall (ES) models is developed. It uses the quantile loss function, analogous to how the…

Statistical Finance · Quantitative Finance 2025-03-06 Richard Gerlach , Antonio Naimoli , Giuseppe Storti

Risk control has become one of the major concern of financial institutions. The need for adequate statistical tools to measure and anticipate the amplitude of the potential moves of financial markets is clearly expressed, in particular for…

Condensed Matter · Physics 2007-05-23 Jean-Philippe Bouchaud , Marc Potters

Volatility is the canonical measure of financial risk, a role largely inherited from Modern Portfolio Theory. Yet, its universality rests on restrictive efficiency assumptions that render volatility, at best, an incomplete proxy for true…

Mathematical Finance · Quantitative Finance 2026-05-01 Sergio Bianchi , Daniele Angelini

We address the problem that classical risk measures may not detect the tail risk adequately. This can occur for instance due to averaging when calculating the Expected Shortfall. The current literature proposes the so-called adjusted…

Mathematical Finance · Quantitative Finance 2025-04-24 Jascha Alexander , Christian Laudagé , Jörn Sass

This paper offers a new class of models of the term structure of interest rates. We allow each instantaneous forward rate to be driven by a different stochastic shock, constrained in such a way as to keep the forward rate curve continuous.…

Statistical Mechanics · Physics 2008-12-02 P. Santa-Clara , D. Sornette

The recent explosion in the amount and dimensionality of data has exacerbated the need of trading off computational and statistical efficiency carefully, so that inference is both tractable and meaningful. We propose a framework that…

Computation · Statistics 2015-06-29 Daniel L. Sussman , Alexander Volfovsky , Edoardo M. Airoldi

We study time-consistency questions for processes of monetary risk measures that depend on bounded discrete-time processes describing the evolution of financial values. The time horizon can be finite or infinite. We call a process of…

Probability · Mathematics 2008-12-10 Patrick Cheridito , Freddy Delbaen , Michael Kupper

The risk of financial positions is measured by the minimum amount of capital to raise and invest in eligible portfolios of traded assets in order to meet a prescribed acceptability constraint. We investigate nondegeneracy, finiteness and…

Risk Management · Quantitative Finance 2014-03-05 Walter Farkas , Pablo Koch-Medina , Cosimo Munari

We discuss a weighted estimation of correlation and covariance matrices from historical financial data. To this end, we introduce a weighting scheme that accounts for similarity of previous market conditions to the present one. The…

Statistical Finance · Quantitative Finance 2010-07-01 Michael C. Münnix , Rudi Schäfer , Oliver Grothe

This article is part of a comprehensive research project on liquidity risk in asset management, which can be divided into three dimensions. The first dimension covers liability liquidity risk (or funding liquidity) modeling, the second…

Risk Management · Quantitative Finance 2021-05-19 Thierry Roncalli , Amina Cherief , Fatma Karray-Meziou , Margaux Regnault

Endowing robots with the capability of assessing risk and making risk-aware decisions is widely considered a key step toward ensuring safety for robots operating under uncertainty. But, how should a robot quantify risk? A natural and common…

Robotics · Computer Science 2017-11-02 Anirudha Majumdar , Marco Pavone

In this research, starting from a widely accepted definition of risk, we support the idea that risk reduction is a more realistic objective than risk minimization, which represents a theoretical utopia. Furthermore, significant risk…

Risk Management · Quantitative Finance 2026-05-01 Pierpaolo Uberti

There are various metrics for financial risk, such as value at risk (VaR), expected shortfall, expected/unexpected loss, etc. When estimating these metrics, it was very common to assume Gaussian distribution for the asset returns, which may…

Applications · Statistics 2020-02-17 Shuguang Zhang , Minjing Tao , Xu-Feng Niu , Fred Huffer

We consider an optimal investment and risk control problem for an insurer under the mean-variance (MV) criterion. By introducing a deterministic auxiliary process defined forward in time, we formulate an alternative time-consistent problem…

Portfolio Management · Quantitative Finance 2021-01-12 Yang Shen , Bin Zou

This paper develops a method to derive optimal portfolios and risk premia explicitly in a general diffusion model for an investor with power utility and a long horizon. The market has several risky assets and is potentially incomplete.…

Probability · Mathematics 2012-03-08 Paolo Guasoni , Scott Robertson

Valuation adjustments are nowadays a common practice to include credit and liquidity effects in option pricing. Funding costs arising from collateral procedures, hedging strategies and taxes are added to option prices to take into account…

Mathematical Finance · Quantitative Finance 2019-06-07 Stefania Gabrielli , Andrea Pallavicini , Stefano Scoleri

Motivated by the Basel 3 regulations, recent studies have considered joint forecasts of Value-at-Risk and Expected Shortfall. A large family of scoring functions can be used to evaluate forecast performance in this context. However, little…

Risk Management · Quantitative Finance 2017-05-15 Johanna F. Ziegel , Fabian Krüger , Alexander Jordan , Fernando Fasciati

We address the problem of learning a decision policy from observational data of past decisions in contexts with features and associated outcomes. The past policy maybe unknown and in safety-critical applications, such as medical decision…

Machine Learning · Computer Science 2020-06-04 Muhammad Osama , Dave Zachariah , Peter Stoica
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