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The leverage effect-- the correlation between an asset's return and its volatility-- has played a key role in forecasting and understanding volatility and risk. While it is a long standing consensus that leverage effects exist and improve…

Statistical Finance · Quantitative Finance 2017-12-12 Kenichiro McAlinn , Asahi Ushio , Teruo Nakatsuma

The research presented in this work is motivated by recent papers by Brigo et al. (2011), Burgard and Kjaer (2009), Cr\'epey (2012), Fujii and Takahashi (2010), Piterbarg (2010) and Pallavicini et al. (2012). Our goal is to provide a sound…

Mathematical Finance · Quantitative Finance 2014-12-11 Tomasz R. Bielecki , Marek Rutkowski

This paper is mainly a survey of recent research developments regarding methods for risk minimization in financial markets modeled by It\^o-L\'evy processes, but it also contains some new results on the underlying stochastic maximum…

Optimization and Control · Mathematics 2014-04-11 Bernt Øksendal , Agnès Sulem

We solve the problem of optimal liquidation with volume weighted average price (VWAP) benchmark when the market impact is linear and transient. Our setting is indeed more general as it considers the case when the trading interval is not…

Trading and Market Microstructure · Quantitative Finance 2019-01-16 Alexander Barzykin , Fabrizio Lillo

We consider a trader who wants to direct his portfolio towards a set of acceptable wealths given by a convex risk measure. We propose a black-box algorithm, whose inputs are the joint law of stock prices and the convex risk measure, and…

Probability · Mathematics 2008-12-10 Soumik Pal

This paper investigates the so-called leakage effect of trading strategies generated functionally from rank-dependent portfolio generating functions. This effect measures the loss in wealth of trading strategies due to renewing the…

Portfolio Management · Quantitative Finance 2019-12-10 Kangjianan Xie

We adress the maximization problem of expected utility from terminal wealth. The special feature of this paper is that we consider a financial market where the price process of risky assets can have a default time. Using dynamic…

Computational Finance · Quantitative Finance 2010-07-13 Thomas Lim , Marie-Claire Quenez

We propose some machine-learning-based algorithms to solve hedging problems in incomplete markets. Sources of incompleteness cover illiquidity, untradable risk factors, discrete hedging dates and transaction costs. The proposed algorithms…

Risk Management · Quantitative Finance 2020-08-13 Simon Fécamp , Joseph Mikael , Xavier Warin

We address the problem of portfolio optimization under the simplest coherent risk measure, i.e. the expected shortfall. As it is well known, one can map this problem into a linear programming setting. For some values of the external…

Physics and Society · Physics 2008-12-02 Stefano Ciliberti , Imre Kondor , Marc Mezard

We consider a model in which a trader aims to maximize expected risk-adjusted profit while trading a single security. In our model, each price change is a linear combination of observed factors, impact resulting from the trader's current…

Trading and Market Microstructure · Quantitative Finance 2012-07-30 Beomsoo Park , Benjamin Van Roy

We prove that a wide class of correlated stochastic volatility models exactly measure an empirical fact in which past returns are anticorrelated with future volatilities: the so-called ``leverage effect''. This quantitative measure allows…

Statistical Mechanics · Physics 2008-12-02 Josep Perello , Jaume Masoliver

In portfolio compression, market participants (banks, organizations, companies, financial agents) sign contracts, creating liabilities between each other, which increases the systemic risk. Large, dense markets commonly can be compressed by…

Computational Engineering, Finance, and Science · Computer Science 2022-12-20 Mihály Péter Hanics

We introduce a new method to calculate the credit exposure of European and path-dependent options. The proposed method is able to calculate accurate expected exposure and potential future exposure profiles under the risk-neutral and the…

Computational Finance · Quantitative Finance 2019-12-04 Kathrin Glau , Ricardo Pachon , Christian Pötz

The classical discrete time model of proportional transaction costs relies on the assumption that a feasible portfolio process has solvent increments at each step. We extend this setting in two directions, allowing for convex transaction…

Mathematical Finance · Quantitative Finance 2021-01-15 Emmanuel Lepinette , Ilya Molchanov

We give a complete solution to the problem of minimizing the expected liquidity costs in presence of a general drift when the underlying market impact model has linear transient price impact with exponential resilience. It turns out that…

Trading and Market Microstructure · Quantitative Finance 2013-03-05 Christopher Lorenz , Alexander Schied

We address imbalanced classification, the problem in which a label may have low marginal probability relative to other labels, by weighting losses according to the correct class. First, we examine the convergence rates of the expected…

Machine Learning · Statistics 2020-05-28 Ziyu Xu , Chen Dan , Justin Khim , Pradeep Ravikumar

We present a financial market model, characterized by self-organized criticality, that is able to generate endogenously a realistic price dynamics and to reproduce well-known stylized facts. We consider a community of heterogeneous traders,…

Statistical Finance · Quantitative Finance 2015-11-04 A. E. Biondo , A. Pluchino , A. Rapisarda

If a financial asset's price movement impacts a firm's product demand, the firm can respond to the impact by adjusting its operational decisions. For example, in the automotive industry, car makers decrease the selling prices of…

Risk Management · Quantitative Finance 2023-06-22 Liao Wang , Jin Yao , Xiaowei Zhang

The purpose of this paper is introducing rigorous methods and formulas for bilateral counterparty risk credit valuation adjustments (CVA's) on interest-rate portfolios. In doing so, we summarize the general arbitrage-free valuation…

Pricing of Securities · Quantitative Finance 2010-02-03 Damiano Brigo , Andrea Pallavicini , Vasileios Papatheodorou

While shrinkage is essential in high-dimensional settings, its use for low-dimensional regression-based prediction has been debated. It reduces variance, often leading to improved prediction accuracy. However, it also inevitably introduces…