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We present a new methodology to analyze large classes of (classical and rough) stochastic volatility models, with special regard to short-time and small noise formulae for option prices. Our main tool is the theory of regularity structures,…

Pricing of Securities · Quantitative Finance 2021-07-30 Peter K. Friz , Paul Gassiat , Paolo Pigato

In frictionless markets, utility maximization problems are typically solved either by stochastic control or by martingale methods. Beginning with the seminal paper of Davis and Norman [Math. Oper. Res. 15 (1990) 676--713], stochastic…

Computational Finance · Quantitative Finance 2010-10-26 J. Kallsen , J. Muhle-Karbe

We introduce a new class of continuous-time models of the stochastic volatility of asset prices. The models can simultaneously incorporate roughness and slowly decaying autocorrelations, including proper long memory, which are two stylized…

Statistical Finance · Quantitative Finance 2021-01-06 Mikkel Bennedsen , Asger Lunde , Mikko S. Pakkanen

Using microscopic price models based on Hawkes processes, it has been shown that under some no-arbitrage condition, the high degree of endogeneity of markets together with the phenomenon of metaorders splitting generate rough Heston-type…

Statistical Finance · Quantitative Finance 2021-01-20 Aditi Dandapani , Paul Jusselin , Mathieu Rosenbaum

We present a framework for hedging a portfolio of derivatives in the presence of market frictions such as transaction costs, market impact, liquidity constraints or risk limits using modern deep reinforcement machine learning methods. We…

Computational Finance · Quantitative Finance 2018-02-12 Hans Bühler , Lukas Gonon , Josef Teichmann , Ben Wood

Based on a criterium of mathematical simplicity and consistency with empirical market data, a stochastic volatility model has been obtained with the volatility process driven by fractional noise. Depending on whether the stochasticity…

Pricing of Securities · Quantitative Finance 2010-07-28 R. Vilela Mendes , Maria João Oliveira

This study first reviews fuzzy random Portfolio selection theory and describes the concept of portfolio optimization model as a useful instrument for helping finance practitioners and researchers. Second, this paper specifically aims at…

Optimization and Control · Mathematics 2014-02-18 Mir Ehsan Hesam Sadati , Ali Doniavi

Computational aspects of the optimal consumption and investment with the partially observed stochastic volatility of the asset prices are considered. The new quantization approach to filtering - density quantization - is introduced which…

Computational Finance · Quantitative Finance 2010-09-30 Grzegorz Hałaj

This paper develops an It\^o-type fractional pathwise integration theory for fractional Brownian motion with Hurst parameters \( H \in (\frac{1}{3}, \frac{1}{2}] \), using the Lyons' rough path framework. This approach is designed to fill…

Probability · Mathematics 2025-11-10 Zhongmin Qian , Xingcheng Xu

Assuming frictionless trading, classical stochastic portfolio theory (SPT) provides relative arbitrage strategies. However, the costs associated with real-world execution are state-dependent, volatile, and under increasing stress during…

Portfolio Management · Quantitative Finance 2025-07-15 Nader Karimi , Erfan Salavati

We show that typical behaviors of market participants at the high frequency scale generate leverage effect and rough volatility. To do so, we build a simple microscopic model for the price of an asset based on Hawkes processes. We encode in…

Trading and Market Microstructure · Quantitative Finance 2016-09-19 El Euch Omar , Fukasawa Masaaki , Rosenbaum Mathieu

We consider an investor facing a classical portfolio problem of optimal investment in a log-Brownian stock and a fixed-interest bond, but constrained to choose portfolio and consumption strategies that reduce a dynamic shortfall risk…

Portfolio Management · Quantitative Finance 2017-08-04 Imke Redeker , Ralf Wunderlich

This paper presents several models addressing optimal portfolio choice, optimal portfolio liquidation, and optimal portfolio transition issues, in which the expected returns of risky assets are unknown. Our approach is based on a coupling…

Portfolio Management · Quantitative Finance 2019-03-21 Alexis Bismuth , Olivier Guéant , Jiang Pu

In this chapter we first briefly review the existing approaches to hedging in rough volatility models. Next, we present a simple but general result which shows that in a one-factor rough stochastic volatility model, any option may be…

Mathematical Finance · Quantitative Finance 2021-05-11 Masaaki Fukasawa , Blanka Horvath , Peter Tankov

We present a simulation-and-regression method for solving dynamic portfolio allocation problems in the presence of general transaction costs, liquidity costs and market impacts. This method extends the classical least squares Monte Carlo…

Portfolio Management · Quantitative Finance 2019-06-05 Rongju Zhang , Nicolas Langrené , Yu Tian , Zili Zhu , Fima Klebaner , Kais Hamza

We analyze characteristics' joint predictive information through the lens of out-of-sample power utility functions. Linking weights to characteristics to form optimal portfolios suffers from estimation error which we mitigate by maximizing…

General Finance · Quantitative Finance 2024-02-05 Christopher G. Lamoureux , Huacheng Zhang

We extend Relative Robust Portfolio Optimisation models to allow portfolios to optimise their distance to a set of benchmarks. Portfolio managers are also given the option of computing regret in a way which is more in line with market…

Portfolio Management · Quantitative Finance 2017-01-12 Gonçalo Simões , Mark McDonald , Stacy Williams , Daniel Fenn , Raphael Hauser

We have recently presented an extension of the standard variational calculus to include the presence of deformed derivatives in the Lagrangian of a system of particles and in the Lagrangian density of field-theoretic models. Classical…

Mathematical Physics · Physics 2017-06-30 J. Weberszpil , J. A. Helayël-Neto

This is the first in a series of papers in which we study an efficient approximation scheme for solving the Hamilton-Jacobi-Bellman equation for multi-dimensional problems in stochastic control theory. The method is a combination of a WKB…

Computational Finance · Quantitative Finance 2014-06-26 Sakda Chaiworawitkul , Patrick S. Hagan , Andrew Lesniewski

In this paper, we employ the Heston stochastic volatility model to describe the stock's volatility and apply the model to derive and analyze the optimal trading strategies for dealers in a security market. We also extend our study to option…

Trading and Market Microstructure · Quantitative Finance 2016-02-02 Wai-Ki Ching , Jia-Wen Gu , Tak-Kuen Siu , Qing-Qing Yang