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We investigate the optimal strategy over a finite time horizon for a portfolio of stock and bond and a derivative in an multiplicative Markovian market model with transaction costs (friction). The optimization problem is solved by a…

Physics and Society · Physics 2011-06-24 Erik Aurell , Paolo Muratore-Ginanneschi

We present a perturbation theory of the market impact based on an extension of the framework proposed by [Loeper, 2018] -- originally based on [Liu and Yong, 2005] -- in which we consider only local linear market impact. We study the…

Trading and Market Microstructure · Quantitative Finance 2019-11-05 Emilio Said

This thesis develops a new framework for modelling price processes in finance, such as an equity price or foreign exchange rate. This can be related to the conventional Ito calculus-based framework through the time integral of a price's…

Mathematical Finance · Quantitative Finance 2025-03-21 Ryan McCrickerd

In this paper, we introduce a new kind of reflected backward stochastic differential equations (RBSDEs) driven by a martingale, in a Markov chain model, but not driven by Brownian motion, and give existence and uniqueness results for the…

Probability · Mathematics 2015-05-14 Dimbinirina Ramarimbahoaka , Zhe Yang , Robert J. Elliott

In recent works on the theory of machine learning, it has been observed that heavy tail properties of Stochastic Gradient Descent (SGD) can be studied in the probabilistic framework of stochastic recursions. In particular,…

Machine Learning · Statistics 2024-03-22 Ewa Damek , Sebastian Mentemeier

We empirically test predictability on asset price by using stock selection rules based on maximum drawdown and its consecutive recovery. In various equity markets, monthly momentum- and weekly contrarian-style portfolios constructed from…

General Finance · Quantitative Finance 2024-05-24 Jaehyung Choi

Given a multi-dimensional It\^{o} process whose drift and diffusion terms are adapted processes, we construct a weak solution to a stochastic differential equation that matches the distribution of the It\^{o} process at each fixed time.…

Probability · Mathematics 2013-07-23 Gerard Brunick , Steven Shreve

Stochastic differential equation (SDE) models are the foundation for pricing and hedging financial derivatives. The drift and volatility functions in SDE models are typically chosen to be algebraic functions with a small number (less than…

Computational Finance · Quantitative Finance 2024-06-04 Lei Fan , Justin Sirignano

We explore the role that random arbitrage opportunities play in hedging financial derivatives. We extend the asymptotic pricing theory presented by Fedotov and Panayides [Stochastic arbitrage return and its implication for option pricing,…

Other Condensed Matter · Physics 2009-11-11 Stephanos Panayides

We present a non-probabilistic, path-by-path framework for studying path-dependent (i.e., where weight is a functional of time and historical time-series), long-only portfolio allocation in continuous-time based on [Chiu & Cont '23], where…

Mathematical Finance · Quantitative Finance 2025-09-05 Henry Chiu

Stochastic differential equations have been an important tool in modeling complex financial relations, equipped with the possibility of being multidimensional to better oversee complexities inherent in finance. This multidimensionality,…

Mathematical Finance · Quantitative Finance 2025-08-22 Ahmet Umur Özsoy

In this paper we propose a novel pricing-hedging framework for volatility derivatives which simultaneously takes into account rough volatility and volatility jumps. Our model directly targets the instantaneous variance of a risky asset and…

Pricing of Securities · Quantitative Finance 2021-11-30 Liang Wang , Weixuan Xia

Numerous empirical proofs indicate the adequacy of the time discrete auto-regressive stochastic volatility models introduced by Taylor in the description of the log-returns of financial assets. The pricing and hedging of contingent products…

Pricing of Securities · Quantitative Finance 2011-10-31 Joan del Castillo , Juan-Pablo Ortega

This paper proposes a semiparametric stochastic volatility (SV) model that relaxes the restrictive Gaussian assumption in both the return and volatility error terms, allowing them to follow flexible, nonparametric distributions with…

Computation · Statistics 2025-06-03 Yudong Feng , Ashis Gangopadhyay

In this paper, we present a method for constructing a (static) portfolio of co-maturing European options whose price sign is determined by the skewness level of the associated implied volatility. This property holds regardless of the…

Pricing of Securities · Quantitative Finance 2016-11-18 Sergey Nadtochiy , Jan Obloj

We consider the pricing problem related to payoffs that can have discontinuities of polynomial growth. The asset price dynamic is modeled within the Black and Scholes framework characterized by a stochastic volatility term driven by a…

Probability · Mathematics 2016-07-26 Viktor Bezborodov , Luca Di Persio , Yuliya Mishura

We hybridize the methods of finite element exterior calculus for the Hodge-Laplace problem on differential $k$-forms in $\mathbb{R}^n$. In the cases $k = 0$ and $k = n$, we recover well-known primal and mixed hybrid methods for the scalar…

Numerical Analysis · Mathematics 2025-06-02 Gerard Awanou , Maurice Fabien , Johnny Guzmán , Ari Stern

In this paper, we consider a generic interest rate market in the presence of roll-over risk, which generates spreads in spot/forward term rates. We do not require classical absence of arbitrage and rely instead on a minimal market viability…

Pricing of Securities · Quantitative Finance 2023-10-06 Claudio Fontana , Simone Pavarana , Wolfgang J. Runggaldier

This paper studies the equal risk pricing (ERP) framework for the valuation of European financial derivatives. This option pricing approach is consistent with global trading strategies by setting the premium as the value such that the…

Computational Finance · Quantitative Finance 2021-02-26 Alexandre Carbonneau , Frédéric Godin

The goal of this paper is to define stochastic integrals and to solve stochastic differential equations for typical paths taking values in a possibly infinite dimensional separable Hilbert space without imposing any probabilistic structure.…

Probability · Mathematics 2019-09-30 Daniel Bartl , Michael Kupper , Ariel Neufeld