Asymptotic expansion for characteristic function in Heston stochastic volatility model with fast mean-reverting correction [PDF]
arXiv, 2013 In this note, we derive the characteristic function expansion for logarithm of the underlying asset price in corrected Heston model as proposed by Fouque and Lorig.
arxiv
An Adaptive Dual-level Reinforcement Learning Approach for Optimal Trade Execution
, 2023 The purpose of this research is to devise a tactic that can closely track the daily cumulative volume-weighted average price (VWAP) using reinforcement learning.
Hong, Youngjoon +3 more
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Non-linear Time Series and Artificial Neural Networks of Red Hat Volatility [PDF]
arXiv, 2018 We extend the empirical results published in article "Empirical Evidence on Arbitrage by Changing the Stock Exchange" by means of machine learning and advanced econometric methodologies based on Smooth Transition Regression models and Artificial Neural Networks.
arxiv
Derivatives Sensitivities Computation under Heston Model on GPU
, 2023 This report investigates the computation of option Greeks for European and Asian options under the Heston stochastic volatility model on GPU. We first implemented the exact simulation method proposed by Broadie and Kaya and used it as a baseline for ...
Arsaguet, Pierre-Antoine, Bilokon, Paul
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Physics-Informed Convolutional Transformer for Predicting Volatility Surface
, 2022 Predicting volatility is important for asset predicting, option pricing and hedging strategies because it cannot be directly observed in the financial market.
Bae, Hyeong-Ohk +4 more
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Large Language Models in Finance: A Survey
, 2023 Recent advances in large language models (LLMs) have opened new possibilities for artificial intelligence applications in finance. In this paper, we provide a practical survey focused on two key aspects of utilizing LLMs for financial tasks: existing ...
Chen, Hang +3 more
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Lévy Processes For Finance: An Introduction In R [PDF]
arXiv, 2015 This brief manuscript provides an introduction to L\'evy processes and their applications in finance as the random process that drives asset models. Characteristic functions and random variable generators of popular L\'evy processes are presented in R.
arxiv
Integration of a Predictive, Continuous Time Neural Network into Securities Market Trading Operations [PDF]
arXiv, 2014 This paper describes recent development and test implementation of a continuous time recurrent neural network that has been configured to predict rates of change in securities. It presents outcomes in the context of popular technical analysis indicators and highlights the potential impact of continuous predictive capability on securities market trading
arxiv
Implied Volatility Surface: Construction Methodologies and Characteristics [PDF]
arXiv, 2011 The implied volatility surface (IVS) is a fundamental building block in computational finance. We provide a survey of methodologies for constructing such surfaces. We also discuss various topics which can influence the successful construction of IVS in practice: arbitrage-free conditions in both strike and time, how to perform extrapolation outside the
arxiv
Learning Embedded Representation of the Stock Correlation Matrix using Graph Machine Learning
, 2022 Understanding non-linear relationships among financial instruments has various applications in investment processes ranging from risk management, portfolio construction and trading strategies.
Mehta, Dhagash +3 more
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