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Machine Learning for Quantitative Finance: Fast Derivative Pricing, Hedging and Fitting
9 references·13 citing·40 second hop
Machine Learning for Quantitative Finance: Fast Derivative Pricing, Hedging and Fitting (2018)Machine Learning for Quantitative Finance…THE RANGE OF TRADED OPTION PRICES (2006)THE RANGE OF TRADED OPTION PR…A note on sufficient conditions for no arbitrage (2005)A note on sufficient conditio…Lévy Processes in Finance (2003)Lévy Processes in FinanceLévy processes in finance pricing financial derivatives (2003)Lévy processes in finance pri…Option valuation using the fast Fourier transform (1999)Option valuation using the fa…The Variance Gamma Process and Option Pricing (1998)The Variance Gamma Process an…A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options (1993)A Closed-Form Solution for Op…Option Pricing With V. G. Martingale Components1 (1991)Option Pricing With V. G. Mar…The Variance Gamma (V.G.) Model for Share Market Returns (1990)The Variance Gamma (V.G.) Mod…On Deep Calibration of (rough) Stochastic Volatility Models (2025)On Deep Calibration of (rough…Machine learning sentiment analysis, COVID-19 news and stock market reactions (2023)Machine learning sentiment an…Imperative Role of Artificial Intelligence and Big Data in Finance and Banking Sector (2023)Imperative Role of Artificial…Machine learning methods in finance: Recent applications and prospects (2022)Machine learning methods in f…Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature (2021)Machine Learning in Finance: …Machine Learning Algorithm for Cryptocurrencies Price Prediction (2021)Machine Learning Algorithm fo…Forecasting mid-price movement of Bitcoin futures using machine learning (2021)Forecasting mid-price movemen…A parallel multi-module deep reinforcement learning algorithm for stock trading (2021)A parallel multi-module deep …Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models (2020)Machine learning for pricing …Deep learning volatility: a deep neural network perspective on pricing and calibration in (rough) volatility models (2020)Deep learning volatility: a d…Option Hedging Using LSTM-RNN: An Empirical Analysis (2019)Option Hedging Using LSTM-RNN…Deep Learning Volatility (2019)Deep Learning VolatilityA neural network-based framework for financial model calibration (2019)A neural network-based framew…The Pricing of Options and Corporate Liabilities (1973)Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options (1996)Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial Economics (2001)The Fine Structure of Asset Returns: An Empirical Investigation (2002)Stochastic Volatility for Lévy Processes (2003)Theory of Rational Option Pricing (1973)A Theory of the Term Structure of Interest Rates (1985)Empirical Performance of Alternative Option Pricing Models (1997)Transform Analysis and Asset Pricing for Affine Jump-diffusions (2000)The Cross‐Section of Volatility and Expected Returns (2006)Continuous Martingales and Brownian Motion (1999)A Jump-Diffusion Model for Option Pricing (2002)Power and Bipower Variation with Stochastic Volatility and Jumps (2004)The Behavior of Stock-Market Prices (1965)Option pricing when underlying stock returns are discontinuous (1976)Lévy Processes in Finance: Theory, Numerics, and Empirical Facts (2000)The cumulant process and Esscher's change of measure (2002)Specification Analysis of Option Pricing Models Based on Time‐Changed Lévy Processes (2004)Prices of State-Contingent Claims Implicit in Option Prices (1978)Martingales and stochastic integrals in the theory of continuous trading (1981)Implied Binomial Trees (1994)ROBUST BOUNDS FOR FORWARD START OPTIONS (2010)Robust pricing and hedging of double no-touch options (2011)A MODEL‐FREE VERSION OF THE FUNDAMENTAL THEOREM OF ASSET PRICING AND THE SUPER‐REPLICATION THEOREM (2013)Martingales and arbitrage in multiperiod securities markets (1979)Theory of rational option pricing (2005)Advances in Mathematical Finance (2007)Robust Hedging of Double Touch Barrier Options (2011)Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards (2004)Giving Content to Investor Sentiment: The Role of Media in the Stock Market (2007)The Unprecedented Stock Market Reaction to COVID-19 (2020)Forecasting the S&P 500 Index Using Mathematical-Based Sentiment Analysis and Deep Learning Models: A FinBERT Transformer Model and LSTM (2023)Enhancing the Prediction of Stock Market Movement Using Neutrosophic-Logic-Based Sentiment Analysis (2024)Nexus between Chat GPT usage dimensions and investment decisions making in Pakistan: Moderating role of financial literacy (2024)Time-changed Lévy processes and option pricing (2003)A Finite Difference Scheme for Option Pricing in Jump Diffusion and Exponential Lévy Models (2005)The application of continuous-time random walks in finance and economics (2005)Pricing early-exercise and discrete barrier options by fourier-cosine series expansions (2009)Some remarks on first passage of Lévy processes, the American put and pasting principles (2005)Fractional Diffusion Models of Option Prices in Markets With Jumps (2006)
this work references cited by second hop

References

  • 1993A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options8,768 cited
  • 1999Option valuation using the fast Fourier transform2,155 cited
  • 1998The Variance Gamma Process and Option Pricing1,786 cited
  • 1990The Variance Gamma (V.G.) Model for Share Market Returns1,470 cited
  • 2003Lévy processes in finance pricing financial derivatives807 cited
  • 2003Lévy Processes in Finance793 cited
  • 1991Option Pricing With V. G. Martingale Components1411 cited
  • 2006THE RANGE OF TRADED OPTION PRICES205 cited
  • 2005A note on sufficient conditions for no arbitrage165 cited

Cited by

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  • 2020Deep learning volatility: a deep neural network perspective on pricing and calibration in (rough) volatility models153 cited
  • 2019A neural network-based framework for financial model calibration106 cited
  • 2022Machine learning methods in finance: Recent applications and prospects96 cited
  • 2021Forecasting mid-price movement of Bitcoin futures using machine learning84 cited
  • 2020Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

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  • 2023Imperative Role of Artificial Intelligence and Big Data in Finance and Banking Sector28 cited