Computational Finance

• Other Authors: Stentoft, Lars (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
• Subjects: Economics, finance, business & management; insurance; Solvency II; risk-neutral models; computational finance; asset pricing models; overnight price gaps; financial econometrics; mean-reversion; statistical arbitrage; high-frequency data; jump-diffusion model; instantaneous volatility; directional-change; seasonality; forex; bitcoin; S& P500; risk management; drawdown; safe assets; securitisation; dealer behaviour; liquidity; bid-ask spread; least-squares Monte Carlo; put-call symmetry; regression; simulation; algorithmic trading; market quality; defined contribution plan; probability of shortfall; quadratic shortfall; dynamic asset allocation; resampled backtests; stochastic covariance; 4/2 model; option pricing; risk measures; American options; exercise boundary; Monte Carlo; multiple exercise options; dynamic programming; stochastic optimal control; asset pricing; calibration; derivatives; hedging; multivariate models; volatility
• Online Access: DOAB: download the publication; DOAB: description of the publication

With the availability of new and more comprehensive financial market data, making headlines of massive public interest due to recent periods of extreme volatility and crashes, the field of computational finance is evolving ever faster thanks to significant advances made theoretically, and to the massive increase in accessible computational resources. This volume includes a wide variety of theoretical and empirical contributions that address a range of issues and topics related to computational finance. It collects contributions on the use of new and innovative techniques for modeling financial asset returns and volatility, on the use of novel computational methods for pricing, hedging, the risk management of financial instruments, and on the use of new high-dimensional or high-frequency data in multivariate applications in today's complex world. The papers develop new multivariate models for financial returns and novel techniques for pricing derivatives in such flexible models, examine how pricing and hedging techniques can be used to assess the challenges faced by insurance companies, pension plan participants, and market participants in general, by changing the regulatory requirements. Additionally, they consider the issues related to high-frequency trading and statistical arbitrage in particular, and explore the use of such data to asses risk and volatility in financial markets.