TY - BOOK ID - 125659263 TI - Computational Finance PY - 2020 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - Economics, finance, business & management KW - insurance KW - Solvency II KW - risk-neutral models KW - computational finance KW - asset pricing models KW - overnight price gaps KW - financial econometrics KW - mean-reversion KW - statistical arbitrage KW - high-frequency data KW - jump-diffusion model KW - instantaneous volatility KW - directional-change KW - seasonality KW - forex KW - bitcoin KW - S& KW - P500 KW - risk management KW - drawdown KW - safe assets KW - securitisation KW - dealer behaviour KW - liquidity KW - bid–ask spread KW - least-squares Monte Carlo KW - put-call symmetry KW - regression KW - simulation KW - algorithmic trading KW - market quality KW - defined contribution plan KW - probability of shortfall KW - quadratic shortfall KW - dynamic asset allocation KW - resampled backtests KW - stochastic covariance KW - 4/2 model KW - option pricing KW - risk measures KW - American options KW - exercise boundary KW - Monte Carlo KW - multiple exercise options KW - dynamic programming KW - stochastic optimal control KW - asset pricing KW - calibration KW - derivatives KW - hedging KW - multivariate models KW - volatility UR - https://www.unicat.be/uniCat?func=search&query=sysid:125659263 AB - 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. ER -