Financial Mathematics, Volatility and Covariance Modelling

Table of contents

1. Cover
2. Half Title
3. Series Page
4. Title
5. Copyright
6. Contents
7. About the editors
8. List of contributors
9. Introduction
10. PART 1 Commodities finance
    1. 1 Long memory and asymmetry in commodity returns and risk: the role of term spread
    2. 2 The quantile-heterogeneous autoregressive model of realized volatility: new evidence from commodity markets
    3. 3 The importance of rollover in commodity returns using PARCH models
11. PART 2 Mathematical stochastical finance
    1. 4 Variance and volatility swaps and futures pricing for stochastic volatility models
    2. 5 A nonparametric ACD model
    3. 6 Sovereign debt crisis and economic growth: new evidence for the euro area
    4. 7 On the spot-futures no-arbitrage relations in commodity markets
    5. 8 Compound hawkes processes in limit order books
12. PART 3 Financial volatility and covariance modeling
    1. 9 Models with multiplicative decomposition of conditional variances and correlations
    2. 10 Do high-frequency-based measures improve conditional covariance forecasts?
    3. 11 Forecasting realized volatility measures with multivariate and univariate models: the case of the US banking sector
    4. 12 Covariance estimation and quasi-likelihood analysis
    5. 13 The Log-GARCH model via ARMA representations
13. Index