Financial Mathematics, Volatility and Covariance Modelling
Volume 2
Herausgeber: Chevallier, Julien; Guerreiro, David; Goutte, Stéphane
Financial Mathematics, Volatility and Covariance Modelling
Volume 2
Herausgeber: Chevallier, Julien; Guerreiro, David; Goutte, Stéphane
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This book provides a key repository on the current state of knowledge, the latest debates and recent literature on financial mathematics, volatility and covariance modelling.
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This book provides a key repository on the current state of knowledge, the latest debates and recent literature on financial mathematics, volatility and covariance modelling.
Produktdetails
- Produktdetails
- Verlag: Jenny Stanford Publishing
- Seitenzahl: 380
- Erscheinungstermin: 17. Juli 2019
- Englisch
- Abmessung: 236mm x 160mm x 25mm
- Gewicht: 635g
- ISBN-13: 9781138060944
- ISBN-10: 1138060941
- Artikelnr.: 57145316
- Verlag: Jenny Stanford Publishing
- Seitenzahl: 380
- Erscheinungstermin: 17. Juli 2019
- Englisch
- Abmessung: 236mm x 160mm x 25mm
- Gewicht: 635g
- ISBN-13: 9781138060944
- ISBN-10: 1138060941
- Artikelnr.: 57145316
Julien Chevallier is Full Professor of Economics at the University Paris 8 (LED), France. He undertakes research and lectures on empirical finance, applied time-series econometrics, and commodity markets. He has published articles in leading refereed journals. Stephane Goutte is a Maître de Conférences-HDR of Financial Mathematics at University Paris 8, France and Senior Lecturer in Mathematics at University of Luxembourg. He is also a researcher at the Chair European Electricity Markets of Paris Dauphine PSL University. David Guerreiro is an Assistant Professor of Economics at the University Paris 8 (LED), France. His fields of research are International Macroeconomics, Monetary Economics and Meta-Analysis and he has published in numerous peer-reviewed journals. Sophie Saglio is an Assistant Professor of Economics at the University Paris 8 (LED), France. Her research focuses on international economics and finance and she has published in various peer-reviewed journals. Bilel Sanhaji is an Assistant Professor of Economics at the University Paris 8 (LED), France. His main research focuses on nonlinear time series econometrics and modelling volatility. He has published theoretical and applied research papers in various peer-reviewed journals.
Introduction. Part 1: Commodities Finance. 1. Long Memory and Asymmetry in
Commodity Returns and Risk: The Role of Term Spread. 2. The
Quantile-Heterogeneous Autoregressive Model of Realized Volatility: New
Evidence from Commodity Markets. 3. The Importance of Rollover in Commodity
Returns using PARCH models. Part 2: Mathematical Stochastical Finance. 4.
Variance and Volatility Swaps and Futures Pricing for Stochastic Volatility
Models. 5. A nonparametric ACD model. 6. Sovereign debt crisis and economic
growth: new evidence for the euro area. 7. On the spot-futures no-arbitrage
relations in commodity markets. 8. Compound Hawkes Processes in Limit Order
Books. Part 3: Financial Volatility and Covariance Modelling. 9. Models
with Multiplicative Decomposition of Conditional Variances and
Correlations. 10. Do High-frequency-based Measures Improve Conditional
Covariance Forecasts?. 11. Forecasting Realized Volatility Measures with
Multivariate and Univariate Models: The Case of the US Banking Sector. 12.
Covariance estimation and quasi-likelihood analysis. 13. The Log-GARCH
Model via ARMA Representations
Commodity Returns and Risk: The Role of Term Spread. 2. The
Quantile-Heterogeneous Autoregressive Model of Realized Volatility: New
Evidence from Commodity Markets. 3. The Importance of Rollover in Commodity
Returns using PARCH models. Part 2: Mathematical Stochastical Finance. 4.
Variance and Volatility Swaps and Futures Pricing for Stochastic Volatility
Models. 5. A nonparametric ACD model. 6. Sovereign debt crisis and economic
growth: new evidence for the euro area. 7. On the spot-futures no-arbitrage
relations in commodity markets. 8. Compound Hawkes Processes in Limit Order
Books. Part 3: Financial Volatility and Covariance Modelling. 9. Models
with Multiplicative Decomposition of Conditional Variances and
Correlations. 10. Do High-frequency-based Measures Improve Conditional
Covariance Forecasts?. 11. Forecasting Realized Volatility Measures with
Multivariate and Univariate Models: The Case of the US Banking Sector. 12.
Covariance estimation and quasi-likelihood analysis. 13. The Log-GARCH
Model via ARMA Representations
Introduction. Part 1: Commodities Finance. 1. Long Memory and Asymmetry in
Commodity Returns and Risk: The Role of Term Spread. 2. The
Quantile-Heterogeneous Autoregressive Model of Realized Volatility: New
Evidence from Commodity Markets. 3. The Importance of Rollover in Commodity
Returns using PARCH models. Part 2: Mathematical Stochastical Finance. 4.
Variance and Volatility Swaps and Futures Pricing for Stochastic Volatility
Models. 5. A nonparametric ACD model. 6. Sovereign debt crisis and economic
growth: new evidence for the euro area. 7. On the spot-futures no-arbitrage
relations in commodity markets. 8. Compound Hawkes Processes in Limit Order
Books. Part 3: Financial Volatility and Covariance Modelling. 9. Models
with Multiplicative Decomposition of Conditional Variances and
Correlations. 10. Do High-frequency-based Measures Improve Conditional
Covariance Forecasts?. 11. Forecasting Realized Volatility Measures with
Multivariate and Univariate Models: The Case of the US Banking Sector. 12.
Covariance estimation and quasi-likelihood analysis. 13. The Log-GARCH
Model via ARMA Representations
Commodity Returns and Risk: The Role of Term Spread. 2. The
Quantile-Heterogeneous Autoregressive Model of Realized Volatility: New
Evidence from Commodity Markets. 3. The Importance of Rollover in Commodity
Returns using PARCH models. Part 2: Mathematical Stochastical Finance. 4.
Variance and Volatility Swaps and Futures Pricing for Stochastic Volatility
Models. 5. A nonparametric ACD model. 6. Sovereign debt crisis and economic
growth: new evidence for the euro area. 7. On the spot-futures no-arbitrage
relations in commodity markets. 8. Compound Hawkes Processes in Limit Order
Books. Part 3: Financial Volatility and Covariance Modelling. 9. Models
with Multiplicative Decomposition of Conditional Variances and
Correlations. 10. Do High-frequency-based Measures Improve Conditional
Covariance Forecasts?. 11. Forecasting Realized Volatility Measures with
Multivariate and Univariate Models: The Case of the US Banking Sector. 12.
Covariance estimation and quasi-likelihood analysis. 13. The Log-GARCH
Model via ARMA Representations