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Book Categories |
| Foreword | ||
| Preface | ||
| 1 | Probability theory: basic notions | 1 |
| 2 | Maximum and addition of random variables | 17 |
| 3 | Continuous time limit, Ito calculus and path integrals | 43 |
| 4 | Analysis of empirical data | 55 |
| 5 | Financial products and financial markets | 69 |
| 6 | Statistics of real prices: basic results | 87 |
| 7 | Non-linear correlations and volatility fluctuations | 107 |
| 8 | Skewness and price-volatility correlations | 130 |
| 9 | Cross-correlations | 145 |
| 10 | Risk measures | 168 |
| 11 | Extreme correlations and variety | 186 |
| 12 | Optimal portfolios | 202 |
| 13 | Futures and options: fundamental concepts | 226 |
| 14 | Options: hedging and residual risk | 254 |
| 15 | Options: the role of drift and correlations | 276 |
| 16 | Options: the Black and Scholes model | 290 |
| 17 | Options: some more specific problems | 300 |
| 18 | Options: minimum variance Monte-Carlo | 317 |
| 19 | The yield curve | 334 |
| 20 | Simple mechanisms for anomalous price statistics | 355 |
| Index of most important symbols | 372 | |
| Index | 377 |
| Price | Condition | Delivery | Seller | Action |
| $99.99 | Digital |
| WonderClub |
Carla Thompson
reviewed Theory of Financial Risk and Derivative Pricing: From Statistical Physics to risk Management on March 23, 2015 Theory of Financial Risk and Derivative Pricing: From Statistical Physics to risk Management
It is a disappointing reading and I eventually gave up. If you have some mathematics background and want to purchase and use the author's softwares for fun, the book is a good guidance and textbook. That's it.
I expected something which can explain to business people how to calculate the value and consider it with the value from traditional valuation methodologies. Most examples are high level, qualitative and back looking (justify the result using real option)
Frankly it's not an issue of this book. It's an issue of the whole concept of real option which is still mostly in the textbook and seldom used by real business and financial world quantitatively. It's no problem for the MBA graduated CEOs to accept the concept and incorporate in the business development and strategy making process, but how comfortable are they to actually rely on and trust the numbers they are presented?
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