Financial Modeling Under Non-Gaussian Distributions (Springer Finance)
Eric Jondeau
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Description for Financial Modeling Under Non-Gaussian Distributions (Springer Finance)
Hardcover. Examines non-Gaussian distributions. This book addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. It is suitable for non-mathematicians who want to model financial market prices. Series: Springer Finance. Num Pages: 559 pages, 44 black & white tables, biography. BIC Classification: KFF. Category: (P) Professional & Vocational. Dimension: 241 x 164 x 34. Weight in Grams: 952.
This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.
This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.
Product Details
Publisher
Springer
Format
Hardback
Publication date
2006
Series
Springer Finance
Condition
New
Weight
951g
Number of Pages
541
Place of Publication
England, United Kingdom
ISBN
9781846284199
SKU
V9781846284199
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Financial Modeling Under Non-Gaussian Distributions (Springer Finance)
From the reviews: Financial Modeling Under Non-Gaussian Distributions ... is thus very welcome as it provides an accessible and easy-to-understand treatment of a broad range of topics, including core material to more advanced techniques on the subject of capturing non-Gaussian properties in the distributions of asset returns. ... ... Read more