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Operational Risk with Excel and VBA
Nigel Da Costa Lewis
€ 86.12
€ 72.12
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Description for Operational Risk with Excel and VBA
Hardcover. Operational Risk with Excel and VBA is a practitioner's guide that only discusses statistical methods that have been shown to work in an operational risk management context. It brings together a wide variety of statistical methods and models that have proven their worth, and contains a concise treatment of the topic. Series: Wiley Finance Series. Num Pages: 268 pages, illustrations. BIC Classification: KF. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 239 x 164 x 26. Weight in Grams: 500.
A valuable reference for understanding operational risk
A valuable reference for understanding operational risk
Operational Risk with Excel and VBA is a practical guide that only discusses statistical methods that have been shown to work in an operational risk management context. It brings together a wide variety of statistical methods and models that have proven their worth, and contains a concise treatment of the topic. This book provides readers with clear explanations, relevant information, and comprehensive examples of statistical methods for operational risk management in the real world.
Nigel Da Costa Lewis (Stamford, CT) is president and CEO of StatMetrics, a quantitative research boutique. He received his ... Read more
Show LessProduct Details
Format
Hardback
Publication date
2004
Publisher
John Wiley and Sons Ltd United States
Number of pages
268
Condition
New
Series
Wiley Finance Series
Number of Pages
288
Place of Publication
New York, United States
ISBN
9780471478874
SKU
V9780471478874
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50
About Nigel Da Costa Lewis
NIGEL DA COSTA LEWIS, PHD, is the President of the quantitative research boutique StatMetrics, offering cutting edge quantitative solutions to a sophisticated institutional client base. Dr. Lewis has many years’ work experience as a quantitative analyst and statistician in London, on Wall Street, and in academia. His work in quantitative risk management dates back to the early 1990s, when he ... Read more
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