Financial Surveillance examines the relationship between Statistical surveillance and financial analysis. Introducing both cultures, the book provides an overview of Statistical methods used in finance. the reader is then guided through more advanced topics, from likelihood–based surveillance of volatility, to sequential monitoring of optimal portfolio weights.
- Comprehensively covers the use of Statistical surveillance in financial analysis, enabling readers to successfully adjust to changes in financial market trends.
- Examines financial trading rules for timely decisions.
- Details schemes for different univariate and multivariate control charts.
- Provides information on different linear and nonlinear time series models, such as GARCH processes, and their applications, including modelling asset returns and exchange rates.
- Discusses the modern use of electronic trading in financial markets and data collection, as well as future directions for the subject.
- Applies methods to real data from worldwide markets, as well as illustrative simulation studies.
- Is accompanied by a website with additional updated information.
This is the first book–length treatment of statistical surveillance methods used in financial analysis. It contains selected chapters written by specialists on different topics. Financial Surveillance is ideal for readers from either Statistics or finance wanting to learn more about the other discipline. It also makes essential reading for advanced level students in statistics, economics and finance.
Statistics in Practice
A series of practical books outlining the use of Statistical techniques in a wide range of applications areas:
- Human and Biological Sciences
- Earth and Environmental Sciences
- Industry, Commerce and Finance
1. Introduction to financial surveillance (Marianne Frisén).
2. Statistical models in finance (Helgi Tómasson).
3. The relation between statistical surveillance and technical analysis.
in finance (David Bock, Eva Andersson and Marianne Frisén).
4. Evaluations of likelihood–based surveillance of volatility (David Bock).
5. Surveillance of univariate and multivariate linear time series (Y. Okhrin and W.Schmid).
6. Surveillance of univariate and multivariate nonlinear time series (Y. Okhrin and W. Schmid).
7. Sequential monitoring of optimal portfolio weights (Vasyl. Golosnoy, Wolfgang Schmid and Iryna. Okhrin).
8. Likelihood–based surveillance for continuous–time processes (Helgi T?omasson).
9 Conclusions and future directions (Marianne Frisén).