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E-grāmata: Decision Making with Quantitative Financial Market Data: Applications, Precautions and Pitfalls

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Use of quantitative data, especially in financial markets, may provide rapid results due to the ease-of-use and availability of fast computational software, but this book advises caution and helps to understand and avoid potential pitfalls.

It deals with often underestimated issues related to the use of financial quantitative data, such as non-stationarity issues, accuracy issues and modeling issues. It provides practical remedies or ways to develop new calculation methodologies to avoid pitfalls in using data, as well as solutions for risk management issues in financial market. 

The book is intended to help professionals in financial industry to use quantitative data in a safer way.

1 Basic Notions
1(14)
1.1 Data: Quantitative Versus Qualitative
1(1)
1.2 Measure: Exact, or Not?
2(2)
1.3 Differences, Spreads, and Percentages
4(1)
1.4 Data as Time Series
5(1)
1.5 Usual Statistics on Data in Probabilistic Time Series
6(9)
2 A Major Problem in Using Time Series of Data: Stationarity
15(4)
2.1 A Preliminary Issue: The Case of Data Frequency
15(4)
3 Another Major Problem in Using Time Series of Data: The Accuracy of the Statistical Measures
19(10)
3.1 Confidence Interval and Standard Error
19(4)
3.2 Application 1
23(2)
3.3 Application 2
25(1)
3.4 A Simplified Alternative to the Use of Confidence Interval or Standard Error
26(3)
4 Issues About Modeling
29(22)
4.1 General
29(1)
4.2 Modeling the Behavior of a Market and Related Valuation Models
29(2)
4.3 Modeling Derivatives Prices
31(7)
4.4 Using the ARCH Family of Processes in Derivatives Modeling
38(1)
4.5 Modeling Credit Derivatives Prices
39(2)
4.6 Use of Non-Gaussian Distributions in Modeling
41(2)
4.7 Use of Non-Gaussian Distributions in Modeling: A Step Further
43(1)
4.8 Other Potential Troubles with Derivatives Valuation
44(3)
4.9 Algorithms: Quantitative ("Algorithmic") Trading Models
47(3)
4.10 As a Conclusion to This
Chapter: Issues About Modeling
50(1)
5 Financial Data: Some Risk Management Issues
51(10)
5.1 Using the Volatility Measure of Losses, That Is, of Negative Returns
51(1)
5.2 The Time's Arrow Matters: The "Accrued Returns Variability" Measure
52(3)
5.3 The Case of the Controversial VaR ("Value at Risk") Measure
55(6)
6 Synthesis
61
Alain Ruttiens is a former banker who has worked with major banks, beginning his career with Banque Indosuez (Belgium) and ending it as director of the Financial Engineering Department at CBC Banque (Brussels, an affiliate of KBC Bank). He is the founding partner of NEURON sąrl (Luxembourg), a consulting firm specialized in financial markets and funds management. He is also an Affiliate Professor at the Ecole Supérieure de Commerce de Paris (France) and teaches or has taught at several universities and institutions, including the HEC Paris, Sorbonne University of Paris I, the Institut dEtudes Politiques (Paris), the CSVG (Vietnam) and the Ecole Supérieure des Affaires, Beirut (Lebanon). Alain is the author of several books and research papers.