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Quantitative Analysis
Parallel Processing
Numerical Analysis
C++ Multithreading
Python for Excel
Python Utilities
Services
Author
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I. Basic math.
II. Pricing and Hedging.
III. Explicit techniques.
IV. Data Analysis.
1. Time Series.
2. Classical statistics.
A. Basic concepts and common notation of classical statistics.
B. Chi squared distribution.
C. Student's t-distribution.
D. Classical estimation theory.
E. Pattern recognition.
a. Decision rule based on loss function.
b. Hypothesis testing problem.
c. Neyman-Pearson Lemma.
3. Bayesian statistics.
V. Implementation tools.
VI. Basic Math II.
VII. Implementation tools II.
VIII. Bibliography
Notation. Index. Contents.

Neyman-Pearson Lemma.


e are still within hypothesis testing setup ( Hypothesis_testing_section ). Let us forget about the structure of the threshold $T$ . We still perform the likelihood ration test MATH where the threshold is chosen according to requirement that MATH for a given level of error $\varepsilon$ . The Neyman-Pearson lemma states that there is no better decision rule MATH . Precisely, the lemma prohibits existence of MATH such that MATH and MATH





Notation. Index. Contents.


















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