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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.

Pattern recognition.


here is a discrete set of states of nature MATH The nature draws a non-observable $\omega$ from $\Omega$ according to some "prior" probability distribution MATH . Then the nature also draws an observable data $x$ according to the probability distribution MATH . Given the $x,$ the prior distribution MATH and the functional form of MATH the market participant (player, observer, researcher) makes decision MATH




a. Decision rule based on loss function.
b. Hypothesis testing problem.
c. Neyman-Pearson Lemma.

Notation. Index. Contents.


















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