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Permutation and Randomization Tests for Trading System Development: Algorithms in C++
86% of respondents would recommend this to a friend
€ 37
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This book provides the trading system developer with a powerful set of statistical tools for measuring vital aspects of performance that are ignored by most developers.
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| Package Weight | 1 Pound |
Who Should Buy?
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Quantitative Analysts
Perfect for quantitative analysts seeking robust statistical methods for validating trading strategies using C programming.
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Algorithm Developers
Ideal for developers needing algorithms that leverage permutation and randomization tests to assess trading system performance.
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Finance Students
Beneficial for finance students wanting to understand the application of statistical tests in financial models effectively.
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Beginner Programmers
Not suitable for beginners who lack foundational programming knowledge, especially in C or statistical methods.
Product Description
Permutation and Randomization Tests for Trading System Development: Algorithms in C++
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Data Processing Editorial Review
Permutation and Randomization Tests for Trading System Development is a highly recommended book for anyone interested in ML and algorithmic trading. The book is well-written and explains complex statistical concepts in an accessible way. The algorithms provided in the book, with both C++ and pseudo-code versions, offer valuable information for testing trading systems. The book addresses the challenge of using out-of-sample data effectively, providing methods to delay its usage until the latest stages of system development. The use of Monte Carlo Permutation tests allows for the evaluation of trading system performance and the detection of potential data overfitting. The book offers tremendous value and is a must-read for those wishing to improve their understanding and application of permutation testing and bootstrapping in financial data.
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Pros
- Well-written and accessible explanations of complex statistical concepts
- Packed with valuable information and important algorithm details
- Effective methods for using out-of-sample data in trading system development
- Provides insights on Monte Carlo Permutation tests and data overfitting
Cons
- Author gives away a lot of valuable information for a relatively low cost
Product Price History
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Features & Benefits
- Includes intuitive justification, basic theory, relevant equations, and highly commented C++ code
- Topics covered: overfitting, luckiness-vs-skill evaluation, effectiveness testing, selection bias removal, probability bounds, and more
- Easy reprogramming in other languages
- Evaluates the best indicator or model's luck versus skill
- Identifies markets with truly superior profits
- Determines the best holding time for risk/return performance
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