Buy Machine Learning for Options Trading by Hayden Van Der Post
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Home > Business and Economics > Finance and accounting > Finance and the finance industry > Investment and securities > Machine Learning for Options Trading: Building Alpha with Data-Driven Signals: Predictive Modeling, Feature Engineering, and Risk-Aware Execution for Derivatives Markets(3 Comprehensive Options 2025)
Machine Learning for Options Trading: Building Alpha with Data-Driven Signals: Predictive Modeling, Feature Engineering, and Risk-Aware Execution for Derivatives Markets(3 Comprehensive Options 2025)

Machine Learning for Options Trading: Building Alpha with Data-Driven Signals: Predictive Modeling, Feature Engineering, and Risk-Aware Execution for Derivatives Markets(3 Comprehensive Options 2025)


     0     
5
4
3
2
1



International Edition


X
About the Book

Reactive PublishingUnlock the Power of Machine Learning to Gain a Competitive Edge in Options Markets In today's hyper-competitive financial landscape, traditional options trading strategies are no longer enough. Machine Learning for Options Trading bridges the gap between theoretical finance and real-world execution by giving you a practical, end-to-end framework to build predictive models, generate trading signals, and optimize execution using Python. This book is your tactical playbook for deploying supervised and unsupervised learning methods to uncover actionable insights buried in options data. From volatility surfaces and skew metrics to time-decay and delta shifts, you'll learn how to engineer features that matter, and turn those features into alpha-generating signals. What You'll Learn Feature Engineering for Derivatives: Moneyness, IV rank, skew, term structure, gamma exposure, and more Signal Generation with ML Models: Random forests, gradient boosting, and ensemble techniques Time Series Forecasting for Options: LSTM and sequence modeling for implied volatility and delta reversion Risk-Aware Portfolio Construction: Designing delta/vega/gamma-neutral baskets Backtesting & Execution: Walk-forward validation, slippage modeling, and trade simulation Tools and Frameworks Covered Python (Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, Keras) OptionMetrics-style datasets and real-time feeds Custom backtesting engines for options-specific performance Who This Book Is For Quantitative traders seeking a machine learning edge Data scientists entering derivatives markets Options professionals upgrading their tech stack Python developers moving into finance Whether you're a seasoned quant or a self-taught trader, this book will help you transition from back-of-the-envelope models to machine-learned alpha with statistical rigor and automation. Data is the new edge. Machine learning is how you extract it. Build smarter signals. Trade with conviction. Outperform the crowd.


Best Sellers


Product Details
  • ISBN-13: 9798268328554
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 229 mm
  • No of Pages: 674
  • Returnable: N
  • Spine Width: 34 mm
  • Weight: 933 gr
  • ISBN-10: 826832855X
  • Publisher Date: 03 Oct 2025
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Series Title: 3 Comprehensive Options 2025
  • Sub Title: Building Alpha with Data-Driven Signals: Predictive Modeling, Feature Engineering, and Risk-Aware Execution for Derivatives Markets
  • Width: 152 mm


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
Machine Learning for Options Trading: Building Alpha with Data-Driven Signals: Predictive Modeling, Feature Engineering, and Risk-Aware Execution for Derivatives Markets(3 Comprehensive Options 2025)
Independently Published -
Machine Learning for Options Trading: Building Alpha with Data-Driven Signals: Predictive Modeling, Feature Engineering, and Risk-Aware Execution for Derivatives Markets(3 Comprehensive Options 2025)
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Machine Learning for Options Trading: Building Alpha with Data-Driven Signals: Predictive Modeling, Feature Engineering, and Risk-Aware Execution for Derivatives Markets(3 Comprehensive Options 2025)

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept


    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!
    Hello, User