Name: Deep Hedging and Reinforcement Learning for Dynamic Derivatives Risk Management under Market Frictions
ISBN: 9788168314368

Book information

Authors: Murali Krishna Pasupuleti
Editions known: 1
Publishers: National Education Services
ISBN-13: 9788168314368
Main topics: Reinforcement Learning for Finance, Risk Management
Also covers: Derivatives Pricing
Related site topics: Options & Derivatives Pricing, Reinforcement Learning for Trading, Risk Management & Tail Risk

Overview

Deep Hedging and Reinforcement Learning for Dynamic Derivatives Risk Management under Market Frictions is a book by Murali Krishna Pasupuleti. In this catalogue it is classified mainly under Reinforcement Learning for Finance and Risk Management, with secondary coverage of Derivatives Pricing.

Audience and depth. The available metadata did not allow a mathematical difficulty estimate, so none is shown; treat the technical level as unknown.

Orientation. The theory-versus-practice balance could not be determined from metadata. The archive holds 6 papers whose topics and vocabulary overlap with this book; those links are inferred (see the research connections below).

How to read this page. Topics, difficulty, prerequisites and orientation are model-derived (rule-based, rule_based_v1) from bibliographic metadata such as title, subject headings and edition data. They were not produced by reading the book and are not a review. Relevance confidence is 71% and difficulty confidence is 0%; the catalogue lists no ratings or awards.

Research assessment

Rule-based and model-derived from metadata (title, subject headings, edition data). These are not reviews or ratings; see the evidence below.

Quant-finance relevance	35/100 confidence 71% Score 35.3/100. Strongest: quant_relevance 0.51, technical_depth 0.40; weakest: practical_applicability 0.00. Evidence: title:'hedging', title:'risk management', title:'derivatives'. Difficulty unknown (neutral technical_depth).
Mathematical difficulty	Unknown
Metadata quality	35% thin metadata: hidden from search engines

Difficulty evidence (1 signal)

dynamic_programming_rl matched in title: “reinforcement learning”

Research connections

Related papers on this site

Similarity of research area (shared vocabulary, topics and methods). Not citations: the paper does not necessarily cite this book.

Deep Hedging with Reinforcement Learning: A Practical Framework for Option Risk Management Topic similarity inferred similarity 0.67
A Risk Sensitive Contract-unified Reinforcement Learning Approach for Option Hedging Topic similarity inferred similarity 0.62
CVA Hedging by Risk-Averse Stochastic-Horizon Reinforcement Learning Topic similarity inferred similarity 0.60
Adaptive Nesterov Accelerated Distributional Deep Hedging for Efficient Volatility Risk Management Topic similarity inferred similarity 0.57
Developing A Multi-Agent and Self-Adaptive Framework with Deep Reinforcement Learning for Dynamic Portfolio Risk Management Topic similarity inferred similarity 0.55
Hedging with Sparse Reward Reinforcement Learning Topic similarity inferred similarity 0.54

Methods covered

Reinforcement Learning inferred

Similar books

Foundations of Reinforcement Learning with Applications in Finance inferred similarity 0.47
Reinforcement Learning for Finance inferred similarity 0.46
Derivatives, risk management & value inferred similarity 0.39
Statistical Reinforcement Learning inferred similarity 0.39
Derivatives and Internal Models inferred similarity 0.38

Author profiles

Murali Krishna Pasupuleti (no profile page: identity not verified or too little data)

External resources

DOI
Search on Amazon (ISBN-13 9788168314368) (search link; may be an affiliate link)

Relationship graph

Solid lines are verified facts (authorship from persistent identifiers, editions); dashed lines are inferred by rules or similarity. Open in the full explorer.

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