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Which books/papers should we all have in our shelves?

There are a couple that I use regularly such as:

Which ones do you recommend for which topics?

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General Finance Textbooks

  • Options, Futures and Other Derivatives, John Hull
  • The Concepts and Practice of Mathematical Finance, Mark Joshi
  • Paul Wilmott on Quantitative Finance, Paul Wilmott

Asset Pricing

  • Asset Pricing (Revised Edition), Cochrane, John H. Princeton University Press, 2009.
  • Financial Decisions and Markets: A Course in Asset Pricing, Campbell, John Y. Princeton University Press, 2017.
  • Asset pricing and portfolio choice theory, Back, Kerry. Oxford University Press, 2010.
  • Damodaran on Valuation, Damodaran, Aswath, Wiley Finance, 2006
  • Dynamic Asset Pricing Theory (Third Edition), Duffie, Darrell. Princeton University Press, 2001.

Asset Allocation

  • Introduction to Risk Parity and Budgeting, Roncalli, Thierry, 2013
  • Asset Management: A Systematic Approach to Factor Investing, Ang, Andrew, Financial Management Association, 2014
  • Expected Returns: An Investor's Guide to Harvesting Market Rewards, Illmanen, Anti, The Wiley Finance Series, 2011

Option Pricing Theory and Stochastic Calculus

  • Financial Calculus: An Introduction to Derivative Pricing, Martin Baxter and Andrew Rennie
  • Arbitrage Theory in Continuous Time, Tomas Björk
  • Stochastic Calculus for Finance I: The Binomial Asset Pricing Model, Steven Shreve
  • Stochastic Calculus for Finance II: Continuous-Time Models, Steven Shreve
  • Martingale Methods in Financial Modelling, Marek Musiela and Marek Rutkowski
  • Mathematical Methods for Financial Markets, Monique Jeanblanc, Marc Yor, and Marc Chesney
  • Financial Modelling With Jump Processes, Rama Cont and Peter Tankov
  • Option Volatility and Pricing, Sheldon Natenberg

Asset Classes

Equity Derivatives:

  • Equity derivatives, Marcus Overhaus et al.
  • Equity Hybrid Derivatives, Marcus Overhaus et al.
  • The Volatility Surface, Jim Gatheral
  • Stochastic Volatility Modeling, Lorenzo Bergomi
  • Dynamic Hedging: Managing Vanilla and Exotic Options, Nassim Nicholas Taleb
  • Option Volatility & Pricing, Sheldon Natenberg
  • Option Valuation Under Stochastic Volatility: With Mathematica Code, Alan L. Lewis

FX Derivatives:

  • Foreign Exchange Option Pricing, Iain J. Clark
  • FX Options and Smile Risk, Antonio Castagna
  • FX Options and Structured Products, Uwe Wystup

Commodity Derivatives:

  • Commodity Option Pricing, Iain J. Clark
  • Commodities and Commodity Derivatives, Helyette Geman
  • Energy and Power Risk Management: New Developments in Modeling, Pricing, and Hedging, Alexander Eydeland, Krzysztof Wolyniec

Interest Rate Derivatives:

  • Interest Rate Option Models, Rebonato
  • Interest Rate Models – Theory and Practice (with Smile, Inflation and Credit), Damiano Brigo and Fabio Mercurio
  • Interest Rate Modeling I, II & III, Leif B. G. Andersen and Vladimir V. Piterbarg
  • Pricing and Trading Interest Rate Derivatives, J H M Darbyshire

Inflation Derivatives:

  • Interest Rate Models – Theory and Practice (with Smile, Inflation and Credit), Damiano Brigo and Fabio Mercurio

Credit Derivatives:

  • Credit Risk - Modeling, Valuation & Hedging, Tomasz R. Bielecki and Marek Rutkowski
  • Modelling Single-name and Multi-name Credit Derivatives, Dominic O’Kane
  • Interest Rate Models – Theory and Practice (with Smile, Inflation and Credit), Damiano Brigo and Fabio Mercurio

XVA:

  • XVA: Credit, Funding and Capital Valuation Adjustments, Andrew Green
  • Counterparty Credit Risk, Collateral and Funding, Damiano Brigo, Massimo Morini, and Andrea Pallavicini

Quantitative Risk Management

  • Quantitative Risk Management: Concepts, Techniques and Tools, Alexander J. McNeil, Rudiger Frey, and Paul Embrechts

Mathematics

Probability and Stochastic Processes:

  • Probability, A.N. Shiryaev
  • Probability, Leo Breiman
  • Stochastic Calculus and Applications, Samuel N. Cohen and Robert J. Elliott
  • Stochastic Differential Equations, Bernt Oksendal
  • Diffusions Markov Processes and Martingales, L. C. G. Roger and D. Williams

Statistics:

  • Statistical Inference, George Casella and Roger Berger

  • Theoretical Statistics - Topics for a Core Course, Robert W. Keener

  • Time Series Analysis, James Hamilton

  • The econometrics of financial markets, Campbell, John Y., Andrew Wen-Chuan Lo, and Archie Craig MacKinlay. Vol. 2. Princeton, NJ: Princeton University Press, 1997.

  • The Elements of Statistical Learning, Hastie, Tibshirani and Friedman

  • Handbook of Markov Chain Monte Carlo, Brooks, Steve, Gelman, Andrew, Jones, Galin , and Meng, Xiao-Li.

  • Analysis of Financial Time Series, Ruey S. Tsay

Machine Learning:

  • Machine Learning: A Probabilistic Perspective, Kevin P Murphy

  • Pattern Recognition and Machine Learning, Christopher Bishop

  • Reinforcement Learning: An introduction, Richard S. Sutton and Andrew G. Barto

  • Advances in Financial Machine Learning, Marcos Lopez de Prado

Programming

  • C++ Design Patterns and Derivatives Pricing, Mark Joshi
  • Python for Data Analysis, Wes McKinney
  • Applied Computational Economics and Finance, Mario J. Miranda and Paul L. Fackler
  • Modern Computational Finance, Antoine Savine

Interviews

  • Quant Job Interview Questions and Answers, Mark Joshi
  • Heard on the Street: Quantitative Questions from Wall Street Job Interviews, Timothy Crack
  • 150 Most Frequently Asked Questions on Quant Interviews, Dan Stefanica, Radoš Radoičić, and Tai-ho Wang
  • An Interview primer for quantitative finance, Dirk Bester

Being a Quant

  • My Life as a Quant: Reflections on Physics and Finance, Emanuel Derman
  • The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It, Scott Patterson
  • A Man for All Markets: From Las Vegas to Wall Street, How I Beat the Dealer and the Market, Edward Thorpe
  • The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution, Gregory Zuckerman

Cultural Classics

  • Reminiscences of a Stock Operator, Jesse Livermore
  • Liar’s Poker, Michael Lewis
  • Against the Gods, Peter Bernstein
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    $\begingroup$ Many titles are missing here and I must admit I haven't read them all but it's a start, please feel free to edit. $\endgroup$
    – Bob Jansen ♦
    Commented Mar 19, 2018 at 21:45
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    $\begingroup$ I added a few more. $\endgroup$
    – Gordon
    Commented Mar 20, 2018 at 13:35
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    $\begingroup$ The papers one should probably be a different question entirely. @phdstudent Can you ask that one too, I can make it CW then. $\endgroup$
    – Bob Jansen ♦
    Commented Mar 20, 2018 at 14:46
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    $\begingroup$ I think the math part should be included, but limited. $\endgroup$
    – Gordon
    Commented Mar 20, 2018 at 14:53
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    $\begingroup$ A great list, but "The Elements of Statistical Learning" by Hastie, Tibshirani and Friedman should be under machine learning, not statistics, or perhaps under both. $\endgroup$
    – Richard Hardy
    Commented Jun 24, 2020 at 15:21
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For equities specifically:

Quantitative Equity Portfolio Management: Modern Techniques and Applications, Qian, Hua, Sorensen

Active Portfolio Management, Grinold and Kahn

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« Stochastic differential equations » by Oksendal is my best reference on SDE for practionners who want a rigorous statement of all important results in the topic while maintaining a decent size for the book. In addition it comes with solved exercises so this is a must.

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Simon Benninga (2014) "Financial Modelling" Fourth edition - The MIT Press

Highly recommended!

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Retail Credit Risk Modelling

  1. The Management of Consumer Credit, Theory and Practice by Steven Finlay
  2. Intelligent Credit Scoring: Building and Implementing Better Credit Risk Scorecards by Naeem Siddiqi
  3. Credit Scoring and Its Applications, Second Edition by Lyn Thomas, Jonathan Crook, David Edelman
  4. Credit Intelligence & Modelling: Many Paths through the Forest of Credit Rating and Scoring by Raymond A. Anderson
  5. Consumer Credit Models: Pricing, Profit and Portfolios by Lyn C. Thomas
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