The objective of this repository is to model the underlying principles of Financial Mathematic. It is largely based on the course SF2701 course at KTH.
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The objective of this repository is to model the underlying principles of Financial Mathematic. It is largely based on the course SF2701 course at KTH.
Index
resources- The objective of this repository is to model the underlying principles of Financial Mathematic. It is largely based on the course SF2701 course at KTH.devitrylouisGithub Repon.d.
- Options, Futures, and Other Derivatives, Ninth Global EditionJohn C. HullBookn.d.
- Stochastic Calculus for Finance ISteven ShreveBookn.d.
- Stochastic Calculus for Finance II: Continuous-Time ModelsSteven ShreveBookn.d.
- Arbitrage Theory in Continuous Time, Third EditionTomas BjörkBook2009
- Monte Carlo Methods in Financial EngineeringPaul GlassermanBookn.d.
- The Volatility Surface: A Practitioner's GuideJim GatheralBook2006
- Advances in Financial Machine LearningMarcos López de PradoBook2018
- Quantitative Trading: How to Build Your Own Algorithmic Trading BusinessErnest P. ChanBook2009
- Active Portfolio Management, Second EditionRichard C. Grinold, Ronald N. KahnBookn.d.
- Fixed Income Securities: Tools for Today's Markets, Second EditionBruce TuckmanBookn.d.
- Modern Portfolio Theory and Investment Analysis, Ninth EditionEdwin J. Elton, Martin J. Gruber, Stephen J. Brown, William N. GoetzmannBookn.d.
- Inside the Black Box: A Simple Guide to Quantitative and High-Frequency TradingRishi K. NarangBookn.d.
- Pairs Trading: Quantitative Methods and AnalysisGanapathy VidyamurthyBookn.d.
- An Introduction to Statistical Learning with Applications in PythonDaniela Witten, Gareth James, Jonathan Taylor, Robert Tibshirani, Trevor HastieBookn.d.
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second EditionJerome Friedman, Robert Tibshirani, Trevor HastieBookn.d.
- Pattern Recognition and Machine LearningChristopher M. BishopBookn.d.
- Probabilistic Machine Learning: An IntroductionKevin P. MurphyBookn.d.
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, Second EditionAurélien GéronBookn.d.
- Statistical Inference, Second EditionGeorge Casella, Roger L. BergerBookn.d.
- All of Statistics: A Concise Course in Statistical InferenceLarry WassermanBookn.d.
- Introduction to ProbabilityJessica Hwang, Joseph K. BlitzsteinBook2019
- A First Course in ProbabilitySheldon RossBook2010
- Probability with MartingalesDavid WilliamsBookn.d.
- Brownian Motion and Stochastic CalculusIoannis Karatzas, Steven E. ShreveBookn.d.
- Continuous Martingales and Brownian MotionDaniel Revuz, Marc YorBookn.d.
- Markov ChainsJ. R. NorrisBookn.d.
- Essentials of Stochastic Processes, Third EditionRichard DurrettBookn.d.
- Introduction to Linear Algebra, Fifth EditionGilbert StrangBookn.d.
- Introduction to Applied Linear Algebra: Vectors, Matrices, and Least SquaresLieven Vandenberghe, Stephen BoydBookn.d.
- Linear Algebra Done Right, Second EditionSheldon AxlerBookn.d.
- Numerical Linear AlgebraDavid Bau III, Lloyd N. TrefethenBookn.d.
- Matrix Computations, Fourth EditionCharles F. Van Loan, Gene H. GolubBookn.d.
- Introduction to Algorithms, Third EditionCharles E. Leiserson, Clifford Stein, Ronald L. Rivest, Thomas H. CormenBookn.d.
- AlgorithmsChristos H. Papadimitriou, Sanjoy Dasgupta, Umesh V. VaziraniBookn.d.
- Algorithm DesignJon Kleinberg, Éva TardosBookn.d.
- Time Series AnalysisJames D. HamiltonBookn.d.
- Introductory Econometrics for FinanceChris BrooksBookn.d.
- Econometric Analysis of Cross Section and Panel Data, Second EditionJeffrey M. WooldridgeBookn.d.
- Bayesian Data Analysis, Third EditionAki Vehtari, Andrew Gelman, David B. Dunson, Donald B. Rubin, Hal S. Stern, John B. CarlinBookn.d.
- Asymptotic StatisticsAad W. van der VaartBookn.d.
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