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Quant finance lecture notes

655 lecture notes selected for learning quantitative finance. Highlighted picks come first. Showing 601–650; page 13 of 14.

601. Stochastic Calculus: Class 11 — Ito (NYU, 2019)

     Jonathan Goodman

     brownian motion · calculus · stochastic calculus · stochastic differential equations · stochastic processes

602. Stochastic Calculus: Class 12 — Ito, theory (NYU, 2019)

     Jonathan Goodman

     brownian motion · calculus · probability · stochastic calculus · stochastic processes

603. Stochastic Calculus: Class 13 — change of measure (NYU, 2019)

     Jonathan Goodman

     brownian motion · calculus · probability · stochastic calculus · stochastic processes

604. Stochastic Calculus: Class 2 — Brownian motion and diffusion equations (NYU, 2019)

     Jonathan Goodman

     brownian motion · calculus · partial differential equations · probability · stochastic calculus · stochastic processes

605. Stochastic Calculus: Class 3 — Backward equations (NYU, 2019)

     Jonathan Goodman

     brownian motion · calculus · partial differential equations · probability · stochastic calculus · stochastic processes

606. Stochastic Calculus: Class 4 — Ito integral for Brownian motion (NYU, 2019)

     Jonathan Goodman

     brownian motion · calculus · stochastic calculus · stochastic processes

607. Stochastic Calculus: Class 5 — multi-component diffusions (NYU, 2019)

     Jonathan Goodman

     calculus · probability · stochastic calculus · stochastic differential equations · stochastic processes

608. Stochastic Calculus: Class 6 — linear problems, more (NYU, 2019)

     Jonathan Goodman

     calculus · probability · stochastic calculus · stochastic differential equations · stochastic processes

609. Stochastic Calculus: Class 8 — More differential equations (NYU, 2019)

     Jonathan Goodman

     calculus · partial differential equations · probability · stochastic calculus · stochastic differential equations · stochastic processes

610. Stochastic Calculus: Class 9 — More differential equations, continued (NYU, 2019)

     Jonathan Goodman

     calculus · partial differential equations · probability · stochastic calculus · stochastic processes

611. Stochastic Calculus: Final Exam Practice (NYU, 2018)

     Jonathan Goodman

     brownian motion · calculus · martingales · probability · stochastic calculus · stochastic differential equations

612. Stochastic Calculus: Lesson 1 — Brownian motion (NYU, 2018)

     Jonathan Goodman

     brownian motion · calculus · probability · stochastic calculus · stochastic processes

613. Stochastic Calculus: Lesson 2 — Diffusion processes (NYU, 2018)

     Jonathan Goodman

     calculus · stochastic calculus · stochastic differential equations · stochastic processes

614. Stochastic Calculus: Lesson 3 — Ito integral (NYU, 2018)

     Jonathan Goodman

     probability · stochastic calculus · stochastic differential equations · stochastic processes

615. Stochastic Calculus: Lesson 4 — Ito’s lemma (NYU, 2018)

     Jonathan Goodman

     calculus · stochastic calculus · stochastic processes

616. Stochastic Calculus: Lesson 5 — SDE and PDE (NYU, 2018)

     Jonathan Goodman

     calculus · partial differential equations · probability · stochastic calculus · stochastic differential equations · stochastic processes

617. Stochastic Calculus: Lesson 6 — Simulating, change of measure (NYU, 2018)

     Jonathan Goodman

     calculus · monte carlo simulation · numerical methods · probability · stochastic calculus · stochastic differential equations

618. Stochastic Calculus: Lesson 8 — Multi-component diffusion (NYU, 2018)

     Jonathan Goodman

     calculus · partial differential equations · probability · stochastic calculus · stochastic processes

619. Stochastic Calculuss, MATH-GA.2903-001 — FinalExamInformation.pdf

     New York University (Courant) · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

620. Stochastic Control and Dynamic Asset Allocation

     University of Edinburgh · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

621. Stochastic Differential Equations (MIT 18.S096, Lecture 21)

     Choongbum Lee, MIT OpenCourseWare

     numerical methods · probability · stochastic calculus · stochastic differential equations · stochastic processes

622. Stochastic Processes I (MIT 18.S096, Lecture 5)

     Choongbum Lee, MIT OpenCourseWare

     probability · stochastic processes

623. Stochastic Processes II (MIT 18.S096, Lecture 17)

     Choongbum Lee, MIT OpenCourseWare

     brownian motion · probability · stochastic processes

624. TEACHING ACTIVITIES

     University of Waterloo · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

625. Teachings — Chaînes de Markov

     Université Paris-Saclay (Évry site) · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

626. Teachings — i‰ 、 ż

     Université Paris-Saclay (Évry site) · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

627. Teachings — sujet de l'examen

     Université Paris-Saclay (Évry site) · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

628. Teachings — য* ∅

     Université Paris-Saclay (Évry site) · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

629. Term Structure Lattice Models (Columbia IEOR E4706)

     Martin Haugh

     derivatives · financial engineering · fixed income · interest rates · martingales · mathematical finance

630. The Black-Scholes Model (Columbia IEOR E4706)

     Martin Haugh

     derivatives · financial engineering · mathematical finance · option pricing · volatility surface

631. The Fundamental Theorem Of Arbitrage Pricing (UChicago, 2001)

     Steven P. Lalley

     asset pricing · derivatives · mathematical finance · option pricing

632. The MinCost Network Flow Problem

     Princeton University · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

633. The Peter Lynch Playbook

     equity analysis · fundamental analysis · growth investing · long term investing · portfolio allocation · risk reward

634. The Principles of Deep Learning Theory

     Boris Hanin, Daniel A. Roberts, Sho Yaida · 2021

     Deep Learning · Effective Theory · Facebook · MIT · Machine Learning · Neural Networks

635. The Probabilistic Method in Combinatorics — Andrew Lin’s Notes

     Stanford University · advanced · quantitative finance

     quantitative finance · student notes · university resources

636. Theory of Deep Learning

     SANJEEV ARORA · 2020

     Deep Learning · Machine Learning · Mathematics · Neural Networks · Theory of Deep Learning

637. TMS Spring 2010 Real Analysis

     Middle East Technical University (METU) · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

638. TMS. Differential Equations (ODE) 1. Compute the first four successive approximations for the solution of the equation dy

     Middle East Technical University (METU) · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

639. Transportation Problem, Assignment Problem

     Princeton University · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

640. UIUC CS441 — Applied Machine Learning, Lecture 1: Introduction

     University of Illinois Urbana-Champaign · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

641. Un problème d'urnes | Transformation 2M-X

     Université Paris-Saclay (Évry site) · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

642. Undergraduate Fundamentals of Machine Learning

     Finale Doshi-Velez, Harvard University, William J. Deuschle · 2018

     Fundamentals · Harvard · Machine Learning · Supervised & Unsupervised Learning · Undergraduate Thesis

643. Warwick MA934 — MA398 Matrix Analysis and Algorithms Mathematics Institute and Centre for Scientific Computing University of Warwick UNITED KINGDOM

     University of Warwick · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

644. Warwick MA934 — MA934 - Numerical Algorithms and Optimisation Dr. Radu Cimpeanu with thanks to Prof. Colm Connaughton Mathematical Modelling for R

     University of Warwick · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

645. Warwick MA934 — Notes 1: Finite precision arithmetic, algorithms and computational complexity

     University of Warwick · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

646. Warwick MA934 — Notes 2: Introduction to data structures

     University of Warwick · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

647. Warwick MA934 — Notes 3: Interpolation, numerical derivatives and numerical integration

     University of Warwick · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

648. Warwick MA934 — Notes 4: Rootfinding algorithms

     University of Warwick · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

649. Warwick MA934 — Notes 5: Numerical linear algebra

     University of Warwick · advanced · quantitative finance

     quantitative finance · teaching materials · university resources

650. Warwick MA934 — Notes 6: Optimisation

     University of Warwick · advanced · quantitative finance

     quantitative finance · teaching materials · university resources