Mathematical Methods in Finance
Master essential mathematical and computational techniques for financial modeling, analysis, and decision-making.
...
Share
Foundational Mathematical Concepts for Finance
Unit 1: Algebra Essentials for Finance
Variables and Equations
Working with Exponents
Logarithmic Functions
Polynomials and Factoring
Systems of Equations
Unit 2: Calculus Fundamentals for Financial Analysis
Limits and Continuity
Derivatives Explained
Differentiation Rules
Optimization and Maxima
Introduction to Integrals
Unit 3: Probability and Statistics for Financial Modeling
Basic Probability
Conditional Probability
Random Variables
Distributions
Regression Analysis
Linear Algebra and Calculus in Financial Modeling
Unit 1: Vectors and Matrices in Finance
Intro to Financial Vectors
Matrix Representation
Vector Operations
Matrix Operations
Linear Systems in Finance
Unit 2: Calculus for Portfolio Optimization
Derivatives in Finance
Optimization Basics
Portfolio Optimization
Sensitivity Analysis
Integral Calculus in Finance
Probability, Statistics, and Time Series Analysis
Unit 1: Foundations of Probability in Finance
Probability Concepts
Random Variables
Common Distributions
Joint Probability
Correlation Analysis
Unit 2: Statistical Inference and Hypothesis Testing
Sampling Techniques
Estimation
Hypothesis Testing Basics
T-Tests
Regression Analysis Intro
Unit 3: Time Series Analysis Fundamentals
Time Series Concepts
Data Preprocessing
AR Models
MA Models
ARMA Models
Stochastic Calculus, Optimization, and Numerical Methods
Unit 1: Introduction to Stochastic Processes
What are SPs?
Brownian Motion Basics
Wiener Process
Martingales
Ito Process Intuition
Unit 2: Ito's Lemma and Applications
Ito's Lemma Explained
Stock Price Dynamics
Option Pricing with Ito
Multi-Variable Ito's Lemma
Change of Numeraire
Unit 3: Optimization Techniques
Optimization Overview
Linear Programming
Quadratic Programming
Convex Optimization
Stochastic Programming
Unit 4: Numerical Methods
Numerical Methods Intro
Monte Carlo Methods
Finite Difference Method
Tree Methods
Integration Techniques
Machine Learning and Advanced Applications in Finance
Unit 1: Introduction to Machine Learning in Finance
ML in Finance: Overview
Data Collection & Prep
Feature Engineering
Model Selection
Backtesting & Deployment
Unit 2: Algorithmic Trading with Machine Learning
Algorithmic Trading Intro
Time Series Analysis
ML-Powered Signals
Risk Management in Algo
Evaluating Algo Performance
Unit 3: Risk Management and Credit Risk Modeling
Risk Management Overview
Credit Risk Fundamentals
ML for Credit Scoring
Fraud Detection
Stress Testing with ML
Unit 4: Advanced Applications and Case Studies
NLP for Finance
ML in Portfolio Opt
Blockchain Analytics
Real-World Case Study 1
Real-World Case Study 2