Quant Finance Bootcamp 24 – Quant Finance Institute (QFI)

About Course

Dear Participants,

Quant Finance Institute (QFI) is thrilled to welcome you to Quant Finance Bootcamp 24, an intensive learning journey designed to equip you with the essential skills and knowledge required to excel in the field of quantitative finance. This program is crafted to bridge the gap between theoretical financial concepts and their practical applications, using real-world data and case studies.

Over the course of this program, you will delve into sophisticated financial models, explore advanced risk management techniques, and develop a deep understanding of derivative markets. Each section of our curriculum is tailored to introduce you to the fundamental and cutting-edge topics necessary for a successful career in finance.

We encourage you to engage fully, and take advantage of the opportunities to interact with fellow learners and instructors. This is more than just a learning experience—it’s a chance to be part of a community that fosters innovation and critical thinking.

We are excited to embark on this journey with you and look forward to seeing the impact of your learning in the world of finance.

Welcome Aboard!

We have detailed the curriculum of the cohort below

Section 1: Derivative Introduction

Exchange Traded Market
Over the Counter Market
Forward
Future
Options (Call & Put)
Swaps
Types of Traders
- Hedger
- Arbitrageur
- Speculator

Section 2: Future Market

Introduction
Specification of Future Contract
Operations of Margin Account
Case Study on Future Market
Forward vs Future

Section 3: Mechanics of Option Market

Types of Options (Call & Put)
Types of Position (Long Call, Long Put, Short Call, Short Put)
Payoff Diagram (Long Call, Long Put, Short Call, Short Put)
Types of Underlying Assets
European Option
American Option

Section 4: Swaps

Introduction
Purpose
Types of Swaps
Interest Rate Swaps
- Structure and Mechanics (fixed for floating, floating for floating)
- Valuation
- Applications: Hedging interest rate risk, modifying cash flow structures

Section 5: Binomial Tree of Pricing American Option

One Step Binomial Tree
Risk Neutral Valuation
Real World vs Risk Neutral World
Two Step Binomial Tree
Quant Modeling Project

Section 6: Mathematical Finance

Stochastic Process (Continuous vs. Discrete)
The Markov Property
Continuous Time Stochastic Process
Weiner Process or Brownian Motion
Discrete Time Model
Monte Carlo Simulation
Correlated Process
Ito’s Lemma

Section 7: The Black Scholes Model

Lognormal property of Stock Price
Estimating Volatility from Historical Data
Assumptions of Black Scholes Model
Formula & Interpretation of Black Scholes Model
Practical Applications
Limitation of BS Model and how to overcome using other Models
Quant Modeling Project

Section 8: Greeks

Risk Measures for Derivative Portfolio
- Delta
- Gamma
- Rho
- Theta
- Vega
Applications of Greeks
- Delta Hedging
- Gamma Hedging
- Vega Hedging

Section 9: Put Call Parity

Put Call Parity for European Option
Put Call Parity for European Option (with Dividends)
Put Call Parity for American Option

Section 10: Value at Risk & Expected Shortfall

Introduction
Variance Covariance Method
Historical Method
Monte Carlo Method
Back Testing VaR (Traffic Light Approach, Kupiec Approach)
Stress Testing VaR (SVaR)
Quant Modeling Project

Section 11: Exotic Options

Asian Option
Binary Option
Barrier Option

Section 12: Stochastic Interest Rate Modeling

Introduction to Interest Rate Models
Vasicek Interest Rate Model
- Model Specification, Properties and Characteristics, Applications
CIR Interest Rate Model
- Model Specification, Properties and Characteristics, Applications
Vasicek vs. CIR – Differences
Model Calibration and Implementation
Quant Modeling Project

Section 13: Model Validation

Introduction to Model Validation
Key Components of Model Validation (Conceptual Soundness, Model Assumptions, Data Quality and Relevance)
Model Testing and Performance (Back testing, Stress Testing, Sensitivity Analysis, Benchmarking)
Validation Metrics

Section 14: Portfolio Management

Alpha
Beta, Adj R2
Volatility
Sortino Ratio, Treynor Ratio, Sharpe Ratio
Maximum Drawdown
Quant Modeling Project

Foundational Knowledge: Gain a solid understanding of derivative markets, including forwards, futures, and options, and the roles of different traders like hedgers, arbitrageurs, and speculators.
Future Markets: Learn the intricacies of futures contracts, margin account operations, and the distinctions between forward and future contracts through case studies.
Options Mechanics: Master the types of options, positions, and payoff diagrams, and differentiate between European and American options.
Option Pricing: Explore the binomial tree method for pricing American options and the concept of risk-neutral valuation.
Stochastic Processes: Delve into continuous and discrete stochastic processes, Brownian motion, and apply Ito's Lemma to quantitative finance models.
Black-Scholes Model: Understand the assumptions, application, and interpretation of the Black-Scholes Merton model for option pricing.
Risk Management with Greeks: Learn how to calculate and use Delta, Gamma, Rho, Theta, and Vega for hedging and risk management.
Value at Risk (VaR): Analyze risk using VaR and Expected Shortfall, with backtesting and stress testing to validate models.
Exotic Options: Explore the unique characteristics and applications of exotic options such as Asian, binary, and barrier options.
Interest Rate Modeling: Study stochastic interest rate models like Vasicek and CIR, focusing on their calibration, implementation, and differences.

Course Content

Introduction to Derivatives

Introduction to Derivative (Forwards & Futures)

01:44:27
Introduction to Derivative (Practical Example)

01:54:25
Introduction to Derivative (Call & Put Option) – Part A

01:05:28
Introduction to Derivative (Call & Put Option) – Part B

56:23
Introduction to Derivative (Operation of Margin Account)

01:16:24
Introduction to Derivative (Practical Example on Options)

19:34

Risk Management in Derivatives

Greeks for Options (Part A)

01:02:28
Greeks for Options (Part B)

58:43
Greeks for Options (Part C)

54:49
Greeks for Options (Part D)

46:38
Greeks for Options (Part E)

34:53
Delta Hedging

51:44
Gamma Hedging

51:22
Delta Gamma Hedging

21:24
Vega Hedging

20:58
Theta Hedging

20:31
Rho Hedging

19:10

Quant Modeling & Stochastic Processes

One Step Binomial Tree & No Arbitrage Argument (Theory)

59:49
Two Step Binomial Tree & Mathematical Calculation

25:03
Quant Modeling: Pricing European Option Using Binomial Tree

37:42
Brownian Motion (Stochastic Process)

01:20:13
Generalized Weiner Process & Ito’s Lemma

57:21
Model Stock Using Geometric Brownian Motion (GBM) (Excel)

56:57
Cholesky Decomposition for Geometric Brownian Motion (GBM)

58:15
Black Scholes Model (Theory)

01:08:16
Black Scholes Model (Excel Implementation)

32:15
Monte Carlo Method for Quant Finance

01:17:41
Pricing European Option Using Monte Carlo Method (Excel)

39:30
Pricing Asian Option Using Monte Carlo Method (Excel)

31:51
Pricing Barrier Option Using Monte Carlo Method (Excel)

57:24

Stochastic Interest Rate Modeling

Value at Risk Modeling

Value at Risk – Introduction (Theory)

29:07
Value at Risk – Historical Method (Theory)

01:16:48
Value at Risk – Historical Method (Excel Implementation)

35:40
Value at Risk – Variance Covariance Method (Theory)

43:29
Value at Risk – Variance Covariance Method (Excel Implementation)

26:47
Value at Risk – Monte Carlo Simulation Method (Theory)

57:10
Value at Risk – Monte Carlo Simulation Method (Excel Implementation)

41:35
Backtest VaR Using Traffic Light Approach (Theory & Excel Implementation)

57:37
Backtest VaR Using Kupiec Test (Theory & Excel Implementation)

45:58
Expected Shortfall (Theory)

38:32
Expected Shortfall (Excel Implementation)

23:32

About Course

What Will You Learn?

Course Content

Introduction to Derivatives

Introduction to Derivative (Forwards & Futures)

Introduction to Derivative (Practical Example)

Introduction to Derivative (Call & Put Option) – Part A

Introduction to Derivative (Call & Put Option) – Part B

Introduction to Derivative (Operation of Margin Account)

Introduction to Derivative (Practical Example on Options)

Risk Management in Derivatives

Greeks for Options (Part A)

Greeks for Options (Part B)

Greeks for Options (Part C)

Greeks for Options (Part D)

Greeks for Options (Part E)

Delta Hedging

Gamma Hedging

Delta Gamma Hedging

Vega Hedging

Theta Hedging

Rho Hedging

Quant Modeling & Stochastic Processes

One Step Binomial Tree & No Arbitrage Argument (Theory)

Two Step Binomial Tree & Mathematical Calculation

Quant Modeling: Pricing European Option Using Binomial Tree

Brownian Motion (Stochastic Process)

Generalized Weiner Process & Ito’s Lemma

Model Stock Using Geometric Brownian Motion (GBM) (Excel)

Cholesky Decomposition for Geometric Brownian Motion (GBM)

Black Scholes Model (Theory)

Black Scholes Model (Excel Implementation)

Monte Carlo Method for Quant Finance

Pricing European Option Using Monte Carlo Method (Excel)

Pricing Asian Option Using Monte Carlo Method (Excel)

Pricing Barrier Option Using Monte Carlo Method (Excel)

Stochastic Interest Rate Modeling

Vasicek Interest Rate Model (Theory)

Vasicek Interst Rate Model (Excel Implementation with Market Calibration)

Cox–Ingersoll–Ross (CIR) Model (Theory)

Cox–Ingersoll–Ross (CIR) Model (Excel Implementation)

Value at Risk Modeling

Value at Risk – Introduction (Theory)

Value at Risk – Historical Method (Theory)

Value at Risk – Historical Method (Excel Implementation)

Value at Risk – Variance Covariance Method (Theory)

Value at Risk – Variance Covariance Method (Excel Implementation)

Value at Risk – Monte Carlo Simulation Method (Theory)

Value at Risk – Monte Carlo Simulation Method (Excel Implementation)

Backtest VaR Using Traffic Light Approach (Theory & Excel Implementation)

Backtest VaR Using Kupiec Test (Theory & Excel Implementation)

Expected Shortfall (Theory)

Expected Shortfall (Excel Implementation)

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