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Financial Derivatives: A Quantitative Finance View 

  • Offered byUDEMY

Financial Derivatives: A Quantitative Finance View
 at 
UDEMY 
Overview

Master arbitrage, the core principle underlying derivatives, quantitative risk management and quantitative trading

Duration

27 hours

Total fee

8,640

Mode of learning

Online

Credential

Certificate

Financial Derivatives: A Quantitative Finance View
 at 
UDEMY 
Highlights

  • The Program comes with 30-Day Money-Back Guarantee
  • The course is offered through 5 articles and 29 downloadable resources, comes with an Lifetime access to the content through mobile and TV
  • Python based tools are provided for computations with bonds, yield curves, and options
  • Course has been created by a mathematician and financial quant holding a Ph.D. from the Courant Institute of Mathematical Sciences at NYU
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Financial Derivatives: A Quantitative Finance View
 at 
UDEMY 
Course details

Who should do this course?
  • Technical and Finance professionals who want to learn about quantitative finance and improve their quantitative skills and learn how to analyze derivative products.
What are the course deliverables?
  • Introduction
  • Fundamentals
  • Arbitrage
  • Forwards, Futures, and Swaps
  • Stochastic Processes and Asset Prices
  • Options
More about this course
  • Learn the limitations of the Black-Scholes theory, and how it is used in practice and use of derivatives to control and manage financial risk
  • Understand the Black-Scholes theory and formula intuitively, avoiding stochastic calculus, Price forwards, futures, swaps and options

Financial Derivatives: A Quantitative Finance View
 at 
UDEMY 
Curriculum

Lecture Series 1

Introduction

Lecture Series 2

Interest Rates

Interest Rates: General Considerations

Interest Rates and Future Values

Compounding Conventions

Investment Return Measures

Interest Rate Conversions

Continuous Compounding

The Time Value of Money

Present Value

Discount Factors

Discounted Cash Flow Analysis

Bonds and Discounted Cash Flow Analysis

Yield to Maturity

Python Tools: Bonds

Simple Interest and Day Count Conventions

LIBOR

Fed Funds Rate

SONIA: The Sterling Overnight Index Average

SOFR: The Secured Overnight Financing Rate

Yield Curves and Discount Curves

Python Tools: Yield Curves I

Bootstrapping Spot Curves from Bonds

Bootstrapping Spot Curves from Bonds II

Python Tools: Yield Curves II

Interest Rates: Default Assumptions

Equity Assets: Stock

Commodities

Modelling Portfolios

Foreign Currencies

Dividends, Convenience Yields, and Storage

Long and Short Positions

Long/Short Example

Lecture Series 3

The Arbitrage Concept

Arbitrage: Formal Definition

Arbitrage Example #1

Arbitrage Example #2

The Law of One Price

Law of One Price: Extensions and Examples

Arbitrage and Discounted Cash Flow Analysis

Lecture Series 4

Derivatives

Derivative Markets

Forward Contracts

Forward Payoffs

Pricing Forward Contracts

The Cash and Carry Arbitrage

Forward Example: A Zero Coupon Bond

Forward Example: A Stock (No Dividends)

Forwards on Assets Paying a Known Income

Forward Valuation with Known Income

Forwards on Assets Paying a Known Yield

Forward Example: A Dividend Paying Stock

FX Forwards

FX Forward Examples

Futures Contracts

Futures Prices

Futures Marking to Market

Futures: Margin Accounts

Futures Prices and Spot Prices

Convergence of Futures Prices to Spot Prices

Futures Contracts and Cash Exposures

Futures Hedging

Futures Hedging Example #1

Futures Hedging and Basis Risk

Futures Hedging Example #2

Futures Hedging Example #3

Speculation and Leverage with Futures

A Futures Speculating Example

The LIBOR Spot Curve

Forward Interest Rates

Forward Rate Agreements

FRA Valuation

Eurodollar Futures

Swaps

Pricing Swaps

Swap Example #1

Swap Example #2

Building a LIBOR Curve: Overview

Building a LIBOR Curve: the Short End

Building a LIBOR Curve: the Midrange

Building a LIBOR Curve: the Long End

Python Tools: Yield Curves III

Lecture Series 5

Stochastic Processes: The Fundamental Idea

Stochastic Processes: Formalities

Time Series Statistics

Fat-Tailed Distributions

Asset Return Measures

The Stylized Facts of Asset Prices

Volatility Clustering

Asset Return Autocorrelation

Fat Tails of Asset Returns

Random Walks

The Distribution of Random Walks

Random Walks as Models for Asset Prices

Random Walks and Efficient Markets

Brownian Motion

Brownian Motion with Drift

Brownian Motion and Asset Prices

The Log-Normal Model

The Log-Normal Model and Asset Prices

Lecture Series 5

Options

Option Payoffs

Arbitrage Bounds on Options: Geometry

Arbitrage Bounds on Option Prices

Arbitrage Inequality #1

Arbitrage Inequality #3

Extensions and Applications of Option Bounds

Bounds on American Options

The Geometry of Put-Call Parity

Put-Call Parity

The Binomial Model: 1 Step

The 1 Step Binomial Model: The General Case

1 Step Risk Neutral Pricing

A 1 Step Risk Neutral Pricing Example

The Binomial Model: 2 Steps

The Distribution in the 2 Step Binomial Model

The Full Binomial Model

Call Pricing in the Binomial Model

Binomial Approximation to a Log-Normal

The Black-Scholes Formula

Flaws of the Black-Scholes Theory

The Black-Scholes Theory in Practice

Option Greeks

Option Theta and Time Decay

Python Tools: Options

Dynamic Hedging and Delta Neutral Trading

Options and Volatility Trading

Implied Volatility

Faculty Icon

Financial Derivatives: A Quantitative Finance View
 at 
UDEMY 
Faculty details

Cameron Connell
Cameron hold a Ph.D. in mathematics from the Courant Institute of Mathematical Sciences at NYU. Now an entrepreneur working in financial and engineering technology with a focus on machine learning applications.

Financial Derivatives: A Quantitative Finance View
 at 
UDEMY 
Entry Requirements

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Financial Derivatives: A Quantitative Finance View
 at 
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