Financial Derivatives: A Quantitative Finance View
4.5 (786 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
5,227 students enrolled

Financial Derivatives: A Quantitative Finance View

The financial engineering of forwards, futures, swaps, and options, with Python tools for fixed income and options
Bestseller
4.5 (786 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
5,227 students enrolled
Created by Cameron Connell
Last updated 7/2020
English
English [Auto]
Current price: $135.99 Original price: $194.99 Discount: 30% off
5 hours left at this price!
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This course includes
  • 25.5 hours on-demand video
  • 5 articles
  • 29 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Learn the fundamentals of derivatives at a quantitative level
  • Master arbitrage, the core principle underlying derivatives, quantitative risk management and quantitative trading
  • Use derivatives to control and manage financial risk
  • Price forwards, futures, swaps and options
  • Understand the Black-Scholes theory and formula intuitively, avoiding stochastic calculus
  • Learn the limitations of the Black-Scholes theory, and how it is used in practice
  • Python based tools are provided for computations with bonds, yield curves, and options
Requirements
  • Calculus and a basic course in probability and statistics
  • No knowledge or background in finance is assumed
Description

Student Testimonials:

  • This course offers an unreal value. Very rich content! This beats any financial course I've taken at my university. Looking forward to completing this course and using some of these skills in my career.--Steven


  • Cameron is an outstanding teacher. Thank you very much for making the most important and difficult Finance concepts so easy to understand. Looking forward to the further courses.--Gevorg


  • I got (am getting) some intuition about quant finance, not just leaning facts without really understanding the concepts.

    Cameron gives nice detailed answers to students questions.--Rich


Interested in a lucrative and rewarding position in quantitative finance?  Are you a quantitative professional working in finance or a technical field and want to bridge the gap and become a full on quant?  Then read on.

The role of a quantitative analyst in an investment bank, hedge fund, or financial company is an attractive career option for many quantitatively skilled professionals working in finance or other fields like data science, technology or engineering.  If this describes you, what you need to move to the next level is a gateway to the quantitative finance knowledge required for this role that builds on the technical foundations you have already mastered.


This course is designed to be exactly such a gateway into the quant world.  If you succeed in this course you will become a master of quantitative finance and the financial engineering of the most influential class of financial products that exist on markets today: derivatives.


About the instructor:

This course was created by a mathematician and financial quant holding a Ph.D. from the Courant Institute of Mathematical Sciences at NYU, and who earned his quant chops on Wall Street after an accomplished career as a theoretical materials scientist.


The focus of the course is thus very much on the practical skills someone working in the trenches in the real world of finance needs to have.  But since the course author also has 10 years of college teaching experience, it is taught with an eye to sound course structure and sensitivity to the concerns of students.


What you will learn:

Many finance students and professionals find derivatives the most challenging subject in their field.  But if you have a background in quantitative fields like statistics or computer science this course will show you that these most daunting of financial products are completely accessible to you.


Even if you are completely new to the world of finance, after completing this course you will have a deep mastery of the fundamental derivative structures traded on markets today: forwards, futures, swaps, and options.  But since this course is presented by a practitioner you will also learn how derivatives are actually used in the real world, as tools for both speculation and risk management.


The world of finance and markets is fast-paced and exciting, but can also be very intimidating.  In the heat of the moment, the markets are volatile and unpredictable, positions go south in unanticipated ways, you have traders yelling at you, you have computer software failing, you're relying on data you can't trust.  Keeping your head above water in this environment can be well nigh impossible.


You need a conceptual framework that allows you to keep above the fray and keep your wits about you.  In this course, my primary purpose is to convey that conceptual framework to my students.  The same conceptual framework that allowed me to survive and thrive in the pits of Wall Street during the dark days of the financial crisis.


Concerned that you may not have the required background to succeed in this course?  As long as you meet the formal prerequisites you need not be.  A quantitatively strong business background is more than enough to meet these requirements.  Any decent course in statistics and the basics of calculus is enough.  In truth, high school mathematics is all that is needed for 80-90% of the course material.  The most important requirement is simply to think analytically and logically.


Here is a sampling of some of the main topics that we'll cover on your journey into the quant profession:

  • Interest rate fundamentals

  • Periodic and continuous compounding

  • Discounted cash flow analysis

  • Bond analysis

  • The fundamentals of equity, currency, and commodity assets

  • Portfolio modelling

  • Long and short positions

  • The principle of arbitrage

  • The Law of One Price

  • Forwards, futures, and swaps

  • Risk management principles

  • Futures hedging

  • Stochastic processes

  • Time series concepts

  • The real statistics of asset prices: volatility clustering and autocorrelation

  • Fat-tailed distribution and their importance for financial assets

  • Brownian motion

  • The log-normal model of asset prices

  • Options

  • Put-call parity

  • The binomial model of option pricing

  • The Black-Scholes theory and formula

  • Option greeks: delta, gamma, and vega

  • Dynamic hedging

  • Volatility trading

  • Implied volatility

Includes Python tools

Python based tools are now included for computations with bonds, yield curves, and options.  All software that is part of this course is released under a permissive MIT license, so students are free to take these tools with them and use them in their future careers, include them in their own projects, whether open source or proprietary, anything you want!


So Sign Up Now!

Accelerate your finance career by taking this course, and advancing into quantitative finance.  With 23 hours of lectures and supplemental course materials including 10 problem sets and solutions, the course content is equivalent to a full semester college course, available for a fraction of that price, not to mention a 30 day money back guarantee.  You can't go wrong!

Who this course is for:
  • Technical professionals who want to learn about quantitative finance
  • Finance professionals who want to improve their quantitative skills and learn how to analyze derivative products
Course content
Expand all 125 lectures 25:58:03
+ Fundamentals
29 lectures 04:57:11
Interest Rates and Future Values
07:47
Compounding Conventions
11:38
Investment Return Measures
08:23
Interest Rate Conversions
07:26
Continuous Compounding
07:58
The Time Value of Money
07:07
Present Value
13:58
Discount Factors
15:57
Discounted Cash Flow Analysis
14:51
Bonds and Discounted Cash Flow Analysis
26:59
Yield to Maturity
07:58
Python Tools: Bonds
03:38
LIBOR
10:27
Fed Funds Rate
08:57
Yield Curves and Discount Curves
16:57
Python Tools: Yield Curves I
04:39
Bootstrapping Spot Curves from Bonds
13:20
Bootstrapping Spot Curves from Bonds II
04:15
Python Tools: Yield Curves II
01:46
Interest Rates: Default Assumptions
05:33
Equity Assets: Stock
13:53
Commodities
05:49
Modelling Portfolios
12:54
Foreign Currencies
11:55
Dividends, Convenience Yields, and Storage
08:34
Long and Short Positions
09:07
Long/Short Example
06:22
+ Arbitrage
7 lectures 02:02:02
The Arbitrage Concept
16:25
Arbitrage: Formal Definition
10:45
Arbitrage Example #1
15:40
Arbitrage Example #2
10:01
The Law of One Price
37:08
Law of One Price: Extensions and Examples
16:45
Arbitrage and Discounted Cash Flow Analysis
15:18
+ Forwards, Futures, and Swaps
42 lectures 08:16:09
Derivatives
07:10
Derivative Markets
10:00
Forward Contracts
18:54
Forward Payoffs
13:08
Pricing Forward Contracts
11:31
The Cash and Carry Arbitrage
13:55
Forward Example: A Zero Coupon Bond
14:19
Forward Example: A Stock (No Dividends)
08:18
Forwards on Assets Paying a Known Income
15:35
Forward Valuation with Known Income
19:00
Forwards on Assets Paying a Known Yield
14:23
Forward Example: A Dividend Paying Stock
09:35
FX Forwards
15:34
FX Forward Examples
19:16
Futures Contracts
11:47
Futures Prices
12:22
Futures Marking to Market
17:26
Futures: Margin Accounts
08:17
Futures Prices and Spot Prices
15:35
Convergence of Futures Prices to Spot Prices
09:08
Futures Contracts and Cash Exposures
09:40
Futures Hedging
09:58
Futures Hedging Example #1
06:06
Futures Hedging and Basis Risk
19:04
Futures Hedging Example #2
04:36
Futures Hedging Example #3
07:54
Speculation and Leverage with Futures
05:59
A Futures Speculating Example
08:43
The LIBOR Spot Curve
14:56
Forward Interest Rates
12:10
Forward Rate Agreements
12:01
FRA Valuation
16:26
Eurodollar Futures
13:48
Swaps
21:30
Pricing Swaps
21:08
Swap Example #1
05:15
Swap Example #2
05:37
Building a LIBOR Curve: Overview
05:19
Building a LIBOR Curve: the Short End
05:17
Building a LIBOR Curve: the Midrange
11:30
Building a LIBOR Curve: the Long End
11:55
Python Tools: Yield Curves III
02:04
+ Stochastic Processes and Asset Prices
18 lectures 04:02:36
Stochastic Processes: The Fundamental Idea
07:31
Stochastic Processes: Formalities
21:15
Time Series Statistics
16:31
Fat-Tailed Distributions
11:50
Asset Return Measures
10:09
The Stylized Facts of Asset Prices
11:55
Volatility Clustering
09:54
Asset Return Autocorrelation
16:28
Fat Tails of Asset Returns
05:49
Random Walks
12:16
The Distribution of Random Walks
18:34
Random Walks as Models for Asset Prices
19:23
Random Walks and Efficient Markets
08:17
Brownian Motion
18:51
Brownian Motion with Drift
06:58
Brownian Motion and Asset Prices
08:21
The Log-Normal Model
19:30
The Log-Normal Model and Asset Prices
19:04
+ Options
28 lectures 06:23:21
Options
18:12
Option Payoffs
20:03
Arbitrage Bounds on Options: Geometry
15:20
Arbitrage Bounds on Option Prices
04:48
Arbitrage Inequality #1
05:35
Arbitrage Inequality #3
10:17
Extensions and Applications of Option Bounds
08:47
Bounds on American Options
15:44
The Geometry of Put-Call Parity
11:24
Put-Call Parity
12:54
The Binomial Model: 1 Step
24:02
The 1 Step Binomial Model: The General Case
21:37
1 Step Risk Neutral Pricing
10:35
A 1 Step Risk Neutral Pricing Example
04:47
The Binomial Model: 2 Steps
20:09
The Distribution in the 2 Step Binomial Model
10:28
The Full Binomial Model
14:21
Call Pricing in the Binomial Model
10:12
Binomial Approximation to a Log-Normal
16:17
The Black-Scholes Formula
18:53
Flaws of the Black-Scholes Theory
11:45
The Black-Scholes Theory in Practice
11:48
Option Greeks
09:49
Option Theta and Time Decay
20:39
Python Tools: Options
08:32
Dynamic Hedging and Delta Neutral Trading
19:28
Options and Volatility Trading
15:47
Implied Volatility
11:08