advanced-algorithmic-trading

7
1.4.1 Mathematics
To get the most out of this book it will be necessary to have taken introductory undergraduate
classes in Mathematical Foundations, Calculus, Linear Algebra and Probability,
which are often taught in university degrees of Mathematics, Physics, Engineering, Economics,
Computer Science or similar.
Thankfully it is unnecessary to have completed a university education in order to make good
use of this book. There are plenty of fantastic resources for learning these topics on the internet.
Some useful suggestions include:
• Khan Academy - https://www.khanacademy.org
• MIT Open Courseware - http://ocw.mit.edu/index.htm
• Coursera - https://www.coursera.org
• Udemy - https://www.udemy.com
However, it should be well noted that Bayesian Statistics, Time Series Analysis and Machine
Learning are quantitative subjects. There is no avoiding the fact that some intermediate level
mathematics will be needed to quantify our ideas.
The following courses are extremely useful for getting up to speed with the required mathematics:
• Linear Algebra by Gilbert Strang - http://ocw.mit.edu/courses/mathematics/18-06sclinear-algebra-fall-2011/index.htm
• Single Variable Calculus by David Jerison - http://ocw.mit.edu/courses/mathematics/18-
01-single-variable-calculus-fall-2006
• Multivariable Calculus by Denis Auroux - http://ocw.mit.edu/courses/mathematics/18-
02-multivariable-calculus-fall-2007
• Probability by Santosh Venkatesh - https://www.coursera.org/course/probability
1.4.2 Programming
Since this book is fundamentally about programming quantitative trading strategies, it will be
necessary to have some exposure to programming languages.
While it is not necessary to be an expert programmer or software developer, it is helpful to
have used a language similar to C++, C#, Java, Python, R or MatLab.
Many will have likely have programmed in VB Script or VB.NET through Excel. However,
taking an introductory Python or R programming course is strongly recommended. There are
many such courses available online:
• Programming for Everybody - https://www.coursera.org/learn/python
• R Programming - https://www.coursera.org/course/rprog