Algorithmic Trading & Time Series Analysis in Python and R

Technical Analysis (SMA and RSI), Time Series Analysis (ARIMA and GARCH), Machine Learning and Mean-Reversion Strategies

4.81 (472 reviews)

Udemy

platform

English

language

Investing & Trading

What you will learn

Understand technical indicators (MA, EMA or RSI)

Understand random walk models

Understand autoregressive models

Understand moving average models

Understand heteroskedastic models and volatility modeling

Understand ARIMA and GARCH based trading strategies

Understand market-neutral strategies and how to reduce market risk

Understand cointegration and pairs trading (statistical arbitrage)

Understand machine learning approaches in finance

Why take this course?

This course is about the fundamental basics of algorithmic trading. First of all you will learn about stocks, bonds and the fundamental basic of stock market and the FOREX. The main reason of this course is to get a better understanding of mathematical models concerning algorithmic trading and finance in the main.

We will use Python and R as programming languages during the lectures

IMPORTANT: only take this course, if you are interested in statistics and mathematics !!!

Section 1 - Introduction

why to use Python as a programming language?
installing Python and PyCharm
installing R and RStudio

Section 2 - Stock Market Basics

types of analyses
stocks and shares
commodities and the FOREX
what are short and long positions?

+++ TECHNICAL ANALYSIS ++++

Section 3 - Moving Average (MA) Indicator

simple moving average (SMA) indicators
exponential moving average (EMA) indicators
the moving average crossover trading strategy

Section 4 - Relative Strength Index (RSI)

what is the relative strength index (RSI)?
arithmetic returns and logarithmic returns
combined moving average and RSI trading strategy
Sharpe ratio

Section 5 - Stochastic Momentum Indicator

what is stochastic momentum indicator?
what is average true range (ATR)?
portfolio optimization trading strategy

+++ TIME SERIES ANALYSIS +++

Section 6 - Time Series Fundamentals

statistics basics (mean, variance and covariance)
downloading data from Yahoo Finance
stationarity
autocorrelation (serial correlation) and correlogram

Section 7 - Random Walk Model

white noise and Gaussian white noise
modelling assets with random walk

Section 8 - Autoregressive (AR) Model

what is the autoregressive model?
how to select best model orders?
Akaike information criterion

Section 9 - Moving Average (MA) Model

moving average model
modelling assets with moving average model

Section 10 - Autoregressive Moving Average Model (ARMA)

what is the ARMA and ARIMA models?
Ljung-Box test
integrated part - I(0) and I(1) processes

Section 11 - Heteroskedastic Processes

how to model volatility in finance
autoregressive heteroskedastic (ARCH) models
generalized autoregressive heteroskedastic (GARCH) models

Section 12 - ARIMA and GARCH Trading Strategy

how to combine ARIMA and GARCH model
modelling mean and variance

+++ MARKET-NEUTRAL TRADING STRATEGIES +++

Section 13 - Market-Neutral Strategies

types of risks (specific and market risk)
hedging the market risk (Black-Scholes model and pairs trading)

Section 14 - Mean Reversion

Ornstein-Uhlenbeck stochastic processes
what is cointegration?
pairs trading strategy implementation
Bollinger bands and cross-sectional mean reversion

+++ MACHINE LEARNING +++

Section 15 - Logistic Regression

what is linear regression
when to prefer logistic regression
logistic regression trading strategy

Section 16 - Support Vector Machines (SVMs)

what are support vector machines?
support vector machine trading strategy
parameter optimization

APPENDIX - R CRASH COURSE

basics - variables, strings, loops and logical operators
functions

APPENDIX - PYTHON CRASH COURSE

basics - variables, strings, loops and logical operators
functions
data structures in Python (lists, arrays, tuples and dictionaries)
object oriented programming (OOP)
NumPy

Thanks for joining my course, let's get started!

Screenshots

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Reviews

Fatih

September 16, 2023

I'm watching the Time Series part... At this point, I'm like "What's he talking about?" I don't need the explanation of how some method in a library is working from scratch. I need to know the when and how to use it. I can't skip the theory parts because there's code samples in between. I'm overwhelmed. People are using libraries for not being overwhelmed! This was going to be a fun weekend course for me...

Zadok

September 13, 2023

the course is quite good just that the instructors code is sometimes not correct therefore you end up spending time trying to fix the errors

Luke

September 9, 2023

Loved the content that was taught, it was very interesting and pretty comprehensive too, and Holczer clearly knows his stuff. The delivery was very slow for my liking and it did get quite repetitive at times, but playing it on 2x speed got over that and I know many people who would be absolutely fine with the delivery style. However, like the previous course, I found the excessive use of OOP in Python to be needlessly overcomplicating everything (why do we have to define "if __name__ = "__main__" every time? Although I do use Spyder rather than PyCharm, which renders this completely useless), while in R the use of a triple nested for loop to brute force the parameters for the ARMA/ARIMA/GARCH models was ridiculous, especially given the auto.arima() function in the forecast package does this for you with a much neater, quicker and more scientifically rigorous method! The fact that I got this on a sale for far less than the RRP makes me happy because I don't think it's worth the usual price and there are other instructors on this site that teach very similar/the same things in a much better way. (For those interested, auto.arima() applies the Hyndman-Khandakar algorithm, which you can read more about here: https://otexts.com/fpp2/arima-r.html)

Owais

September 2, 2023

Very nicely covering all the topics related to trade and related to coding. A must have course for every financial, data analyst

Kelvin

September 2, 2023

One of the best on the topic. Trainer clearly knows what he's talking about, and material is extremely concise and intuitive. Would rate 100/5 stars if I could :D

Jay

March 12, 2023

The content was good. It definitely shows you how to obtain market data (free) and analyze market data (free) via python and R algorithms. I think it gives you a starting point for working with algorithmic trading. I think you may be able to extend the algorithms presented. The mathematical foundation presented is also of significant value. Those things are probably the real value in the course (rather than trying to use the algorithms directly as they have been presented).

Casper

January 26, 2023

I like the concept of visual teaching, the lectures are in a constructive order and good for getting the general idea. I would like to have a Syllabus for background reading after the lectures. The provided powerpoint sheets require to redo lessons if things are less clear, while a written side-note can safe time. The provided transscipt is a speach-to-text result, it is not accurate enough for using it as side-note (lecture-text). But overall I love the lectures and the tempo of instructions. Thanks.

Lennart

December 22, 2022

The content covered is easily understandable and well taught from a practical perspective. I can apply it immediately. It covers a broad range of topics beyond my expectations.

John

September 15, 2022

This instructor is excellent and covers a tremendous amount of detail very quickly. This is truly a comprehensive Financial Analysis course.

José

April 16, 2022

This course has been a very good choice. I really liked the implementation of the momentum strategy, also the use of Backtrader, time series models and the last part of machine learning. All very complete. Thank you so much for everything.

Anthony

February 23, 2022

Needs to cover mathematical theory in more depth and provide more insightful explanations for the observation seen.

Akshay

May 30, 2021

Very informative and Educating ..It helps you to understand the jargons that you may have heard and always wanted to know :)

Anirban

December 12, 2020

This course is good to get a grasp on financial Time Series forecasting. Though one needs to know some of the basic about stock prices and a good understanding of statistics. The instructor could have included the assessment of performance and future implementations. Also one portion of the code needs a very long time of processing, that needs to be optimized.

Abhishek

October 10, 2020

Indeed, it's much better to see the impact with live examples. This course match my expectiation of understanding the implementation of statistics that i have learned so far.

Jeffrey

March 23, 2020

Holczer does a good job. I have taken a few of his courses and they are always worthwhile. Nice pace and he covers both theory and practice.

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