Technical Analysis is all about using mathematics, statistics and other quantitative methods to see patterns in stock price, volume and other data. It is by no means an easy discipline to master, but with the right strategy, it can be a game changer when it comes to picking the right stocks at the right time. Which is why some of the largest funds and investment firms use technical analysis to make their investment decisions.
It can be a bit tricky for new investors to correctly apply technical analysis as part of their investment strategy and that often leads to sub optimal results. For technical analysis to yield meaningful results, you have to do it right. I have picked a list of courses that should help you learn technical analysis whether its for trading on your own personal account or just to brush up your skills if you intend to apply to a technical analysis role at an investment firm.
1. Fundamentals of Technical Analysis from the New York Institute of Finance
The New York Institute of Finance has been training bankers, traders and even financial regulators for almost a century now. It was founded by the New York Stock Exchange in 1922 and thousands of finance professionals have been trained by them in those decades. Today, NYIF is one of the leading names when it comes to financial education, especially when it comes to trading.
This particular course focuses on the fundamentals of technical analysis. You will learn how to use chart patterns for security analysis, the different types of chart types and how to construct and interpret them, concepts like gaps, support, resistance, various patterns, technical indicators like RoC, MACD, stochastic, moving averages, Bloomberg indicators, sentiment, breadth, relative strength, Dow theory, Elliott wave theory, Fibonacci sequence etc. There is a lot of very detailed information in there and some of these concepts can be very complex. But to their credit, the instructors manage to explain these crucial concepts and theories in a way that is engaging and approachable.
This course is meant for professional traders or individual traders who are serious about technical analysis. While it is beginner friendly, the information it provides is meant to satisfy even the most demanding traders.
Summary
| Time to Complete | Around 15 hours |
| Format | Self-paced, fully online |
| Level | Intermediate |
2. Artificial Intelligence for Trading from Udacity
The big technological leap in technical analysis is using Python to do it for you. Technical analysis is very time consuming and computationally expensive. This course helps you design an AI system that can do the heavy lifting so that you don’t have to. This makes it one of the most powerful tools in technical analysis and makes this one of my favourite courses for technical analysis. Note that you do need a bit of Python programming experience for this. Some statistics knowledge is also required like with every technical analysis course.
The course will teach you the basics of quantitative trading including data processing, trading signal generation, portfolio management, as well as using Python to work with historical, stock data and develop multi-factor trading strategies. The first few weeks are spent on quantitative trading concepts like market mechanics, signal generation, momentum trading etc. The best of this course is that you have practical exercises after every single module which means you will be developing a momentum trading model and a breakout signal model here. There is also a crash courses on portfolio optimization, market indices, ETFs, Smart Beta ETF, as well as using these factors to build your own portfolio as part of an exercise.
One of the most interesting modules in this course is using natural language processing and deep learning to perform sentiment analysis. One of my friends got her doctorate on this topic and its something that has always fascinated me. This is cutting edge stuff. There are of course practical exercises and you will get to build your own NLP model here.
The last few modules focus on combining multiple signals for enhanced alpha as well as a practical exercise to see it work in action. Then using historical data and rigours back testing to refine your trading signals and using them to generate trades.
Udacity also provides several value added services like industry experts to help guide you, plenty of real world projects that give you the confidence that academic programs alone cant provide, technical mentor support and even career services.
Click here to generate your personalized discount for this course!
Summary
| Time to Complete | Around 6 months at 10 hours a week |
| Format | Self-paced, fully online |
| Level | Intermediate |
3. Oxford Algorithmic Trading Programme
You need a lot of computing power to perform solid technical analyses and this is the course that is going to teach you how to do that. You are not only going to learn about technical analysis but also to build algorithms to automate part of the process for you.
The course starts off with an introduction to classic and behavioural finance theory. The efficient market hypothesis, the efficient frontier, behavioural biases in the market, terminology used, trends, and rule based algo trading. Systematic trading industry from the point of view of hedge funds is also explored. These funds are the at the bleeding edge of innovation here and its important to be able to learn about their systematic trading strategies and methodologies.
This is followed by an in depth look at technical analysis and trading system designs that are built around that. Back-testing, statistical verification, model performance, trading rules, ratios, use of APIs, building and optimizing trend models, selecting the right data, testing model variability and functionality etc. are just some of the topics covered here. This is the bread and butter of algo trading using technical signals.
Finally, we move on to evaluation criteria for such systematic funds and the funds that use them,. This includes investigating the strengths and weakness of such funds. Future trends in the filed are also explored like robo-advisors, AI ,machine learning and algorithmic technology for systemic trading.
This course from Oxford should give you a solid platform to build from and the confidence you need to use these techniques int he real world. Its also an excellent personal branding opportunity and you can use the certificate to signal your competence to employers and other stakeholders.
Click here and use code GS-AF-BBD15 for a 15% discount on this course!
Summary
| Time to Complete | 6 weeks, at 8-10 hours a week |
| Format | Self-paced, fully online |
| Level | Intermediate |
4. Quantitative Technical Analysis from the New York Institute of Finance
Technical analysis is all about the math. And if you have ready to take that deep dive into the wonderful and
mesmerizing world of quantitative finance, then this is the course for you! There are few courses that go as deep into the subject as this one here and touch on topics that will have you scratching your head for a while (as it should be). But the reward for all your effort will be equally satisfying as you crack the deepest mysteries of the equity markets using your newly acquired quantitative toolbox.
You’ll spend a good amount of time understanding algorithmic trading and learning how to develop the system for that purpose. Whether that is entry or exit rules or monitoring performance or determining trading frequency or what to trade in the first place. These are practical concerns, and they are addressed eloquently. Next up is position sizing which is a complex topic in itself followed by implementing a system driven approach to technical analysis.
I recommend this for users who already know a little bit and want to broaden their horizons. This is not a beginners course but it should serve you really well after you have completed one of the other courses on this list and want to reach the next level of proficiency and expertise.
Summary
- Time to Complete: Around 10 hours assuming you know the basics.
- Available fully online and on-demand. Complete it at your own pace.
5. Practical Time Series Analysis from The State University of New York
This course focuses on time series analysis using R and does a good job of simplifying that somewhat complex topic. Some amount of technical competency is required, especially in terms of statistics. You will look at data that represents sequential information like stock prices, the prices of commodities etc. and use mathematical models, graphical representation to provide insights into this data and predict future movements.
You’ll spend the first few hours learning the basics of inferential and descriptive statistics needed for the course. You’ll also be downloading and installing R. From there, you move on visualizing and modeling time series data. This is where things start to get interesting and a bit technical.
Concepts like Stationarity, Backward shift operator, Invertibility, Duality, Autoregressive processes, Yule-Walker equations, partial autocorrelation, Akaike Information criterion, ARMA, ARIMA, SARIMA, Seasonality, Mixed Models, Integrated Models etc. are also explored in depth. This is quite comprehensive and should provide you with all the tools you need to get started with time series analysis. In fact, it is one of the best courses out there for this topic.
There are a lot of quizzes and and practical exercises along the way that really help cement your understanding of an otherwise complicated topic. Its not easy to teach such abstract topics but the instructors have done a great job of it.
Summary
| Time to Complete | Around 26 hours |
| Format | Self-paced, fully online |
| Level | Intermediate |
6. Stock Market Trading: The Complete Technical Analysis Course
If you are looking for a compact, easy-to-digest and superbly explained beginner friendly course on technical analysis, then this is it. This course covers the all the basics you need to learn without bogging you down with a lot of complex mathematics. To be fair, technical analysis is all math so you should definitely expect a fair bit of it, but this course is more focused towards the technical side of things. The instructor wants you to start trading stocks using technical analysis instead of just studying it from a distance.
You start off with some basic core concepts like how to look at a chart, price bars, candlestick analysis, trading gaps, etc. You then move on to more advanced topics covering chart pattern recognition, moving averages, momentum, volatility, etc. There are plenty of practical examples to really help cement the concept and fun little tidbits and insights liberally strewn around. Some of the later topics do get complicated but if you want to learn technical analysis, you have to put in the work. However, the lessons themselves do not become too long or droning. They are still divided into bite-sized chunks for quick reference, and you can take things at your own pace.
One thing I appreciate about this course is that the author’s attitude and approach is towards the practical side of things. You are continuously encouraged to formulate your own trading strategy and philosophy. To really explore just what kind of a trader you want to be. This is the right approach in my opinion as it helps oyu build confidence which is a key attribute of a successful trader.
Summary
- Time to Complete: The course has around 12-13 hours of videos and should take about 15 hours to complete overall.
- Available fully online and on-demand. Complete it at your own pace.
7. Machine Learning for Trading from NYIF
This is a great course for day traders, hedge fund analysts, investment/ portfolio managers, and anyone else looking to up their trading game using machine learning and Python. The courses uses the Google Cloud platform to develop and deploy server-less, scalable, machine learning models to create trading strategies. You do need a solid background in Python and statistics so consider this an intermediate to advanced course.
The course starts off with an introduction to machine learning, trading and the Google cloud platform. Basic concepts like trends, stop-loss, profit sources, quantitative trading etc. are explored. You will also learn how the model actually learns.
You will then move on to using the machine learning model to implement advanced trading strategies like quantitative trading, pairs trading, momentum trading and so on. The use of reinforcement learning for developing trading strategies as well as integration with neural networks and application to time series data.
This is a very practical course with good video lectures that provide you with the tools you need to get started with machine learning for trading. Its by no means an easy topic so the job they have done here of building a foundation is excellent.
Summary
| Time to Complete | Around 48 hours |
| Format | Self-paced, fully online |
| Level | Intermediate |
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