Welcome to your FREE Algorithmic Trading resource where you will learn how to develop profitable algorithmic trading strategies and gain a career in quantitative trading.
Estimating the risk of loss to an algorithmic trading strategy, or portfolio of strategies, is of extreme importance for long-term capital growth. Many techniques for risk management have been developed for use in institutional settings. One technique in particular, known as Value at Risk or VaR, will be the topic of this article. Read more...
A lot of you have emailed recently asking what it is actually like to work in a quant fund. I've written before about my experiences as a quant dev but I thought I'd outline a normal day so you can get a feel for whether you would enjoy the role. Read more...
In this article we are going to discuss an issue that repeatedly crops up via the QuantStart mailbox, namely how to get a quant job once you have a PhD. There's a lot of confusion around this topic because quite a few people who currently work in academia and want to make the shift believe that it is quite straightforward to "walk into" a high-paying financial role. While this may have been true 10-15 years ago, the reality of the current job market is such that quant roles are now highly competitive and candidates need to stand out if they are to get the best jobs. Read more...
We've discussed the importance of statistical modelling and machine learning in various articles on QuantStart. Machine learning is particularly important if one is interested in becoming a quantitative trading researcher. In this article I want to highlight some books that discuss machine learning from a programmatic perspective, rather than a mathematical one. This route is more appropriate for the quantitative developer or traditional software developer who wishes to eventually break into quantitative trading. Read more...
Risk and money management are absolutely critical topics in quantitative trading. We have yet to explore these concepts in any reasonable amount of detail beyond stating the different sources of risk that might affect strategy performance. In this article we will be considering a quantitative means of managing account equity in order to maximise long-term account growth and limiting downside risk. Read more...
- A Day in the Life of a Quantitative Developer
- How To Get A Quant Job Once You Have A PhD
- Why a Masters in Finance Won't Make You a Quant Trader
- Self-Study Plan for Becoming a Quantitative Trader - Part I
- How to Get a Job at a High Frequency Trading Firm
- Getting a Job in a Top Tier Quant Hedge Fund
- Self-Study Plan for Becoming a Quantitative Analyst
- Self-Study Plan for Becoming a Quantitative Developer
- Can You Still Become a Quant in Your Thirties?
- Which Programming Language Should You Learn To Get A Quant Developer Job?
- Top 5 Essential Books for Python Machine Learning
- Free Quantitative Finance Resources
- Top 10 Essential Resources for Learning Financial Econometrics
- Quantitative Finance Reading List
- Top 5 Essential Beginner C++ Books for Financial Engineers
- Top 5 Finite Difference Methods books for Quant Analysts
- 5 Top Books for Acing a Quantitative Analyst Interview
- 5 Important But Not So Common Books A Quant Should Read Before Applying for a Job
- Quant Reading List Python Programming
- Quant Reading List Numerical Methods
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