Quantitative Trading Strategies and Models

Yes, you will be awarded with a certification from QuantInsti after successfully completing the online learning units.

No, there are no live or classroom sessions in the course. You can ask your queries on community and get responses from fellow learners and faculty members.

Yes, you can ask your queries related to the course on the community: https://quantra.quantinsti.com/community

Fast-speed internet connection and a browser application are required for this course. For best experience, use Chrome.

There is no admission criterion. You are recommended to go through the prerequisites section and be aware of skill sets gained and required to learn most from the course.

We respect your time, and hence, we offer concise but effective short-term courses created under professional guidance. We try to offer the most value within the shortest time. There are a few courses on Quantra which are free of cost. Please check the price of the course before enrolling in it. Once a purchase is made, we offer complete course content. For paid courses, we follow a 'no refund' policy.

Some of the course material is downloadable such as Python notebooks with strategy codes. We also guide you how to use these codes on your own system to practice further.

We focus on teaching these quantitative and machine learning techniques and how learners can use them for developing their own strategies. You may or may not be able to directly use them in your own system. Please do note that we are not advising or offering any trading/investment services. The strategies are used for learning & understanding purposes and we don't take any responsibility for the performance or any profit or losses that using these techniques results in.

Quantra environment is a zero-installation solution to get beginners to start off with coding in Python. While learning you won't have to download or install anything! However, if you wish to later implement the learning on your system, you can definitely do that. All the notebooks in the Quantra portal are available for download at the end of each course and they can be run in the local system just the same as they run in the portal. The user can modify/tweak/rework all such code files as per his need. We encourage you to implement different concepts learnt from different learning tracks into your trading strategy to make it more suited to the real-world scenario.

No. We provide you guidance on how to create strategy using different techniques and indicators, but no strategy is plug and play. A lot of effort is required to backtest any strategy, after which we fine-tune the strategy parameters and see the performance on paper trading before we finally implement the live execution of trades.

You can learn with or without coding knowledge. If you would like to do the analysis on excel, we would suggest you to start with course on Statistical Arbitrage in Trading. You can create and test your trading strategies using excel.

Alternatively, you can do the course on Python for Trading which will help you gain knowledge in all these fields: Python, Analysis and Financial markets.

Lifetime access means that once you enroll in the course, you will have unlimited access to all course materials, including videos, resources, readings, and other learning materials for as long as the course remains available online. There are no time limits or expiration dates on your access, allowing you to learn at your own pace and revisit the content whenever you need it, even after you've completed the course. It's important to note that "lifetime" refers to the lifetime of the course itself—if the platform or course is discontinued for any reason, we will inform you in advance. This will allow you enough time to download or access any course materials you need for future use.

The primary advantage of quantitative trading is that it allows a trader to effectively test his strategy on a lot more securities than a manual trader.

This is because computer algorithms are used to do the heavy lifting in terms of finding patterns, backtesting historical data and classifying results in buy or sell signals. Add to this the fact that the calculations are correct and mistakes are eliminated (such as fat finger errors), making quantitative trading far superior to manual trading.

Another advantage of quantitative trading is that if it is implemented in live markets, it will be faster than manual traders as the time it takes for a manual trader to place the order is in seconds at best, while quantitative trading operates in milliseconds.

Most of the popular quantitative trading strategies are:

Mean reverting strategies: The logic is that if we plot the prices of a stock for a long period of time, we can say that the price doesn't stray far from the mean. Thus, if the stock price falls sharply, we can say with a fair amount of certainty that it will bounce back

Trend following strategy: In this strategy, we analyse stocks to find a trend in the prices and follow that trend, i.e. going long on a bull trend or going short on a bear trend

Pairs trading strategy: We try to find a pair of stocks which are correlated and if we see one of those stocks falling then we would short the outperforming stock and go long on the underperforming stock

Statistical Arbitrage (or Stat Arb): It is based on the statistical mispricing of one or more assets compared to the expected future value of these assets. Statistical Arbitrage is a computational and quantitative approach to trading