Quantitative Portfolio Management

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.

What is a capstone project?

A capstone project is a multi-faceted hands-on project that lets you apply what you\'ve learned in an advanced course. This project is relevant to how the concepts are applied in real-world scenarios and helps to cement your understanding of the concepts.

Who will review my work?

Since the capstone project involves trading on real-world assets, the best measure for performance is the profitability and the performance metrics like the Sharpe ratio, drawdown, etc. There is no formal or peer review and you can refer to the model solution at the end of this section.

Will I get a solution for the above project?

We have provided a model solution to help you understand how to get things working. The input features or the hyperparameters can all be changed, added, or removed as per your need.

What to do if I\'m stuck?

If you get stuck, we encourage you to view the model solution and compare it with your solution to see what went wrong. If you still need help, feel free to reach out to us via the community forum and we will be happy to help you!

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.

Whenever you create a portfolio, you should know about the risk and reward size. Common knowledge dictates that risk should be lower, and reward should be highest. But given the fact that there are more than a thousand stocks listed on NYSE alone, we need a mechanism to select the securities in an efficient manner. We should also have an idea about the price movement of securities so that we can invest with logic. In this scenario, we can say that the key elements of portfolio management are:

Capital allocation: Kelly's criterion, Modern portfolio theory and Risk parity are a few of the methods used to evaluate the asset mix and make sure the portfolio is optimally balanced.

Diversification: While it is really difficult to predict the winners on a consistent basis, diversification helps us cast a wide net to be able to reap more rewards.

Periodic assessment: Initially, we keep a certain percentage in mind while investing in different securities. After a few months, this mix could be altered due to our portfolio optimisation. Thus, it is important to analyse the portfolio on a periodic basis to make sure our risk exposure is according to our expectations.

Quantitative portfolio management involves using quantitative techniques to calculate the risk and variance as well as construct models to optimise the portfolio according to the investor’s risk profile.

The advantage of quantitative techniques is that we can create a strategy and include a much larger universe of stocks in our analysis than was previously possible. It also helps us compute faster and arrive at results which are far more accurate and precise than traditional portfolio management.