Crypto Trading Strategies: Advanced

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.

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 Hurst exponent is a statistical tool used to measure a long-term memory of time series. It relates to the autocorrelations of the time series and the rate at which these decrease as the lag between pairs of values increases. The value of Hurst exponent (H) lies between 0 and 1. H = 0.5 indicates a random walk where the prediction of the future based on past data is not possible. 0 < H < 0.5 indicates an anti-persistent series which has a characteristic of mean-reverting. 0.5 < H < 1 shows a persistent series which translates to trending behaviour.
Refer to Section 5 and 6 of Crypto Trading Strategies: Advanced course for a trading strategy based on Hurst exponent.

It is the use of mathematical and quantitative models to test hypothesis and make decisions about buying or selling cryptocurrencies. This method relies on data and statistics to predict market trends.

Strategies including arbitrage, mean reversion, anomaly detection and hypothesis testing are strategies which use models to find differences or patterns in the market. These require technical skills and detailed knowledge of the market behavious, which can be learned.

Cryptocurrency trading is often characterised by high volatility and sudden price changes is a big risk. Along with that, as cryptocurrency is built on a technology, you might face technical issues and security breaches, which can lead to significant losses.

Yes, AI can be used to analyse large amounts of data and identify trends, making it useful for automating trading decisions. However, while it can improve decision-making, it does not eliminate the risks inherent in the market.