Hi to all, sending the next questons that I sent to sales mail with any answer, is it possible to get some help?
I hope this email finds you well. I am interested in the: Deep Reinforcement Learning Trading course offered at Quantra by QuantInsti | Courses on Algorithmic and Quantitative Trading and have a few questions regarding its content and capstone project:
- Could you provide information about the next set of questions in the course?
- Is it possible to run the capstone project in Google Colab using a GPU 100 or GPU L4?
- Does the capstone project demonstrate positive results in terms of PnL or Sharpe Ratio?
- Does the project utilize real market data or synthetic data? If real, does it cover stocks, Forex, or crypto?
- Does the provided code include an option to avoid being in the market at all times? Specifically, can it:
- Open a ong trade,
- Close the long trade and wait for the next opportunity,
- Avoid closing a long position by opening a short trade?
- When was the codebase created? Does it incorporate recent reinforcement learning algorithms, or does it rely on models from previous years?
- Does the project rely solely on public Python libraries, or does it use proprietary libraries from Quantra that require a key/password for access?
I would appreciate your insights on these queries and any additional details you can provide.
Looking forward to your response.
Alejandro Holguin M
