65 points by datafreak 1 year ago flag hide 15 comments
john_doe 1 year ago next
Interesting approach! I've been working on similar projects and I find it fascinating that reinforcement learning can be applied to stock trading.
mike_rogers 1 year ago next
Absolutely, I agree. The implementation of reinforcement learning for stock trading has the potential to revolutionize current trading systems.
john_doe 1 year ago prev next
Thank you! I used a mixture of well-known tech stocks, as well as some lesser-known stocks to test the robustness of the reinforcement learning model.
sarah_smith 1 year ago prev next
What types of stocks did you use for your dataset? I'm considering doing something similar and wondered if you had any recommendations.
paul_lee 1 year ago next
I would recommend starting with a well-established algorithm like Q-learning before trying out other, more complex models. This helped me better understand the underlying principles.
mark_kim 1 year ago prev next
I'm curious to know more about the reinforcement learning algorithm used. Could you provide some details about the implementation?
mark_kim 1 year ago next
Thanks for the suggestion. I'll start with Q-learning and then move on to other algorithms like Deep Q Networks.
emily_wang 1 year ago prev next
I've heard that reinforcement learning can be quite sensitive to hyperparameters. How did you go about tuning your hyperparameters for the RL model?
joy_clark 1 year ago next
I couldn't agree more. I used a combination of random search with a grid search to fine-tune the hyperparameters of my reinforcement learning model. It was quite a time-consuming process but essential for better performance.
adam_johnson 1 year ago prev next
How did you handle the data preprocessing and feature selection for the stock trading dataset?
samantha_garcia 1 year ago next
I used some basic preprocessing, such as outlier detection and normalization. For feature selection, I looked at technical indicators and fundamental financial data to select the most important features for the model.
joseph_park 1 year ago prev next
This is really cool. I'm interested in exploring other applications of reinforcement learning beyond just stock trading. Got any ideas to share?
brittany_reed 1 year ago next
I think autonomous driving and chatbots are great examples of real-world applications of reinforcement learning. The challenges in these fields require creative approaches and complex solutions that RL can provide.
edward_nguyen 1 year ago prev next
Are there any libraries or frameworks that you used for implementing reinforcement learning? I'm new to the topic and looking for resources to learn from.
jacob_shaw 1 year ago next
I recommend looking into TensorFlow and Stable Baselines for RL implementations. TensorFlow's an open-source library that provides tools for deploying ML applications, and Stable Baselines offers many deep RL algorithms out of the box.