188 points by mlstockforecast 6 months ago flag hide 14 comments
johnsmith 6 months ago next
Fascinating article. I've been researching ML applied to finance and this is really promising. I wonder how much of the success ratio and error margin there is.
codewiz 6 months ago next
I agree! I've seen some models boast up to 80% success rate. However, the risk is that when it fails, it can be costly. https://example.com/ML_fallibility
masterprogrammer 6 months ago prev next
Machine learning is impressive, but we can't ignore the role of human emotions in stock price fluctuations. Any thoughts on blending ML with behavioral economics?
janeche 6 months ago next
There are some interesting projects trying to bridge that gap. A hybrid model might help to minimize the impact of unexpected market shifts. https://example.com/hybrid_model
quantjake 6 months ago prev next
The key to stock prediction would be granular real-time data. Do you know of any data sources that offer this level of detail without massive overhead costs?
moredata 6 months ago next
Some data providers have APIs tailored to financial ML models, with costs varying depending on data frequency. You might want to check out: - https://example.com/realtime_data_api - https://example.com/alternate_data
deeplearner 6 months ago prev next
I'm curious whether anyone has tried using reinforcement learning for stock price prediction?
rlrocks 6 months ago next
There's some early research on this, but it's challenging to balance between exploration and exploitation in such a dynamic environment. Still promising, though! https://example.com/RL_finance
gofast 6 months ago prev next
How would backtesting work with machine learning models? It's important to avoid p-hacking.
backtester 6 months ago next
You're right. Best practice is to split your data into test, training, and validation sets, and ensure the model doesn't suffer from overfitting. Cross-validation is also a good technique. https://example.com/backtesting_ML
precision 6 months ago prev next
I'm worried about regulatory compliance when applying ML to the financial sector. Thoughts?
compliance_guru 6 months ago next
Indeed, regulatory bodies are paying more attention to AI in finance. Make sure you document your model thoroughly and consult with legal experts before deploying any solution. https://example.com/AI_finance_regulations
dataanalyst 6 months ago prev next
The use of cutting-edge technology like ML in finance can provide an excellent opportunity for business innovation. Have you considered the potential for creating new revenue streams and serving untapped market segments?
futurefinance 6 months ago prev next
Many organizations are exploring these very opportunities and more. It's an exciting time to be involved in the financial sector. https://example.com/fintech_innovation