Hey Dev Community! 👋

I wanted to share an interesting project I’ve been working on lately as a financial advisor with a focus on trading and market analysis. As we all know, making data-driven decisions is key to success in both trading and advising clients, so I’ve been diving deep into financial data and using machine learning models to enhance my trading strategies. 📊

Here’s a brief breakdown of what I’ve been doing:

Data Collection: I’ve been gathering historical price data, sentiment analysis from news sources, and social media trends to build a more holistic view of market movements. (I use APIs like Alpha Vantage and Quandell for this.)

Modeling: I’m using Python and Pandas for cleaning and analyzing the data, and scikit-learn to build prediction models. The goal is to spot patterns that can help forecast short-term price movements in Forex and crypto markets.

Backtesting: To ensure my models are reliable, I’m backtesting them using past data and comparing their predictions against actual market outcomes. This step has been crucial in refining my approach.

Automation: I'm also exploring ways to automate some of my processes using algorithmic trading and building a few auto-trading bots that can execute trades based on model predictions in real-time.

The results so far? Not groundbreaking, but certainly progressive—I’ve been able to identify key indicators that can make a difference in volatility-driven markets, like cryptos.

My next step is to move into real-time trading environments and use data analytics to make more strategic decisions in the financial markets. 🚀

Would love to hear your thoughts:

Are any of you also integrating data science into your trading or financial advising?
What tools or models have you found helpful in analyzing market data?
Any tips on optimizing trading strategies?
Looking forward to learning from all of you!