Part 1: Data Collection
• Technical historical (price, volume, OHLC changed percentage)
• Technical Indicators (MA, MACD, Momentum, CCI, RSI, …)
• Fundamental data (Key ratios, finance statement)
• Macroeconomics ratios (GDP, CPI, Job, Interest rate, …)
• Sentiment data (Google news, Social networks)
Part 2: Data Preprocessing
• Dummy variables
• Concatenate data frames
• Missing data
• Scaling data
• Feature processing using ensemble feature selection
o Increase the dimension
o Reduce the dimension
o Avoid overfitting
o Select the optimal feature selection. Since then we also find out some strategies (Decision tree/Association Rules, etc.
Part 3: Machine Leaning and DL Models
1. ML model
• Random Forest
• Deep Learning (LTSM,HTM, Tensorfow, etc)
Part 4: Portfolio Construction/Optimization
• Portfolio Combination and permutation
• Portfolio Allocation
• Portfolio Optimization
Part 5: Backtest
Require freelancer have experienced in Quantitative Trading.
Prefer Academic professional in Quants/Machine Learning in Finance
If you are confident please inbox direct to me.
29 freelancers are bidding on average $618 for this job
Hi, I am an expert in machine learning and stock prediction. I am very familiar with Regression, KNN, Random Forest, SVM, ANN and Deep Learning. I can do your project perfectly. Thanks.