Economy USD/JPY Pred Modeling ipynb
from alpha_vantage.timeseries import TimeSeries import pandas as pd import matplotlib.pyplot as plt from sklearn.linear_...
Technology
カテゴリ "Technology"：7件
Economy 
Economy Three-value classification(USDJPY) – Preparation, Learning, Importances
Estimate USDJPY after 1 day based on 10 years of data by using scikit-learn # import libraries import pandas as pd impor...
Economy Forex Forecasting with Random Forests – 1/N Preproccesing
# Import libraries import numpy as np import pandas as pd import datetime as dt from sklearn.model_selection import trai...
Economy Forex Forecasting with Random Forests 2/N – Technical indicators
## Feature creation/processing #- Addition of technical indicators #- Creation of statistics that may be valid for each ...
Economy Forex Forecasting with Random Forests 3/N – Modeling and tuning
# # Create model with best params seed = 17 model = RandomForestClassifier(**best_param, random_state=seed) model.fit(X_...
Economy Forex Forecasting with Random Forests 4/N – Precision Rating
### Trade Simulation def trade_simulation(dfx,leverage,start_balance): i = 0 for index,item in dfx.iterrows(): # Margin ...
Economy Forex Forecasting with Random Forests /ALL – Back/forward test and importances
### Back test # Leverage multiple leverage = 25 # Balance at start start_balance = 1000000 # Profit and loss calculation...