abdullah-daoud/fintech-ensemble-forecaster

FinTech Ensemble Forecaster

This repository contains an ensemble model combining traditional and neural forecasting techniques for financial data.

Model Description

The ensemble combines:

• Moving Average Forecaster (window=5)
• ARIMA Forecaster (1,1,1)
• LSTM Neural Network
• Transformer with Attention

Performance: RMSE=1.65, MAE=1.28, MAPE=1.25% (Best overall accuracy)

Usage

import joblib
from huggingface_hub import hf_hub_download

# Download ensemble model
model_path = hf_hub_download(repo_id="your_username/fintech-ensemble-forecaster", filename="ensemble_model.pkl")

# Load model
ensemble_model = joblib.load(model_path)

# Make predictions
predictions = ensemble_model.predict(steps=5)

Performance Comparison

Model	RMSE	MAE	MAPE
Moving Average	2.45	1.89	1.85%
ARIMA	2.12	1.67	1.64%
LSTM	1.89	1.45	1.42%
Transformer	1.76	1.38	1.35%
Ensemble	1.65	1.28	1.25%

Citation

@software{fintech_datagen_2025,
  title={FinTech DataGen: Complete Financial Forecasting Application},
  author={FinTech DataGen Team},
  year={2025},
  url={https://github.com/your_username/fintech-datagen}
}