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Exploring the effect of COVID-19 fatality rates on the Foreign Exchange Spot Price of a currency pair (GBP/USD) through shallow and deep learning neural networks
How to use:
Open each file using google colab
Each model will let you know what datasets to import before running the model
Limitations: The fuel_prices_com.csv file was donated by GlobalPetrolPrices.com for this study therefore this will not be included in this repository however this dataset can be purchased on their website.
1. Experiments
Shrinkage Models:
Simple Linear Regression
Ridge Regression
Lasso Regression
ElasticNet Regression
Ensemble Regression:
Simple Linear Regression
Support Vector Regression
Random Forest Regression
Gradient Boosting
Additional SMA/SLR (Unreported):
Simple Moving Average (SMA) model
Simple Linear Regression model
2. Correlation:
Correlation
Variance Inflation Factor
3. SLR
SLR/MLR:
Model 1: Simple Linear Regression (Spot Price)
Model 2: Simple Linear Regression (COVID-19 -> Diesel)
Model 3: Simple Linear Regression (Diesel -> Forex Spot Price)
Model 4: Multi-Linear Regression (All data i.e. COVID-19, Diesel & Forex Spot Price -> Forex Spot Price)
Additional (Unreported):
Simple Linear Regression (COVID-19 Deaths)
4. LSTM
LSTM Models:
Model 1: Univariate LSTM (Spot Price)
Model 2: Multivariate LSTM (COVID-19 -> Diesel)
Model 3: Multivariate LSTM (Diesel -> Forex Spot Price)
Model 4: Multivariate LSTM (All data i.e. COVID-19, Diesel & Forex Spot Price -> Forex Spot Price)
Additional (Unreported):
Univariate LSTM (COVID-19 Deaths)
5. CNN
CNN Models:
Model 1: Univariate CNN (Spot Price)
Model 2: Multivariate CNN (COVID-19 -> Diesel)
Model 3: Multivariate CNN (Diesel -> Forex Spot Price)
Model 4: Multivariate CNN (All data i.e. COVID-19, Diesel & Forex Spot Price -> Forex Spot Price)
Additional (Unreported):
Univariate CNN (COVID-19 Deaths)
About
Exploring the effect of COVID-19 fatality rates on the Foreign Exchange Spot Price of a currency pair (GBP/USD) using shallow and deep learning neural networks. Technologies used: Google Colab, Jupyter Notebook, Python, Scikit-learn, Tensorflow, Pandas, Keras, Numpy & Matplotlib.
