Cross currency basis swap is a floating/floating swap through which two counterparties exchange different currencies. The EURUSD basis has been negative and more volatile since 2008. This project tries to predict the changes of 2y EURUSD basis by determining effective features. See the proposal.
Changes of basis during period t-1
US Dollar Index published by Bloomberg which indicates the dollar strength in the spot FX market
Reverse Yankee issuance which is the Euro debt issued by US companies
USD LIBOR/OIS spread which indicates credit risk
CME global volatility index (VIX)
ted spread (3m US libor-3m treasury yield)
BAML GFSI Solvency Component which indicates global solvency risk
Try KNN/logistic/SVM/RandomForest/bagging/AdaBoost to choose a better model.
It’s a dataset of 2 year EURUSD basis and its possible contributors.
Include data of changes of basis, Bloomberg US Dollar index, CME global volatility index, ted spread (3m US libor-3m treasury yield), overnight libor/ois spread, American corporates’ issuance of Euro bonds and BAML GFSI Solvency Component.
There are respectively weekly data(622 samples) and daily data(2974 samples) from 2005/4/26 to 2017/4/10.
There is no obvious difference in test accuracies(between 0.5 and 0.6) among different algorithms and between different data frequencies(daily and weekly). however, CV accuracies' standard deviations are smaller when using daily data.