PCAapplied_and_European_Yield_Curve

This paper aims to explore the time series’ proprieties of the features extracted by using the Principal Component Analysis (PCA) technique on the European AAA-rated Government Bond Yield curve. The PCA can greatly simplify the problem of modelling the yield curve by massively reducing its dimensionality to a small set of uncorrelated features. It finds several applications in finance and in the fixed income particularly from risk management to trade recommendation. After selecting a subset of Principal Components (PCs), this paper first analyzes their nature in comparison to the original rates and the implications in terms of information retained and lost. Then the time-series characteristics of each PC are studied and, when possible, Auto-Regressive Moving-Average (ARMA) models will be fitted on the data. One hundred observations of the original dataset are set aside as a test set to evaluate the predictive power of these models. Eventually, further analyses are performed on the PCs to evaluate the presence of heteroscedasticity and GARCH-ARCH models are fitted when possible. Tests are performed on the fitted coefficient to investigate the real nature of the conditional variance process.

Recession_in_the_USA_Chapter_II

Forecasting_a_Recession_in_the_USA_Chapter_I

Closet_Index_Tracking

Closet Index Tracking (or Closet Indexing and Index Hugging) relates to the practice of a fund manager claiming to actively manage an investment portfolio when in reality the fund closely tracks an index. This paper explores the problem of identifying a Closet Index Tracker Fund. This paper first provides a general overview of the regulatory background and the challenges it poses. Then it moves to analyse a set of funds investing in European Large capitalization Equities according to Morningstar’s classification. After calculating a set of statistics on these funds against a set of indices, the paper outlines a procedure to spot potential passive tracker funds relying on clustering unsupervised machine learning algorithms

Forecasting_a_Recession_in_the_USA_Chapter_I

Forecasting a Recession in the USA