SC²S Colloquium - October 27, 2017
|Date:||October 27, 2017|
|Time:||3:00 pm, s.t.|
Jonas Bürger: A Monte Carlo approach for clustering uncertain data using sparse grids density estimation
Ingo Mayer: Analysis of sparse-grids-based financial time series prediction
This Bachelor's Thesis applies the delay embedding theorem on financial time series to forecast future values using sparse grids. Sparse grids reduce the impact of the curse of dimensionality and are therefore ideally suited for this regression task. The prediction is applied to the S&P 500 index as a good representative of the global capital market and to a selection of cryptographic currencies to determine the role of volatility in the forecast. For this purpose an automated pipeline was developed in Python, using the general sparse grid toolbox SG++.