Currency Forecasting using Multiple Kernel Learning with Financially Motivated Features

Details Currency Forecasting using Multiple Kernel Learning with Financially Motivated Features Currency Forecasting using Multiple Kernel Learning with Financially Motivated Features

2010-11-28

arxiv.org/abs/1011.6097v1

Economy

Quantitative Finance

Statistical Finance

To be presented at NIPS 2010 workshop: New Directions in Multiple Kernel Learning

Scientific paper

Multiple Kernel Learning (MKL) is used to replicate the signal combination process that trading rules embody when they aggregate multiple sources of financial information when predicting an asset's price movements. A set of financially motivated kernels is constructed for the EURUSD currency pair and is used to predict the direction of price movement for the currency over multiple time horizons. MKL is shown to outperform each of the kernels individually in terms of predictive accuracy. Furthermore, the kernel weightings selected by MKL highlights which of the financial features represented by the kernels are the most informative for predictive tasks.

Affiliated with

Also associated with

No associations

Rating

Currency Forecasting using Multiple Kernel Learning with Financially Motivated Features does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Currency Forecasting using Multiple Kernel Learning with Financially Motivated Features, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Currency Forecasting using Multiple Kernel Learning with Financially Motivated Features will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-219942