文档介绍：Submitted to European Journal of Finance
Intra-day Trading of the FTSE-100 Futures Contract
Using works With Wavelet Encodings
D L Toulson
S P Toulson∗
Intelligent Financial Systems Limited
Suite Greener House
66-69 Haymarket
London SW1Y 4RF
SW1Y 4RF
Tel: (020) 7839 1863
Email: ifs@
* Please send correspondence and proofs to this author.
Intra-day Trading of the FTSE-100 Futures Contract
Using works With Wavelet Encodings
ABSTRACT
In this paper, we shall examine bined use of the Discrete Wavelet Transform and
regularised works to predict intra-day returns of the FTSE-100 index future. The
Discrete Wavelet Transform (DWT) has recently been used extensively in a number of
signal processing applications. The manner in which the DWT is most often applied to
classification / regression problems is as a pre-processing step, transforming the original
signal to a (hopefully) pact and meaningful representation. The choice of the
particular basis functions (or child wavelets) to use in the transform is often based either
on some pre-set sampling strategy or on a priori heuristics about the scale and position of
the information likely to be most relevant to the task being performed.
In this work, we propose the use of a specialised work architecture (WEAPON)
that includes within it a layer of wavelet neurons. These wavelet neurons serve to
implement an initial wavelet transformation of the input signal, which in this case, will be a
set of lagged returns from the FTSE-100 future. We derive a learning rule for the WEAPON
architecture that allows the dilations and positions of the wavelet nodes to be determined
as part of the standard back-propagation of error algorithm. This ensures that the child
wavelets used in the transform are optimal in terms of providing the best discriminatory
information for the prediction task.
We then focus on a