Bachelorarbeit – Banking and Finance
Predicting Financial Times Series in the Short Run With Echo State Networks (ESNs) GRADUATE Simon Blum SUPERVISOR Dr. Simon Rentzmann
Financial time series forecasting in stock and foreign ex
The MATLAB simulations trading results of MT with the
change markets has attracted the attention of investors,
broker FXCM were used to deliver commonly used perfor
speculators, and researchers over recent decades due to
mance metrics trading profits, including all transaction
its enormous potential returns. Various advances in ana
costs and spreads. The timeframe resolution for the ESN
lytical and computational procedures have led to a number
time series is usually one day with a one-step ahead pre
of promising new approaches to financial time series min
diction. This paper investigates, in contrast, a higher time
ing, based on nonlinear and nonstationary models. Among
frame resolution – one hour with a one-step ahead fore
an expanding variety of methods, artificial neural networks
cast.
are the most widely used models to analyze and handle stochastic and nonlinear systems. Financial time series are
The findings confirm that simulations tend to overfit and
widely known as chaotic, nonstationary, and difficult to
lead to poor outcomes in terms of profits and winning
predict, which in fact lies within the scope of neural net
trade ratios. It was possible, however, to tune the entry
works.
parameters and adjust the settings manually to avoid over fitting, which gives better results.
This Bachelor’s thesis presents a study of a novel recurrent neural network – the Echo State Network (ESN) – to pre
It could, therefore, be shown that ESN can be applied to
dict the next closing price in foreign exchange markets.
foreign exchange markets successfully and that it can pro
The main purpose of this paper was to verify whether ESN
vide important forecasts in the short run. In this context,
could be used as a prediction model for the foreign ex
ESN is a state-of-the-art prediction model in forecasting
change market in the short run.
financial time series with a higher resolution in certain time frames, as well as having still great potential in terms of
A review of the current state of the literature revealed
developing the network structure.
agreement among researchers concerning the predictive power of Echo State Networks in the financial domain and yielded a selection of the most relevant applications to stock and foreign exchange markets. The thesis suggests various improvements to the base model provided by Her bert Jaeger. New in this field of research is the direct linking of the ESN to a trading account of a large foreign exchange (FOREX) and contract for difference (CFD) broker through METATRADER (MT) and MATLAB. This relationship is de scribed in detail and used to evaluate the prediction accu racy and performance of the ESN.
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