Abstract:
"
Forex (foreign exchange) is a unique financial industry in the financial world,
with high risks and great return possibilities for traders. The market is also very
simple, with traders able to profit simply by accurately predicting the direction of
two currencies’ exchange rates. In comparison to other traditional financial mar kets, incorrect projections in the FX market can lead to far greater losses. This
problem differs from more typical forms of time-series forecasting challenges in
that it requires direction prediction. I used deep learning to create direction fore casts in the Forex market using a well-known deep learning approach known as
""long short-term memory"" (LSTM), which has been shown to be very successful
in many time-series forecasting problems"
