Background When you make a forex transaction, you sell one currency and buy another. If
the currency you buy increases against the currency you sell, you profit, and you do this …

Foreign exchange (Forex) rate forecasting is presently pursued by many researchers as it
plays an important role in financial technology and business. The challenge of Forex …

Since it is one of the world's most significant financial markets, the foreign exchange (Forex)
market has attracted a large number of investors. Accurately anticipating the forex trend has …

This paper describes the use of long short-term memory (LSTM) for session-based
recommendations. This paper aims to test and propose the best solution using word-level …

This paper is a review of studies that have been published related to the forecasting and
modeling of foreign exchange (forex) price movements or exchange rate since 2000. The …

The use of long short-term memory (LSTM) for session-based recommendations is
described in this research. This study uses char-level LSTM as a real-time recommendation …

Purpose: This study aims to predict the closing price of the EUR/JPY currency pair in the
forex market using recurrent neural network (RNN) architectures, namely Long Short-Term …

We employ a recurrent neural network with Long short-term memory for the task of stock
price forecasting. We chose three stocks from the same sub-industry: Visa, Mastercard, and …

Predicting currency exchange rates, particularly for major currencies such as USD and EUR,
poses considerable difficulty owing to the complex nature of financial temporal data. This …

The Autoencoder method can be used for multiple scenarios, as it is very variable. In this
case, the method is used for suggesting actions. This paper describes the theoretical …