k-NN Based Forecast of Short-Term Foreign Exchange Rates

Author(s):  
Haruya Umemoto ◽  
Tetsuya Toyota ◽  
Kouzou Ohara
Author(s):  
Leong-Kwan Li ◽  
Wan-Kai Pang ◽  
Wing-Tong Yu ◽  
Marvin D. Troutt

Movements in foreign exchange rates are the results of collective human decisions, which are the results of the dynamics of their neurons. In this chapter, we demonstrate how to model these types of market behaviors by recurrent neural networks (RNN). The RNN approach can help us to forecast the short-term trend of foreign exchange rates. The application of forecasting techniques in the foreign exchange markets has become an important task in financial strategy. Our empirical results show that a discrete-time RNN performs better than the traditional methods in forecasting short-term foreign exchange rates.


Author(s):  
Vasily Derbentsev ◽  
◽  
Vitalii Bezkorovainyi ◽  
Andrey Ovcharenko ◽  
◽  
...  

2014 ◽  
pp. 74-89 ◽  
Author(s):  
Vinh Vo Xuan

This paper investigates factors affecting Vietnam’s stock prices including US stock prices, foreign exchange rates, gold prices and crude oil prices. Using the daily data from 2005 to 2012, the results indicate that Vietnam’s stock prices are influenced by crude oil prices. In addition, Vietnam’s stock prices are also affected significantly by US stock prices, and foreign exchange rates over the period before the 2008 Global Financial Crisis. There is evidence that Vietnam’s stock prices are highly correlated with US stock prices, foreign exchange rates and gold prices for the same period. Furthermore, Vietnam’s stock prices were cointegrated with US stock prices both before and after the crisis, and with foreign exchange rates, gold prices and crude oil prices only during and after the crisis.


Sign in / Sign up

Export Citation Format

Share Document