Exchange Rate Forecasting Using Machine learning: Explore Gains From External Information

2021 ◽  
Author(s):  
Zhenlin Liang ◽  
Xiang Li
2021 ◽  
Vol 67 (3) ◽  
pp. 3451-3461
Author(s):  
Samreen Naeem ◽  
Wali Khan Mashwani ◽  
Aqib Ali ◽  
M. Irfan Uddin ◽  
Marwan Mahmoud ◽  
...  

2021 ◽  
Vol 15 (1) ◽  
pp. 2
Author(s):  
Jonathan Felix Pfahler

Historically, exchange rate forecasting models have exhibited poor out-of-sample performances and were inferior to the random walk model. Monthly panel data from 1973 to 2014 for ten currency pairs of OECD countries are used to make out-of sample forecasts with artificial neural networks and XGBoost models. Most approaches show significant and substantial predictive power in directional forecasts. Moreover, the evidence suggests that information regarding prediction timing is a key component in the forecasting performance.


1992 ◽  
Vol 8 (1) ◽  
pp. 116-117
Author(s):  
David Stallings

2012 ◽  
Vol 42 (4) ◽  
pp. 415-431 ◽  
Author(s):  
Georgios A. Vasilakis ◽  
Konstantinos A. Theofilatos ◽  
Efstratios F. Georgopoulos ◽  
Andreas Karathanasopoulos ◽  
Spiros D. Likothanassis

2021 ◽  
Vol 3 (3) ◽  
pp. 31-44
Author(s):  
Nenubari Ikue John ◽  
Emeka Nkoro ◽  
Jeremiah Anietie

There is a pool of techniques and methods in addressing dynamics behaviors in higher frequency data, prominent among them is the ARCH/GARCH techniques. In this paper, the various types and assumptions of the ARCH/GARCH models were tried in examining the dynamism of exchange rate and international crude oil prices in Nigeria. And it was observed that the Nigerian foreign exchange rates behaviors did not conform with the assumptions of the ARCH/GARCH models, hence this paper adopted Lag Variables Autoregressive (LVAR) techniques originally developed by Agung and Heij multiplier to examine the dynamic response of the Nigerian foreign exchange rates to crude oil prices. The Heij coefficient was used to calculate the dynamic multipliers while the Engel & Granger two-step technique was used for cointegration analysis.  The results revealed an insignificant dynamic long-term response of the exchange rate to crude oil prices within the periods under review. The coefficient of dynamism was insignificantly in most cases of the sub-periods. The paper equally revealed that the significance of the dynamic multipliers depends greatly on external information about both market indicators which are two-way interactions. Thus, the paper recommends periodic intervention in the foreign exchange market by the monetary authorities to stabilize the market against any shocks in the international crude oil market, since crude oil is the main source of foreign exchange in Nigeria.


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