Forward Exchange Rate Biasedness Across Developed and Developing Country Currencies: Do Observed Patterns Persist Out of Sample?

2012 ◽  
Author(s):  
Brian M. Lucey ◽  
Grace Loring
Keyword(s):  
Exchange Rate ◽  
Developing Country ◽  
Out Of Sample

Liberal development, 1925–46

2017 ◽  
Author(s):  
John Toye
Keyword(s):  
Developing Countries ◽  
Economic Development ◽  
Exchange Rate ◽  
Developing Country ◽  
Trade Protection ◽  
Communist Country ◽  
Economic Policies ◽  
Government Finance ◽  
Soviet Government ◽  
Experimental Economic

Keynes’s writings are often disregarded in the context of economic development, overlooking that Russia was a developing country in his lifetime. He wrote about the experimental economic techniques that the Soviet government employed. He visited Russia three times and wrote A Short View of Russia in which he explained and criticized Bolsheviks’ policy of export and import monopolies, an overvalued exchange rate, inflationary government finance, and the subsidization of industry. These were policies that many developing countries adopted after decolonization. Keynes’s conclusion was that they were inefficient and that ‘bourgeois economics was valid in a communist country’. Did Keynes change his mind in the 1930s? If anything, he grew more harshly critical of Soviet economic policies and carefully distinguished them from his own endorsement of moderate trade protection and government supplementary investment in times of depression.

scholarly journals Modeling and Predictability of Exchange Rate Changes by the Extended Relative Nelson–Siegel Class of Models

2018 ◽  
Vol 6 (3) ◽  
pp. 68
Author(s):  
Hokuto Ishii
Keyword(s):  
Exchange Rate ◽  
Prediction Accuracy ◽  
Factor Model ◽  
Five Factor Model ◽  
Model Fitting ◽  
Extended Model ◽  
Out Of Sample ◽  
Exchange Rate Changes ◽  
Relative Spread ◽  
Future Exchange

This paper investigates the predictability of exchange rate changes by extracting the factors from the three-, four-, and five-factor model of the relative Nelson–Siegel class. Our empirical analysis shows that the relative spread factors are important for predicting future exchange rate changes, and our extended model improves the model fitting statistically. The regression model based on the three-factor relative Nelson–Siegel model is the superior model of the extended models for three-month-ahead out-of-sample predictions, and the prediction accuracy is statistically significant from the perspective of the Clark and West statistic. For 6- and 12-month-ahead predictions, although the five-factor model is superior to the other models, the prediction accuracy is not statistically significant.

PALM OIL PRICE–EXCHANGE RATE NEXUS IN INDONESIA AND MALAYSIA

2021 ◽  
Vol 24 (2) ◽  
pp. 169-180
Author(s):  
Afees Salisu ◽  
Abdulsalam Abidemi Sikiru
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Palm Oil ◽  
Commodity Prices ◽  
Oil Price ◽  
Future Research ◽  
Daily Data ◽  
Out Of Sample ◽  
Exchange Rate Movements ◽  
Predictive Content

In this study, we extend the literature analyzing the predictive content of commodity prices for exchange rates by examining the role of palm oil price. Our analysis focuses on Indonesia and Malaysia, the two top producers and exporters of palm oil, and utilizes daily data covering the period from December 12, 2011 to March 29, 2021, which is partitioned into two sub-samples based on the COVID-19 pandemic. Relying on a methodology that accommodates some salient features of the variables of interest, we find that on average the in-sample predictability of palm oil price for exchange rate movements is stronger for Indonesia than for Malaysia. While Indonesia’s exchange rate appreciates due to a rise in palm oil price regardless of the choice of predictive model, Malaysia’s exchange rate only appreciates after adjusting for oil price. However, both exchange rates do not seem to be resilient to the COVID-19 pandemic as they depreciate amidst dwindling palm oil price. Similar outcomes are observed for the out-of-sample predictability analysis. We highlight avenues for future research and the implications of our results for portfolio diversification strategies.

scholarly journals The Predictability of the Exchange Rate When Combining Machine Learning and Fundamental Models

2020 ◽  
Vol 13 (3) ◽  
pp. 48 ◽  
Author(s):  
Yuchen Zhang ◽  
Shigeyuki Hamori
Keyword(s):  
Machine Learning ◽  
Exchange Rate ◽  
Random Walk ◽  
Exchange Rates ◽  
Price Index ◽  
Economic Models ◽  
Superior Performance ◽  
Support Vector ◽  
Out Of Sample ◽  
Modern Machine

In 1983, Meese and Rogoff showed that traditional economic models developed since the 1970s do not perform better than the random walk in predicting out-of-sample exchange rates when using data obtained after the beginning of the floating rate system. Subsequently, whether traditional economical models can ever outperform the random walk in forecasting out-of-sample exchange rates has received scholarly attention. Recently, a combination of fundamental models with machine learning methodologies was found to outcompete the predictability of random walk (Amat et al. 2018). This paper focuses on combining modern machine learning methodologies with traditional economic models and examines whether such combinations can outperform the prediction performance of random walk without drift. More specifically, this paper applies the random forest, support vector machine, and neural network models to four fundamental theories (uncovered interest rate parity, purchase power parity, the monetary model, and the Taylor rule models). We performed a thorough robustness check using six government bonds with different maturities and four price indexes, which demonstrated the superior performance of fundamental models combined with modern machine learning in predicting future exchange rates in comparison with the results of random walk. These results were examined using a root mean squared error (RMSE) and a Diebold–Mariano (DM) test. The main findings are as follows. First, when comparing the performance of fundamental models combined with machine learning with the performance of random walk, the RMSE results show that the fundamental models with machine learning outperform the random walk. In the DM test, the results are mixed as most of the results show significantly different predictive accuracies compared with the random walk. Second, when comparing the performance of fundamental models combined with machine learning, the models using the producer price index (PPI) consistently show good predictability. Meanwhile, the consumer price index (CPI) appears to be comparatively poor in predicting exchange rate, based on its poor results in the RMSE test and the DM test.

Policy shocks, current account and the macroeconomy in a developing country

2019 ◽  
Vol 46 (3) ◽  
pp. 710-726
Author(s):  
Moumita Basu ◽  
Ranjanendra Narayan Nag
Keyword(s):  
Exchange Rate ◽  
Developing Country ◽  
Foreign Exchange ◽  
Current Account ◽  
Current Account Balance ◽  
Foreign Exchange Reserves ◽  
Effective Demand ◽  
Content Type ◽  
Traded Goods ◽  
The Current Account

Purpose This is a theoretical paper in the field of international macroeconomics. The purpose of this paper is to focus on a dynamic interaction between current account imbalance and unemployment in response to some policy-induced shocks for a small open economy under a flexible exchange rate. Design/methodology/approach The paper uses a two-sector framework: one sector is traded and another is the non-traded sector that is subject to an effective demand constraint. The current account imbalance arises due to the discrepancy between production of traded goods, household consumption of traded goods and government purchases of importables. The authors keep the asset structure simple by considering only domestic currency and foreign bonds that are imperfect substitutes. The paper considers a standard methodology of dynamic adjustment process involving change in foreign exchange reserves and exchange rate under perfect foresight. The saddle path properties of the equilibrium are also examined. Findings The results of comparative static exercises depend on a set of structural features of a developing country, which include asset substitutability, wage price rigidity and sectoral asymmetries. The paper shows that expansionary monetary policy, balanced budget fiscal expansion and financial liberalization have an ambiguous effect on the current account balance, foreign exchange reserves, non-traded sector and the level of employment. Originality/value The existence of Keynesian unemployment with fixed prices is the key ingredient of this paper. The paper introduces the problem of effective demand to analyze the dynamics of current account balance and exchange rate, which, in turn, determine the sectoral composition of output and level of employment.

Out-of-sample exchange rate predictability with Taylor rule fundamentals

2009 ◽  
Vol 77 (2) ◽  
pp. 167-180 ◽  
Author(s):  
Tanya Molodtsova ◽  
David H. Papell
Keyword(s):  
Exchange Rate ◽  
Taylor Rule ◽  
Out Of Sample ◽  
Exchange Rate Predictability
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