Understanding the dynamics of foreign reserve management: The central bank intervention policy and the exchange rate fundamentals

Akdogan, Idil Uz

doi:10.1016/j.inteco.2019.11.002

Cited by 11 publications

(8 citation statements)

References 23 publications

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“…A country’s foreign exchange reserves influence the choice of monetary policies, such as the scope and extent of foreign exchange interventions, which in turn, have a feedback effect on exchange rate movements (Akdogan 2020 ). Despite nontrivial holding costs, emerging market countries prefer to maintain a high level of reserves.…”

Section: Theoretical Underpinningsmentioning

confidence: 99%

Openness and Real Exchange Rate Volatility: Evidence from China

Yang

Peng

2023

Open Econ Rev

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In recent years, China has introduced a series of trade and financial liberalization policies and taken a crucial step towards the internationalization of RMB. These new developments bring about one question: how has openness affected the RMB real exchange rate volatility? Our empirical results reveal that in the long term, both trade and financial openness reduce exchange rate volatility; in the short term, the effect of financial openness varies across the three financial sub-accounts. Financial development can magnify (mitigate) the impact of trade openness on volatility in the short (long) term, but its role in affecting the impact of financial openness depends on the financial sub-account involved. Economic policy uncertainty (EPU) weakens the impact of openness on exchange rate volatility. In addition, financial openness absorbs more external shocks than trade openness. Foreign exchange reserves, while offsetting financial crisis shocks, cannot adequately absorb current account balance shocks.

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Section: Theoretical Underpinningsmentioning

confidence: 99%

Openness and Real Exchange Rate Volatility: Evidence from China

Yang

Peng

2023

Open Econ Rev

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“…One possible explanation for a more harmonized behavior of the national currencies could be attributed to the fact that five of these currencies were replaced by the euro. There had been a significant increase in the speed of reserve accumulation in European countries since the 2008 Financial Crisis, so countries were likely to respond more aggressively to an exchange rate appreciation (Uz Akdogan, 2020). There is clear evidence that the behavior of the RER was different before, during, and after the crisis.…”

Section: Real Exchange Rate Determinants In Eecmentioning

confidence: 99%

The demand for money and the real exchange rate misalignments in emerging European countries: A nonlinear approach

Akdogan

2022

Bulletin of Econ Res

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This paper investigates the extent to which domestic and foreign money balances in emerging European countries are influenced by foreign exchange considerations.A well-specified and stable relationship between real money demand and the exchange rate can be perceived as an important part of a successful monetary policy.This study examines the long-run determinants of real exchange rates (RERs)associated with the behavioral equilibrium exchange rate (BEER) approach and identifies currency misalignments in these countries. The misalignment is later used to test the nonlinear behavior of the demand for money. The results indicate that the RER misalignments have a significant impact on domestic money demand. When the currencies are overvalued, there is a reduction in domestic money demand, and when they are undervalued, there is an increase in domestic money demand. Furthermore, it can be concluded that overvaluation causes an increase in foreign money demand indicating a shift of preference from domestic to foreign currency. K E Y W O R D Sbehavioral equilibrium exchange rate, demand for money, misalignments, real exchange rates, smooth transition regressionThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…The demonstration of carry trading in the present article expands the possibility of applying machine learning-based forecasting to financial trading. (3) The O(n 3 ) time complexity in an SVR algorithm means that the performance of the SVR-based method may be reduced in big data applications [118]. Nevertheless, the FSPSOSVR model outperformed all the other models in monthly rate forecasting.…”

Section: Supplementary Materialsmentioning

confidence: 99%

“…From the point of view of monetary authorities, reliable exchange rate forecasting also contributes to the management of exchange rates and conduction of monetary policies. Under a managed exchange rate regime, exchange rates are allowed to fluctuate within an undisclosed band, and the authorities may intervene in this regime depending on their future expectations of the exchange rates [3]. Moreover, when a government uses monetary policies such as cutting interest rates to stimulate the economy, this will increase the income and demand for the imported goods of a country, appreciating the currency, which will ultimately negatively affect the competitiveness of exported goods.…”

Section: Introductionmentioning

confidence: 99%

An Effective Hybrid Approach for Forecasting Currency Exchange Rates

Shen¹,

Lee

Liu³

et al. 2021

Sustainability

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Accurately forecasting the movement of exchange rates is of interest in a variety of fields, such as international business, financial management, and monetary policy, though this is not an easy task due to dramatic fluctuations caused by political and economic events. In this study, we develop a new forecasting approach referred to as FSPSOSVR, which is able to accurately predict exchange rates by combining particle swarm optimization (PSO), random forest feature selection, and support vector regression (SVR). PSO is used to obtain the optimal SVR parameters for predicting exchange rates. Our analysis involves the monthly exchange rates from January 1971 to December 2017 of seven countries including Australia, Canada, China, the European Union, Japan, Taiwan, and the United Kingdom. The out-of-sample forecast performance of the FSPSOSVR algorithm is compared with six competing forecasting models using the mean absolute percentage error (MAPE) and root mean square error (RMSE), including random walk, exponential smoothing, autoregressive integrated moving average (ARIMA), seasonal ARIMA, SVR, and PSOSVR. Our empirical results show that the FSPSOSVR algorithm consistently yields excellent predictive accuracy, which compares favorably with competing models for all currencies. These findings suggest that the proposed algorithm is a promising method for the empirical forecasting of exchange rates. Finally, we show the empirical relevance of exchange rate forecasts arising from FSPSOSVR by use of foreign exchange carry trades and find that the proposed trading strategies can deliver positive excess returns of more than 3% per annum for most currencies, except for AUD and NTD.

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Understanding the dynamics of foreign reserve management: The central bank intervention policy and the exchange rate fundamentals

Cited by 11 publications

References 23 publications

Openness and Real Exchange Rate Volatility: Evidence from China

Openness and Real Exchange Rate Volatility: Evidence from China

The demand for money and the real exchange rate misalignments in emerging European countries: A nonlinear approach

An Effective Hybrid Approach for Forecasting Currency Exchange Rates

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