scholarly journals Volatility of exchange rates in selected new EU members: Evidence from daily data

2008 ◽  
Vol 32 (1) ◽  
pp. 103-118 ◽  
Author(s):  
Jarko Fidrmuc ◽  
Roman Horváth
Keyword(s):  
Exchange Rates ◽  
Daily Data ◽  
New Eu Members

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.

A RESEARCH ON THE CAUSAL RELATIONSHIP BETWEEN INVESTMENT PREFERENCES

2021 ◽  
Vol 6 (16) ◽  
pp. 36-46
Author(s):  
Elif YÜCEL
Keyword(s):  
Interest Rate ◽  
Exchange Rates ◽  
Causal Relationship ◽  
Causality Test ◽  
Daily Data ◽  
Domestic Debt ◽  
The Interest Rate ◽  
Index Value ◽  
Macro Variables ◽  
Investment Choices

This study aims to measure the causal relationship between the dollar and euro at exchange rates among today's investment instruments and the deposit interest rate, Gold, Bist xu100 and the index of government domestic debt securities.Dec. Dec. The data in the study are daily data between 17/08/2017-26/05/2021 and were selected from a recent time Dec. Data with CBRT evds resources investing.com retrieved from. In this way, it is possible to see how variables adapt to today's financial world and the pandemic period. The method of the study is the Granger causality test, which is often used in time series analysis. When individuals make investment choices, they choose according to the fact that macro variables such as inflation, growth rate, and Exchange Rates fluctuate during periods of crisis and recession. This often affects even the credit demands of institutional investors. Central banks want to influence macro variables with various intervention tools, but because the economies of some countries are fragile, individuals can often suffer even as a result of these optimistic policies. According to the results of this study, the dependent variable in the model where the BIST100 index of the dollar and gold values, the probability of 0.000<0.05 causal relationship is true of dollars for deposit in the model where the dependent variable is the interest rate of government securities of the index, the probability value of 0.0001 p<0.05 and Bist100 index 0.0162 probability value<0.05 and the probability for the value of the dollar 0.02<0.05 can be considered to be a causal relationship due to being towards deposit rates. The probability of the dependent variable in a model of the euro BIST100 index value 0.0001 p<0.05, gold probability value of 0.000<0.05 Euros causal relationship is true for government securities in another model where the dependent variable of 0.0040 p<0.05 probability value from deposits with interest ,0.0000 p<0.05 0.0043 Bist100 index and the probability value p<0.05 is the probability for the value of government securities under de towards causality can be said. In a model in which the Bist100 index is a dependent variable, there was a causal relationship towards the Bist100 index ,as the probability value of the euro was 0.0012<0.05, the probability value of gold was 0.0000<0.05, the probability value of government domestic debt securities was 0.0013<0.05, and the probability value of the dollar was 0.0007<0.05. Finally, the model in which gold is a dependent variable concluded that there is no causal relationship between the Euro, dollar, dibs and Bist100 index and deposit interest to gold, since the probability values of other variables are greater than 0.05.

scholarly journals The Relationship between Stock Prices and Exchange Rates: The Focus on Dar Es Salaam Stock Exchange (DSE)

2017 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Fredynandy M John ◽  
Zakayo S Kisava
Keyword(s):  
Exchange Rates ◽  
Granger Causality ◽  
Stock Prices ◽  
Stock Exchange ◽  
Dar Es Salaam ◽  
Data Sets ◽  
Short Term ◽  
Vector Autoregressive ◽  
United States Dollar ◽  
Daily Data

This paper aims to examine the existing relationship between the prices of different stocks traded in the Dar es Salaam Stock Exchange (DSE) and the Tanzanian Shillings – United States dollar exchange rates (TZS/USD). In this study, we use the daily data sets covering a period of six years from August 15, 2011 through July 28, 2017 making 1455 observations. Vector Autoregressive (VAR) – Granger Causality model is employed accompanied with several tests conducted on the variables and the model itself. The findings conclude that, there is a short-term association between Stock Prices (SP) and Exchange Rates (ExR). Additionally, Stock Prices Granger Causes Exchange Rates as evidenced by Granger Causality and the Impulse test. These findings are supported by the fact that shocks in the Exchange Rates have no effect in the Stock Prices. This could mean that an investor can invest in short term at the DSE.

The Dynamic Relationship between Oil Prices and Exchange Rates

2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Hamid Sakaki
Keyword(s):  
Financial Crisis ◽  
Exchange Rates ◽  
Oil Prices ◽  
Significant Negative Correlation ◽  
Crisis Period ◽  
Dynamic Correlation ◽  
Dynamic Relationship ◽  
Daily Data ◽  
Us Dollar ◽  
Dollar Depreciation

<p>Using daily data of oil prices and exchange rates of 14 countries for the period January 1999 to November 2014, this study examines the dynamic correlation between oil prices and exchange rates by DCC-GARCH model. The results show the significant negative correlation between oil prices and exchange rates over the period. These results imply that the increase of oil price is coinciding with US dollar depreciation and vice versa.  This correlation strengthens in negative direction during financial crisis period, while it shifts to an upward trend after financial crisis period.</p>

scholarly journals OFFSHORE AND ONSHORE IDR MARKET: AN EVIDENCE ON INFORMATION SPILLOVER

2012 ◽  
Vol 14 (4) ◽  
pp. 323-348
Author(s):  
Yayat Cadarajat ◽  
Alexander Lubis
Keyword(s):  
Exchange Rates ◽  
Information Transmission ◽  
Emerging Market ◽  
Spot Market ◽  
Forward Rate ◽  
Spot Rate ◽  
Currency Markets ◽  
Daily Data ◽  
Egarch Model ◽  
Information Spillover

This paper investigates the information transmission between off-shore and on-shore Rupiah currency markets Indonesian. We found the evidence of persistent volatility in all IDR/USD markets. Using EGARCH model on daily data for the period of 2008 - 2011, this paper provide several empirical conclusions.-First, the persistent volatility in all IDR/USD currency markets is evident. Second, the leverage effects are present in the rupiah exchange rates, indicating that IDR/USD markets have responded more to depreciation than appreciation, which is generally common in emerging market currencies. Third, the evidence of mean spillover are observed to be uni-directional; from NDF to both spot and forward rupiah markets. However, there are two ways return transmission between NDF and forward rate changes in the period of Europe crisis. Fourth, on the volatility, the spillover is only significant from NDF market to spot market for the entire period. However, in the time of crises, there is interdependence between volatility in offshore NDF and onshore spot rate changes, while information transmission is only valid from NDF to forward rate changes, not the other way around. Fifth, the negative spread of domestic interest rate may lead to depreciation pressure on the currency and positive spread may indicate the appreciation pressure. Keywords: Foreign Exchange, Non-Deliverable Forward, exchange rate, spillover, EGARCH.JEL Classification: F31, G13, C51

scholarly journals Forecasting Exchange Rate Across Countries with Gold Price as Exogenous Variable Using Transfer Function and VARI-X Model

MATEMATIKA ◽  
2020 ◽  
Vol 36 (3) ◽  
pp. 181-196
Author(s):  
Alhassan Sesay ◽  
Suhartono Suhartono ◽  
Dedy Dwi Prastyo
Keyword(s):  
South Africa ◽  
Exchange Rate ◽  
Transfer Function ◽  
Exchange Rates ◽  
Arima Model ◽  
Gold Price ◽  
Savings Accounts ◽  
Daily Data ◽  
The Relationship

Investors and collectors hold gold as protection for their savings and wealth atlarge. Gold does not pay interest like treasure bonds or savings accounts, but current goldprices often reflect increases and decreases of an asset. This research aims to provide amodel for the relationship between the exchange rate, which is vital in exporting gold, andgold prices across countries. The Australia, Brazil, and South Africa exchange rates areused as a case study against the gold price. The ARIMA model is used for forecasting goldprice as an input for the Transfer Function and VARIX models. The Transfer Functionmodel only considers the relationship between gold prices as input with the exchange ratein each country, whereas the VARIX model also considers the interrelationship betweenexchange rates in these countries. Daily data is used for the period 1st June 2010 to the28th February 2018. The RMSE and MAPE are used as criteria for selecting the bestmodel. The results show that VARIX is the best model for forecasting the Australianexchange rate, while the Transfer function is the best model for forecasting South Africanand Brazilian exchange rates.

scholarly journals Revisiting spillover effect: An empirical evidence from GARCH-ARMA approach

Industrija ◽  
2021 ◽  
Vol 49 (1) ◽  
pp. 67-80
Author(s):  
Huruta Dolfriandra ◽  
Andreas Hananto ◽  
Roberto Forestal ◽  
Anboli Elangovan ◽  
John Diaz
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Empirical Evidence ◽  
Stock Prices ◽  
Stock Price ◽  
Spillover Effect ◽  
Commodity Markets ◽  
Commodity Exchange ◽  
Daily Data ◽  
Positive Spillover

This study analyzes the spillover effect of markets' commodity, exchange rate, and stock price. Starting from July 1, 2009, the daily data to December 31, 2019, are conducted in our study. The GARCH-ARMA approach has been undertaken in this study. The results show that four pairs experience the unidirectional (positive) spillover effect of return. Yet, the spillover effect of volatility shows a two-way relationship (both positive and negative) between commodity markets, stock prices, and exchange rates. To conclude, both stock prices and gold are volatility's net transmitters to other markets, while the EURUSD market is some markets' net receiver of volatility.

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