Time-Gap effects of crude oil prices on the foreign exchange rates: Evidence from Nigeria

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.

JUAL BELI VALUTA ASING DALAM PERSPEKTIF HUKUM ISLAM

ABSTRAKKejadian baru-baru ini yang melanda bangsa Indonesia mengenai krisis ekonomi telah banyak menyengsarakan kehidupan rakyat khususnya dalam bidang pangan. Kejadian krisis tersebut selain dilanda wabah covid-19 juga diakibatkan dengan salah satunya adalah adanya transaksi jual beli valas di bursa valas yang disalahgunakan oleh para spekulan. Mereka hanya bertujuan untuk mencari keuntungan yang sebesar-besarnya (menjadikan uang dan sebagai alat tukar menjadi alat komoditi) tanpa melihat kehidupan bangsa Indonesia di masa yang akan datang. Hal ini tentunya muncul berbagai permasalahan, di antaranya: 1) Bagaimana pelaksanaan transaksi kurs beli dan kurs jual valuta asing, dan 2) Bagaimana alasan ketetapan jual beli valuta asing menurut hukum Islam. Tujuan dari penelitian ini adalah: 1) untuk mengetahui pelaksanaan transaksi kurs beli dan kurs jual valuta asing, dan 2) untuk mengetahui alasan ketetapan jual beli valuta asing menurut hukum Islam. Berdasarkan hasil pengkajian dan penelitian terhadap literatur-literatur yang relevan dengan permasalahan ditemukan bahwa dalam Islam dikenal berbagai transaksi jual beli baik yang dilarang maupun yang dibolehkan. Terdapat tiga bagian dalam transaksi valas, yaitu: transaksi spot, transaksi forward, dan transaksi swap. Dari ketiga transaksi tersebut berdasarkan pengkajian terhadap literatur yang dibolehkan menurut hukum Islam adalah transaksi spot atau dalam istilah hukum Islam yadan biyadin (tunai). Sedangkan transaksi forward dan transaksi swap hukumnya haram, karena transaksi tersebut di dalamnya mengandung unsur riba.ABSTRACTThe recent events that hit the Indonesian people regarding the economic crisis have made many people's lives miserable, especially in the food sector. Apart from being hit by the COVID-19 outbreak, this crisis was also caused by one of which was the existence of foreign exchange buying and selling transactions on the forex market that were misused by speculators. They only aim to seek the maximum profit (making money and as a medium of exchange into a commodity) without looking at the life of the Indonesian people in the future. Of course, various problems arise, including: 1) How to carry out transactions of buying and selling foreign exchange rates, and 2) What are the reasons for the determination of buying and selling foreign exchange according to Islamic law. The objectives of this study are: 1) to determine the implementation of the transaction of buying and selling foreign exchange rates, and 2) to find out the reasons for the determination of buying and selling foreign exchange according to Islamic law. Based on the results of studies and research on the literature relevant to the problem, it was found that in Islam there are various buying and selling transactions, both prohibited and permitted. There are three parts to foreign exchange transactions, namely: spot transactions, forward transactions, and swap transactions. Of the three transactions, based on a review of the literature, what is permitted under Islamic law is a spot transaction or in terms of Islamic law yadan biyadin (cash). Meanwhile, forward transactions and swap transactions are illegitimate, because these transactions contain elements of usury.

Empirical determinants of exchange-rate volatility: evidence from selected Asian economies

Purpose This paper aims to explore the empirical determinants of exchange-rate volatility (ERV) in selected Asian economies, namely, Bangladesh, China, India, Indonesia, Malaysia and Pakistan. Specifically, it examines how the volatility of foreign reserves, government spending, industrial production, gold prices and terms of trade affect monthly ERV during the examined period. Design/methodology/approach The authors carry out the empirical analysis by using monthly data for the period January 1997–March 2019. First, the volatility of the underlying variables is measured based on the conditional variances obtained by estimating the univariate (generalized) autoregressive conditional heteroskedasticity [(G)ARCH] model for each variable during the study period. Next, the autoregressive conditional heteroscedasticity (ARCH)-Lagrange multiplier test is applied to ensure that there are no remaining ARCH effects in the residuals. Finally, the multivariate autoregressive-moving average-GARCH (1, 1) models are estimated to examine whether and how the volatility of the underlying variables affects ERV. Findings The results reveal that the current period volatility of exchange rates is significantly affected by ERV in the previous period in all selected countries. The results also indicate that the volatilities of the underlying macroeconomic variables are quite differently related to ERV in examined Asian countries. Foreign-reserve volatility (VFXRES) has negative and significant impacts on ERV in Bangladesh, China and Malaysia. Government-spending volatility is negatively related to ERV in India, whereas it is positively related to ERV in all other examined countries. The results also suggest that although terms-of-trade volatility reduces ERV in both Bangladesh and Pakistan, it amplifies ERV in the remaining examined countries. However, gold-price volatility (VGOLDP) significantly, positively contributes to ERV in Bangladesh, Indonesia and Malaysia. On the contrary, the higher volatility in industrial production (VIPI) results in lower ERV in Indonesia and Pakistan, whereas it increases ERV in China, India and Malaysia. Practical implications The findings have several important policy implications. First, the findings suggest that both Bangladesh and Malaysia should keep an adequate level of foreign reserves to stabilize their foreign exchange rates. Second, as government-spending volatility has a vital role in determining ERV, it is necessary to bring sustainability and continuity in government expenditures. Bangladesh and Pakistan can stabilize their foreign exchange rates by making exports more competitive, viable and accessible. Originality/value This paper significantly contributes to the existing literature by exploring how the behavior of unexpected variations in the factors determining exchange rates affects ERV in selected Asia countries. Most of the published studies have examined the determinants of exchange rates by considering the macroeconomic variables at their levels. Departing from the existing studies, this paper significantly relates the volatility (second moment) of exchange rate determinants to the behavior of ERV. Further, this paper provides firsthand empirical evidence on this issue for the selected Asian economies.

Wavelet-Based Elman Neural Network with the Modified Differential Evolution Algorithm for Forecasting Foreign Exchange Rates

It is challenging to forecast foreign exchange rates due to the non-linear characters of the data. This paper applied a wavelet-based Elman neural network with the modified differential evolution algorithm to forecast foreign exchange rates. Elman neural network has dynamic characters because of the context layer in the structure. It makes Elman neural network suit for time series problems. The main factors, which affect the accuracy of the Elman neural network, included the transfer functions of the hidden layer and the parameters of the neural network. We applied the wavelet function to replace the sigmoid function in the hidden layer of the Elman neural network, and we found there was a “disruption problem” caused by the non-linear performance of the wavelet function. It didn’t improve the performance of the Elman neural network, but made it get worse in reverse. Then, the modified differential evolution algorithm was applied to train the parameters of the Elman neural network. To improve the optimizing performance of the differential evolution algorithm, the crossover probability and crossover factor were modified with adaptive strategies, and the local enhanced operator was added to the algorithm. According to the experiment, the modified algorithm improved the performance of the Elman neural network, and it solved the “disruption problem” of applying the wavelet function. These results show that the performance of the Elman neural network would be improved if both of the wavelet function and the modified differential evolution algorithm were applied integratedly.

Factors that Determine and Influences Foreign Exchange Rates

The Foreign Exchange rate is very much crucial for determining the economic health level of the country. The foreign exchange rate provides financial stability, enhances purchasing power and allows global trades. This rate usually fluctuates due to the market forces which control the supply and demand of the currency. Nominal and relative inflation and income level have a substantial effect on determining the exchange rates. Government measures, international situations, natural disasters or any unexpected situation like Covid-19, Rohingya crisis etc. can affect the exchange rates. Besides this, the interaction between the factors can create different reasoning to affect the market. This study tries to identify some factors with relevant examples.

Chaotic time series forecasting with residual analysis using synergy of ensemble neural networks and Taguchi's design of experiments

This dissertation aims to develop an effective and practical method to forecast chaotic time series. Chaotic behaviour has been observed in the areas of marketing, stock markets, supply chain management, foreign exchange rates, weather forecasting and many others. An effective forecasting model can reduce the potential risks and uncertainty and facilitate planning and decision making in chaotic systems. In this study, residual analysis using a combination of the embedding theorem and ensemble artificial neural networks is adopted to forecast chaotic time series. Based on the embedding theorem, the embedding parameters are determined and the time series is reconstructed into proper phase space points. The embedded phase space points are fed into the first neural network and trained. The weights and biases are kept to predict the future values of phase space points and accordingly to obtain future values of chaotic time series. The residual of the predicted time series is further analyzed; and, if a chaotic behaviour is observed, then the residuals are processed as a new chaotic time series and predicted. This iterative residual analysis can be repeated several times depending on the desired accuracy level and computational efficiency. Finally, the last neural network is trained using neural networks' result values of the time series and the residuals as input and the original time series as output. The initial weights and biases of the neural networks are improved using genetic algorithms. Taguchi's design of experiments is adopted to identify appropriate factor-level combinations to improve the result of the proposed forecasting method. A systematic approach is proposed to improve the combination of ensemble artificial neural networks and their parameters. The proposed methodology is applied to a number of benchmark and some real life chaotic time series. In addition, the proposed forecasting method has been applied to financial sector time series, namely, the stock markets and foreign exchange rates. The experimental results confirm that the proposed method can predict the chaotic time series more effectively in terms of error indices when compared with other forecasting methods in the literature.