This paper investigates daily exchange rate volatility behaviors with a focus on a small open economy’s currency, the Swedish krona (SEK), against four currencies: the U.S. dollar, Euro, the Pound Sterling (GBP), and the Norwegian krone (NOK) over the whole period from Jan. 2010 to March 2023, whereas the whole period is divided into different sub-sample periods based on the economic events. In the framework of APARCH models, we find that volatility behavior of the Swedish krona (SEK) exchange rates varies across different currency pairs (SEK being included in all cases) and sub-sample periods. Precisely, a negative asymmetric return-volatility relationship was found for the case of the SEK/EUR exchange rate, while an inverted asymmetric relationship was detected in the case of SEK/NOK exchange rate. Significant asymmetric effects of volatility in the SEK/USD and SEK/GBP exchange rates were not observed for either the whole period or the three sub-sample periods. As the return of exchange rate are all non-normally distributed, we then use a distribution-free support vector machine-based regression, called support vector regression (SVR), to estimate and forecast volatility in the framework of the chosen APARCH model for each krona exchange rate. The result shows that the SVR-APARCH based volatility forecasting performs better than the forecasting based on APARCH model estimated by maximum likelihood estimation (MLE).

The objective of this paper is to re-examine the causal relationship between oil prices and economic activity for five Asian economies. We apply the unrestricted MIDAS (U-MIDAS) model using monthly data for real oil prices and quarterly data for real GDP for the period from 1998Q1 to 2019Q4. The causal nexus between oil prices and economic activity is also studied by means of wavelet analysis to investigate whether the relationship between the variables changes over different time scales. The key empirical results under the MIDAS approach show that there is a clear significant causal link from oil prices to economic activity, which is not as clearly found under the standard VAR approach. In addition, our results using impulse response functions suggest that the five Asian economies respond, in general, positively in economic activity to an oil price shock at shorter time horizons (less than two years), while the positive responses switch to mostly negative ones at longer time horizons (from two to four years). Our results, in general, support that the (theoretically) expected negative causal nexus between oil price fluctuations and economic activity for oil importers is dominant over longer time horizons for our dataset. An exception to this pattern is China, which has a dissimilar country profile in terms of its oil market and production structure from the profiles of the other Asian economies in the study.

This paper investigates the asymmetric behavior of oil price volatility using different types of Asymmetric Power ARCH (APARCH) model. We compare the estimation and forecasting performance of the models estimated from the maximum likelihood estimation (MLE) method and support vector machine (SVM) based regressions. Combining nonparametric SVM method with parametric APARCH model not only enables to keep interpretations of the parametric models but also leads to more precise estimation and forecasting results. Daily or weekly oil price volatility is investigated from March 8, 1991 to September 13, 2019. This whole sample period is split into four sub-periods based on the occurrence of certain economic events, and we examine whether the asymmetric behavior of the volatility exists in each sub-period. Our results indicate that SVM regression generally outperforms the other method with lower estimation and forecasting errors, and it is more robust to the choice of different APARCH models than the MLE counterparts are. Besides, the estimation results of the SVM based regressions in each sub-period show that the ARCH models with asymmetric power generally perform better than the models with symmetric power when the data sub-period includes large swings in oil price. The asymmetric behavior of oil price volatility, however, is not detected when the analysis is done using the whole sample period. This result underscores the importance of identifying the dynamics of the dataset in different periods to improve estimation and forecasting performance in modelling oil price volatility. This paper, therefore, examines volatility behavior of oil price with both methodological and economic underpinnings.

This study investigates Granger causality and instantaneous causality between financial development and economic development for 76 economies of four different income levels. The main novelty of the study is that it fills a gap in existing studies on the relationship between financial development and economic development by employing wavelet analysis, which enables us to study the varying time-scale relationships of the variables. Among the findings is that at the scale of 4-8 years it is more common for financial development and economic development to support each other once a country achieves at least lower-middle-income status.

Unlike previous studies on causal relationships between government revenue and expenditures in China, this study takes into consideration structural breaks in the data by performing wavelet decomposition prior to testing for Granger causality between the fiscal components. The use of wavelet decomposition is motivated by economic theories, which suggest allowing for different budgetary considerations at different time horizons, as well as by the existence of special properties in the data in the form of unit roots and structural breaks. The results from the Granger causality test when using the wavelet-decomposed quarterly data over the period 1980–2015 indicate that government revenue Granger-causes government expenditure (tax-and-spend hypothesis) in the wavelet scales of two to four quarters. The results also show that bidirectional causality (fiscal synchronisation) exists in the wavelet scale of eight to sixteen quarters. Understanding the causal relationships between revenue and expenditure at different time scales is important for formulating relevant policy measures in order to maintain fiscal sustainability in China.

The objective of this paper is to re-examine the relationship between real oil prices and real effective exchange rates (REER) for major oil-exporting countries with floating exchange rates. We apply the wavelet-based principles of Gallegati et al. (2016) using monthly data for the period 1996 to 2015. In contrast to many previ-ous studies, our results support the theoretically expected positive nexus between the real oil prices and REER for our dataset. This (theoretically-expected) positive relationship is stronger at the larger time scales (that is, at the 4-8 and 8-16 month wavelet scales) compared to the smaller time scales (that is, at the 1-2 and 2-4 month wavelet scales). The findings of this study therefore add to the existing literature, since they disentangle the specific relationship between oil prices and exchange rates at different time scales, which has important policy implications.

This article examines whether the purchasing power parity (PPP) theory holds or not for the economies in different developing regions located in Africa, Asia and Latin America. In order to investigate this issue, a nonlinear panel unit root test is used to determine if some or all of the real exchange rates in a panel follow a stationary exponential smooth transition autoregressive process. By applying the nonlinear panel unit root test, our results demonstrate an empirical support for the theory of PPP for the economies in developing regions.

This paper applies wavelet multi-resolution analysis (MRA), combined with two types of causality tests, to investigate causal relationships between three variables: real oil price, real interest rate, and unemployment in Norway. Impulse response functions were also utilised to examine effects of innovation in one variable on the other variables. We found that causal relations between the variables tend to be stronger as the wavelet time scale increases; specifically, there were no causal relationships between the variables at the lowest time scales of one to three months. A causal relationship between unemployment rate and interest rate was observed during the period of two quarters to two years, during which time a feedback mechanism was also detected between unemployment and interest rate. Causal relationships between oil price and both interest rate and unemployment were observed at the longest time scale of eight quarters. In conjunction with Granger causality analysis, impulse response functions showed that unemployment rates in Norway respond negatively to oil price shocks around two years after the shocks occur. As an oil exporting country, increases (or decreases) in oil prices reduce (or increase) unemployment in Norway under a time horizon of about two years; previous studies focused on oil importing economies have generally found the inverse to be true. Unlike most studies in this field, we decomposed the implicit aggregation for all time scales by applying MRA with a focus on the Norwegian economy. Thus, one main contribution of this paper is that we unveil and systematically distinguish the nature of the time-scale dependent relationship between real oil price, real interest rate, and unemployment using wavelet decomposition.

In this article we investigate if the Swedish consumer prices for electricity are adjusted equally fast regardless of whether the NordPool power market prices are decreased or increased. Due to relatively moderate variations in the variables, we have applied quantile regression, since it is mainly the large changes (above the median) that essentially tend to have a considerable effect on the consumer prices. Moreover, in order to adjust for stochastic- and deterministic trends, autocorrelation, structural breaks as well as to measure APT effects in the short- and in the medium-run, we apply a wavelet decomposition approach. Our results show evidence that significantly positive asymmetric price transmission (APT) effects exist in this market. More specifically, in the short-run (based on the wavelet decomposition D1 for 1–2 months cycles), we find that that there is a higher propensity to rapidly and systematically increase the consumer prices subsequently to an increase in the NordPool market price, compared with the propensity to decrease their customers prices subsequently to a corresponding drop in the NordPool market prices. However, no significant APT effects were detected in the medium- or in the long-run (i.e. the asymmetric price transmission effects are observed only in the short-run). In summary, we could isolate significant APT effects in the short-run (1–2 months decomposition cycles), and for large changes in the dependent variable (percentiles = 0.9). Therefore, only large changes in the NordPool prices lead to feedback effects in the form of asymmetric price transmission effects. Our evidence supports the notion of firms’ downward stickiness of retail prices for maximizing profit, which are not expected to be found on a fully efficient market. Although our finding shows that the price inefficiency is short-lived, these large temporal inefficiencies are still costly for the consumers. It should be noted that blunt traditional powerless methods do not detect these APT effects, while our wavelet quantile methods are powerful and make a significant contribution in the literature by providing new empirical evidence.

This paper uses wavelet analysis to investigate causality between the spot exchange rate and the nominal interest rate differential for seven country pairs, which includes Sweden. Impulse response functions are also utilized to examine the signs of how one of these variables affects the other over time. One key empirical finding from the causality tests is that there is strengthening evidence of the nominal interest rate differential Granger causing the exchange rate as the wavelet time scale increases. When considering impulse responses on how the interest rate differential affects the exchange rate, there appears to be some evidence of more negative relationships at the shorter time scales (i.e. an increase in the Swedish interest rate compared to that of another country is associated with a lower Swedish krona price of the other country's currency) and more positive relationships at the longer time scales.