Periodicities of FX Markets in Intrinsic Time

This paper utilises advanced methods from Fourier Analysis in order to describe financial ultra-high frequent transaction data. The Lomb-Scargle Fourier Transform is used to take into account the irregularity in spacing in the time-domain. It provides a natural framework for the power spectra of different inhomogeneous time series processes to be easily and quickly estimated,without significant computational effort, in contrast to the common econometric approaches in the finance literature. An event-based approach (intrinsic time), which by its own nature is inhomogeneous in time, is employed using different event thresholds to filter the foreign exchange tick-data leading to a power-law relationship. The calculated spectral density demonstrates that the price process in intrinsic time contains different periodic components, especially in the medium-long term, implying the existence of new stylised facts of ultra-high frequency data in the frequency domain

Forecasting and Combining Competing Models of Exchange Rate Determination

This paper investigates the out-of-sample forecast performance of a set of competing models of exchange rate determination. We compare standard linear models with models that characterize the relationship between exchange rate and its underlying fundamentals by nonlinear dynamics. Linear models tend to outperform at short forecast horizons especially when deviations from long-term equilibrium are small. In contrast, nonlinear models withmore elaborate mean-reverting components dominate at longer horizons especially whendeviations from long-term equilibrium are large. The results also suggest that combining different forecasting procedures generally produces more accurate forecasts than can be attained from a single model.non-linearity, exchange rate modelling, forecasting

Investigating the first level of pass -through effects of the SACU region monetary transmission mechanism

The purpose of this thesis is to investigate the first-level pass-through effects of monetary policy transmission in SACU using the wavelet analysis methodology. The thesis comprises four empirical themes. 1. Investigating the time-frequency relationship in the Fisher’s effect for SACU countries. 2. Investigating the time-frequency relationship in the Purchasing Power Parity (PPP) for SACU countries. 3. Investigating the time-frequency relationship between the exchange rate and the stock returns for SACU countries. 4. Investigating the time-frequency relationship between interest rates, exchange rates, and stock returns for SACU countries. Whilst there exists a considerable amount of empirical works which have studied the four themes in SACU countries that are covered in this study, there is a need for more empirical investigation for several reasons. Firstly, a majority of the studies have focused on South Africa with very little empirical literature existing for Botswana and Lesotho. Secondly, the previous SACU based studies present contradicting findings. Thirdly, Most of these studies did not cover the themes comprehensively, as is the case in this study. Finally, to the best of my knowledge, this methodology has not been employed in any SACU related literature until now. Altogether, the thesis bridges the inconsistencies found in previous SACU-related literature and offers fresh implications for policymakers and market participants. From an empirical perspective, the wavelet coherence analysis proves to be a powerful tool in reconciling previous contradicting empirical evidence on the existence of the Fisher effect in SACU countries. From a policy perspective, more fined tuned implications are derived from the findings of the study as wavelets are able to depict a more accurate description of the different first-level monetary transmission relationships.Thesis (PhD) -- Faculty of Business and Economic Sciences, School for Economics, Development and Tourism, 202

Investigating the first level of pass -through effects of the SACU region monetary transmission mechanism

The purpose of this thesis is to investigate the first-level pass-through effects of monetary policy transmission in SACU using the wavelet analysis methodology. The thesis comprises four empirical themes. 1. Investigating the time-frequency relationship in the Fisher’s effect for SACU countries. 2. Investigating the time-frequency relationship in the Purchasing Power Parity (PPP) for SACU countries. 3. Investigating the time-frequency relationship between the exchange rate and the stock returns for SACU countries. 4. Investigating the time-frequency relationship between interest rates, exchange rates, and stock returns for SACU countries. Whilst there exists a considerable amount of empirical works which have studied the four themes in SACU countries that are covered in this study, there is a need for more empirical investigation for several reasons. Firstly, a majority of the studies have focused on South Africa with very little empirical literature existing for Botswana and Lesotho. Secondly, the previous SACU based studies present contradicting findings. Thirdly, Most of these studies did not cover the themes comprehensively, as is the case in this study. Finally, to the best of my knowledge, this methodology has not been employed in any SACU related literature until now. Altogether, the thesis bridges the inconsistencies found in previous SACU-related literature and offers fresh implications for policymakers and market participants. From an empirical perspective, the wavelet coherence analysis proves to be a powerful tool in reconciling previous contradicting empirical evidence on the existence of the Fisher effect in SACU countries. From a policy perspective, more fined tuned implications are derived from the findings of the study as wavelets are able to depict a more accurate description of the different first-level monetary transmission relationships.Thesis (PhD) -- Faculty of Business and Economic Sciences, School for Economics, Development and Tourism, 202

Requirements for Defining Utility Drive Cycles: An Exploratory Analysis of Grid Frequency Regulation Data for Establishing Battery Performance Testing Standards

Battery testing procedures are important for understanding battery performance, including degradation over the life of the battery. Standards are important to provide clear rules and uniformity to an industry. The work described in this report addresses the need for standard battery testing procedures that reflect real-world applications of energy storage systems to provide regulation services to grid operators. This work was motivated by the need to develop Vehicle-to-Grid (V2G) testing procedures, or V2G drive cycles. Likewise, the stationary energy storage community is equally interested in standardized testing protocols that reflect real-world grid applications for providing regulation services. As the first of several steps toward standardizing battery testing cycles, this work focused on a statistical analysis of frequency regulation signals from the Pennsylvania-New Jersey-Maryland Interconnect with the goal to identify patterns in the regulation signal that would be representative of the entire signal as a typical regulation data set. Results from an extensive time-series analysis are discussed, and the results are explained from both the statistical and the battery-testing perspectives. The results then are interpreted in the context of defining a small set of V2G drive cycles for standardization, offering some recommendations for the next steps toward standardizing testing protocols

Public News in The Exchange Rate Market

In this thesis, we tackle the question of how newly available public information is absorbed in the FX market. The existing literature uses a standardized news transformation on macroeconomic data before using it in time-series models, due to a link between the transformation and the rational expectations hypothesis. Our results challenge a de facto approach by highlighting that the choice of the news transformation has a significant effect on the results. In addition, we propose several methodological improvements to the popular time-series approach. However, combining low frequency macroeconomic indicators and high-frequency FX processes in time-series models creates an ill-structured problem. To shed new light on the popular existing methodology, we propose an innovative way of restructuring the problem so that less restrictive methods - such as scaling laws, dominance testing and probability metrics - can be applied. Our results show weak evidence for a widely reported observation that new information causes elevated levels of volatility in FX markets, and in fact the reverse is observed in some cases. Further investigation reveals that the only significant factor driving FX news shocks is an anticipation effect of the news release. Once we account for the anticipation effect, we observe that most releases have positive influence irrespective of the sign of the data indicator released

Complexity and Persistence of Price Time Series of the European Electricity Spot Market

The large variability of renewable power sources is a central challenge in the transition to a sustainable energy system. Electricity markets are central for the coordination of electric power generation. These markets rely evermore on short-term trading to facilitate the balancing of power generation and demand and to enable systems integration of small producers. Electricity prices in these spot markets show pronounced fluctuations, featuring extreme peaks as well as occasional negative prices. In this article, we analyze electricity price time series from the European Power Exchange market, in particular the hourly day-ahead, hourly intraday, and 15-min intraday market prices. We quantify the fluctuations, correlations, and extreme events and reveal different time scales in the dynamics of the market. The short-term fluctuations show remarkably different characteristics for time scales below and above 12 h. Fluctuations are strongly correlated and persistent below 12 h, which contributes to extreme price events and a strong multifractal behavior. On longer time scales, they get anticorrelated and price time series revert to their mean, witnessed by a stark decrease of the Hurst coefficient after 12 h. The long-term behavior is strongly influenced by the evolution of a large-scale weather pattern with a typical time scale of four days. We elucidate this dependence in detail using a classification into circulation weather types. The separation in time scales enables a superstatistical treatment, which confirms the characteristic time scale of four days, and motivates the use of q-Gaussian distributions as the best fit to the empiric distribution of electricity prices