Browsing by Subject "Fractional Brownian motion"
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Item Open Access On the modeling of CO2 EUA and CER prices of EU-ETS for the 2008–2012 period(John Wiley and Sons, 2016) Gürler, Ü.; Yenigün, D.; Çağlar, M.; Berk, E.Increased consumption of fossil fuels in industrial production has led to a significant elevation in the emission of greenhouse gases and to global warming. The most effective international action against global warming is the Kyoto Protocol, which aims to reduce carbon emissions to desired levels in a certain time span. Carbon trading is one of the mechanisms used to achieve the desired reductions. One of the most important implications of carbon trading for industrial systems is the risk of uncertainty about the prices of carbon allowance permits traded in the carbon markets. In this paper, we consider stochastic and time series modeling of carbon market prices and provide estimates of the model parameters involved, based on the European Union emissions trading scheme carbon allowances data obtained for 2008–2012 period. In particular, we consider fractional Brownian motion and autoregressive moving average–generalized autoregressive conditional heteroskedastic modeling of the European Union emissions trading scheme data and provide comparisons with benchmark models. Our analysis reveals evidence for structural changes in the underlying models in the span of the years 2008–2012. Data-driven methods for identifying possible change-points in the underlying models are employed, and a detailed analysis is provided. Our analysis indicated change-points in the European Union Allowance (EUA) prices in the first half of 2009 and in the second half of 2011, whereas in the Certified Emissions Reduction (CER) prices three change-points have appeared, in the first half of 2009, the middle of 2011, and in the second half of 2012. These change-points seem to parallel the global economic indicators as well.Item Open Access Regulated fractionally integrated processes(Wiley-Blackwell Publishing Ltd., 2013) Trokic, M.Regulated (bounded) integrated time series are of significant practical importance and a recent development in the time series literature. Although regulated integrated series are characterized by asymptotic distributions that differ substantially from their unregulated counterparts, most inferential exercises continue to be performed with complete disregard for this potential feature of time series data. To date, only Cavaliere (2005) and Cavaliere and Xu (2011) have attempted to develop a theory for regulated integrated time series, particularly in the context of unit root testing. Unfortunately, no such theory has been developed for regulated fractionally integrated series, which are particularly important in financial time series and also in some unit root testing literature. This article achieves just this: it establishes a framework for regulated fractionally integrated processes and develops their functional central limit distributions. In addition, this article presents some simulation evidence and discusses several algorithms for obtaining the limiting distributions for these processes.Item Open Access Wavelet energy ratio unit root tests(Taylor and Francis Inc., 2016) Trokić, M.This article uses wavelet theory to propose a frequency domain nonparametric and tuning parameter-free family of unit root tests. The proposed test exploits the wavelet power spectrum of the observed series and its fractional partial sum to construct a test of the unit root based on the ratio of the resulting scaling energies. The proposed statistic enjoys good power properties and is robust to severe size distortions even in the presence of serially correlated MA(1) errors with a highly negative moving average (MA) parameter, as well as in the presence of random additive outliers. Any remaining size distortions are effectively eliminated using a novel wavestrapping algorithm. 2016 Copyright © Taylor & Francis Group, LLC