3,848 research outputs found

    Time series aggregation, disaggregation and long memory

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    We study the aggregation/disaggregation problem of random parameter AR(1) processes and its relation to the long memory phenomenon. We give a characterization of a subclass of aggregated processes which can be obtained from simpler, "elementary", cases. In particular cases of the mixture densities, the structure (moving average representation) of the aggregated process is investigated

    Analysis of aggregated tick returns: evidence for anomalous diffusion

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    In order to investigate the origin of large price fluctuations, we analyze stock price changes of ten frequently traded NASDAQ stocks in the year 2002. Though the influence of the trading frequency on the aggregate return in a certain time interval is important, it cannot alone explain the heavy tailed distribution of stock price changes. For this reason, we analyze intervals with a fixed number of trades in order to eliminate the influence of the trading frequency and investigate the relevance of other factors for the aggregate return. We show that in tick time the price follows a discrete diffusion process with a variable step width while the difference between the number of steps in positive and negative direction in an interval is Gaussian distributed. The step width is given by the return due to a single trade and is long-term correlated in tick time. Hence, its mean value can well characterize an interval of many trades and turns out to be an important determinant for large aggregate returns. We also present a statistical model reproducing the cumulative distribution of aggregate returns. For an accurate agreement with the empirical distribution, we also take into account asymmetries of the step widths in different directions together with crosscorrelations between these asymmetries and the mean step width as well as the signs of the steps.Comment: 9 pages, 10 figures, typos correcte

    Macroeconometric Modelling with a Global Perspective

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    This paper provides a synthesis and further development of a global modelling approach introduced in Pesaran, Schuermann and Weiner (2004), where country specific models in the form of VARX* structures are estimated relating a vector of domestic variables to their foreign counterparts and then consistently combined to form a Global VAR (GVAR). It is shown that VARX* models can be derived as the solution to a dynamic stochastic general equilibrium (DSGE) model where over-identifying long-run theoretical relations can be tested and imposed if acceptable. Similarly, short-run over-identifying theoretical restrictions can be tested and imposed if accepted. The assumption of the weak exogeneity of the foreign variables for the long-run parameters can be tested, where foreign variables can be interpreted as proxies for global factors. Rather than using deviations from ad hoc statistical trends, the equilibrium values of the variables reflecting the long-run theory embodied in the model can be calculated

    Impact of Unexpected Events, Shocking News and Rumours on Foreign Exchange Market Dynamics

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    We analyze the dynamical response of the world's financial community to various types of unexpected events, including the 9/11 terrorist attacks as they unfolded on a minute-by-minute basis. We find that there are various 'species' of news, characterized by how quickly the news get absorbed, how much meaning and importance is assigned to it by the community, and what subsequent actions are then taken. For example, the response to the unfolding events of 9/11 shows a gradual collective understanding of what was happening, rather than an immediate realization. For news items which are not simple economic statements, and hence whose implications are not immediately obvious, we uncover periods of collective discovery during which collective opinions seem to oscillate in a remarkably synchronized way. In the case of a rumour, our findings also provide a concrete example of contagion in inter-connected communities. Practical applications of this work include the possibility of producing selective newsfeeds for specific communities, based on their likely impact

    Collaborative learning exercises for Teaching Protein Mass Spectrometry [post-print]

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    A collaborative learning module for teaching protein mass spectrometry has been developed to overcome common obstacles to incorporating the modern topic of biological mass spectrometry into the undergraduate chemistry curriculum. Protein mass spectrometry data is provided to eliminate the need for expensive instrumentation, and an instructor’s manual gives necessary details for those unfamiliar with the topic. The first section provides background information on proteins and the field of proteomics. The second section describes the use of electrospray ionization to determine the molecular weight of a protein. The third section shows how to identify a protein using peptide mass mapping, and the fourth section describes tandem MS experiments for de novo peptide sequencing. Each section also includes lessons on the analytical instrumentation used to make mass measurements including electrospray ionization, matrix assisted laser desorption ionization, and time-of-flight mass spectrometry. The module includes preclass reading assignments and small group problem solving exercises to be used during class sessions. The module was implemented over several semesters at both a small liberal arts college and a large research university. Assessment data from both institutions suggest that the module is effective in helping students to learn about mass-spectrometry-based proteomics. This freely available resource will assist instructors in introducing these topics to the undergraduate curriculum

    Smooth transitions, asymmetric adjustment and unit roots

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    The aim of this article is to develop a unit root test that takes into account two sources of nonlinearites in data, i.e. asymmetric speed of mean reversion and structural changes. The asymmetric speed of mean reversion is modelled by means of a exponential smooth transition autoregression (ESTAR) function for the autoregressive parameter, whereas structural changes are approximated by a smooth transition in the deterministic components. We find that the proposed test performs well in terms of size and power, in particular when the autoregressive parameter is near unity

    Tourism income and economic growth in Greece: Empirical evidence from their cyclical components

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    This paper examines the relationship between the cyclical components of Greek GDP and international tourism income for Greece for the period 1976–2004. Using spectral analysis the authors find that cyclical fluctuations of GDP have a length of about nine years and that international tourism income has a cycle of about seven years. The volatility of tourism income is more than eight times the volatility of the Greek GDP cycle. VAR analysis shows that the cyclical component of tourism income is significantly influencing the cyclical component of GDP in Greece. The findings support the tourism-led economic growth hypothesis and are of particular interest and importance to policy makers, financial analysts and investors dealing with the Greek tourism industry
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