Search results for "High-frequency data"

showing 4 items of 4 documents

Causal flows between oil and forex markets using high-frequency data: Asymmetries from good and bad volatility

2019

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. This paper investigates the causal linkages in volatility between crude oil prices and six major bilateral exchange rates against the U.S. dollar in the time-frequency space using high-frequency intraday data. Special attention is paid to the potential asymmetries in the causal effects between oil and forex markets. The wavelet-based Granger causality method proposed by Olayeni (2016) is applied to quantify the causal relations in the time and frequency domains simultaneously. Moreover, the realized semivariance approach of Barndoff-Nielsen et a…

Economics and EconometricsRealized variance020209 energycrude oil prices02 engineering and technologyMonetary economicsexchange ratesrealized volatilityGranger causality0502 economics and business0202 electrical engineering electronic engineering information engineeringEconomics050207 economics05 social scienceswavelet analysisgood and bad volatilityhigh-frequency dataGeneral EnergyCurrencyFinancial crisisLiberian dollarGranger causalityFinancializationVolatility (finance)Foreign exchange marketasymmetry
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Emergence of statistically validated financial intraday lead-lag relationships

2014

According to the leading models in modern finance, the presence of intraday lead-lag relationships between financial assets is negligible in efficient markets. With the advance of technology, however, markets have become more sophisticated. To determine whether this has resulted in an improved market efficiency, we investigate whether statistically significant lagged correlation relationships exist in financial markets. We introduce a numerical method to statistically validate links in correlation-based networks, and employ our method to study lagged correlation networks of equity returns in financial markets. Crucially, our statistical validation of lead-lag relationships accounts for mult…

Bootstrap methodFinancial market01 natural sciencesLead-lag correlation010305 fluids & plasmasFOS: Economics and businessCorrelationSettore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Statistically validated network0502 economics and business0103 physical sciencesStatisticsEconomicsEconometricsStock (geology)FinanceStatistical Finance (q-fin.ST)050208 financeHigh-frequency databusiness.industry05 social sciencesFinancial marketMarket efficiencyEquity (finance)Quantitative Finance - Statistical FinanceStock returnSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Economics Econometrics and Finance (all)2001 Economics Econometrics and Finance (miscellaneous)Multiple comparisons problemLead–lag compensatorbusinessGeneral Economics Econometrics and FinanceTransaction dataFinanceQuantitative Finance
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A new method to "clean up" ultra high-frequency data

2007

In the applied econometrics, the availability of ultra high-frequency databases is having an important impact on the research market microstructure theory. The ultra high-frequency databases contain detailed reports of all the financial market activity information which is available. However, ultra high-frequency databases cannot be directly used. On one hand recording mistakes can be present, on the other hand missing information has to be inferred from the available data. In this paper, we propose a simple method in order to clean up the ultra high-frequency data from possible errors and we examine the method efficacy when we analyze data by using an autoregressive conditional duration (A…

Ultra high-frequency data stock exchange outliers ACD models
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High frequency data entry: statistical findings at high frequency

2010

We introduce some of the most common types of high-frequency financial data: tick-by-tick data, trade andquote data, order bookdata, andmarket member data. We describe the types of variables that are usually available in the most popular high-frequency financial databases. We discuss the issues related to the handling of these data, including cleaning protocols, timing issues, and issues related to data size. We then briefly consider the issues related to the stylized facts detected in the empirical analysis of high- frequency data. Specifically, we consider (i) the irregular temporal spacing of the events at high frequency and its relevance for the econometric modeling of financial variables, (…

financial markets high-frequency data data analysis tick-by-tick data order bookdata market microstructure econophysicsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
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