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one can detect jumps of height no smaller than ?t?2log(n)/n. We construct a test which achieves this rate in the case for …. Applying our tests to high-frequency fi?nancial data, we detect more jumps in the data than are found by other tests. …
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We introduce a heuristic bias-adjustment for the transaction price-based realized range estimator of daily volatility in the presence of bid–ask bounce and non-trading. The adjustment is an extension of the estimator proposed in Christensen et al. (2009). We relax the assumption that all...
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same reason rare random jumps are not critical either. It is more important to choose a proper data type and prefilter the …
Persistent link: https://www.econbiz.de/10005620054
This article introduces a new model for transaction prices in the presence of market microstructure noise in order to study the properties of the price process on two different time scales, namely, transaction time where prices are sampled with every transaction and tick time where prices are...
Persistent link: https://www.econbiz.de/10005511893
This article evaluates the economic benefit of methods that have been suggested to optimally sample (in an MSE sense) high-frequency return data for the purpose of realized variance/covariance estimation in the presence of market microstructure noise (Bandi and Russell, 2005a, 2008). We compare...
Persistent link: https://www.econbiz.de/10005476176
difference between them strongly depends on whether or not the stock price process has jumps. Subsequently, we propose two new …
Persistent link: https://www.econbiz.de/10010847051
measures of volatility, allowing for both microstructure noise and jumps. We establish the asymptotic normality of the test …
Persistent link: https://www.econbiz.de/10010664699