Testing for jumps and jump intensity path dependence

Corradi, Valentina; Silvapulle, Mervyn J.; Swanson, Norman R.

doi:10.1016/j.jeconom.2018.02.004

Cited by 23 publications

(26 citation statements)

References 45 publications

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“…We use the setup of Corradi et al (2018). Namely, assume that asset (log-)prices are recorded at an equally spaced discrete interval, ∆ = 1 m , where m is the total number of observations on each trading day.…”

Section: Setupmentioning

confidence: 99%

“…In this paper, we add to the financial econometrics literature by carrying out an extensive Monte Carlo and empirical analysis comparing different types of jump tests used in the specification process associated with fitting continuous time models of financial variables. 1 We focus on tests due to Barndorff-Nielsen and Shephard (2006); Lee and Mykland (2008); Aït-Sahalia and Jacod (2009); Corsi et al (2010), and Podolskij and Ziggel (2010), who study "fixed time span" jump tests; and tests due to Corradi et al (2014) and Corradi et al (2018) who study so-called "long time span" jump 1 In risk management and financial engineering, investors and researchers often require knowledge of the data generating process (DGP) that governs asset price movements. For example, asset prices are frequently modeled as continuous-time processes, such as (Itô-)semimartingales (see, e.g., Aït-Sahalia (2002a, 2002b; Chernov et al (2003); and Andersen et al (2007b)).…”

Section: Introductionmentioning

confidence: 99%

“…In our experiments, we consider two types of the CSS1 jump test (i.e., CSS1 and CSS1 tests). Both of these build on earlier work of Aït-Sahalia (2002a, 2002b, and are special cases of the CSS test introduced in Corradi et al (2018). One test assumes no leverage.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, when the jump intensity is 0.4 and the jump size parameter is our largest, rejection rates of the ASJ, BNS and PZ tests at a 0.05 significance level are only around 0.26, 0.38, and 0.36, respectively. Second, sequential testing bias grows rapidly as 2 Specifically, when focusing on long time span tests, we evaluate the CSS test of Corradi et al (2018), and the CSS1 test of Corradi et al (2014). In an interesting paper related to this paper, Huang and Tauchen (2005) discuss issues associated with applying asymptotic approximations used in fixed time span jump tests over an (long time span) entire sample.…”

Section: Introductionmentioning

confidence: 99%

“…They suggest that an appropriate way to solve both inconsistency and size distortion problems associated with fixed time span jump tests is to use test statistics that are asymptotically valid under a double asymptotic scheme where both T → ∞ and ∆ → 0. This is the approach taken by Corradi et al (2018). 4 It is important to note that these tests have a different null hypotheses than fixed time span tests.…”

Section: Introductionmentioning

confidence: 99%

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Fixed and Long Time Span Jump Tests: New Monte Carlo and Empirical Evidence

Cheng

Swanson

2019

Econometrics

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Numerous tests designed to detect realized jumps over a fixed time span have been proposed and extensively studied in the financial econometrics literature. These tests differ from “long time span tests” that detect jumps by examining the magnitude of the jump intensity parameter in the data generating process, and which are consistent. In this paper, long span jump tests are compared and contrasted with a variety of fixed span jump tests in a series of Monte Carlo experiments. It is found that both the long time span tests of Corradi et al. (2018) and the fixed span tests of Aït-Sahalia and Jacod (2009) exhibit reasonably good finite sample properties, for time spans both short and long. Various other tests suffer from finite sample distortions, both under sequential testing and under long time spans. The latter finding is new, and confirms the “pitfall” discussed in Huang and Tauchen (2005), of using asymptotic approximations associated with finite time span tests in order to study long time spans of data. An empirical analysis is carried out to investigate the implications of these findings, and “time-span robust” tests indicate that the prevalence of jumps is not as universal as might be expected.

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Section: Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fixed and Long Time Span Jump Tests: New Monte Carlo and Empirical Evidence

Cheng

Swanson

2019

Econometrics

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Information shocks, market returns and volatility: a comparative analysis of developed equity markets in Asia

et al. 2023

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This research explores the function of information shocks in equity returns and integrated volatility of emerging Asian markets using Swap Variance (SwV) approach on the period of 20 years (Feb 2001–Feb 2020). It compares average monthly returns and volatility of shock periods with non-shock periods after separating negative and positive shocks. Findings reveal frequent occurrence of information shocks in all Asian developed equity markets with positive shocks than that of negative shocks. Moreover, highly volatile Asian developed markets earn higher returns during shocks periods, while markets with higher volatility and lower continuous returns are adversely affected during shocks periods. The ratio of total realized volatility and the average ratio of shocks volatility establish that shocks account for a considerable amount of volatility, and integrated volatility is higher during negative shocks phases. The study has implications for all stakeholders of financial markets for rational investment decisions.

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