Department of Economics and Business Economics

Time-Varying Periodicity in Intraday Volatility

Research output: Working paperResearch

Standard

Time-Varying Periodicity in Intraday Volatility. / Andersen, Torben Gustav; Thyrsgaard, Martin; Todorov, Viktor.

Aarhus : Institut for Økonomi, Aarhus Universitet, 2018.

Research output: Working paperResearch

Harvard

Andersen, TG, Thyrsgaard, M & Todorov, V 2018 'Time-Varying Periodicity in Intraday Volatility' Institut for Økonomi, Aarhus Universitet, Aarhus.

APA

Andersen, T. G., Thyrsgaard, M., & Todorov, V. (2018). Time-Varying Periodicity in Intraday Volatility. Aarhus: Institut for Økonomi, Aarhus Universitet. CREATES Research Papers, No. 2018-05

CBE

Andersen TG, Thyrsgaard M, Todorov V. 2018. Time-Varying Periodicity in Intraday Volatility. Aarhus: Institut for Økonomi, Aarhus Universitet.

MLA

Andersen, Torben Gustav, Martin Thyrsgaard and Viktor Todorov Time-Varying Periodicity in Intraday Volatility. Aarhus: Institut for Økonomi, Aarhus Universitet. (CREATES Research Papers; Journal number 2018-05). 2018., 59 p.

Vancouver

Andersen TG, Thyrsgaard M, Todorov V. Time-Varying Periodicity in Intraday Volatility. Aarhus: Institut for Økonomi, Aarhus Universitet. 2018 Jan 15.

Author

Andersen, Torben Gustav ; Thyrsgaard, Martin ; Todorov, Viktor. / Time-Varying Periodicity in Intraday Volatility. Aarhus : Institut for Økonomi, Aarhus Universitet, 2018. (CREATES Research Papers; No. 2018-05).

Bibtex

@techreport{b73473b7e47648d9b663c204e4136834,
title = "Time-Varying Periodicity in Intraday Volatility",
abstract = "We develop a nonparametric test for deciding whether return volatility exhibits time-varying intraday periodicity using a long time-series of high-frequency data. Our null hypothesis, commonly adopted in work on volatility modeling, is that volatility follows a stationary process combined with a constant time-of-day periodic component. We first construct time-of-day volatility estimates and studentize the high-frequency returns with these periodic components. If the intraday volatility periodicity is invariant over time, then the distribution of the studentized returns should be identical across the trading day. Consequently, the test is based on comparing the empirical characteristic function of the studentized returns across the trading day. The limit distribution of the test depends on the error in recovering volatility from discrete return data and the empirical process error associated with estimating volatility moments through their sample counterparts. Critical values are computed via easy-to-implement simulation. In an empirical application to S&P 500 index returns, we find strong evidence for variation in the intraday volatility pattern driven in part by the current level of volatility. When market volatility is elevated, the period preceding the market close constitutes a significantly higher fraction of the total daily integrated volatility than is the case during low market volatility regimes.",
keywords = "high-frequency data, periodicity, semimartingale, specification test, stochastic volatility",
author = "Andersen, {Torben Gustav} and Martin Thyrsgaard and Viktor Todorov",
year = "2018",
month = "1",
day = "15",
language = "English",
publisher = "Institut for {\O}konomi, Aarhus Universitet",
type = "WorkingPaper",
institution = "Institut for {\O}konomi, Aarhus Universitet",

}

RIS

TY - UNPB

T1 - Time-Varying Periodicity in Intraday Volatility

AU - Andersen,Torben Gustav

AU - Thyrsgaard,Martin

AU - Todorov,Viktor

PY - 2018/1/15

Y1 - 2018/1/15

N2 - We develop a nonparametric test for deciding whether return volatility exhibits time-varying intraday periodicity using a long time-series of high-frequency data. Our null hypothesis, commonly adopted in work on volatility modeling, is that volatility follows a stationary process combined with a constant time-of-day periodic component. We first construct time-of-day volatility estimates and studentize the high-frequency returns with these periodic components. If the intraday volatility periodicity is invariant over time, then the distribution of the studentized returns should be identical across the trading day. Consequently, the test is based on comparing the empirical characteristic function of the studentized returns across the trading day. The limit distribution of the test depends on the error in recovering volatility from discrete return data and the empirical process error associated with estimating volatility moments through their sample counterparts. Critical values are computed via easy-to-implement simulation. In an empirical application to S&P 500 index returns, we find strong evidence for variation in the intraday volatility pattern driven in part by the current level of volatility. When market volatility is elevated, the period preceding the market close constitutes a significantly higher fraction of the total daily integrated volatility than is the case during low market volatility regimes.

AB - We develop a nonparametric test for deciding whether return volatility exhibits time-varying intraday periodicity using a long time-series of high-frequency data. Our null hypothesis, commonly adopted in work on volatility modeling, is that volatility follows a stationary process combined with a constant time-of-day periodic component. We first construct time-of-day volatility estimates and studentize the high-frequency returns with these periodic components. If the intraday volatility periodicity is invariant over time, then the distribution of the studentized returns should be identical across the trading day. Consequently, the test is based on comparing the empirical characteristic function of the studentized returns across the trading day. The limit distribution of the test depends on the error in recovering volatility from discrete return data and the empirical process error associated with estimating volatility moments through their sample counterparts. Critical values are computed via easy-to-implement simulation. In an empirical application to S&P 500 index returns, we find strong evidence for variation in the intraday volatility pattern driven in part by the current level of volatility. When market volatility is elevated, the period preceding the market close constitutes a significantly higher fraction of the total daily integrated volatility than is the case during low market volatility regimes.

KW - high-frequency data, periodicity, semimartingale, specification test, stochastic volatility

M3 - Working paper

BT - Time-Varying Periodicity in Intraday Volatility

PB - Institut for Økonomi, Aarhus Universitet

CY - Aarhus

ER -