Stock market volatility forecasting: Do we need high-frequency data?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14560%2F21%3A00119320" target="_blank" >RIV/00216224:14560/21:00119320 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61384399:31110/21:00056547

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0169207020301874" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0169207020301874</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ijforecast.2020.12.001" target="_blank" >10.1016/j.ijforecast.2020.12.001</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Stock market volatility forecasting: Do we need high-frequency data?

Popis výsledku v původním jazyce

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.

Název v anglickém jazyce

Stock market volatility forecasting: Do we need high-frequency data?

Popis výsledku anglicky

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50206 - Finance

Projekt

<a href="/cs/project/GA18-05829S" target="_blank" >GA18-05829S: Predikce volatility na rozvijících se finančních trzích</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of Forecasting

ISSN

0169-2070

e-ISSN

—

Svazek periodika

37

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

19

Strana od-do

1092-1110

Kód UT WoS článku

000656489100006

EID výsledku v databázi Scopus

2-s2.0-85098665343