There's more to volatility than volume

Fabrizio Lillo, J. Doyne Farmer, Fabrizio Lillo, László Gillemot

Risultato della ricerca: Article

43 Citazioni (Scopus)

Abstract

it is widely believed that fluctuations in transaction volume, as reflected in the number of transactions and to a lesser extent their size, are the main cause of clustered volatility. Under this view bursts of rapid or slow price diffusion reflect bursts of frequent or less frequent trading, which cause both clustered volatility and heavy tails in price returns. We investigate this hypothesis using tick by tick data from the New York and London Stock Exchanges and show that only a small fraction of volatility fluctuations are explained in this manner. Clustered volatility is still very strong even if price changes are recorded on intervals in which the total transaction volume or number of transactions is held constant. In addition the distribution of price returns conditioned on volume or transaction frequency being held constant is similar to that in real time, making it clear that neither of these are the principal cause of heavy tails in price returns. We analyse recent results of Ane and Geman (2000: J. Finance, 55, 2259-2284) and Gabaix et al. (2003: Nature, 423, 267-270), and discuss the reasons why their conclusions differ from ours. Based on a cross-sectional analysis we show that the long-memory of volatility is dominated by factors other than transaction frequency or total trading volume
Lingua originaleEnglish
pagine (da-a)371-384
Numero di pagine14
RivistaQuantitative Finance
Volume6
Stato di pubblicazionePublished - 2006

Fingerprint

Heavy tails
Ticks
Fluctuations
Trading volume
Price changes
Factors
Nature
London Stock Exchange
Long memory
New York Stock Exchange
Cross-sectional analysis
Finance

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics, Econometrics and Finance(all)

Cita questo

Lillo, F., Farmer, J. D., Lillo, F., & Gillemot, L. (2006). There's more to volatility than volume. Quantitative Finance, 6, 371-384.

There's more to volatility than volume. / Lillo, Fabrizio; Farmer, J. Doyne; Lillo, Fabrizio; Gillemot, László.

In: Quantitative Finance, Vol. 6, 2006, pag. 371-384.

Risultato della ricerca: Article

Lillo, F, Farmer, JD, Lillo, F & Gillemot, L 2006, 'There's more to volatility than volume', Quantitative Finance, vol. 6, pagg. 371-384.
Lillo F, Farmer JD, Lillo F, Gillemot L. There's more to volatility than volume. Quantitative Finance. 2006;6:371-384.
Lillo, Fabrizio ; Farmer, J. Doyne ; Lillo, Fabrizio ; Gillemot, László. / There's more to volatility than volume. In: Quantitative Finance. 2006 ; Vol. 6. pagg. 371-384.
@article{7a52ff5153fe4119b9bc5997eda52ee6,
title = "There's more to volatility than volume",
abstract = "it is widely believed that fluctuations in transaction volume, as reflected in the number of transactions and to a lesser extent their size, are the main cause of clustered volatility. Under this view bursts of rapid or slow price diffusion reflect bursts of frequent or less frequent trading, which cause both clustered volatility and heavy tails in price returns. We investigate this hypothesis using tick by tick data from the New York and London Stock Exchanges and show that only a small fraction of volatility fluctuations are explained in this manner. Clustered volatility is still very strong even if price changes are recorded on intervals in which the total transaction volume or number of transactions is held constant. In addition the distribution of price returns conditioned on volume or transaction frequency being held constant is similar to that in real time, making it clear that neither of these are the principal cause of heavy tails in price returns. We analyse recent results of Ane and Geman (2000: J. Finance, 55, 2259-2284) and Gabaix et al. (2003: Nature, 423, 267-270), and discuss the reasons why their conclusions differ from ours. Based on a cross-sectional analysis we show that the long-memory of volatility is dominated by factors other than transaction frequency or total trading volume",
keywords = "financial markets, subordinated processes, volatility, volume",
author = "Fabrizio Lillo and Farmer, {J. Doyne} and Fabrizio Lillo and L{\'a}szl{\'o} Gillemot",
year = "2006",
language = "English",
volume = "6",
pages = "371--384",
journal = "Quantitative Finance",
issn = "1469-7688",
publisher = "Routledge",

}

TY - JOUR

T1 - There's more to volatility than volume

AU - Lillo, Fabrizio

AU - Farmer, J. Doyne

AU - Lillo, Fabrizio

AU - Gillemot, László

PY - 2006

Y1 - 2006

N2 - it is widely believed that fluctuations in transaction volume, as reflected in the number of transactions and to a lesser extent their size, are the main cause of clustered volatility. Under this view bursts of rapid or slow price diffusion reflect bursts of frequent or less frequent trading, which cause both clustered volatility and heavy tails in price returns. We investigate this hypothesis using tick by tick data from the New York and London Stock Exchanges and show that only a small fraction of volatility fluctuations are explained in this manner. Clustered volatility is still very strong even if price changes are recorded on intervals in which the total transaction volume or number of transactions is held constant. In addition the distribution of price returns conditioned on volume or transaction frequency being held constant is similar to that in real time, making it clear that neither of these are the principal cause of heavy tails in price returns. We analyse recent results of Ane and Geman (2000: J. Finance, 55, 2259-2284) and Gabaix et al. (2003: Nature, 423, 267-270), and discuss the reasons why their conclusions differ from ours. Based on a cross-sectional analysis we show that the long-memory of volatility is dominated by factors other than transaction frequency or total trading volume

AB - it is widely believed that fluctuations in transaction volume, as reflected in the number of transactions and to a lesser extent their size, are the main cause of clustered volatility. Under this view bursts of rapid or slow price diffusion reflect bursts of frequent or less frequent trading, which cause both clustered volatility and heavy tails in price returns. We investigate this hypothesis using tick by tick data from the New York and London Stock Exchanges and show that only a small fraction of volatility fluctuations are explained in this manner. Clustered volatility is still very strong even if price changes are recorded on intervals in which the total transaction volume or number of transactions is held constant. In addition the distribution of price returns conditioned on volume or transaction frequency being held constant is similar to that in real time, making it clear that neither of these are the principal cause of heavy tails in price returns. We analyse recent results of Ane and Geman (2000: J. Finance, 55, 2259-2284) and Gabaix et al. (2003: Nature, 423, 267-270), and discuss the reasons why their conclusions differ from ours. Based on a cross-sectional analysis we show that the long-memory of volatility is dominated by factors other than transaction frequency or total trading volume

KW - financial markets

KW - subordinated processes

KW - volatility

KW - volume

UR - http://hdl.handle.net/10447/23444

M3 - Article

VL - 6

SP - 371

EP - 384

JO - Quantitative Finance

JF - Quantitative Finance

SN - 1469-7688

ER -