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High-frequency volatility estimation and the relative importance of market microstructure variables

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@techreport{33afb8f62ecf44cebe03dccdeefab47b,
title = "High-frequency volatility estimation and the relative importance of market microstructure variables",
abstract = "In this paper we use an autoregressive conditional intensity approach to estimate local high-frequency volatility, and examine to what extent a large universe of market microstructure variables affects local volatility. Our findings support a sequential information arrival hypothesis on the high-frequency level since we show that contemporaneous trading volume is negatively, and lagged trading volume is positively related to local volatility. The use of a penalized likelihood method allows us to obtain a ranking in terms of the relative importance of all market microstructure variables considered. We find that, in a descending order, contemporaneous volume, bid-ask spread, absolute order imbalance, absolute order flow and absolute quote difference carry the most important information for local volatility modelling.",
keywords = "High-Frequency Volatility Estimation, Market Microstructure Effects, Volume-Volatility Relationship, ACI Model ",
author = "Yifan Li and Ingmar Nolte and Sandra Nolte",
year = "2015",
month = sep,
day = "25",
language = "English",
type = "WorkingPaper",

}

RIS

TY - UNPB

T1 - High-frequency volatility estimation and the relative importance of market microstructure variables

AU - Li, Yifan

AU - Nolte, Ingmar

AU - Nolte, Sandra

PY - 2015/9/25

Y1 - 2015/9/25

N2 - In this paper we use an autoregressive conditional intensity approach to estimate local high-frequency volatility, and examine to what extent a large universe of market microstructure variables affects local volatility. Our findings support a sequential information arrival hypothesis on the high-frequency level since we show that contemporaneous trading volume is negatively, and lagged trading volume is positively related to local volatility. The use of a penalized likelihood method allows us to obtain a ranking in terms of the relative importance of all market microstructure variables considered. We find that, in a descending order, contemporaneous volume, bid-ask spread, absolute order imbalance, absolute order flow and absolute quote difference carry the most important information for local volatility modelling.

AB - In this paper we use an autoregressive conditional intensity approach to estimate local high-frequency volatility, and examine to what extent a large universe of market microstructure variables affects local volatility. Our findings support a sequential information arrival hypothesis on the high-frequency level since we show that contemporaneous trading volume is negatively, and lagged trading volume is positively related to local volatility. The use of a penalized likelihood method allows us to obtain a ranking in terms of the relative importance of all market microstructure variables considered. We find that, in a descending order, contemporaneous volume, bid-ask spread, absolute order imbalance, absolute order flow and absolute quote difference carry the most important information for local volatility modelling.

KW - High-Frequency Volatility Estimation

KW - Market Microstructure Effects

KW - Volume-Volatility Relationship

KW - ACI Model

M3 - Working paper

BT - High-frequency volatility estimation and the relative importance of market microstructure variables

ER -