Stochastic volatility models including open, close, high and low prices

Abstract

ABSTRACT. Mounting empirical evidence suggests that the observed extreme prices within a trading period can provide valuable information about the volatility of the process within that period. In this paper we define a class of stochastic volatility models that uses opening and closing prices along with the minimum and maximum prices within a trading period to infer the dynamics underlying the volatility process of asset prices and compares it with similar models that have been previously presented in the literature. The paper also discusses sequential Monte Carlo algorithms to fit this class of models and illustrates its features using both a simulation study and data form the S&P500 index.

Correlation network analysis for multi-dimensional data in stocks market

“…The data are available for most series through the common data providers (e.g., Datastream, Reuters, Bloomberg), and it provides several advantages. As mentioned in Introduction section, the relevance of OHLC prices data is well-known [22][23][24][25][26].…”

“…All of the models of stocks market have focused on the behavior of price returns and losing the possibility of embodying information from opening price, highest price and lowest price. The importance of opening, highest, lowest and closing (OHLC in short) prices information is wellknown and has been used by a number of authors, including Rogers and Satchell [22], Rogers et al [23], Rogers [24], Rogers and Zhou [25] and Horst et al [26].…”

Information Theoretic Ranking of Extreme Value Returns

“…Ong (2015) employed information theory to examine the dynamic relationships between stock returns, volatility and trading volumes for SP 500 stocks. Literature in this context has shown evidence that the information contained in the level of the extreme returns (which is lost while using the observed ranges for inferences) can also contribute to more efficient estimation of volatility (Horst et. al., 2012).…”

Market Quality and Structural Changes in the Trading System: The Case of X-Stream on the Colombian Stock Exchange

“…4 . We acknowledge the existence of more elaborate models that allow a better estimation of intra-day volatility, as the stochastic volatility models discussed in Alizadeh, Brand andDiebolt (2002) andTer Hortes, Rodriguez, Gzyl andMolina (2012). However, we stick to the models used in our study because they have been used in previous market quality studies (see, for example, Liu and Zhu (2009)).…”