Stock and Bond Market Liquidity: A Long-Run Empirical Analysis

Goyenko, Ruslan; Ukhov, Andrey D.

doi:10.2139/ssrn.669942

Cited by 47 publications

(54 citation statements)

References 52 publications

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“…It is expected that market liquidity is influenced by factors that affect simultaneously the risk of many firms, so macroeconomic variables seem to be good candidates. Despite the prevalence of some ambiguity, main results suggest that monetary policy plays an important role in explaining time variation of systematic liquidity (Watanabe 2004;Chordia et al 2005;Goyenko and Ukhov 2009;Fernández-Amador et al 2013, among others). It seems that an expansionary (a recessive) monetary policy is associated with an increase (a decrease) in stock market liquidity.…”

Section: Inter-temporal Variation Of Systematic Liquiditymentioning

confidence: 99%

“…Following Chordia et al (2005), Goyenko and Ukhov (2009) wide the empirical evidence about liquidity in US bond and stock market and cross relations between these markets. They use bid-ask spreads to proxy for Treasury bond liquidity and Amihud (2002) illiquidity ratio for stock market liquidity.…”

Section: Inter-temporal Variation Of Systematic Liquiditymentioning

confidence: 99%

“…However, it is important to understand the sources of systematic liquidity variation due to its impacts on returns. The latest and incipient research has been directed at filling this gap (Chordia et al 2001;Chordia et al 2005;Miralles-Marcelo et al 2007;Goyenko and Ukhov 2009;Lu and Glascock 2010;Jensen and Moorman 2010;Naes et al 2011;Fernández-Amador et al 2013). The empirical evidence reported is at some extent ambiguous, but some macroeconomic factors were identified as determinants of time variation of liquidity.…”

Section: Introductionmentioning

confidence: 99%

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Systematic liquidity: commonality and inter-temporal variation in the Portuguese stock market

2015

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The aim of this paper is to study systematic liquidity at the Euronext Lisbon Stock Exchange. The motivation for this research is provided by the growing interest in financial literature about stock liquidity and the implications of commonality in liquidity for asset pricing since it could represent a source of non-diversifiable risk. Namely, it is analysed whether there exist common factors that drive the variation in individual stock liquidity and the causes of the inter-temporal variation of aggregate liquidity. Monthly data for the period between January 1988 and December 2011 is used to compute some of the most used proxies for liquidity: bid-ask spreads, turnover rate, trading volume, proportion of zero returns and the illiquidity ratio. Following Chordia et al. (2000) methodology, some evidence of commonality in liquidity is found in the Portuguese stock market when the proportion of zero returns is used as a measure of liquidity. In relation to the factors that drive the inter-temporal variation of the Portuguese stock market liquidity, the results obtained within a VAR framework suggest that changes in real economy activity, monetary policy (proxied by changes in monetary aggregate M1) and stock market returns play an important role as determinants of commonality in liquidity.

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Section: Inter-temporal Variation Of Systematic Liquiditymentioning

confidence: 99%

Section: Inter-temporal Variation Of Systematic Liquiditymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Systematic liquidity: commonality and inter-temporal variation in the Portuguese stock market

2015

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“…2 The most commonly used measure in the recent empirical literature is the price impact ratio of Amihud (2002), which is defined as the average monthly ratio of daily absolute returns to daily trading volume in monetary terms (henceforth, RtoV) (see e.g. Acharya and Pedersen (2005), Korajczyk and Sadka (2008), Goyenko and Ukhov (2009)). This measure is appealing because it is easy to compute for long time periods given the wide availability of returns and trading volume data.…”

Section: Introductionmentioning

confidence: 99%

Trading frequency and asset pricing on the London Stock Exchange: Evidence from a new price impact ratio

Florackis

Gregoriou

Kostakis

2011

Journal of Banking & Finance

119

155

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In this study we propose a new price impact ratio as an alternative to the widely used Amihud's (2002) Return-to-Volume ratio (RtoV). This new measure, which is deemed Return-to-Turnover ratio (RtoTR), essentially modifies RtoV by substituting trading volume in its denominator with the turnover ratio for each security. We demonstrate that the new price impact ratio has a number of appealing features. Using daily data from all stocks listed on the London Stock Exchange over the period 1991-2008, we provide overwhelming evidence that this ratio, while being unequivocal to construct and interpret, is also free of a size bias. More importantly, it encapsulates the stocks' cross-sectional variability in trading frequency, a relatively neglected but possibly important determinant of stock returns given the recently observed trends in financial markets. Overall, our findings argue against the conventional wisdom that there is a simple direct link between trading costs and stock prices by strongly suggesting that it is the compound effect of trading frequency and transaction costs that matters for asset pricing, not each aspect in isolation. JEL classification: G10; G12; G14 Trading Frequency and Asset Pricing on the London Stock Exchange:Evidence from a New Price Impact Ratio AbstractIn this study we propose a new price impact ratio as an alternative to the widely used Amihud's (2002) Return-to-Volume ratio (RtoV). This new measure, which is deemed Return-to-Turnover ratio (RtoTR), essentially modifies RtoV by substituting trading volume in its denominator with the turnover ratio for each security. We demonstrate that the new price impact ratio has a number of appealing features. Using daily data from all stocks listed on the London Stock Exchange over the period 1991-2008, we provide overwhelming evidence that this ratio, while being unequivocal to construct and interpret, is also free of a size bias. More importantly, it encapsulates the stocks' cross-sectional variability in trading frequency, a relatively neglected but possibly important determinant of stock returns given the recently observed trends in financial markets. Overall, our findings argue against the conventional wisdom that there is a simple direct link between trading costs and stock prices by strongly suggesting that it is the compound effect of trading frequency and transaction costs that matters for asset pricing, not each aspect in isolation.

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“…As the name suggests, investors faced with uncertainty seek a safe haven for their wealth where it is protected from loss. This phenomenon is most commonly characterised by the movement of investors' money from equity markets into bond markets or cash (Goyenko & Ukhov, 2009). This allows holders of safe-haven assets to experience greater returns than equity holders, as these returns are less volatile and less affected by economic downturns.…”

Section: Introductionmentioning

confidence: 99%