What Are the Best Liquidity Proxies for Global Research?*

Fong, Kingsley Y. L.; Holden, Craig W.; Trzcinka, Charles

doi:10.1093/rof/rfx003

Cited by 356 publications

(113 citation statements)

References 39 publications

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“…21 The last column 20 Other possible measures include the Pástor and Stambaugh (2003) Gamma, the Zero measure by Lesmond, Ogden, and Trzcinka (1999) and the Hasbrouck (2004) Gibbs measure. Goyenko, Holden, andTrzcinka (2009) andFong, Holden, andTrzcinka (2011) run horse races among different liquidity proxies and recommend the Amihud (2002) measure as a good proxy of market illiquidity.…”

Section: Comparison With Market Illiquiditymentioning

confidence: 99%

International Illiquidity

Malkhozov

Mueller

Vedolin

2017

Int. finance discuss. pap.

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We build a parsimonious international asset pricing model in which deviations of government bond yields from a fitted yield curve of a country measure the tightness of investors' capital constraints. We compute these measures at daily frequency for six major markets and use them to test the modelpredicted effect of funding conditions on asset prices internationally. Global illiquidity lowers the slope and increases the intercept of the international security market line. Local illiquidity helps explain the variation in alphas, Sharpe ratios, and the performance of betting-against-beta (BAB) strategies across countries. The recent financial crisis has dramatically illustrated how market frictions can impede orderly investment activity and have significant effects on asset prices.1 These phenomena are even more prominent when looking at asset prices in an international context where specialized institutions, such as hedge funds and investment banks, are responsible for a large fraction of active cross-country investments. In order to understand the specific mechanisms at work and to test various friction-based asset pricing theories, researchers and policymakers alike require economically-motivated indicators of market stress.In this paper, we study the effect of frictions, such as funding constraints or barriers that impede smooth cross-border movement of capital, on asset prices internationally.We generically refer to the tightness of these frictions as illiquidity. Our contribution to the existing literature is threefold. First, we develop a parsimonious international asset pricing model with constrained investors who trade in equity and bond markets globally.Second, we construct model-implied proxies for country-level and global illiquidity from daily bond market data of six developed countries. Third, in line with the model predictions, we find that global illiquidity affects the international risk-return trade-off by lowering the slope and increasing the intercept of the international security market line, stocks in countries with higher local illiquidity earn higher alphas and Sharpe ratios, and, as a result, accounting for the cross-country differences in illiquidity improves on the performance of traditional betting-against-beta (BAB) type strategies.We measure illiquidity as the average squared deviation of observed government bond prices from those implied by a smooth fitted yield curve. This approach has been proposed by Hu, Pan, and Wang (2013), who argue that "noise" in the US Treasury yield curve contains a strong signal about the general scarcity of investment capital in financial markets. Government bonds are particularly well suited in this context because they are among the safest and most liquid assets, they are actively traded for investment purposes, and they are used as the main source of collateral to obtain funding.Moreover, their prices are known to be well described by a simple factor structure during normal times. In our model bond price deviations emerge in equilibrium because ...

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Section: Comparison With Market Illiquiditymentioning

confidence: 99%

International Illiquidity

Malkhozov

Mueller

Vedolin

2017

Int. finance discuss. pap.

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“…The first measure is a proxy for the proportional bid-ask spread and reflects the trading cost of small transactions. The measure developed by Fong, Holden and Trzcinka (2017) is a simplification of the earlier measure developed by Lesmond, Ogden and Trzcinka (1999). It is based on the same assumption, but is less demanding in terms of computational efforts.…”

Section: Methodsmentioning

confidence: 99%

Stock liquidity on the Warsaw Stock Exchange in the 21st century: Time-series and cross-sectional dependencies

Stereńczak

2018

Zeszyty Naukowe Uniwersytetu Szczecińskiego Finanse Rynki Finansowe Ubezpieczenia

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Purpose -The aim of the study is to describe the dynamics of market liquidity and cross-sectional variation in stock liquidity on the Warsaw Stock Exchange in the years [2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013][2014][2015][2016]. Design/methodology/approach -To measure stock liquidity three measures have been applied, namely the FHT measure of transaction costs, and the intra-daily version of Amihud's ILLIQ to measure price impact and trading volume to measure trading activity. Measures were computed for the monthly intervals, and to compute market-wide liquidity equally-weighted and volume-weighted averages of liquidity of all listed companies were used. Findings -The main finding is that market liquidity commoves with the Warsaw Stock Exchange Index (WIG) and the cross-sectional variation of stock liquidity increases with the decrease of market liquidity. Originality/value -To the best of the author's knowledge, this is the first study on the cross-sectional variation in stock liquidity on the WSE.

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“…Although our analysis is confined to daily data, the number of available liquidity proxies is still large. Fong et al (2017) give an overview about daily and monthly liquidity measures on the stock market and compare their performance to high-frequency measures. The analysis reveals the closing percentage quoted spread and the Amihud (2002) ratio as the best daily liquidity proxies.…”

Section: Liquidity Measuresmentioning

confidence: 99%

Drivers of seasonal return patterns in German stocks

Weigerding

Hanke

2018

Bus Res

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Using a data set of German stocks that includes the financial crisis, this paper identifies market liquidity as the main driver of return seasonality. In comparison, the economic significance of order flow imbalance is markedly weaker. Applying panel regressions and controlling for unobserved effects, we investigate the effects of both variables simultaneously, together with dummies for calendar effects. US macroeconomic news announcements, which have been identified as one driver of return seasonality in previous studies using non-US data, are of little importance for our data set of German stocks.

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What Are the Best Liquidity Proxies for Global Research?*

Cited by 356 publications

References 39 publications

International Illiquidity

International Illiquidity

Stock liquidity on the Warsaw Stock Exchange in the 21st century: Time-series and cross-sectional dependencies

Drivers of seasonal return patterns in German stocks

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