1998
DOI: 10.2139/ssrn.128888
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Liquidity in the Futures Pits: Inferring Market Dynamics with Incomplete Data

Abstract: Motivated by economic models of sequential trade, empirical analyses of market dynamics frequently estimate liquidity as the coefficient of signed order flow in a pricechange regression. This paper implements such an analysis for futures transaction data from pit trading. To deal with the absence of timely bid and ask quotes (which are used to sign trades in most equity-market studies), this paper proposes new techniques based on

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Cited by 27 publications
(1 citation statement)
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References 74 publications
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“…The rank and signed variance ratio test was applied to test the market validity and obtained a weak form of validity for the European carbon emissions trading market over the period 2011-2022 [7]. In the study on market liquidity, incomplete data were applied to the study of dynamic market liquidity in traditional futures trading pools in the US [8]. The new liquidity ratio indicator was constructed for a study of the EUA futures market, which concluded that market liquidity was increasing in the first phase [9].…”
Section: Introductionmentioning
confidence: 99%
“…The rank and signed variance ratio test was applied to test the market validity and obtained a weak form of validity for the European carbon emissions trading market over the period 2011-2022 [7]. In the study on market liquidity, incomplete data were applied to the study of dynamic market liquidity in traditional futures trading pools in the US [8]. The new liquidity ratio indicator was constructed for a study of the EUA futures market, which concluded that market liquidity was increasing in the first phase [9].…”
Section: Introductionmentioning
confidence: 99%