Lehman Brothers: Did Markets Know?

Gehrig, Thomas; Haas, Marlene

doi:10.2139/ssrn.2408489

Cited by 2 publications

(3 citation statements)

References 29 publications

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“…We estimate these three cost components using the Huang and Stoll (1997) spread decomposition, as refined by Gehrig and Haas (2015). In the framework of Huang and Stoll, order processing costs are identified by the variance of the bid-ask bounce, while inventory holding costs are identified by serial correlation of transactions prices and adverse selection costs are identified by changing means of relative bid-ask spreads.…”

Section: Decomposition Of Bid-ask Spreadsmentioning

confidence: 99%

“…The dependent variables are company specific average excess returns. The explanatory variables include a market return beta, adverse selection risk betas (measured according to Gehrig and Haas (2015) and set relative to stock prices, alternative measures of adverse selection risk betas (Kyle's lambda and the adverse selection measure of Hendershott et al (2011))), an inventory holding risk beta (inventory holding costs relative to stock prices), an order processing risk beta (order processing costs relative to stock prices), and the the Fama-French factors betas, all of which were estimated in the first stage of the estimation procedure. The underlying time period covers the years of 1905 to 1910.…”

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confidence: 99%

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Rumors and Runs in Opaque Markets: Evidence from the Panic of 1907

Fohlin

Gehrig

Haas³

2015

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. and 1910, we study the impact of information asymmetry during the liquidity freeze and market run of October 1907 -one of the most severe financial crises of the 20th century. We estimate that the market run drove up spreads from 0.5% to 3% during the peak of the crisis and, using a spread decomposition, we identify information risk as the largest component of illiquidity. Terms of use: Documents inInformation costs rose most in the mining sector -the origin of the stock corner and a sector with among the worst track records of corporate governance and accounting. We find other hallmarks of information-based illiquidity: trading volume dropped and price impact rose. Despite short-term cash infusions into the market, the market remained relatively illiquid for several months following the peak of the panic. Notably, market illiquidity risk is priced in the cross section of stock returns. Thus, our findings demonstrate how opaque systems allow idiosyncratic rumors to spread and amplify into a long-lasting, market-wide crisis.JEL-Codes: G000, G140, N000, N200.

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Section: Decomposition Of Bid-ask Spreadsmentioning

confidence: 99%

mentioning

confidence: 99%

Rumors and Runs in Opaque Markets: Evidence from the Panic of 1907

Fohlin

Gehrig

Haas³

2015

SSRN Journal

Self Cite

View full text Add to dashboard Cite

show abstract

“…The dependent variables are company specific average excess returns. The explanatory variables include a market return beta, adverse selection risk betas (measured according to Gehrig and Haas (2015) and set relative to stock prices, alternative measures of adverse selection risk betas (Kyle's lambda and the adverse selection measure of Hendershott et al (2011))), an inventory holding risk beta (inventory holding costs relative to stock prices), an order processing risk beta (order processing costs relative to stock prices), and the the Fama-French factors betas, all of which were estimated in the first stage of the estimation procedure. This table reports the results of quantile regression of relative bid-ask spreads on low call money rates and controls for volatility, share price, and panic indicator variables.…”

Section: Discussionmentioning

confidence: 99%