What happened to the quants in August 2007? Evidence from factors and transactions data

Khandani, Amir E.; Lo, Andrew W.

doi:10.1016/j.finmar.2010.07.005

Cited by 248 publications

(47 citation statements)

References 62 publications

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“…Other market participants observing this sale can join in the sell-off, and this pattern can continue for a few days. Khandani and Lo (2011) document this rapid deleveraging for quant hedge funds in August 2008. Note that these are not conventional fire sale, as the assets sold are highly liquid.…”

Section: Bank-bank Linkagementioning

confidence: 99%

The Robustness of the Sovereign-Bank Interconnection: Evidence from Contingent Claims Analysis

2018

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Section: Bank-bank Linkagementioning

confidence: 99%

The Robustness of the Sovereign-Bank Interconnection: Evidence from Contingent Claims Analysis

2018

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“…However, simple versions of such strategies have been proposed intellectual property. However, simple versions of such strategies have been proposed and studied by Lehmann (1990), Lo and MacKinlay (1990), and Khandani and Lo and studied by Lehmann (1990), Lo and MacKinlay (1990), and Khandani andLo (2007, 2011), and we provide a more detailed exposition of them in the sections (2007,2011), and we provide a more detailed exposition of them in the sections that follow. that follow.…”

Section: Arbitrage Tradingmentioning

confidence: 99%

Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents

Kirilenko

2013

Journal of Economic Perspectives

175

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Financial markets have undergone a remarkable transformation over the past two decades due to advances in technology. These advances include faster and cheaper computers, greater connectivity among market participants, and perhaps most important of all, more sophisticated trading algorithms. The benefits of such financial technology are evident: lower transactions costs, faster executions, and greater volume of trades. However, like any technology, trading technology has unintended consequences. In this paper, we review key innovations in trading technology starting with portfolio optimization in the 1950s and ending with high-frequency trading in the late 2000s, as well as opportunities, challenges, and economic incentives that accompanied these developments. We also discuss potential threats to financial stability created or facilitated by algorithmic trading and propose “Financial Regulation 2.0,” a set of design principles for bringing the current financial regulatory framework into the Digital Age.

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“…We view this new variable as a complement to a number of asset-class-speci…c liquidity measures (see, for example, Acharya and Pedersen (2005), Pastor and Stambaugh (2003), Khandani andLo (2011), andBongaerts, de Jong, andDriessen (2012)) that have been utilized extensively in the literature.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Hedge Funds on Asset Markets

2013

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This paper provides evidence of the impact of hedge funds on asset markets. We construct a simple measure of the aggregate illiquidity of hedge fund portfolios, based on the cross-sectional average …rst order autocorrelation coe¢ cient of hedge fund returns, and show that it has strong and robust in-and out-of-sample forecasting power for 72 portfolios of international equities, corporate bonds, and currencies over the 1994 to 2013 period. The forecasting ability of hedge fund illiquidity for asset returns is in most cases greater than, and provides independent information relative to, well-known predictive variables for each of these asset classes. We rationalize these …ndings using a simple equilibrium model in which hedge funds provide liquidity in asset markets.We thank Gavin Boyle, John Campbell, Wayne Ferson, Thierry Foucault, Rene Garcia, Andrew Lo, Narayan Naik, Martin Luehrmann, Kevin Sheppard, Denitsa Stefanova, Marta Szymanowska, David Thesmar, Dimitri Vayanos, Mungo Wilson, and seminar participants at the 2014 FMA Napa Conference, the 6th Annual Hedge Fund Research Conference in Paris, Erasmus University, HEC Paris, Imperial College, the Inquire UK and LBS Joint Conference, INSEAD, the Luxembourg Asset Management Summit, the Oxford-Man Institute of Quantitative Finance, Saïd Business School and the University of Sydney for helpful discussions and comments.y Kruttli is at Oxford-Man Institute of Quantitative Finance. Email: mathias.kruttli@gmail.com. Part of Kruttli's work on this paper was completed while being at Department of Economics, Oxford University. Patton is at Department of Economics, Duke University, and Oxford-Man Institute of Quantitative Finance. Email: andrew.patton@duke.edu. Part of Patton's work on this paper was completed while visiting the Discipline of Finance at the University of Sydney. Ramadorai is at Saïd Business School, Oxford University, Oxford-Man Institute, and CEPR. Email: tarun.ramadorai@sbs.ox.ac.uk. The Impact of Hedge Funds on Asset MarketsABSTRACT This paper provides evidence of the impact of hedge funds on asset markets. We construct a simple measure of the aggregate illiquidity of hedge fund portfolios, based on the cross-sectional average …rst order autocorrelation coe¢ cient of hedge fund returns, and show that it has strong and robust in-and out-of-sample forecasting power for 72 portfolios of international equities, corporate bonds, and currencies over the 1994 to 2013 period. The forecasting ability of hedge fund illiquidity for asset returns is in most cases greater than, and provides independent information relative to, well-known predictive variables for each of these asset classes. We rationalize these …ndings using a simple equilibrium model in which hedge funds provide liquidity in asset markets.

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What happened to the quants in August 2007? Evidence from factors and transactions data

Abstract: Using the simulated returns of long/short equity portfolios based on five valuation factors,

Cited by 248 publications

References 62 publications

The Robustness of the Sovereign-Bank Interconnection: Evidence from Contingent Claims Analysis

The Robustness of the Sovereign-Bank Interconnection: Evidence from Contingent Claims Analysis

Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents

The Impact of Hedge Funds on Asset Markets

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