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The Journal of Finance, 1994 Abstract The efficiency of security prices depends upon arbitrage, that is, trading based upon knowledge that the price of an asset is different from its fundamental value. (Although the term ‘arbitrage,’ strictly speaking, refers to an entirely riskless speculation, we use the term in the broader sense common among practitioners.) For ...
James Dow, Gary Gorton
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Ordering Arbitrage Portfolios and Finding Arbitrage Opportunities
SSRN Electronic Journal, 2021Concepts are introduced for analyzing arbitrage portfolios in the face of ambiguity about investor risk preferences and initial portfolio holdings. A Stochastic Arbitrage Opportunity is a self-financing overlay portfolio which enhances every feasible host portfolio for all relevant utility functions.
Stelios Arvanitis, Thierry Post
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Do Limits to Arbitrage Explain the Benefits of Volatility-Managed Portfolios?
Journal of Financial Economics, 2020We investigate whether transaction costs, arbitrage risk, and short-sale constraints explain the abnormal returns of volatility-managed equity portfolios.
Pedro Barroso, Andrew Detzel
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No Arbitrage and Arbitrage Pricing: A New Approach
The Journal of Finance, 1993ABSTRACTWe argue that arbitrage‐pricing theories (APT) imply the existence of a low‐dimensional nonnegative nonlinear pricing kernel. In contrast to standard constructs of the APT, we do not assume a linear factor structure on the payoffs. This allows us to price both primitive and derivative securities.
Bansal, Ravi, Viswanathan, S
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Between autonomy and control: Strategies of arbitrage in the “on-demand” economy
New Media & Society, 2018The “on-demand” economy is built upon company strategies of arbitrage between worker autonomy and worker control. Using ethnographic and interview data, I show how these strategies undermine the economic theory that justifies the on-demand business model.
Aaron Shapiro
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Intraday Arbitrage Between ETFs and their Underlying Portfolios
Journal of Financial Economics, 2020Prior research suggests that ETF arbitrage affects the market quality of underlying securities. We directly test this proposition by examining minute-by-minute returns and order imbalances, but find little evidence that trading in ETFs impacts the ...
Travis Box +3 more
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Left-Tail Momentum: Underreaction to Bad News, Costly Arbitrage and Equity Returns
Journal of Financial Economics, 2017This paper documents a significantly negative cross-sectional relation between left-tail risk and future returns on individual stocks trading in the US and international countries.
Yigit Atilgan +3 more
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Annual Review of Financial Economics, 2010
We survey theoretical developments in the literature on the limits of arbitrage. This literature investigates how costs faced by arbitrageurs can prevent them from eliminating mispricings and providing liquidity to other investors. Research in this area is currently evolving into a broader agenda, emphasizing the role of financial institutions and ...
Dimitri Vayanos +3 more
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We survey theoretical developments in the literature on the limits of arbitrage. This literature investigates how costs faced by arbitrageurs can prevent them from eliminating mispricings and providing liquidity to other investors. Research in this area is currently evolving into a broader agenda, emphasizing the role of financial institutions and ...
Dimitri Vayanos +3 more
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SSRN Electronic Journal, 2018 AbstractWe study the dynamics of cash-and-carry arbitrage using the U.S. crude oil market. Sizable arbitrage-related inventory movements occur at the New York Mercantile Exchange (NYMEX) futures contract delivery point but not at other storage locations, where instead, operational factors explain most inventory changes.
Louis H. Ederington +4 more
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Nearly Exact Bayesian Estimation of Non-linear No-Arbitrage Term-Structure Models*
Journal of Financial Econometrics, 2018We propose a general method for the Bayesian estimation of a very broad class of non-linear no-arbitrage term-structure models. The main innovation we introduce is a computationally efficient method, based on deep learning techniques, for approximating
Marcello Pericoli, Marco Taboga
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