A trading simulation test for weak‐form efficiency in live cattle futures

Kastens, Terry L.; Schroeder, Ted C.

doi:10.1002/fut.3990150605

Cited by 14 publications

(4 citation statements)

References 25 publications

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“…This is consistent with previous results, e.g. Kastens and Schroeder (1995) simulated various trading strategies which outperformed the live cattle futures market over a thirty year period. It was also found that the live cattle futures market contains a short-run timevarying risk premium.…”

Section: V C O N C L U S I O N Ssupporting

confidence: 91%

“…The question of to what extent, if any, have livestock futures markets experienced periods of downward bias has generated much empirical research. See, for example, Martin and Garcia (1981), Kolb and Gray (1983), Hayenga et al (1984), and more recently, Deaves and Krinsky (1995), and Kastens and Schroeder (1995). In a similar vein, hedging returns for livestock producers would be limited if corn and soybean meal futures prices are biased upward.…”

Section: Introductionmentioning

confidence: 95%

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Market efficiency in agricultural futures markets

McKenzie¹,

Holt²

2002

Applied Economics

131

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Market efficiency and unbiasedness are tested in four agricultural commodity futures markets - live cattle, hogs, corn, and soybean meal - using cointegration and error correction models with GQARCH-in-mean processes. Results indicate each market is unbiased in the long run, although cattle, hogs and corn futures markets exhibit short-run inefficiencies and pricing biases. Models for cattle and corn outperform futures prices in out-of-sample forecasting. Results also suggest short-run time-varying risk premiums in cattle and hog futures markets.

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Section: V C O N C L U S I O N Ssupporting

confidence: 91%

Section: Introductionmentioning

confidence: 95%

Market efficiency in agricultural futures markets

McKenzie¹,

Holt²

2002

Applied Economics

131

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“…If our findings have practical values, trading based on "liked" threads should not generate superior profits. Following the trading simulation guidelines in the literature (Kastens and Schroeder, 1995;Xie et al, 2020), we designed four trading strategies: "random", "buy-lowsell-high", "liked threads" and "disliked threads". The first two trading strategies serve as benchmarks for comparison.…”

Section: Trading Simulationmentioning

confidence: 99%

The failure of online endorsement systems in investment communities: evidence from Yahoo! Finance

Xie

et al. 2023

ITP

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PurposeIn prior literature, online endorsement system allowing the users to “like” or “dislike” shared information is found very useful in information filtering and trust elicitation in most social networks. This paper shows that such systems could fail in the context of investment communities due to several psychological biases.Design/methodology/approachThis study develops a series of regression analyses to model the “like”/“dislike” voting process and whether or not such endorsement distinguishes between valuable information and noise. Trading simulations are also used to validate the practical implications of the findings.FindingsThe main findings of this research are twofold: (1) in the context of investment communities, online endorsement system fails to signify value-relevant information and (2) bullish information and “wisdom over the past event” information receive more “likes” and fewer “dislikes” on average, but they underperform in stock market price discovery.Originality/valueThis study demonstrates that biased endorsement may lead to the failure of the online endorsement system as information gatekeeper in investment communities. Two underlying mechanisms are proposed and tested. This study opens up new research opportunities to investigate the causes of biased endorsement in online environment and motivates the development of alternative information filtering systems.

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“…The rejection of market efficiency through weak-form tests implies the rejection of semi-strong and strong-form efficiency. While there is evidence that the live cattle futures market is not weak-form efficient (e.g., Kastens and Schroeder, 1995), we are less interested in the specific results of the efficiency test than we are details of the modeling and testing effort. We examine the incorporation of proprietary information through the price discovery process.…”

Section: Introductionmentioning

confidence: 98%

Rational expectations and market efficiency in the U.S. live cattle futures market: The role of proprietary information

Schaefer¹,

Myers

Koontz

2004

Journal of Futures Markets

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The role of proprietary information in forecasting and market efficiency in the U.S. live cattle futures market is investigated. the proprietary data. We also test whether the initial estimates from the Cattle on Feed Report have new information that moves prices once the information contained in the proprietary data source has been taken into account. Results suggest that the information contained in the proprietary data source does have statistically significant explanatory power for forecasting final revised Cattle on Feed Report numbers and for predicting short-term price movements of futures contracts. The results are inconsistent with strong-form market efficiency in the live cattle futures market. We also find that the initial estimates in the Cattle on Feed Report still have new information that moves prices even after accounting for the unique information in both the Knight-Ridder pre-release forecasts and the proprietary data.

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A trading simulation test for weak‐form efficiency in live cattle futures

Abstract: period spanning 90% of the time over which live cattle futures have The helpful comments of anonymous reviewers are gratefully acknowledged.

Cited by 14 publications

References 25 publications

Market efficiency in agricultural futures markets

Market efficiency in agricultural futures markets

The failure of online endorsement systems in investment communities: evidence from Yahoo! Finance

Rational expectations and market efficiency in the U.S. live cattle futures market: The role of proprietary information

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