Noise Momentum Around the World

We study the nonlinear limits to arbitrage in a model. When mispricing is small, arbitrage activity increases with mispricing because of the higher cost‐adjusted return. However, at high levels of mispricing, arbitrageurs are deterred by larger mispricing as funding constraints become more binding. Testing the model predictions on the index spot‐futures arbitrage with a Markov‐switching model, we document an inverse U‐shaped relationship between mispricing and arbitrage activity. The extreme regime is with the largest mispricing but least arbitrage activity, and coincides with the market turmoil, suggesting that funding constraints become the main driver behind the limit to arbitrage.

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Nonlinear limits to arbitrage

Chen

Cai

Faff

et al. 2022

Journal of Futures Markets

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Investor sentiment and the economic policy uncertainty premium

Nartea

Bai

2020

Pacific-Basin Finance Journal

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Motivated by recent studies documenting an equity premium associated with economic policy uncertainty (EPU), we test the hypothesis that the EPU premium is stronger (weaker) following periods of low (high) investor sentiment. We estimate stock sensitivity to an economic policy uncertainty (EPU) index and show that stocks in the Australian equities market in the highest uncertainty beta tertile underperform stocks in the lowest tertile, similar to US stocks. However, we find that this negative uncertainty premium remains significant only following periods of low investor sentiment as it disappears following periods of high sentiment. Our results complement the US evidence in that uncertainty averse investors are willing to pay high prices for stocks with positive uncertainty beta and require extra compensation to hold stocks with negative beta, but only in low sentiment periods. These results are consistent with strong (weak) intertemporal hedging demand for positive EPU beta stocks in low (high) sentiment periods. It is also consistent with limited (full) participation of pessimistic investors and investors with high aversion to uncertainty in low (high) sentiment periods. Our results suggest that betting against EPU as a trading strategy would be relatively more profitable when executed during low sentiment periods.

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A machine learning analysis of citation impact among selected Pacific Basin journals

Jones

Alam

2019

Accounting & Finance

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This study uses a machine learning approach to identify and predict factors which influence citation impacts across five Pacific Basin journals: Abacus, Accounting & Finance, Australian Journal of Management, Australian Accounting Review and the Pacific Accounting Review from 2008 to 2018. The machine learning results indicate that citation impact is mostly influenced by: length of a journal article; the field of research (particularly environmental accounting), sample size; whether the sample is local or international; choice of research method (e.g., archival vs survey/interview); academic rank of the first author; institutional status of the first author; and number of authors of the article. The results may be useful for predicting future trends in citation impact as well as providing strategies for authors and editors to improve citation impact.

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Noise Momentum Around the World

Cited by 3 publications

References 35 publications

Nonlinear limits to arbitrage

Nonlinear limits to arbitrage

Investor sentiment and the economic policy uncertainty premium

A machine learning analysis of citation impact among selected Pacific Basin journals

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