@article{doi:10.1198/jbes.2009.07205,
author = {S. Borağan Aruoba and Francis X. Diebold and Chiara Scotti},
title = {Real-Time Measurement of Business Conditions},
journal = {Journal of Business \& Economic Statistics},
volume = {27},
number = {4},
pages = {417-427},
year  = {2009},
publisher = {Taylor & Francis},
doi = {10.1198/jbes.2009.07205},

URL = { 
    
        https://doi.org/10.1198/jbes.2009.07205
    
    

},
eprint = { 
    
        https://doi.org/10.1198/jbes.2009.07205
    
    

}

}




@techreport{NBERw19523,
 title = "Time Variation in Asset Price Responses to Macro Announcements",
 author = "Goldberg, Linda S and Grisse, Christian",
 institution = "National Bureau of Economic Research",
 type = "Working Paper",
 series = "Working Paper Series",
 number = "19523",
 year = "2013",
 month = "October",
 doi = {10.3386/w19523},
 URL = "http://www.nber.org/papers/w19523",
 abstract = {Although the effects of economic news announcements on asset prices are well established, these relationships are unlikely to be stable. This paper documents the time variation in the responses of yield curves and exchange rates using high frequency data from January 2000 through August 2011. Significant time variation in news effects is present for those announcements that have the largest effects on asset prices.  The time variation in effects is explained by economic  conditions, including the level of policy rates at the time of the release, and risk conditions: government bond yields increase in response to "good news", but less so when risk is elevated. Risk conditions matter since they can capture the effects of uncertainty on the information content of news announcements, the interaction of monetary policy and financial stability objectives of central banks, and the effect of news announcements on the risk premium.},
}
@article{SCOTTI20161,
title = {Surprise and uncertainty indexes: Real-time aggregation of real-activity macro-surprises},
journal = {Journal of Monetary Economics},
volume = {82},
pages = {1-19},
year = {2016},
issn = {0304-3932},
doi = {https://doi.org/10.1016/j.jmoneco.2016.06.002},
url = {https://www.sciencedirect.com/science/article/pii/S0304393216300320},
author = {Chiara Scotti},
keywords = {Business cycle, Dynamic factor model, State space model, Forecasting weights},
abstract = {Two daily, real-time, real-activity indexes are constructed for the United States, euro area, United Kingdom, Canada, and Japan: (i) a surprise index summarizing recent economic data surprises and measuring optimism/pessimism about the state of the economy, and (ii) an uncertainty index measuring uncertainty related to the state of the economy. The surprise index parsimoniously preserves the properties of the underlying series when affecting asset prices. For the United States, the real-activity uncertainty index is compared to other uncertainty proxies to show that, when uncertainty is strictly related to real activity only, it has a potentially milder effect on economic activity.}
}

@article{10.1257/aer.20190964,
Author = {Känzig, Diego R.},
Title = {The Macroeconomic Effects of Oil Supply News: Evidence from {OPEC} Announcements},
Journal = {American Economic Review},
Volume = {111},
Number = {4},
Year = {2021},
Month = {April},
Pages = {1092-1125},
DOI = {10.1257/aer.20190964},
URL = {https://www.aeaweb.org/articles?id=10.1257/aer.20190964}}
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}

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  year={2016},
  publisher={World Scientific}
}

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  volume={34},
  number={3},
  year={2013},
  publisher={International Association for Energy Economics}
}

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  title={Macroeconomic factors do influence aggregate stock returns},
  author={Flannery, Mark J and Protopapadakis, Aris A},
  journal={Review of Financial Studies},
  volume={15},
  number={3},
  pages={751--782},
  year={2002},
  publisher={Oxford University Press}
}

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  pages={1901--1915},
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  number={4},
  year={1997}
}


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  year={1990}
}

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}

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  year={2006},
  publisher={Taylor \& Francis}
}

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  number={8},
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  publisher={Elsevier}
}

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}

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  year={2017},
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  title={Financialization and structural change in commodity futures markets},
  author={Irwin, Scott H and Sanders, Dwight R},
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  number={1379-2016-113661},
  pages={371--396},
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}

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  institution={National Bureau of Economic Research}
}

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}

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@article{irwin2012financialization,
  title={Financialization and structural change in commodity futures markets},
  author={Irwin, Scott H and Sanders, Dwight R},
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  volume={44},
  number={3},
  pages={371--396},
  year={2012},
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}

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@article{cai2001moves,
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  volume={21},
  number={3},
  pages={257--278},
  year={2001},
  publisher={Wiley Online Library}
}


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  institution={National Bureau of Economic Research}
}

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@article{brunetti2016speculators,
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@techreport{cheng2012convective,
  title = {Convective Risk Flows in Commodity Futures Markets},
  author = {Cheng, Ing-Haw and Kirilenko, Andrei and Xiong, Wei},
  year = {2012},
  institution = {National Bureau of Economic Research}
}

@article{cheng2015convective,
  title = {Convective Risk Flows in Commodity Futures Markets},
  author = {Cheng, Ing-Haw and Kirilenko, Andrei and Xiong, Wei},
  journal = {Review of Finance},
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  number = {5},
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@article{daigler1999impact,
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  author = {Daigler, Robert T. and Wiley, Marilyn K.},
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  volume = {54},
  number = {6},
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  year = {1999},
  publisher = {Wiley Online Library}
}

@article{erb2013golden,
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@article{fishe2012identifying,
  title = {Identifying Informed Traders in Futures Markets},
  author = {Fishe, Raymond P.H. and Smith, Aaron},
  journal = {Journal of Financial Markets},
  volume = {15},
  number = {3},
  pages = {329--359},
  year = {2012},
  url = {https://files.asmith.ucdavis.edu/2012_JFinM_FS_informed.pdf},
  keywords = {finance},
  abstract = {We use daily positions of futures market participants to identify informed traders. These data contain 8,921 unique traders. We identify between 94 and 230 traders as overnight informed and 91 as intraday informed with little overlap. Floor brokers/traders are over-represented in the overnight informed group. The intraday informed group is dominated by managed money traders/hedge funds and swap dealers, with commercial hedgers under-represented. We find that characteristics such as experience, position size, trading activity, and type of positions held offer significant predictive power for who is informed. An analysis of daily trader profits confirms that we select highly profitable traders.},
  publisher = {North-Holland}
}

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}

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