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Informed Trading Intensity

Fos, Vyacheslav - ; Vincent Bogousslavsky - ; Dmitriy Muravyev - ;

We train a machine learning method on a class of informed trades to develop a new measure of informed trading, informed trading intensity (ITI). ITI increases before earnings, mergers and acquisitions, and news announcements, and has implications for return reversal and asset pricing. ITI is effective because it captures nonlinearities and interactions between informed trading, volume, and volatility. This data-driven approach can shed light on the economics of informed trading, including impatient informed trading, commonality in informed trading, and models of informed trading. Overall, learning from informed trading data can generate an effective informed trading measure.


Ketersediaan

Call NumberLocationAvailable
PSB lt.2 - Karya Akhir (Koleksi Majalah)1
Penerbit: The American Finance Association 2024
EdisiVolume 79, Issue 2, April 2024, Pages 903-948
SubjekFinancial markets
Trading Intensity
ISBN/ISSN1540-6261
KlasifikasiNONE
Deskripsi Fisikill, chart, table, grafik, 924 hal, 20 cm
Info Detail SpesifikThe Journal of Finance
Other Version/RelatedTidak tersedia versi lain
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  • Informed Trading Intensity

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