Southville International School and Colleges Search for 'su:"Frequency."'

Externalizing psychopatholgy and gain-loss feedback in a simulated gambling task : dissociable components of brain response revealed by time-frequency analysis /

By Bernat, E..
2011 .
120 : 2, page 352

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Reading dream literature : frequency, influencing factors, and self-rated benefit /

By Schred, Michael..
2012 .
125 : 2, page 227

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9 to 5 Do You Know If Your Boss Knows Where You Are? Case Studies of Radio Frequency Identification Usage in the Workplace

By Balkovich, Edward;Bikson, Tora K.;Bitko, Gordon.
RAND Corporation 2005 9780833037190

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High frequency trading and extreme price movements / by Jonathan Brogaard, Allen Carrion, Thibaut Moyaert, Ryan Riordan, ... Konstantin Sokolov

Amsterdam Elsevier 2018 .
Pages 253-265 , Abstract Are endogenous liquidity providers (ELPs) reliable in times of market stress? We examine the activity of a common ELP type—high frequency traders (HFTs)—around extreme price movements (EPMs). We find that on average HFTs provide liquidity during EPMs by absorbing imbalances created by non-high frequency traders (nHFTs). Yet HFT liquidity provision is limited to EPMs in single stocks. When several stocks experience simultaneous EPMs, HFT liquidity demand dominates their supply. There is little evidence of HFTs causing EPMs.

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Market intraday momentum / by Lei Gao, Yufeng Han, Sophia Zhengzi Li & Guofu Zhou

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Pages 394-414 , Abstract Based on high frequency S & P 500 exchange-traded fund (ETF) data from 1993–2013, we show an intraday momentum pattern: the first half-hour return on the market as measured from the previous day’s market close predicts the last half-hour return. This predictability, which is both statistically and economically significant, is stronger on more volatile days, on higher volume days, on recession days, and on major macroeconomic news release days. Intraday momentum also exists for ten other most actively traded domestic and international ETFs. Theoretically, the intraday momentum is consistent not only with Bogousslavsky’s (2016) model of infrequent portfolio rebalancing but also with a model of late-informed trading near the market close.

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