The Sound Of Many Funds Rebalancing
Alex Chinco and
No 13561, CEPR Discussion Papers from C.E.P.R. Discussion Papers
This paper proposes that computational complexity generates noise. In modern financial markets, it is common to find the same asset held for completely different reasons by funds following a wide variety of threshold-based trading rules. Under these conditions, we show that it can be computationally infeasible to predict how these various trading rules will interact with one another. Formally, we prove that it is NP hard to predict the sign of the net demand coming from a large interacting mass of funds at a rate better than chance. Thus, market participants will treat these demand shocks as random noise even if they are fully rational. This noise-generating mechanism can produce noise in a wide range of markets and also predicts how noise will vary across assets. We verify this prediction empirically using data on the exchange-traded fund (ETF) market.
Keywords: Complexity; Indexing; noise; thresholds (search for similar items in EconPapers)
JEL-codes: G14 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cmp
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at firstname.lastname@example.org
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:13561
Ordering information: This working paper can be ordered from
http://www.cepr.org/ ... rs/dp.php?dpno=13561
Access Statistics for this paper
More papers in CEPR Discussion Papers from C.E.P.R. Discussion Papers Centre for Economic Policy Research, 33 Great Sutton Street, London EC1V 0DX.
Bibliographic data for series maintained by ().