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IIASA PURE
Article . 2012
Data sources: IIASA PURE
SSRN Electronic Journal
Article . 2010 . Peer-reviewed
Data sources: Crossref
Quantitative Finance
Article . 2012 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2009
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Leverage Causes Fat Tails and Clustered Volatility

Authors: Thurner, S.; Farmer, J.D.; Geanakoplos, J.;

Leverage Causes Fat Tails and Clustered Volatility

Abstract

We build a simple model of leveraged asset purchases with margin calls. Investment funds use what is perhaps the most basic financial strategy, called "value investing", i.e. systematically attempting to buy underpriced assets. When funds do not borrow, the price fluctuations of the asset are normally distributed and uncorrelated across time. All this changes when the funds are allowed to leverage, i.e. borrow from a bank, to purchase more assets than their wealth would otherwise permit. During good times competition drives investors to funds that use more leverage, because they have higher profits. As leverage increases price fluctuations become heavy tailed and display clustered volatility, similar to what is observed in real markets. Previous explanations of fat tails and clustered volatility depended on "irrational behavior", such as trend following. Here instead this comes from the fact that leverage limits cause funds to sell into a falling market: A prudent bank makes itself locally safer by putting a limit to leverage, so when a fund exceeds its leverage limit, it must partially repay its loan by selling the asset. Unfortunately this sometimes happens to all the funds simultaneously when the price is already falling. The resulting nonlinear feedback amplifies large downward price movements. At the extreme this causes crashes, but the effect is seen at every time scale, producing a power law of price disturbances. A standard (supposedly more sophisticated) risk control policy in which individual banks base leverage limits on volatility causes leverage to rise during periods of low volatility, and to contract more quickly when volatility gets high, making these extreme fluctuations even worse.

19 pages, 8 figures

Country
Austria
Keywords

Physics - Physics and Society, 330, FOS: Physical sciences, Physics and Society (physics.soc-ph), Clustered vulnerability, Crash, FOS: Economics and business, Systemic risk, Leverage, Quantitative Finance - Trading and Market Microstructure, Statistical Finance (q-fin.ST), Margin calls, Quantitative Finance - Statistical Finance, Fat tails, Trading and Market Microstructure (q-fin.TR), Risk Management (q-fin.RM), Systemic risk, Clustered volatility, Fat tails, Crash, Margin calls, Leverage, Quantitative Finance - Risk Management, jel: jel:G01, jel: jel:E32, jel: jel:G12, jel: jel:E37, jel: jel:G14

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
156
Top 1%
Top 1%
Top 1%
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bronze