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Short Selling Bans and Institutional Investors' Herding Behavior: Evidence from the Global Financial Crisis Martin T. Bohl a , Arne C. Klein a and Pierre L. Siklos b a Department of Economics, Westphalian Wilhelminian University of Münster , Germany

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slide1

Short Selling Bans and Institutional Investors' Herding Behavior:

Evidence from the Global Financial Crisis

Martin T. Bohla, Arne C. Kleina and Pierre L. Siklosb

a Department of Economics, WestphalianWilhelminian University of Münster, Germany

b Department of Economics, Wilfrid Laurier University and Viessmann European Research Centre, Canada

testable hypotheses
Testable Hypotheses
  • Does herding become more relevant during a financial crisis? In other words, are regulators desired to displace SS during a crisis because herding is exacerbated during falling markets?
    • YES? Herding implies investors’ difference of opinion is relatively small
    • NO? Divergences of opinion increase during a crisis. Therefore, adverse herding is a possibility
      • SENTIMENT plays a role
  • Is the evidence for/against herding similar across countries?
contribution to the literature

Contribution to the literature

Do short sales constraints (SSC) have a significant impact on herding behavior?

contribution to the literature1

Contribution to the literature

Do short sales constraints (SSC) have a significant impact on herding behavior?

The answer, in turn, entails important information for stock market regulators

contribution to the literature2

Contribution to the literature

Do short sales constraints (SSC) have a significant impact on herding behavior?

The answer, in turn, entails important information for stock market regulators

and deepens insights into institutional investors’ trading behavior

markets under consideration

Marketsunder consideration

Setting and Data: Short Sale Constraints in

The United States

07/15/2008 – 08/12/2008

Naked short sales in (18) selected stocks

United Kingdom

09/19/2008 - 01/16/2009

All economic short positions in (32) selected stocks

Germany

09/22/2008 – 01/31/2010

Naked short sales in (10) selected stocks

markets under consideration1

Marketsunder consideration

France

09/22/2008 – 01/31/2010

Short Sales in (12) selected stocks

South Korea

09/30/2008

All short sales

06/01/2009

Lifted for non-financials

markets under consideration2

Marketsunder consideration

Australia

09/22/2008

Naked short sales

11/19/2008

Lifted for non-financials being member of the S&P/ASX 200 and APRA-regulated business

05/24/2009

Ban expires

markets under consideration4

Marketsunder consideration

US & UK > 200%

GER, FR, AUS > 100%

ROK ≈ 90%

In 2007 (Gonnard (2008))

literature review

Literature Review

Miller (1977), Diamond and Verrecchia (1987)

Short selling bans

miller 1977

Miller (1977)

Divergence of opinion

miller 19771

Miller (1977)

Divergence of opinion

SSC deter pessimists from expressing their beliefs

miller 19772

Miller (1977)

Divergence of opinion

SSC deter pessimists from expressing their beliefs

therefore, market prices are build upon optimists’ valuation

miller 19773

Miller (1977)

Divergence of opinion

SSC deter pessimists from expressing their beliefs

therefore, market prices are build upon optimists’ valuation

Overvaluation

diamond and verrecchia 1987

Diamond and Verrecchia (1987)

SSC reduce informational efficiency:

new information is impounded into prices with a delay

diamond and verrecchia 19871

Diamond and Verrecchia (1987)

SSC reduce informational efficiency:

new information is impounded into prices with a delay

this holds for both positive and negative news

diamond and verrecchia 19872

Diamond and Verrecchia (1987)

SSC reduce informational efficiency:

new information is impounded into prices with a delay

this holds for both positive and negative news

but the effect is stronger for negative information

crisis related bans

Crisis related Bans

Previous literature on the short selling bans reports strong evidence for deteriorations in market quality and liquidity

Bris (2008), Boulton and Braga-Alves (2010) and Kolanski et al. (2010) for the July/August ban in the US

Boehmer et al. (2009) and Kolanski et al. (2010) for the September/October ban in the US

crisis related bans1

Crisis related Bans

Marsh and Payne (2010) for the UK

Helmes et al. (2010) for Australia

A broad international perspective incl. 30 countries is given in Beber and Pagano (2011)

beber and pagano 2011

Beber and Pagano (2011)

Their results for 30 countries underscore negative effects on market liquidity

beber and pagano 20111

Beber and Pagano (2011)

Their results for 30 countries underscore negative effects on market liquidity

In addition, they find increased autocorrelations in the residuals of market model regressions

empirical approach

Empirical Approach

We aim at identifying the impact of short sale constraints on herding behavior

empirical approach1

Empirical Approach

We aim at identifying the impact of short sale constraints on herding behavior

A measure of herding is needed

empirical approach2

Empirical Approach

We aim at identifying the impact of short sale constraints on herding behavior

A measure of herding is needed

Control for the effects of the crisis per se is needed

empirical approach3

Empirical Approach

We aim at identifying the impact of short sale constraints on herding behavior

A measure of herding is needed

Control for the effects of the crisis per se is needed

Robust inference based on small/medium size samples

measure of dispersion
Measure of Dispersion

Measure of Dispersion as an input to evaluate Herding: details

Measure of Dispersion

  • St = dispersion: captures a key characteristics of herd behavior
    • N = number of stocks,
    • T = number of observations
    • rit =return, stock i, time t;
    • rmt = cross-sectional weighted average of returns in a ‘portfolio’ of Nstocks

NOT anE(r)

Average deviation of a stock from the market proxies how investors discriminate between stocks

Christie and Huang (1995)

methodology regression form
Methodology: Regression Form

(2)

  • > 0 under rational
  • Asset pricing;
  • {e.g., changing 
  • may be one
  • reason}

BANNED CONTROL

IMPLIES SSR have

an effect

Autocorrelation:Schwert’s criterionFrom max to min,use a 10% criterion

  • 0 meansdeviation from rational
  • Asset pricing

Proxies variance since

Chang et al. (2000)

matching

Matching

Matching variables: Market capitalization, trading volume and market beta (all standardized)

matching1

Matching

Matching variables: Market capitalization, trading volume and market beta (all standardized)

Matching metric: Sum of squared differences in those three variables (Euclidean distance)

interpretation

Interpretation

In general, evidence supporting an effect of short sale constraints is found if the estimate for significantly differs between test and control groups

interpretation1

Interpretation

In particular, support for regulators’ point of view is given in case of a dampening effect of SSC on herding which, in turn, is found if is significantly negative for the control group while being equal to zero for the banned stocks.

interpretation2

Interpretation

By contrast, evidence in line with a amplifying effect of SSC on herding, is found if is negative for the test group but equal to zero for the control stocks.

bootstrap

Bootstrap

A bootstrap algorithm

enables us to draw reliable inference from small and medium samples

bootstrap1

Bootstrap

A bootstrap algorithm

enables us to draw reliable inference from small and medium samples

allows us to directly test the H0 of Rational Asset Pricing (i.e., CAPM-type)

bootstrap2

Bootstrap

We generate data by the following processes

1.

bootstrap3

Bootstrap

We generate data by the following processes

1.

2.

further empirical issues
Further empirical issues
  • Persistently rising vs falling markets may make a difference: sort St, by length of runs l {1,2}
further empirical issues1
Further empirical issues
  • Persistently rising vs falling markets may make a difference: sort St, by length of runs l {1,2}
  • Threshold effects?
further empirical issues2
Further empirical issues
  • Persistently rising vs falling markets may make a difference: sort St, by length of runs l {1,2}
  • Threshold effects?
  • Small cap versus large cap: former exhibit more herding than latter; former lag latter in terms of correlation of returns
empirical results

Empirical Results

Recall that we bootstrap deviations from Rational Asset Pricing

empirical results1

Empirical Results

Recall that we bootstrap deviations from Rational Asset Pricing

Significance does not mean significantly different from zero

empirical results2

Empirical Results

Recall that we bootstrap deviations from Rational Asset Pricing

Significance does not mean significantly different from zero

but significantly different from the value implied by the asset pricing model

empirical results3

Empirical Results

Adverse Herding! Herding

empirical results5

Empirical Results

Almost no herding (either adverse or regular) in case of unbanned stocks

empirical results6

Empirical Results

Almost no herding (either adverse or regular) in case of unbanned stocks

strong evidence for adverse herding for the stocks subject to the constraints for some countries

interpretation3

Interpretation

It is well known in the literature that short sale constraints create uncertainty about fundamental asset values

interpretation4

Interpretation

It is well known in the literature that short sale constraints create uncertainty about fundamental asset values

The work of Hwang and Salmon (2004, 2009) suggests that during such turmoils investors loose trust in the market consensus and come back to fundamental based pricing

interpretation5

Interpretation

It is well known in the literature that short sale constraints create uncertainty about fundamental asset values

The work of Hwang and Salmon (2004, 2009) suggests that during such turmoils investors loose trust in the market consensus and come back to fundamental based pricing

This may show up in adverse herding, via an increased dispersion of returns