Did Investors Herd during the Financial Crisis? Evidence from the US Financial Industry

• DOI: http://doi.org/10.1111/irfi.12140
• Published date: 01 March 2018
• Date: 01 March 2018
• Author: M. Humayun Kabir

M. HUMAYUN KABIR

School of Economics and Finance, Massey University, Palmerston North, New Zealand

ABSTRACT

We examine the herding behavior of investors in the US financial industry,

especially commercial banks, S&Ls, investment and insurance firms during global

financial crisis of 2008 towards own sub-sector and market consensus using

augmented cross sectional absolute deviation of returns (CSAD) model. After

distinguishing between fundamental and non-fundamental information, we find

agreaterinfluence of global financial crisis on spurious herding for commercial

and investment banks, and such herding increases in the down market and with

conditional volatility of returns, but adverse herding is prevalent among investors

during normal period in response to fundamental information. We also find that

herding intensity on fundamental information is relatively high with market

consensus for all financial institutions except insurance firms in high volatility

regime, and intentional herding is only significant and limited to S&Ls and

investment banks in high volatility regime. Our findings suggest limited

spillover effects of herding when investors face non-fundamental information.

JEL Codes: G11; G12; G21; G29

Accepted: 30 May 2017

I. INTRODUCTION

Herding behavior emerges when individuals ignore or suppress their own belief

or private signal and follow the actions of other individuals or investors. Early

studies focus on rational herding showing that such behavior may be optimal

as individuals, who are followed by others may possess important information

(Bikhchandani et al. 1992), and managers or analysts want to protect reputation

(Scharfstein and Stein 1990; Trueman 1994; Graham 1999) or insure against

underperformance with peers (Rajan 2006). However, Froot et al. (1992) show

that naïve investors may herd in short investment horizon to exploit the

informed investors. Other studies depart from investors’rationality and put more

emphasis on the presence of irrational and psychological or sentiment that affect

trading behavior leading to herd phenomena (Shleifer and Summers 1990;

DeLong et al. 1991; Cipriani and Guarino 2005). If the correlated behavior of

investors due to suppression of private information leads to the situation when

© 2017 International Review of Finance Ltd. 2017

International Review of Finance, 2017

DOI: 10.1111/irfi.12140

Did Investors Herd during the

Financial Crisis? Evidence from

the US Financial Industry

International Review of Finance, 18:1, 2018: pp. 59–90

DOI:10.1111/irfi .12140

© 2017 International Review of Finance Ltd. 2017

the market price fails to reflect fundamental information, herding can result in

extreme effects in mispricing and inefficiency in the asset market. Studies based

on trading data by institutional investors find mixed evidence of herding

(Lakonishok et al. 1992; Grinblatt et al. 1995; Nofsinger and Sias 1999; Sias

2004; Choi and Sias 2009; Brown et al. 2013; Holmes et al. 2013).

1

Methodologically different from such studies, Gleason et al. (2004), Tan et al.

(2008), Zhou and Lai (2009), Chiang and Zheng (2010), Gębka and Wohar

(2013), and Chiang et al. (2013) use aggregate market data to detect herd

behavior by investors across markets or sectors following Chang et al. (2000).

The purpose of the present study is to examine the herding behavior of

investors in the US financial industry, especially commercial banks, savings and

loan institutions (S&L), investment and insurance firms during global financial

crisis of 2008 following the methodology of Chang et al. (2000). The epicenter

of the 2007–2008 financial crisis was the banks and other financial institutions.

The crisis was triggered by the revelation of losses faced by major financial

institutions from subprime mortgages. Later, subsequent losses due to

counterparty exposures resulted in systemic risk with collapse and near-failure

of major banks. Beltrattia and Stulz (2012) find that the buy-and-hold dollar

return of larger banks worldwide was 51.84% with standard dev iation of

27.74% during the period of 2007–2008 crisis, which is extremely high. The

interconnectedness and the complexity of financial structure and institutions

have contributed to such systemic failure. For example, although insurance

industry did not have direct exposure to the financial crisis, American

International Group (AIG), the world’s largest insurance company, was on the

verge of collapse. The fact is that AIG was a complex financial group, consisting

of 70 US-based insurance companies and another more than 170 other financial

service companies. The complexity of such interconnections created through

credit default swaps and securities lending resulted in AIG to be an important

counterparty to other systemically important banks. The losses and systemic risk

during 2007–2008 reached to such an extent that Fed and Treasury had to come

up with the plan to rescue banks, and prevent disorderly winding of exposed

financial institutions.

2

Treasury established several programs under TARP to

stabilize banking institutions, restart credit markets, and avoid foreclosures.

3

1 More discussion is presented in literature review in section II.

2 A comprehensive financial crisis timeline and policy actions have been documented by

Federal Reserve Bank of St Louis, and available online: https://www.stlouisfed.org/financial-

crisis/full-timeline

3 Congress initially authorized $700 billion for TARP in October 2008, which was reduced to

$475 billion by the Dodd-Frank Wall Street Reform and Consumer ProtectionAct (Dodd-Frank

Act). Approximately $250 billion of that amount was committed in programs to stabilize

banking institutions, $27 billion was committed through programs to restart credit markets,

$70 billion was committed to stabilize American International Group (AIG), and Treasury

purchased $20 billion in preferred stock from two institutions, Citigroup Inc. and Bank of

America. Treasury also provided capital to 707 financial institutions in 48 states, including

more than 450 small and community banks and 22 certified community developmentfinancial

institutions (CDFIs). The largest investment was $25 billion and the smallestwas $301,000.

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Given the extent and depth of the crisis, it is worthwhile to examine how

investors buying and selling financial stocks behave in the market when financial

institutions were facing hurdles as their interdependence through different

channels exerting systemic risks. Did the investors participate based on their

own belief or swayed away by other investors when defaults on mortgages spread

to investment banks and commercial banks via an elaborate network of

derivatives? Did the ripple effects of the demise of some financial institutions

as well as the evaporation of liquidity through the interaction of market liquidity

and funding liquidity result in nervousness in investors’psyche generating

market transactions following each other? Previous studies concentrate

examining mostly herding in national markets leaving sector-level herding,

especially in the financial sector which was vital during the financial crisis of

2007–2008.

4

Diamond and Dybvig (1983), Swary (1986), and Lang and Stulz (1992) have

shown how a bank-specific event or bank-specific trouble can create shock to

other banks and affects the whole financial sector. Similarly, investors’

expectations, beliefs, and memories of past crises (Masson 1998 and

Mullainathan 1998), and information asymmetry between the informed and

uninformed investors (Clavo 1999) can generate contagious effects in response

to a crisis. James (1991) suggests that the direct costs of bank failures are larger

than that of bankruptcy of non-financial firms. Acharya and Yorulmazer (2008)

develop a model to explore various aspects of systemic risk analyzing the ex-ante

effects of bank failures and losses, and likelihood of information contagion that

induce profit maximizing bank owners to herd with other banks.

Herding behavior is manifested in an increased similarity of returns across

stocks resulting in a lower cross-sectional variability of returns. Chang et al.

(2000) propose a measure of cross-sectional variability of returns, CSAD, cross-

sectional absolute standard deviation with respect to the average return of all

stock returns. Chiang et al. (2013) find that herding is time-varying and depends

on prevailing market returns and conditional volatility. Motivated by Chiang

et al. (2013), we augment the base CSAD model to explore the possibility of

herding towards own sub-sector as well as the market (for example, commercial

banks herding towards the consensus or equally weighted returns of all

commercial banks, and equally weighted returns of CRSP firms). However, Gębka

and Wohar (2013) argue that there might be an increased dispersion in returns

across assets leading to adverse herding when investors overemphasize their

own view or focus on views dominant among subset of actors excessively

ignoring market information. We also explore such possibility, which might be

due to localized herding (Gębka and Wohar 2013), excessive “flight to quality”

during market stress (Favero and Giavazzi 2002; Kaminsky et al. 2004; Baur and

4Gębka and Wohar (2013) find no evidence of herding using DataStream sectoral indices in a

global scale. They also find that some sector-specific indices like basic materials, consumer

services, and oil and gas reveal traders’irrationality, which could be due to overconfidence,

or excessive flight to quality.

Do Investors Herd during the Financial Crisis?

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Did Investors Herd during the Financial Crisis?

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