Will the Use of Credit Default Swaps
Affect Firm Risk and Value?
Evidence from U.S. Life and Property/Casualty Insurance
Companies
Hung-Gay Fung
College of Business Administration
University of Missouri-St. Louis
Min-Ming Wen
College of Business and Economics
California State University, Los Angeles
Gaiyan Zhang
1
Motivation
• Financial Crisis in 2008
• AIG was on the edge of falling apart
 the (ab)use of CDS?
• Insurance companies have been among the most
active market participants in the credit derivatives
market
– According to British Bankers’ Association
(2006), insurers worldwide held an 18% market
share for selling CDS protection; 6% of the CDS
market for buying credit protection.
• This study examines the use of CDS in the pre-crisis
period. (from 2001-2007)
2010 Taiwan Conferences -Fung, Wen & Zhang
2
CDS trading motives
• Why do insurers sell CDS?
– income generation (for taking credit risks)
– replication (similar to bond holdings for
receiving fixed payment by taking credit risks;
but with a more flexible choice in maturity)
– speculation (simply for transaction purpose)
• Why do insurers buy CDS?
– hedging (managing credit risks embedded in
bond portfolios)
– speculation (simply for transaction purpose)
2010 Taiwan Conferences -Fung, Wen & Zhang
3
CDS and Risk: Literature Review
• Existing studies on CDS usage have primarily
focused on risk-hedging and/or risk-taking
behaviors by banks and hedge funds.
• Credit derivatives use by banks (Minton, Stulz and
Williamson (2009), Shao (2010))
 Shao (2009) finds an increase in the risk profiles for bank
protection sellers but no evidence that bank protection
buyers have higher risk.
 Instefjord (2005) risk-sharing benefits from credit
derivatives may encourage banks to take more risk
 Morrison (2005) finds that credit derivatives can reduce
banks’ incentives to monitor their loan portfolios.
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CDS and Risk
• Credit derivatives use by hedge funds (Chen, 2010)
 the use of credit derivatives decreases total risk
for hedge funds.
• Derivative use by insurers (Colquitt and Hoyt 1997;
Cummins, Phillips, and Smith 1997, 2001).  not
CDS specifically!
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Research Questions
• CDS Buy position reduces credit risk if it is for hedging
purpose  can this be transferred to risk-reduction as a
whole?
• CDS Buy position carries investment risk if it is for
transaction purpose  how does it affect firm’s risks?
• CDS sell position increases credit risk if it is for income
generation purpose  how does it affect firm’s risks?
• CDS sell position reduce asset-liability duration risk  can
it be transferred to the reduction of firm’s risks?
How does the use of CDS affect firm risks?
How are the effects of CDS use on firm risks
transferred to the effects on firm value?
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Research Design
• CDS use
 Buyers v.s. sellers
• Risk Measures
 total risk, market risk, and idiosyncratic
risk
• Firm value measure
 Tobin’s Q (market-based measure), ROA
(accounting-based measure)
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Main Findings: CDS & Risk
CDS-Participation
Total risk
Systematic Risk Idiosyncratic risk
Life
+
+
+
PC
+
+
+
CDS Positions
Life – Net Sellers
Total risk
+
Life – Net Buyers
Systematic Risk Idiosyncratic risk
+
+
+
PC – Net Sellers
+
PC – Net Buyers
+
+
+
+
 risk-increasing trading dominates risk-decreasing trading
 risk increasing trading is associated with income generation &
speculation purposes
 risk-decreasing trading: hedging and replication.
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Main Findings: CDS & Firm Value
CDS-Participation Tobin’s Q:
MV/BV (equity) ROA
MV/BV (assets)
Life
-
-
-
PC
-
-
-
CDS Net Sell/Net
Tobin’s Q:
Buy Positions
MV/BV (assets)
Life – Net Sellers
NS
MV/BV (equity) ROA
NS
NS
Life – Net Buyers
-
-
-
PC – Net Sellers
-
-
-
PC – Net Buyers
-
-
-
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Data
• Data sources: the merge of NAIC derivative data,
CompuStat and CRSP.
– Data uniqueness: the detailed nature of the data on credit
derivatives use reported by insurance companies to NAIC
• Our focus: the behaviors of 44 distinct insurers who
participate in the CDS market and have CompuStat
and CRSP data available.
– 33 Life insurers and 11 PC insurers.
– firm-year observations are 427 (Life) and 666 (PC).
– the total number of transaction observations: 4,889 (Life)
and 1,639 (PC)
– CDS non-users: 212 publicly-listed insurers including 85
(Life) 127 (PC).
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Methodology and Empirical Results
• Simultaneous Equation Model on Risk Analysis: potential
endogeneity between risk and derivative use (Graham and
Rogers, 2002)
Riski,t= α1 + β ×CDSi,t +   Z + β ×Div_yieldi + β ×CDS_Changei,t +
1,1
1,i
β1,4 ×Spread_Volti,t + ε1,i,t
i ,t
1,2
1,3
(3)
CDSi,= α2 + β2,1 ×Riski,t +  2,i  Zi,t + β2,2 ×NY_Dummyi,t + β2,3 ×CDS_Changei,t +
β2,4 ×Spread_Volti,t +ε2,i,t ,
(4)
Risk Variable: total risk, systematic risk, and idiosyncratic risk.
CDS Variable:
CDS_Dummyi,t = one if insurer i participates in CDS transactions
Net_Buyeri,t = one if the aggregate notional amount of the CDS buy
position is greater than that of the sell position;
Net_Selleri,t = one if the aggregate notional amount of the CDS sell
position is greater than that of the buy position.
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Table 1. Summary of CDS Transactions for
Life and PC Insurers
• 2010Taiwan_Presentation_Tables.doc
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Table 2. Descriptive Statistics for the Entire
Sample (CDS_users & Non_CDS Users)
• Table 2 presents the descriptive statistics of
risk, firm value, and other control variables
used in the analysis.
• Panels A and B are for the samples of Life
and PC insurers, respectively.
• 2010Taiwan_Presentation_Tables.doc
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Table 3.
• Table 3 compares medians and means of risk, firm
value, and other firm characteristic variables
between insurers – CDS users, CDS net buyers,
CDS net sellers – and those non-CDS users.
• 2010Taiwan_Presentation_Tables.doc
• Life insurers with CDS transactions: have a larger
systematic risk, lower idiosyncratic risk, and lower
total risk than those of non-CDS users.
• Both net buyers and net sellers have significantly
higher systematic risk, lower idiosyncratic risk, and
lower total risk than non-CDS users.
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Table 3
• Life Insurers: non-CDS users have larger Tobin’s Q, market-to-book
value of equity, and return on asset than CDS users, net buyers, net
sellers.
• PC Insurers:
– No significant difference in total risk between CDS users and non-users.
– CDS users have higher systematic risk and lower idiosyncratic risk than
those of non-CDS users.
– Net buyers have significantly higher systematic risk and lower idiosyncratic
risk than non-CDS users.
– No significant difference in total risk between net buyers and non-users.
– Net sellers show significantly higher market risk and higher idiosyncratic
risk than non-users,
– No significant difference in total risk between net sellers and non-users.
• CDS users have lower Tobin’s Q, lower market-to-book equity value,
and lower ROA than non-users.
• CDS net buyers and net sellers also have lower Tobin’s Q, market-tobook equity value, and ROA than non-users.
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Summary of Univariate Analysis
• Life and PC CDS users (regardless of their positions
as net buyers or net sellers) have higher market risk
than non-users
 a positive relation between the market risk of
insurers and their participation in the CDS market.
• Second, Life CDS users have lower idiosyncratic
risk and total risk than non-users.
• Finally, Life and PC CDS users have lower firm
values.
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Table 4. Risk Models
CDS-Participation
Total risk
Systematic Risk Idiosyncratic risk
Life
+
+
+
PC
+
+
+
CDS Positions
Life – Net Sellers
Total risk
+
Life – Net Buyers
Systematic Risk Idiosyncratic risk
+
+
+
PC – Net Sellers
+
PC – Net Buyers
+
+
+
+
 risk-increasing trading dominates risk-decreasing trading
 risk increasing trading is associated with income generation &
speculation purposes
 risk-decreasing trading: hedging and replication.
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Table 4. Risk Models
• 2010Taiwan_Presentation_Tables.doc
• Panel A1: (risk equation, Life insurers): participation in CDS
transactions significantly increases total risk; Net sellers
dummy variable significantly increase total risk
 writing CDS contracts increases Life insurers’ total risk.
 buying CDS protection has insignificant effects on Life
insurers’ total risk.
• In the CDS equation: CDS use and participation positions
are positively and significantly related to total risk.
 those insurers with higher total risk are more likely to
engage in CDS transactions, both as net sellers and as net
buyers, holding other things constant.
• Panel B1 (PC insurers) are quite similar to those for Life
insurer sample;
• both net buyers and net sellers have significantly higher total
risk.
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Table 5: Regression Model on Firm Performance
Performance=
α0 + βj ×CDSi,t +
 i  Zi,t + εi,t
(5)
Proxy for firm value/performance measure:

Tobin’s Q, ratio of market value of equity to book-value equity,
Tobin’s Q is defined as the market value of equity plus the book value of liabilities
divided by the book value of assets,
i.e.,
TQ 
BV (total assets)  BV ( common equity)  MV ( common equity)
BV (total assets)
,
where MV (common equity) is the product of stock price and number shares
outstanding;
MV ( Eqty ) _ BV ( Eqty ) 

MV(Eqty)/BV(Eqty)

ROA is return on book value asset.
2010 Taiwan Conferences -Fung, Wen & Zhang
MV ( common equity)
BV ( common equity)
;
19
Table 5: Regression Model on Firm
Performance
• 2010Taiwan_Presentation_Tables.doc
2010 Taiwan Conferences -Fung, Wen & Zhang
Table 5: Regression Model on Firm
Performance
20
CDS-Participation Tobin’s Q:
MV/BV (equity) ROA
MV/BV (assets)
Life
-
-
-
PC
-
-
-
CDS Net Sell/Net
Tobin’s Q:
Buy Positions
MV/BV (assets)
Life – Net Sellers
NS
MV/BV (equity) ROA
NS
NS
Life – Net Buyers
-
-
-
PC – Net Sellers
-
-
-
PC – Net Buyers
-
-
-
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Contributions
• We extend a series of studies on derivative usage by insurance
companies by focusing on credit derivatives, credit default
swaps on particular
• Our paper complements the study on bank and hedge fund use
of credit derivatives
– Shed light on the opaque and largely unregulated CDS
market
• This study shows:
– CDS utilization alters the risk profile of both Life and PC insurers by
increasing each dimension of risk.
– CDS utilization deteriorates the financial performance.
• Our findings support the effort of the NAIC working with the
insurance regulators to monitor more closely how insurance
companies engage in derivative transactions.
2010 Taiwan Conferences -Fung, Wen & Zhang