Transcript CDS users
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)
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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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4
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