Brent W. Ambrose. Penn State Jean Helwege. South Carolina Kelly N. Cai. U. Michigan Dearborn

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Brent W. Ambrose Penn State Jean Helwege South Carolina Kelly N. Cai U. Michigan Dearborn

When bonds lose their investment grade status from the rating agencies, institutions are forced to sell them Regulations are stricter for insurance companies and pension funds than for mutual funds and other institutions. Regulatory arbitrage suggests it is the last investment grade rating that triggers rules on holdings Ambrose, Cai and Helwege (2008) show that fallen angels are sold by insurance companies far more often than other bonds Rating agencies are often slow to act so a large number of downgrades are met with no reaction from investors Weinstein (1977), Hand, Holthausen and Leftwich (1992) This allows us to look at price pressure effects of selling when information effects are absent

Many papers attempt to determine whether demand curves for securities slope downward. Asset pricing models like the CAPM say the price is invariant to the quantity sold. Market microstructure theory (Kyle (1985)) says selling a large quantity in the open market is likely to involve a discount: Dealers are concerned about buying at too high a price from an informed trader Block trades, IPO lock-ups, etc suggest that selling a large equity stake involves significant downward pressure on stocks Scholes (1972), Mikkelson and Partch (1985), Keim and Madhavan (1998), Clarke, Dunbar and Kahle (2004), Field and Hanka (2001), Corwin (2003), Ofek and Richardson (2000) and Schultz (2006)).

Price pressure occurs when a large volume of sales reduces the price of a security or a large amount of buying increases the price Pure price pressure occurs even when the trading is unconnected to future performance or expectations of future performance We want an experiment where the only thing that changes is the amount sold or bought Even if no information, dealers may worry that there are information effects. Sunshine trading (Admati and Pfleiderer (1991)) Roell (1990)

Find bonds that are sold by insurance companies after a downgrade to speculative-grade Must be junk because of regulations (other changes don t count) Separate bonds into cases of no information and negative information based on stock reaction No information is when the stock does not react significantly Likely reflects that the stock reacted earlier to the bad news Examine trading patterns to see if insurers try to hide The sunshine effect Look at bond prices before and after downgrade Negative stock reaction firms should have both price pressure and info No stock reaction firms should just suffer from price pressure

1. Identify fallen angels from FISD (1995-2008) Moody s, S&P, Fitch and Duff and Phelps data 2337 bonds downgraded by Moody s and S&P 1476 bonds downgraded by all agencies that count 2. Stock data from CRSP 3. Watchlist and other rating data from FISD 4. Bond sales and prices from FISD 5. Bond index data from Lehman/BGI indexes

Insurers should have an easier time selling their fallen angel bonds when everyone understands that there is no information element to their trades (sunshine trading) We construct 3 measures of dealer liquidity: Ability to predict future bond sales (Hite & Warga, 1997) On Watchlist Estimate downgrade probability Adverse selection component in issuer s stock Proxy for bond liquidity Issue size Age Time to maturity Zero trading days

No Information Full Sample Group Last IG Agency % of Bonds % on WL % of Bonds % on WL Duff & Phelps 1.51 0.0 2.2 0.0 Fitch 43.4 2.2 44.6 2.2 Moody s 27.6 16.6 24.3 14.3 S&P 26.3 0.9 28.9 0.9 Total 100.0 5.86 100.0 4.71 Less than 6% of the fallen angels were on a Watchlist, indicating that it might be difficult for the market to prepare for the last rating action.

Model 1 Coefficient Chi-Square Intercept -0.13 1.74 Watchlist 1.91 57.58 Junk Spread -0.08 49.21 NBER Recession -0.17 1.34 Previous DG 0.08 0.25 Capitalization -0.01 1.28 Low CAR 1.61 138.27 N 1586 Pseudo R Square 0.14 Statistics of ExAnte Probability of Downgrade within 180 Days Number Mean Std Max Min Median 744 65% 17.9% 98% 25% 68%

Follow Gibson, Singh, and Yerramilli (2003) to separate out the adverse selection component of the firm s stock price bid-ask spread. Assume that high stock adverse selection implies high adverse selection in bonds. Number Mean Std Max Min Median 774 0.086 0.065 0.339 0.000 0.071 Most firms have very little adverse selection component in their stock trades.

Mean Std Max Min Median % of days w/0 volume 96.7 5.9 100 54.7 98.5 Total trading volume ($M) 10.3 26.4 372 0.0 0.2 Total number of trades 3.7 8.4 95 0.0 1 Offering Amount ($M) 330 505 5000 5 200 Bond Age at Downgrade 4.9 3.8 25.7 0.1 3.9 Time-to-Maturity 12.7 11.98 100.01 0.2 10.0 As with most corporate bonds, fallen angels are not very liquid. Majority do not trade on any given day # and volume of trades per month is low

No Info bonds Negative info bonds 1m before DG 1m after DG Diff. N Mean Std Mean Std t-stat. # 774 0.85 2.91 1.24 4.71-1.93 $ 774 0.01 0.02 0.01 0.06-3.05 # 233 2.63 6.98 3.24 5.89-1.02 $ 233 0.01 0.02 0.02 0.04-2.59 Sunshine trading implies that sales after downgrade should be greater for no information group.

Not on WL On WL& 1 IG rating 1m before DG 1m after DG Diff. N Mean Std Mean Std t-stat. # 734 0.87 2.97 1.15 4.5-1.42 $ 734 0.01 0.02 0.01 0.06-2.84 # 40 0.60 1.24 2.83 7.21-1.92 $ 40 0.01 0.02 0.02 0.05-1.30 Trading for bonds on Watchlist much higher after downgrade.

Compare downgrades effects on bonds with negative information and those without information Consider whether bond returns are significantly different from zero Adjusted returns different if price pressure exists No info group should show smaller absolute bond returns than negative information group Less impact on price if dealers view insurers trade as uninformed To avoid information effects use a fairly narrow window of two weeks before or after the downgrade date Should have few information effects but remember stock return was only investigated over three day window

Bond returns over 2 weeks around DG Panel A: [-14, 13] window Fallen Angels Identified Based on Four Agencies Negative No Diff. in Info Info means Group Group t-stat. Number of Bonds 53 67 Raw Returns -11.42% -1.21% (-2.66) (-3.07) (-1.23) Adjusted Returns -11.69% -1.30% (-2.77) (-3.23) (-1.33) Information effects are large, price pressure effects are small.

So far, our evidence suggests that price pressure effects are minimal. If any price pressure exists, ought to be greater for bonds with more selling pressure Look at amount of selling across no info bonds If any price pressure exists, ought to be more important for less liquid bonds Look at liquidity variation in no info bonds

Liquidity Factor Coefficient % zero volume days Not Significant Trading volume Number of trades Offering amount Bond age Time to maturity Not Significant Not Significant Not Significant Significant (Negative) Not Significant

Sales Pressure Factor Number of sell transactions in [-1,30] Volume of sell transactions in [-1,30] Number of sell transactions on after_date Volume of sell transactions on after_date Coefficient Not Significant Not Significant Not Significant Not Significant

Classification of the stocks is based on std dev in earlier period. If std dev high then easier to count firms as no info. Stock returns for neg info group sharply lower than for no info group No info group in the 4 agency classification has downgrade later in time on average: Among neg info in 4 agency sample, over 75% have downgrade on same day as Moody s and S&P Among no info in 4 agency sample, only 61% have downgrade on same day as Moody s and S&P

Potentially some stocks are really no info stocks but have major price pressure effects we would put them in the wrong group and their price pressure on bonds would show up as info effects All bonds were investment grade so all were in the category of large cap Stocks are under much less regulatory pressure because insurance companies and pension funds have a much smaller share of the stock market If stocks suffer from selling pressure ought to see a bounce-back in a fairly short period of time

Difference in negative info and no info stocks Fallen Angels Identified Based on Four Agencies Negative Diff. in Info No Info Means Group Group t-stat. Number of Stocks 14 28 Abnormal Stock Return (-1,+1) -13.52% 0.05% Zero Trading Days 0 0 Adjusted Trading Volume 55.49 23.31 (1.46) (2.63) (3.59) Bid-Ask Spread from CRSP (%) 1.20 0.64 (1.37) (3.12) (4.49) TAQ Bid-Ask Spread [-1,1] 0.0578 0.0545 (-0.30) (-97) (-193)

Adjusted Trading Volume Average Daily Adjusted Trading Volume Surrounding the Downgrade Date - FAs Identified Based on 4 Agencies 90 80 70 60 50 40 30 20 10 0-100 -91-82 -73-64 -55-46 -37-28 -19-10 -1 8 17 Trading Day Negative Abnormal Stock Return 26 35 44 53 62 Restricted Sample 71 80 89 98

Cululative Return (%) 5-Week MA of Median Culumative Returns of Downgraded Bonds 0% -20-18 -16-14 -12-10 -8-6 -4-2 0 2 4 6 8 10 12 14 16 18-5% -10% -15% -20% -25% -30% -35% -40% Week All Issues Negative Group No Information Group

Absent information effects, expect flat demand curve Information about fundamentals already out Dealers know the insurers are not informed traders Often easy to predict that the bonds will become FA Clean test of selling where no info-related motivation Regulations rely on ratings, which are slow in many cases Separate out the slow adjustment cases by looking at the stock returns at the downgrade announcement When the information is already out the downgrade triggers selling without any information effects We don t find much price pressure Four agency is more relevant for forced selling and it shows no price pressure Price reversals only exist for negative info bonds