paper on us+canada risk arb deals 1998-2010, incl. termination rate

8/9/2019 Paper on US+Canada risk arb deals 1998-2010, incl. termination rate

1/14Electronic copy available at: http://ssrn.com/abstract=1705548

Macroeconomic drivers

behind risk arbitrage strategy

Fabienne Cretin, Slimane Bouacha, Stphane Dieudonn

OCTOBER 2010

Macroeconomic drivers behind risk arbitrage strategy? OFI ASSET MANAGEMENT 1All rights reserved


2/14Electronic copy available at: http://ssrn.com/abstract=1705548

Abstract

This document is a quantitative analysis of risk arbitrage strategy across a sample of 1,911M&A deals announced between January 1998 and September 2010 in the US and Canada.The study highlights the macroeconomic factors that might affect the risk/yield calculation fora risk arbitrage position. The main factors are: US unemployment, the investor confidence

indicator, the investment grade credit spread, P/E and price on the S&P 500, short terminterest rates and the yield curve. Ultimately, it is hoped that this document will providemanagers with an interpretation of the mergers & acquisitions market as well as a decision-making tool to complement traditional qualitative analysis.

1. Introduction

Following the announcement of a merger & acquisition deal, Risk Arbitrage is a strategy tocapitalise on the possible difference between the listed price of the target and thecorresponding bid price. This price difference, known as the discount or spread1, reflects the

period of time that must elapse until the deal is finalised but also, and most importantly, the

risk that the deal will fall through, which would lead to the price of the target falling back toits price before the announcement. Spread and termination probability are the two key

parameters in managing a risk arbitrage portfolio.

To implement this strategy in practical terms, managers most commonly apply a qualitativeand fundamental investment process that analyses the specific risks of each deal. Is the dealdependant on financing? Which competition authorities need to approve and within whattimeframe? Must the buyer sell certain assets to obtain this approval? Must the deal beapproved by the shareholders of the buyer and the seller? etc. These are the sorts of questionsthat we address every day when analysing a new bid.

The approach of the risk arbitrage strategy proposed in this note is more quantitative than

qualitative. This top-down approach places each deal in the general context that prevails at thetime of the announcement by seeking to establish whether there are exogenous factors (stockmarket or macroeconomic) that might influence the success of a deal and therefore thestrategys yield. For the purposes of this study, we looked at 1,911 M&A deals announced

between January 1998 and September 2010 in the US and Canada.

This note does not aim to build a risk arbitrage investment process based on a statistical

model to replace the traditional fundamental approach. It aims rather to identify themain variables that might influence this strategy. Ultimately, it is hoped that this documentwill provide managers with an interpretation of the mergers & acquisitions market as well as adecision-making tool.

This analytical work is the culmination of experience and knowhow accumulated by ourmanagement team since the launch of the first OFI Risk Arbitrage fund in March 2000 andthen the OFIRisk Arb Absoluin March 2004. This top-down approach also strengthened ourqualitative risk analysis, which is now the cornerstone of the investment process for these twofunds.

2. Methodology

To implement this quantitative approach, we first had to compile as comprehensive a databaseas possible of mergers & acquisitions. The North American market (US and Canada) was a

natural choice as it has a long record in this respect and is still the top global market for thistype of deal.

1A glossary of the main technical terms may be found in the appendix

Macroeconomic drivers behind risk arbitrage strategy? OFI ASSET MANAGEMENT 2


3/14

Bloomberg has a database that lists all the mergers & acquisitions together with the maindetails of each (size of the operation, premium paid by the buyer, terms of the bid, typology ofthe bidder, etc.). However, for the purposes of our analysis, there was no information on thetwo key parameters of expected yield and termination rate.

Bloomberg does not keep a record of the risk arbitrage spread, whereas the level of the spreadover the first days of the announcement provides precious information, as we shall show later.

With regard to the termination rate, the Bloomberg database lacks detail on the status of thedeal, which is either completewhen finalised, or terminatedif abandoned. For example, a dealmay have been abandoned following opposition by competition watchdogs, but also followinga counterbid for the target by a third party. In the first case, the outcome for the arbitrageur isnegative, insofar as the price of the target falls by the equivalent of the acquisition premiumand, in the second case, the outcome is positive as the price rises towards the terms of thecounterbid.

For liquidity reasons, we have only taken deals exceeding $ 500m from the Bloombergdatabase. We have also only used deals for which the terms are consistent with setting up anarbitrage strategy. The scope of our study eliminates spin-offs, acquisitions of minority stakes

and exits from bankruptcy situations. All in all, we have made detailed analyses of 1,911announcements merger & acquisition proceedings on listed companies in the US and

Canada over the 1998-2010 period.

For each deal, we have calculated thenet spread1of the arbitrage strategy, i.e. the annualised

spread less the yield on US 3 month T-bills at the time the deal was announced. To make itrealistic, this net spreadis determined on the basis of the average for the five days followingthe announcement of the bid. Although this calculation is simple in theory, the calculation hassometimes required adjustments to the prices of targets and bidders to take into accountcorporate events such as extraordinary dividends, spin-offs or share splits. In this way, byeliminating the time until finalisation of the deal, we have been able to plot a time-consistent picture of the net spreadover the observation period.

For each abandoned deal, we have also:

calculated the yield2 of the corresponding position to distinguish favourable outcomesfrom unfavourable outcomes.

ascertained the reasons the bids were abandoned.

All in all, we have made a monthly calculation of the termination rate for M&A deals over theperiod concerned by dividing the number of deals abandoned with an unfavourable impact bythe total number of deals finalised year on year.

The bottom of the cycle for M&A was in 2009, making it a good year to undertake this

considerable task. Alongside the daily management of our funds, we were thereby able to puttime and energy into building this proprietary database.

3. Analysis of macroeconomic factors that could have abearing on Risk Arbitrage strategy

This database means that we are now able to tackle the first issue we are interested in: arethere outside factors that could influence the termination rate and the net spread at a givenmoment on the market?

1See appendix for definition

2See appendix for definition



4/14

3.1 Methodology for multiple linear regression

Chart 1 shows the trend for these two parameters calculated every month over the periodconsidered. The orange line represents the 12 month rolling average for the termination rate.The blue line represents the six-month rolling average for net spreads of risk arbitrage for allthe deals announced. We have stripped out all the negative spreads from this calculation, i.e.

when a target is trading above the terms of the bid. Indeed, when this is the case, the spread isno longer a genuine reflection of the bid failing but rather the potential for improvement ofthe bid by the buyer or a third party.

0%

5%

10%

15%

20%

25%

12/98 06/99 12/99 06/00 12/00 06/01 12/01 06/02 12/02 06/03 12/03 06/04 12/04 06/05 12/05 06/06 12/06 06/07 12/07 06/08 12/08 06/09 12/09 06/10

0%

5%

10%

15%

20%

25%

30%Taux d'chec observ sur 12 mois glissants (chelle de gauche)

Spread moyen observ sur 6 mois glissants (chelle de droite)6 month rolling average for net spread (right-hand

12 month rolling average for the termination rate (left-hand)

Chart 1 : Trend in termination rate and risk arbitrage spread for M&A deals announced in the US and Canada over the1998-2010 period. Sources: Bloomberg and OFI AM

Firstly, contrary to what might have been expected, risk arbitrage strategy is not just a long,smooth ride! The annualised yield above the risk-free rate varies on average by between 5 and15%, peaking at over 25% in late 2008 following the downfall of Lehman. Similarly, thetermination rate for deals fluctuates between 2% and 13%, with a plateau of over 20% forseveral months in late 2008-2009, showing that around one in five deals announced finished

badly for the arbitrageurs!

Let us return to our top-down approach. The aim is to model variations in these twoparameters by using explanatory exogenous variables. By exogenous, we mean asindependent as possible from the Risk Arbitrage universe. We have therefore tested themarket and macroeconomic variables listed in Table 1.



5/14

Name of the variable Comment

VIX Volatility index on the S&P 500

Bull/Bear Index Index measuring the percentage of optimistic investorsconstructed form AAII US Investor Sentiment data

S&P 500

S&P 500 trend over 1, 3 and6 months

Change in the index over 1, 3 and 6 sliding months

P/E 1 yr forward on the S&P 500

Equity market risk premium Equity yield (inverse P/E) US 10yr T-bill yield. Proxy forrisky assets

Investment Grade creditspread

Markit CDX North America Investment Grade Index

Marketvariables

Yield curve Difference between the 10yr and 3M yields in the US.Proxy for future growth

Household confidence Conference Board Consumer Confidence

University of Michigan Survey of Consumer ConfidenceSentiment

Business climate Philadelphia Fed Business Outlook Survey

Business indicators ISM Indices

Economic growth leadindicator

ECRI weekly growth

Access to credit Indicator measuring conditions of access to credit forcompanies and individuals constructed from the SeniorLoan Officer Opinion Survey. Negative when lendingconditions tighten (e.g.: -40 in September 2008) andpositive when they ease (e.g.: +3 in 2005)

Macroeconomicvariables

US weekly jobless claims US Initial Jobless Claims

Table 1 : List of explanatory variables tested to model the termination rate and the risk arbitrage spread.Source: OFI AM

We have applied multiple linear regression quite traditionally using the formula:

Y = a0+ a1X1+ a2X2 + + anXn+

Whereby,

Y is the variable to be explained, the termination rate then the spread

X1to Xnare the explicatory stock market and macroeconomic variables featured in table 1

a0 to an are the parameters of the model that we want to estimate with the help of theinformation contained in our database

quantifies the spreads between actual recorded values and values predicted by the model

The regression aspect resides in:

selection of the most relevant X variables. The model must limit the number of these

variables to be reliable and a true reflection of the reality.

the estimation and above all the analysis of aparameters corresponding to the X variablesused.



6/14

measuring the models explanatory power. One of the models quality indicators is thecoefficient R2, which expresses the proportion of Y variability reflected by the model.The closer this indicator is to 1, the better the model.

3.2 Analysing the termination rate

We applied an initial linear regression by using all of the explanatory variables. The resultsappear interesting at first sight since R2works out at 0.86. However, close inspection revealsthat certain estimated aparameters are inconsistent with our understanding of the subject. Forinstance, a rise in volatility would lead to a decline in the termination rate. Anyone whoexperienced the aftermath of the Lehman debacle will spot the inconsistency!

In fact, among all the variables in Table 1, a certain number are inter-correlated. For example,the VIX and Investment Grade credit spread, the ISM indexes and that of the Philadelphia FedBusiness Outlook Survey or the variation in the S&P 500 over a sliding 6-month period andgrowth of the ECRI. Moreover, certain variables appear irrelevant from the outset such as the

variation of the S&P 500 over a 1-month sliding period. Although they seem to improve theR2, the correlated and irrelevant variables impair calculation of the regression and give rise toinconsistent results.

We therefore ran a second regression eliminating all of these redundant variables. With an R2of 0.79, the standard of this regression seems slightly inferior to the first one. However, theregression called on a limited number of variables: jobless claims in the US, the Bull/Bearindex, access to credit, the level of the S&P 500 and the yield curve . The a parametersestimated also give the model the capacity to explain the actual situation in a simple and solidmanner as summarised in Table 2.

A change in the variable of leads to a change in thetermination rate of

US weekly jobless claims +50 k +103 bp

Bull/Bear index +500 bp -76 bp

Access to credit +5 points -75 bp

S&P 500 +50 points -41 bp

Yield curve +50 bp -32 bp

Table 2 : Analysis of variables used and estimators for the regression model applied to the termination rate.Source: OFI AM

Table 2should be interpreted as follows: if investors become more optimistic prompting theBull/Bear index to rise from 50% to 55%, all other things being equal then the terminationrate declines for instance from 6.0% to 5.3%.

Chart 2 shows the contribution each of these four variables makes to variations in thetermination rate estimated by the model.



7/14

90

95

100

105

110

115

12/98 06/99 12/99 06/00 12/00 06/01 12/01 06/02 12/02 06/03 12/03 06/04 12/04 06/05 12/05 06/06 12/06 06/07 12/07 06/08 12/08 06/09 12/09 06/10

Taux d'chec estim

Demandes d'emplois US

Accs au crdit

Indice Bull/Bear

S&P 500

Pente de taux

US weekl obless claimsUS weekl obless claims

US weekly jobless claims

Access to credit

Bull/Bear index

S&P 500

Yield curve

Estimated termination rate

Chart 2 : Contribution of the four external variables to variations in the termination rate estimated by the model (eachvariable has been standardised to 100 at the start of the period. Sources: OFI AM and Bloomberg

As one might expect, when the variables move in a positive direction (increase in the numberof optimistic investors, improved conditions of access to credit, rising equity markets andsteepening of the curve), the termination rate declines. Conversely, a rise in unemployment isreflected by an increased termination rate. Some might find it surprising that the VIX is notamong the relevant variables since market volatility is often perceived as the foe of mergers &acquisitions. In fact, as this variable presents a significant colinearity with the InvestmentGrade credit spread, we used the latter as it makes a bigger contribution to the overallstandard of the regression than the VIX.

Since a chart is often clearer than a table of figures, Chart 3 compares the trends in thetermination rate and its estimation using the regression model. With the exception of fromMarch 2010 to the present, the model is fairly close to what actually occurred.

0%

5%

10%

15%

20%

25%

12/98 06/99 12/99 06/00 12/00 06/01 12/01 06/02 12/02 06/03 12/03 06/04 12/04 06/05 12/05 06/06 12/06 06/07 12/07 06/08 12/08 06/09 12/09 06/10

Taux d'chec observ sur 12 mois glissants

T reaux d'chec estim par rgression linaiTermination rate estimated by the model

12 month rolling average for the termination rate

Chart 3 : Trend comparison between the termination rate and its estimate by our multiple linear regressionmodel. Sources: OFI AM and Bloomberg



8/14

The recent counter-performance is due to factors related to the model as well as specificfeatures of the upturn in the mergers & acquisitions market.

On the one hand, unemployment has continued to grow and the yield curve flattenedsignificantly over the summer with the decline in long term interest rates.

On the other hand, it appears that against an uncertain medium term macroeconomic

backdrop, management teams are only willing to embark on an acquisition after havingdiscussed all the financial, industrial and legal aspects of the projects with their boards ofdirectors. As such, friendly bids usually succeed and hostile bids win over their targetcompanies thanks to the high level of acquisition premiums that are currently offered. Alltold, the termination rate is currently at a historically low level that the regression is unable tomodel correctly.

3.3 Analysis of the net spread

We have taken a similar approach as for the termination rate: an initial regression to see

followed by a second from which we have eliminated the correlating and irrelevant variables.The resulting model is very simple, entailing just two explanatory variables: market P/Eand the Investment Grade credit spread. In practical terms (see table 3), if market P/Eincreases from 10x to 15x for example, the spread widens from 4.0% to 6.7%. The predictive

power of the model is also interesting as it can explain over 70% of spread variations.

A change in the variable of leads to a change in thespread of

P/E +5 points +270 bp

Investment Grade credit spread +10 bp +100 bp

Table 3 : Analysis of the selected variables and the regression models estimators applied to the termination rate.Source: OFI AM

The link between the risk arbitrage spread and the credit spread is ultimately fairly naturalinsofar as both these parameters are components of relatively correlated risky assets yields.Conversely, the relationship between the market P/E and the average risk arbitrage spread isworth looking at in detail. Indeed

Chart 4shows that there is a significant correlation over the 1998-2007 period but that this isdisrupted over the 2008-2009 period.



9/14

0%

5%

10%

15%

20%

25%

30%

06/98 06/99 06/00 06/01 06/02 06/03 06/04 06/05 06/06 06/07 06/08 06/09 06/10

0

5

10

15

20

25

30

Spread de risk arbitrage (chelle de gauche) PE du S&P500 (chelle de droite)

Compression of the P/E and

narrowing of the risk arb spreadInverted relationship between

the P/E and the risk arb spread

Risk arbitrage spread (left-hand scale) Market PE on S&P 500 (right-hand scale)

Chart 4 : Trend comparison between the average Risk Arbitrage spread and the market P/E over the 1998-2010 period.Sources: OFI AM and Bloomberg

The high P/Es of the 1998-2000 internet bubble correspond to very appealing risk arbitrageyields. During this phase of irrational exuberance, companies were ready to acquire anyasset whatsoever at very high acquisition premiums of about 40% vs. 30% on average. For thearbitrageur, the acquisition premium represents the potential loss in the event the deal falls

through. He is therefore inclined to ask for higher remuneration for the risk undertaken.The bursting of this bubble led to the compression of P/E and the tightening of Risk Arbitragespreads from 2000 to 2007. This relationship was inverted with the subprime crisis, whichfirstly led to a dramatic widening of spreads while the trend of declining P/E that began 10years earlier continued.

Next, the March 2009 rally led to a normalisation of Risk Arbitrage spreads while at the sametime P/Es expanded for a 9-month period. Finally, the correlation between the two parametershas been positive again since the beginning of 2010 with a compression of P/E concomitantwith a tightening of risk arbitragespreads.

3.4 Improvement of the model

Analysis of the explanatory P/E variable sheds light on an important point: the formation ofspeculative bubbles and their bursting are a significant factor in explaining Risk Arbitragespread trends. As such, none of the explanatory variables tested, except perhaps thosereflecting market sentiment, really take this phenomenon into account. We thereforeintroduced a new explanatory variable, which admittedly is no longer completely exogenousto the risk arbitrage universe, but is a good reflection of the euphoria or despair that may

prevail over the markets at a given moment: the percentage of potentially higher bids,measured by the percentage of deals trading above the terms of the bid in the five daysfollowing the announcement. Note that this is an estimate of the number of potentially higher

bids, not the number of higher bids that actually take place.



10/14

This variable offers a dual advantage:

It is a good measure of optimism (or pessimism) for both the investors prepared to buy thetarget above the price set by the buyer and for companies prepared to embark on costly

bidding wars.

It has no significant colinearity with the other explanatory variables in our model.

Furthermore, it is a good indicator of market timing! As shown by chart 5, moments ofdespair or euphoria in the risk arbitrage world coincide within a few months with peaks ortroughs on the S&P 500.

0%

10%

20%

30%

40%

50%

60%

70%

03/98 03/99 03/00 03/01 03/02 03/03 03/04 03/05 03/06 03/07 03/08 03/09 03/10

0

200

400

600

800

1000

1200

1400

1600

1800

Chart 5 : Trend comparison between the S&P 500 and the percentage of announced deals trading above the bid price.Sources: OFI AM and Bloomberg

By introducing this new variable, the model loses a little of its simplicity with five variables(the Investment Grade credit spread, P/E, the percentage of deals trading above the bid,the 3M rate and the University of Michigan Survey) instead of two previously.Conversely, its explanatory power is improved with an R2 of 0.77. Chart 6 shows that thesecond model is an improvement on the first in phases of pronounced widening or narrowingsuch as in 2001, 2009 and above all the beginning of 2010.

% de surenchres potentielles (chelle de gauche) S&P 500 (chelle de droite)

Euphoria !Despair !

% of potentially higher bids (left-hand scale) S&P 500 (right-hand scale)



11/14

0%

5%

10%

15%

20%

25%

30%

06/98 12/98 06/99 12/99 06/00 12/00 06/01 12/01 06/02 12/02 06/03 12/03 06/04 12/04 06/05 12/05 06/06 12/06 06/07 12/07 06/08 12/08 06/09 12/09 06/10

Spread de risk arbitrage observ

Estimation avec la variable % de surenchres potentielles

Estimation sans la variable % de surenchres potentielles

Risk arbitrage spread estimated without the variable percentage of potentially higher bids

Risk arbitrage spread

Risk arbitrage spread estimated with the variable percentage of potentially higher bids

Chart 6 : Comparison between the actual risk arbitrage spread and the two estimates calculated by our multiple linear

regression model. Source: OFI AM

4. Conclusion and what comes next

To the question are there exogenous factors that can explain termination rate levels and riskarbitrage spreads?, the answer is yes. Relatively simple models with five macroeconomicvariables are capable of explaining 80% of the variations of these two parameters.

Among these explanatory factors, note the combined influence of the credit market(Investment Grade spread and 3M rate) and the equity market (level of the S&P 500

and P/E).

For those used to a traditional fundamental approach, this should be a fairly troublingconclusion. Indeed, each merger & acquisition is a specific and particular story with its own

players, industrial/financial reasoning and competitive situation. However, once they areaggregated, these stories can be summarised fairly simply by a few factors that are outside theworld of risk arbitrage!

These models do not aim to forecast future trends for spreads and termination rates. They areintended simply to help the manager take the stock market and macroeconomic environmentinto account when analysing the risk/return of deals in their portfolio and to improve theoverall allocation of risk.

In our next study, we continue this quantitative risk arbitrage approach by analysing, from aprobabilistic angle, the main risk factors that are specific to each merger & acquisition.

Another avenue of thought for a future study: if the merger & acquisitions market is drivenby macroeconomic forces affecting the volume of deals1, the termination rate and the spread,how can the risk arbitrage strategy be seen as decorrelated from the main asset classes? Weshall see how measuring risk allows a manager to transform cyclical raw material into afinished product that is as non-volatile as possible, i.e. a low- fund able to generate anabsolute performance.

1Marina Martynova and Luc Renneboog, 2005, A Century of Corporate Takeovers: What Have We Learned and

Where Do We Stand?, SSRN



12/14

Example

To illustrate the main technical terms, we have used the example of Intels acquisition ofMcAfee announced on 19 August 2010. The bid was made in cash at $ 48 per share. Beforethe bid, McAfee was trading at $ 29.93. Over the five days following the announcement, theshare was trading at an average of $ 47.05. The bid is expected to end on 31 December 2010,

i.e. in 134 days.

28

33

38

43

48

53

07/04/2010 07/05/2010 07/06/2010 07/07/2010 07/08/2010 07/09/2010

US$

Cours de McAfee

P erix de l'offrOffer price

MCAfee stock price

Spread de risk arb

Prime d'acquisition

Jour de l'annonceAnnouncement date

Acquisition premium

Risk arbitrage spread

Chart 7 : McAfee stock price before and after the announce of Intels offer.Sources: OFI AM and Bloomberg

Acquisition premium

Difference between the price of the bid and the price before the bid was announced, i.e.

60.4% = ($ 48 - $ 29.93) / $ 29.93

In our database, we have calculated the acquisition premium compared to the average over the20 days prior to the announcement of the bid to eliminate speculative impacts that sometimesoccur just a few days before an announcement.

Spread or risk arbitrage discount

Difference between the average price five days after the announcement and the price of thebid, i.e.

2.0% = ($ 48 - $ 47.05) / $ 47.05

Net risk arbitrage spread

Annualised risk arbitrage spread less the 3M T-bill at the time of the announcement, i.e.

5.4% = 2.0% * 365 days / 134 days 0.13%



13/14

Yield from the risk arbitrage position

We assume that the arbitrageur opens his position over the first five days following theannouncement.

If the deal is finalised as expected, the positions yield will be equal to the spread calculatedabove, i.e. 2% gross or 5.4% annualised above the risk-free rate.

If the deal fails, it is possible that the McAfee share will fall back to the pre-bid rate. Thestrategys yield would then be:

-36.4% = ($ 29.93 - $ 47.05) / $ 47.05



14/14

Bibliography

Keith C. Brown and Michael V. Raymond,Risk Arbitrage and the Prediction of SuccessfulCorporate Takeovers, Financial Management, 1986

Marina Martynova and Luc Renneboog,A Century of Corporate Takeovers: What Have We

Learned and Where Do We Stand?, Journal of Banking & Finance, 2008

Mark Mitchell and Todd Pulvino, Characteristics of Risk and Return in Risk Arbitrage,Journal of Finance, 2000

G. Andrew Karolyi and John Shannon, Wheres the Risk in Risk Arbitrage?, CanadianInvestment Review, 1999

paper on us+canada risk arb deals 1998-2010, incl. termination rate

Documents