Property Catastrophes and Equity Markets

Andrew J. Sterge, Ph.D. April 2014 AQR Reinsurance Reinsurance has become increasingly popular with investors for its equity-like risk premium

and low correlation to equity and other capital market returns. It pays to further investigate the low-correlation evidence, however, because while dislocations in the global equity markets have no known bearing on the likelihood or severity of major natural or man-made catastrophes, the converse of zero causality between these events and equity markets is not so clear. This is the topic we address in this paper, and the evidence is nuanced. In the U.S., for example, equity market reactions to large-scale catastrophes have been transient and relatively small in scale, ostensibly because the U.S. economy is big and robust enough to handle such losses in stride. In smaller economies, however, where catastrophes can cause losses that are meaningful percentages of GDP, equity market reactions to such catastrophes can be meaningful as well.

The author wishes to thank John Lummis for suggesting this study; Kathleen Rode, AQR Capital Management, LLC David Bookstaber and Bernard van der Stichele for their valuable research Two Greenwich Plaza assistance; Mark Stein for his helpful comments; Jennifer Buck for her layout and Greenwich, CT 06830 design; and Peter Nakada from RMS for data and his insightful comments. p: +1.203.742.3600 f: +1.203.742.3100 w: aqr.com

Property Catastrophes and Equity Markets 1

Introduction year period are too small relative to the economy to have an impact on broad-based U.S. stock Reinsurance has become increasingly popular indices. However, the situation is different in with investors for its equity-like risk premium and smaller economies such as Japan’s and low correlation to equity and other capital market Thailand’s, where major natural disasters can returns. It pays to further investigate the low- cause (and have caused) losses that are correlation evidence, however, because while meaningful percentages of GDP. In such dislocations in the global equity markets have no instances, large property loss events can foment known bearing on the likelihood or severity of relatively long-term equity market losses. major natural or man-made catastrophes, the converse of zero causality between these events We have not experienced disasters like this in the and equity market performance is not so clear. U.S., but that does not mean one could not occur. Indeed, as insurance losses caused by Using third-party modeled simulations of natural catastrophes have become increasingly large over catastrophes, we investigate the likelihood of the past 50 years (see Exhibit 1), it might be that there being events in the U.S. of similar relative these losses have grown large enough to shake magnitude as those that negatively affected the investor confidence and drive down stock prices stock markets of smaller economies. We do the while also inflicting losses on reinsurance same for Europe. Our conclusion is that any investments. natural catastrophe in the U.S. or Europe that could cause anything greater than a transient This is the topic we address in this paper, and the negative reaction in equity markets would be well evidence is nuanced. For example, the U.S. beyond a 1-in-100-year occurrence. economy — and by extension the U.S. — has been big and robust enough to The Evidence handle $100 billion insurance catastrophes in stride (such as the September 11 terror attacks in Consider Exhibit 2, which compares U.S. equity 2001 and Hurricane Katrina in 2005)1. Further, returns 100 trading days before and after the five there appears sufficient evidence that the kinds of most expensive U.S. natural catastrophe disasters insurance losses one would expect in any 100- since 1980. Hurricane Katrina (2005), the most

Exhibit 1: U.S. Aggregate Property Catastrophe Insured Losses (in 2012 dollars)

90 80

70

60 50

40 US$ billion US$ 30 20 10

0

1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 1950 Source: Property Claims Services, The Bureau of Economic Analysis (BEA).

1 The $100 billion we refer to are estimated economic losses in current (i.e., 2012) dollars.

2 Property Catastrophes and Equity Markets

Exhibit 2: Major U.S. Property Cat Losses vs. U.S. Equity Performance Change in the S&P500 index 100 trading days before and after the five most expensive U.S. natural disasters since 1980

20% 10% 0% -10% -20% -30% -40% -50% -100 -80 -60 -40 -20 0 20 40 60 80 100 Northridge Andrew Sandy Katrina Ike

Source: Bloomberg L.P. expensive at an estimated $125 billion of tremendous loss for those in its path, and it had economic losses in 2005 dollars, caused no the potential to be even more disruptive had it noticeable effect on equities. This stands to damaged offshore oil infrastructure, it is doubtful reason because these losses were less than 1% of that a loss of this magnitude (0.25% of GDP) did the $13.1 trillion U.S. GDP in 20052. The same was anything to exacerbate an established bear true for Sandy (2012); the Northridge, market that eventually erased approximately $8 California, earthquake (1994); and Hurricane trillion in the market value of U.S. stocks4. This Andrew (1992), which are estimated to have illustrates an important principle: random events caused $65 billion, $44 billion and $27 billion of that are independent can still happen in the same economic losses in original dollars, respectively3. year, thereby creating the appearance of As terrible as these were in terms of lives lost and correlation when none exists. All in all, we find property damaged, they were not big enough no connection between the biggest historical U.S. relative to the overall economy to affect U.S. property catastrophes and U.S. equity market stocks on whole. performance; presumably, the events have all been too small relative to GDP to matter. Hurricane Ike (2008), which caused an estimated $38 billion in economic losses at the time, appears All of the top 10 U.S. property catastrophes are to be an exception. While this event was a listed in Exhibit 3. With the exception of

Exhibit 3: Top 10 U.S. Natural Catastrophes (1980–2012) Losses from even the costliest disasters have been relatively small compared with the overall U.S. economy Economic Losses Insured Losses Economic Losses Insured Losses U.S. GDP Name Year (2012 $B) (2012 $B) (Original $B) (Original $B) $B Hurricane Katrina 2005 155 77 125 62 13,095 Northridge, CA earthquake 1994 98 34 44 15 7,309 Hurricane Sandy 2012 65 30 65 30 16,245 Hurricane Andrew 1992 64 42 26 17 6,593 Hurricane Ike 2008 42 20 38 19 14,720 Hurricane Ivan 2004 30 18 23 14 12,277 Hurricane Wilma 2005 27 16 22 13 13,095 2004 24 11 18 8 12,277 Hurricane Rita 2005 20 15 16 12 13,095 Hurricane Frances 2004 16 7 12 6 12,277

Source: Munich Re NatCatService, BEA

2 Source: data.worldbank.org/indicator. 3 Munich Re NatCatService. 4 Wilshire Total Market Index, Bloomberg L.P.

Property Catastrophes and Equity Markets 3

Exhibit 4: Major Terror Losses vs. Equity Performance Change in benchmark equity-market indices 100 days before and after major terror attacks

30% 25% 20% 15% 10% 5% 0% -5% -10% -15% -20% -100 -80 -60 -40 -20 0 20 40 60 80 100

9/11 WWII Sarin Madrid

Source: Bloomberg L.P.

Hurricane Ike, the graphs of equity index after the sarin attack and Madrid bombing, performance surrounding the event are all although both reverse in order. As horrible similarly flat (i.e., including those not shown). as these events were, they were not big enough to affect earnings expectations or risk aversion in Terror — An Exception? any meaningful or long-term way. The September While the equity-market impact of large-scale 11 attacks, after which a short-term market sell- property loss from natural catastrophes is the off also followed, destroyed more property and focus of this discussion, terror events can also was a more transformative event than the sarin cause large-scale destruction of wealth and attack or Madrid bombing, but the negative property, so it is worthwhile to examine the effect market reaction was still short-lived. Indeed, after of these events as well. Data from developed 9/11 the U.S. equity markets were closed until markets are thankfully sparse; we examine three: September 17; upon reopening, the S&P500 fell 11 the September 11 terror attacks in the U.S. (2001), percent over the ensuing 4 days before fully sarin gas poisonings (1995) and the Madrid recovering to its pre-9/11 close exactly one month train bombing (2004)5. We also include the Pearl later, on October 11, 2001. Only after the Pearl Harbor (1941) bombing for context, though from Harbor attack was there an extended sell-off and an insurance standpoint per se, this was not a recovery, with the Dow Jones Industrial Average major event. falling 20% after the event, and then taking almost one year to fully recover, in November Exhibit 4 shows the pre- and post-event analysis 1942. using the major domestic stock market indices relevant for each event (i.e., the Dow Jones From an insurance loss-to-GDP standpoint, none Industrial Average (Pearl Harbor), S&P 500 (9/11), of these events, or others in the historical record Nikkei 225 and IBEX 35 indices). In contrast to of terror strikes, are large events. Still, it is not the imperceptible reactions we see post major surprising that we see equity market reactions, U.S. catastrophes, stock markets fall immediately however short-lived. Terror events are different from natural disasters. For one, they are more

5 confidence shaking; when one hits we feel we are These examples were chosen based on their financial market impact; other terror acts destroyed more property and assets but were not losing the battle against evil. For another, they market-moving. See, for example, “Top 10 Costliest Acts of Terror,” Property Casualty 360, September 24, 2013. are not random occurrences but planned as to

4 Property Catastrophes and Equity Markets location, time and intensity. A natural years for the index to recover, but since then it catastrophe cannot intentionally wreak havoc at has rallied considerably and as of this writing strategically important financial centers like New stands almost 40% above where it was before the York or , for example, whereas these are disaster. It is arguable the Nikkei could have prime locations for terror strikes. begun its bull market sooner had the Japanese economy been spared Tohoku’s destruction, but Albeit with little data to go on, it would seem of course this is conjecture. reasonable to conclude that large-scale terror events have the potential to negatively affect The 2011 floods in Thailand were an even more equity markets, perhaps even more so than extreme local-economy event, causing almost $50 natural catastrophes, at least insofar as the U.S. billion in economic losses, equivalent to 15% of evidence can be extrapolated. that country’s GDP7. As shown in Exhibit 5, this event affected Thailand’s SET equity index, Large Events in Smaller Economies though like Japan post-Tohoku, the SET index It would stand to reason that U.S. equities have has rallied considerably once recovery began. The not been substantially affected by the significant SET fell 23% (from 1,134 to 869) from the start of insurance and reinsurance events we have the floods at the beginning of August 2011 to its experienced because, as painful as these events low two-and-a-half months later. But since then were for the people and property directly affected, Thai stocks have nearly doubled. The 23% fall they were not meaningful enough in the context was certainly painful to local market investors, of U.S. GDP at the time of the event to matter. but it also proved transient. However, what if we considered major insurance In stark contrast to equity market responses to losses in countries with smaller economies and Kobe, Tohoku and the Thai floods are the cases of equity markets? The 1995 Kobe and 2011 Tohoku the Chile (2010) and New Zealand (2010–2011) earthquakes in Japan, the 2011 Thai floods and earthquakes. In the case of Chile, the 2010 2010 Chile and New Zealand earthquakes are earthquake was one of the costliest natural telling in this regard. In Japan, for example, these disasters on record, at $30 billion of economic major earthquakes caused estimated economic losses, or 14% of Chile’s 2010 GDP8. However, losses in 2012 dollars of $110 billion for Kobe and Chile’s equity market declined only 2% in $210 billion for Tohoku, or approximately 2% and response and then rallied thereafter. Why this 3%, respectively, of Japan’s current $6 trillion magnitude 8.8 earthquake that destroyed roads, GDP6. fishing ports and more than 200,000 homes was Kobe happened in January 1995, amid a bear such an equity market non-event can probably be market that saw the Nikkei index fall from 39,000 explained by the fact that Chile’s economy is in 1989 to less than 8,000 in 2003. The index fell export- rather than consumer-driven. As powerful more than 22% immediately after the event, as the earthquake was, it did not affect Chile’s which killed more than 6,000 people, then status as the world’s leading copper producer, nor recovered a year later before resuming its long did it measurably affect its other natural resource slide. Tohoku, which killed more than 15,000 exporters or the banks and other companies between the quake and subsequent , supporting them. Moreover, as we look back, occurred in March 2011 and the Nikkei fell almost Chile’s GDP has increased approximately 50% 20% over the next two days. It took almost two 7 “Lloyd’s Analyzes Repercussions of Thai Floods a Year Later,” Insurance Journal, October 3, 2012; GDP data from data.worldbank.org/indicator. 6 data.worldbank.org/indicator. 8 Munich Re NatCatService; data.worldbank.org/indicator.

Property Catastrophes and Equity Markets 5

Exhibit 5: Major Non-U.S. Insurance Losses vs. Equity Performance Change in benchmark equity-market indices 100 trading days before and after major non-U.S. natural disasters

10%

0%

-10%

-20%

-30% -100 -80 -60 -40 -20 0 20 40 60 80 100

Tohoku Kobe Thai Floods

20%

10%

0%

-10%

-20% -100 -80 -60 -40 -20 0 20 40 60 80 100

Chile Quake NZ Quake

Source: Bloomberg L.P. since the catastrophe, testimony to the economy’s small portion of the losses10. This alone might resilience and momentum before and after the explain why the market shrugged it off, but event, though the recovery and rebuilding effort perhaps more compelling is that the largest undoubtedly contributed thereto. company in the NZX50 index (at 11% weight) is international construction conglomerate Fletcher The 2010 Canterbury earthquake in New Building Ltd. — a company the market would Zealand, and ensuing aftershocks in the first half assume would benefit from the disaster. of 2011, caused estimated economic losses of $16 Consistent with this, Fletcher stock was up 5% on 9 billion, equivalent to 11% of that country’s GDP . the trading day immediately following the event Yet New Zealand equities rallied in the face of (the NZX50 index was up 1.2%), and the this destruction. We cannot completely explain company did in fact report significant earnings why, but similar to the case with Chile, gains in 2011 due to earthquake reconstruction11. idiosyncratic details likely known by the market Even in light of this evidence, the equity market’s beforehand may offer explanation. For one, $13 rise after this major catastrophe still seems billion of the estimated economic losses were surprising. The same could be said for the 2010 insured losses, and $11 billion of those were Chile event. Like any study of market behavior, indemnified by global reinsurers, meaning the we are not dealing with an exact science here. New Zealand economy itself bore a relatively 10 Munich Re NatCatService; “Impacts of the Canterbury earthquakes on New Zealand’s international accounts,” Statistics New Zealand Information Centre, www.stats.govt.nz. 11 2011 Annual Report: www.fletcherbuilding.com/investor- 9 Ibid. centre/reports.

6 Property Catastrophes and Equity Markets

On whole, there is too little data in our historical section, since none we can analyze historically event study to be anything other than suggestive. have been big enough relative to the economy to If any generalization can be drawn, it is that if a matter. In the next section we take another look country seems susceptible to property at this from a theoretical perspective. We catastrophes that are large relative to that examine Europe from this perspective as well but country’s GDP, then the disasters have the leave out Asia and Japan, because as we have just potential to cause equity market reactions. Why illustrated, big natural catastrophes can cause the effects are not unambiguously negative is a negative equity market reactions in those mystery. One reason is that there are mitigating, economies. countervailing effects. When property or assets are destroyed they need to be rebuilt or replaced. Modeled Losses — U.S. This generates economic activity, which may in The economic losses of 9/11 and Katrina, the two fact be accretive if older vintage technology is biggest events in current dollars at about $100 brought up to date, which in turn could lead to billion each12, have evidently not been large higher productivity. However, as Bastiat (1850) enough relative to U.S. GDP to affect U.S. points out in his parable of the broken window, equities in any meaningful, permanent way. But there are unseen effects that counteract the this analysis is incomplete and biased because reconstruction activity that is seen. In their study the country has been hit by only a few of the economic effects of natural disasters from catastrophic events since it has developed great 1961 to 2005, Loayzqa et. al. (2009) provide concentrations of wealth and assets. Moreover, evidence for Bastiat’s theory, showing empirically some events the U.S. has experienced — like the that on average a major hurricane or earthquake Great Miami Hurricane of 1926, the Northeast’s increases industrial growth by almost 1%, but Great Hurricane of 1938, the 1811 New Madrid that it hurts other sectors (e.g., agriculture) by a earthquake, The Galveston Hurricane of 1900, similar amount, leading to zero or negative and even Hurricane Andrew — could cause losses growth in aggregate. Equity market non-reactions big enough to affect financial markets if they or even rallies in the face of major natural were to repeat today. But when these big events disasters might therefore be plausible based on did occur they were, in a relative sense, in the this evidence, especially if the market were middle of nowhere. As a result, we obtain no dominated by industrial or technology salient information for our study from these companies. In sum, however, we have to believe large-scale events. that major catastrophes hurt an economy overall; they may spur visible growth in some sectors, but To address this issue we look to the stochastic bottom line capital that could have more event catalog from Risk Management Solutions, productively been used elsewhere must be spent Inc. (RMS), one of three catastrophe-modeling to repair, replace or rebuild that which could have firms commonly used by the insurance and been more productively spent elsewhere. Still, the reinsurance industries to estimate loss countervailing effects certainly mitigate the distributions from natural perils13. RMS’s models, economic destruction, and this undoubtedly is like the other firms’, are simulations representing understood by equity markets. sets of synthetic events that are calibrated off historical data, and the scientific understanding It is not known whether the U.S. stock market is susceptible to property catastrophe insurance 12 9/11 economic loss estimate from Institute for the Analysis of Global losses as large as the ones discussed in this Security. 13 The others are AIR Worldwide (a unit of Verisk, Inc.) and EQECAT, Inc.

Property Catastrophes and Equity Markets 7

Exhibit 6: Top 20 U.S. Property Catastrophe Modeled Losses The 20 worst single-event losses to insurance companies based on 10,000-year simulation of U.S. natural catastrophe occurrences per RMS $ Insured Loss Occurrence Year Territory/Peril 587,024,841,096 351 Category 5 Hurricane FL 563,444,961,055 9283 Category 5 Hurricane FL 362,508,928,252 9633 Category 5 Hurricane TX 338,886,464,877 6927 Category 5 Hurricane FL 329,603,713,055 1861 Category 4 Hurricane FL 295,199,852,556 2402 Category 3 Hurricane NY 259,531,782,321 6832 Category 4 Hurricane FL 248,519,930,586 2398 MW 7.0 EQ New Madrid 233,105,800,744 6056 Category 5 Hurricane FL 231,629,287,652 9461 MW 7.0 EQ New Madrid 230,265,384,856 9697 Category 5 Hurricane LA 228,710,617,863 6363 MW 9.0 EQ Pacific Northwest 222,278,849,371 8784 Category 5 Hurricane FL 212,067,532,834 5085 MW 7.0 EQ New Madrid 209,789,633,822 7757 Category 5 Hurricane FL 202,314,188,908 2113 Category 4 Hurricane LA 197,791,617,359 9748 Category 5 Hurricane FL 196,808,578,133 4144 Category 5 Hurricane FL 195,790,803,227 3653 Category 4 Hurricane TX 194,814,350,368 4212 Category 4 Hurricane FL

Source: AQR. of the physical processes and their impact on catastrophe with a 100 year return period is $140 property assets. One of the outputs of these billion, making all of the top 20 events worse than models, for a particular cataloged event, is an 1-in-100 year catastrophes. In the 10,000-year estimated aggregate loss to the insurance underlying event catalog, there are 1,618 U.S. industry. events out of 147,502 in total that would be expected to cause over $140 billion of losses. Note In reviewing the RMS simulated events for 10,000 that more than one-half of these are Florida years specific to the U.S., we find that the top 20 hurricanes. For context, in Exhibit 7 we also list events cause between $190 billion and $590 billion RMS’s estimated losses for the biggest historical of insurance industry losses (Exhibit 6 lists the events in the U.S., simulated as if they were to top 20 U.S. of these as per RMS’s U.S. earthquake occur today. However, none of these replayed and hurricane simulations). According to this historical events would make it into RMS’s top 20 same simulation, the RMS loss estimate for a simulated events (although the worst of the Exhibit 7: 10 Most Expensive Replayed U.S. Historical Events RMS’s modeled estimates of losses for the 10 most expensive historical events if they were to repeat in 2013 Name Year $ Loss New Madrid 1811-12 sequence 1811-12 184,808,706,844 The Great Miami Hurricane 1926 130,855,802,912 The Gale of 1878 1878 90,865,145,222 The Okeechobee Hurricane 1928 78,327,045,743 Hurricane Andrew 1992 61,889,485,497 The 1900 Galveston Hurricane 1900 60,662,385,202 The 1932 Freeport Hurricane 1932 58,260,796,613 1893 Cheniere Caminada Hurricane 1893 51,500,816,249 1947 Fort Lauderdale Hurricane 1947 49,979,718,732 The Great 1906 San Fran. Earthquake 1906 49,541,224,410

Source: AQR.

8 Property Catastrophes and Equity Markets

Exhibit 8: Top 10 Europe Property Catastrophe Modeled Losses Ten worst single-event losses to insurance companies based on 10,000-year simulation of European natural catastrophes as per RMS $ Insured Loss Occurrence Yr. Description 41,763,053,628 3752 Winterstorm DE-UK-FR-BE-NO-NL… 29,475,604,802 2752 Winterstorm FR-UK-BE-DE-NL-CH… 27,621,715,069 2293 Winterstorm DE-UK-FR-BE-NL-NO… 26,611,160,625 2058 MW 7.8 EQ Portugal 23,368,044,184 7037 Winterstorm DE-BE-UK-NL-FR-PL-CZ… 19,997,250,966 773 Winterstorm FR-UK-DE-BE-NL-CH-IE… 19,742,029,586 4262 MW 8.0 EQ Izmit 17,232,151,667 3688 Winterstorm DE-UK-FR-BE-NL-NO-DK… 16,990,796,936 6273 SSI200=7.09 FR-UK-BE-NL-IE-W3 16,307,088,141 4437 Winterstorm DE-UK-FR-BE-NL-CZ-PL…

Source: RMS. Country codes: AT-Austria, BE-, CH-Switzerland, CZ-Czech Republic, DE-Germany, FR-, IE-Ireland, LU-Luxembourg, NL- Netherlands, NO-, PL-Poland, SE-Sweden, SK-Slovakia, UK-, W3-Offshore Northern Europe. historical events, the New Madrid earthquake Modeled Losses — Europe sequence of 1811, comes close). Europe has not received much attention in our discussion thus far. The region does not appear How events such as these would affect U.S. stocks susceptible to the types of natural catastrophes is an open question, but we are talking about that can inflict economic losses on the scale of unprecedented economic losses on the order of what could happen in the U.S. or Japan. In part $400 billion to $1.2 trillion (i.e., two times the “$ this is due to the types of natural perils faced by Insured Loss” numbers in Exhibit 6)14, or about Europe; namely, winter storms and floods, 3% to 5% of current U.S. GDP. The only data we neither of which pack the energy of a hurricane or can relate these to are the Kobe and Tohoku “hot zone” earthquake15. In the historical record earthquakes and Thai floods. Events similar to since 1980, there have been four events (all winter these disasters, if they were to occur in the U.S., storms) that caused economic losses greater than would most likely have a measurable, but $10 billion in current dollars: the twin temporary, effect on U.S. stocks. Among the Lothar and Martin (1999), The Great Storm of unknowns, though, is that since the U.S. 1987 (known in insurance circles as “87J”), Daria economy is the world’s largest there could be (1990) and Kyrill (2007)16. Only the combination deleterious cause-and-effect ramifications in the of Lothar and Martin produced losses of more U.S. or abroad due to economic shocks of such than $20 billion. Given the European Union’s magnitude. Making it worse, some insurers and $17.5 trillion GDP17, repeats of events such as reinsurers might fail, though it does not logically these are too small to worry about from an equity- follow that any of these would create systemic market perspective. It is worth mentioning, risks the way big bank failures could have in however, that storm 87J occurred on the eve of 2008. The bottom line is that an unprecedentedly the 1987 stock market crash, and probably large natural catastrophe would likely cause a exacerbated its losses due to the disruption it negative equity market reaction in the U.S., caused in London’s financial center. This is especially if the event hit Manhattan and led to another example of unfortunate, but market dysfunction, but as far as we can tell the negative reaction would be temporary.

15 “Hot zone” means active tectonic plate boundaries, such as the Pacific Ring of Fire. 16 Munich Re NatCatService. 14 Based on casual comparison of insured loss and economic loss from 17 EuroStat--28 Country European Union GDP = €13 trillion; converted Munich Re’s NatCatService tables of the most costly natural disasters. at €1 = $1.35.

Property Catastrophes and Equity Markets 9 uncorrelated, insurance and equity market losses U.S. GDP to matter. However, when we look at happening at the same time. events on the order of 5% to 10% of GDP in Japan or Thailand, we do find a measurable post-event RMS’s modeled loss-event catalog for Europe equity market loss in those countries. The gives us little to worry about as well (see Exhibit evidence is anecdotal in that we study only five 8). Only the 10 biggest events in the 10,000-year such events, but it stands to reason that some simulation generate economic losses nearing 1% conclusions may be inferred: After sufficiently to 2% of European Union GDP. Modeled loss large disasters, confidence is shaken, financial events of the 1-in-100-year variety are on the assets have to be liquidated to pay for the order of $30 billion of insured losses, or roughly recovery, and future earnings prospects of many $60 billion (0.5% of GDP) in economic losses. businesses are compromised18. These are events comparable to Katrina in the U.S. — devastating catastrophes, but not big We augment our event study in the U.S. by enough to induce broad equity-market losses. considering the largest modeled hurricane or earthquake losses in the RMS stochastic catalog Conclusion and speculate that only the biggest of these might While it is becoming accepted that investing in meaningfully affect U.S. stocks, at least property catastrophe reinsurance as an asset temporarily, which is similar to what we have class offers portfolio benefits because it is observed in Japan and Thailand. The modeled diversified from financial market risks, actually frequency of such events in the U.S., however, is measuring the diversification potential of only 1-in-100 years. We do the same modeled loss reinsurance is problematic because there is no analysis for Europe and find very little evidence publicly available data to study the premium that it is susceptible to equity market-moving versus loss experience of a portfolio of natural catastrophes. reinsurance contracts. While it is intuitive that In sum, from a global market perspective, there is financial market volatility, panics, squeezes and scant evidence from the historical or modeled other dislocations would have no bearing on the record that large insurance losses would cause natural disasters that would drive reinsurance aggregate equity market losses; there could be performance, it could well be that major natural relatively measurable and long-lasting such or man-made property catastrophes would cause effects within smaller economies, however, but market sell-offs, particularly in equity markets. not in the U.S. or global equity market on whole. Answering this question is hampered by data limitations, since property catastrophes large enough to affect capital markets are rare by definition. But after examining data on the largest global property catastrophes, we only find suggestions of catastrophe-to-equity sell-off causality in economies susceptible to property catastrophes that are large relative to GDP in those economies. In the U.S., for example, the S&P 500 has not been affected by large U.S. insurance events because nothing in the 18 Some companies, like construction and engineering firms, may historical record has been big enough relative to experience improved prospects post-disaster, but in general the exceptions are few.

10 Property Catastrophes and Equity Markets

Related Studies

Albala-Bertrand, J.M., 1993, “Natural disaster situations and growth: A macroeconomic model for sudden disaster impacts,” World Development, 21(9), 1417–1434. Anbarci, Nejat Monica Escaleras, and Charles A. Register, 2005, “Earthquake fatalities: the interaction of nature and political economy,” Journal of Public Economics, 89(9–10), 1907–1933. Bastiat, Frederic, 1850, “What is Seen and What is Not Seen,” in Selected Essays on Political Economy, The Foundation for Economic Education, Irving-on-Hudson, NY, 1995, translated by Seymour Cain. Benjamin, Kleidt, Schiereck Dirk and Sigi-Grueb Christof, 2009, “Rationality at the eve of destruction: Insurance stocks and huge catastrophic events,” Journal of Business Valuation and Economic Loss Analysis, 4(2), 1–27. Brynjolfsson. John, and Matt Dorsten, 2007, “Do natural disasters affect the stock market?” Pacific Co. Forbes.com, 2010, “Chile’s Post Earthquake Economic Strength,” March 4. IMF.org, 2010, “Chile: Strong Recovery After Devastating Earthquake,” September 29. Insurance Journal, 2006, “AIR Sees Possible $50 Billion Insured Losses,” October 26. Karen Clark & Company, 2013, “The Great New England Hurricane of 1938: What a 100 Year Northeast Hurricane Will Do Today,” September 16. Lamb, R. P., 1998, “An examination of market efficiency around hurricanes,” The Financial Review, 33(1) 163–172. Li, Siqiwen, 2013, “Natural Disaster-Induced Australian Equity Market Reaction: Discrimination Across Industries,” Journal of Law & Financial Management, 12(1), 18-28. Loayza, Norman, et. al., 2009, “Natural Disasters and Growth: Going Beyond the Averages,” Policy Research Working Paper 4980, The World Bank. Maierhofer, Simon, 2011, “5 Worst Disasters — How Did the Stock Market React?” www.etfguide.com, March 25. Noy, Illan, 2009. "The macroeconomic consequences of disasters," Journal of Development Economics, 88(2), 221-231. Risk Management Solutions Inc., 2007, “The Great Storm of 1987: 20-Year Retrospective,” Special Report. The Economist, 2011, “Market Tremors,” March 16. The Economist, 2011, “Counting the Cost,” March 21. The Economist, 2012, “Counting the Cost of Calamities,” January 14. Wang, Lin, 2013, “The Impact of Japanese Natural Disasters on Stock Market,” working paper, Southern Illinois University. Worthington, Andrew and Abbas Valadkhani, 2004, "Measuring the impact of natural disasters on capital markets: an empirical application using intervention analysis," Applied Economics, 36(19), 2177- 2186. Worthington, Andrew and Abbas Valadkhani, 2005, “Catastrophic Shocks and Capital Markets: A Comparative Analysis by Disaster and Sector,” Global Economic Review, 34(3), 331-344. U.S. Geological Survey, 2011, “Report on the 2010 Chilean Earthquake and Tsunami Response.”

Property Catastrophes and Equity Markets 11

Biographies

Andrew J. Sterge, Ph.D. Andrew is Chairman of the Portfolio Management Committee of AQR Re, the Bermuda-based reinsurance affiliate of AQR Capital Management. Prior to AQR Re, Andrew was president of the AJ Sterge Division of Magnetar Capital, where he managed reinsurance investments and quantitative trading strategies while serving as a director of Magnetar’s reinsurance affiliate, Pulsar Re. Prior to that he founded and was Chief Executive of AJ Sterge LP, which Magnetar acquired in 2006. Before that he was Chairman and Chief Executive of the CooperNeff Group, a unit of BNP Paribas. His groundbreaking equity trading strategy remains the centerpiece of BNP Paribas' proprietary equity trading. Andrew earned a B.S. in mathematics from Wake Forest University and a Ph.D. in mathematics from Cornell University.

The author wishes to thank John Lummis for suggesting this study; Kathleen Rode, David Bookstaber and Bernard van der Stichele for their valuable research assistance; Mark Stein for his helpful comments; Jennifer Buck for her layout and design; and Peter Nakada from RMS for data and his insightful comments.

12 Property Catastrophes and Equity Markets

Disclosures

This document has been provided to you solely for information purposes and does not constitute an offer or solicitation of an offer or any advice or recommendation to purchase any securities or other financial instruments and may not be construed as such. The factual information set forth herein has been obtained or derived from sources believed by the author and AQR Capital Management, LLC (“AQR”) to be reliable but it is not necessarily all-inclusive and is not guaranteed as to its accuracy and is not to be regarded as a representation or warranty, express or implied, as to the information’s accuracy or completeness, nor should the attached information serve as the basis of any investment decision. This document is intended exclusively for the use of the person to whom it has been delivered by AQR, and it is not to be reproduced or redistributed to any other person. The information set forth herein has been provided to you as secondary information and should not be the primary source for any investment or allocation decision. This document is subject to further review and revision.

Past performance is not a guarantee of future performance

This presentation is not research and should not be treated as research. This presentation does not represent valuation judgments with respect to any financial instrument, issuer, security or sector that may be described or referenced herein and does not represent a formal or official view of AQR.

The views expressed reflect the current views as of the date hereof and neither the speaker nor AQR undertakes to advise you of any changes in the views expressed herein. It should not be assumed that the speaker or AQR will make investment recommendations in the future that are consistent with the views expressed herein, or use any or all of the techniques or methods of analysis described herein in managing client accounts. AQR and its affiliates may have positions (long or short) or engage in securities transactions that are not consistent with the information and views expressed in this presentation.

The information contained herein is only as current as of the date indicated, and may be superseded by subsequent market events or for other reasons. Charts and graphs provided herein are for illustrative purposes only. The information in this presentation has been developed internally and/or obtained from sources believed to be reliable; however, neither AQR nor the speaker guarantees the accuracy, adequacy or completeness of such information. Nothing contained herein constitutes investment, legal, tax or other advice nor is it to be relied on in making an investment or other decision.

There can be no assurance that an investment strategy will be successful. Historic market trends are not reliable indicators of actual future market behavior or future performance of any particular investment which may differ materially, and should not be relied upon as such. Target allocations contained herein are subject to change. There is no assurance that the target allocations will be achieved, and actual allocations may be significantly different than that shown here. This presentation should not be viewed as a current or past recommendation or a solicitation of an offer to buy or sell any securities or to adopt any investment strategy.

The information in this presentation may contain projections or other forward‐looking statements regarding future events, targets, forecasts or expectations regarding the strategies described herein, and is only current as of the date indicated. There is no assurance that such events or targets will be achieved, and may be significantly different from that shown here. The information in this presentation, including statements concerning financial market trends, is based on current market conditions, which will fluctuate and may be superseded by subsequent market events or for other reasons. Performance of all cited indices is calculated on a total return basis with dividends reinvested.

The investment strategy and themes discussed herein may be unsuitable for investors depending on their specific investment objectives and financial situation. Please note that changes in the rate of exchange of a currency may affect the value, price or income of an investment adversely.

Neither AQR nor the author assumes any duty to, nor undertakes to update forward looking statements. No representation or warranty, express or implied, is made or given by or on behalf of AQR, the author or any other person as to the accuracy and completeness or fairness of the information contained in this presentation, and no responsibility or liability is accepted for any such information. By accepting this presentation in its entirety, the recipient acknowledges its understanding and acceptance of the foregoing statement.

Hypothetical performance results (e.g., quantitative backtests) have many inherent limitations, some of which, but not all, are described herein. No representation is being made that any fund or account will or is likely to achieve profits or losses similar to those shown herein. In fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently realized by any particular trading program. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. For example, the ability to withstand losses or adhere to a particular trading program in spite of trading losses are material points which can adversely affect actual trading results. The hypothetical performance results contained herein represent the application of the quantitative models as currently in effect on the date first written above and there can be no assurance that the models will remain the same in the future or that an application of the current models in the future will produce similar results because the relevant market and economic conditions that prevailed during the hypothetical performance period will not necessarily recur. There are numerous other factors related to the markets in

Property Catastrophes and Equity Markets 13 general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results, all of which can adversely affect actual trading results. Discounting factors may be applied to reduce suspected anomalies. This backtest’s return, for this period, may vary depending on the date it is run. Hypothetical performance results are presented for illustrative purposes only. n addition, our transaction cost assumptions utilized in backtests , where noted, are based on AQR's historical realized transaction costs and market data. Certain of the assumptions have been made for modeling purposes and are unlikely to be realized. No representation or warranty is made as to the reasonableness of the assumptions made or that all assumptions used in achieving the returns have been stated or fully considered. Changes in the assumptions may have a material impact on the hypothetical returns presented.

There is a risk of substantial loss associated with trading commodities, futures, options, derivatives and other financial instruments. Before trading, investors should carefully consider their financial position and risk tolerance to determine if the proposed trading style is appropriate. Investors should realize that when trading futures, commodities, options, derivatives and other financial instruments one could lose the full balance of their account. It is also possible to lose more than the initial deposit when trading derivatives or using leverage. All funds committed to such a trading strategy should be purely risk capital.

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