Valuation compression in the mid-cap reinsurance industry

The only long-term "buy & hold" investment I have right now is a small-cap/mid-cap reinsurance company called Montpelier Re (MRH). I purchased it a few years ago and I'm slightly down overall, mainly because US$ declined against C$, and also because I made a newbie valuation mistake (I didn't know insurance companies should be valued based on book value.) In any case, in the last two years, I have thought about purchasing more shares. The company is very high-risk and is a black box (I have no clue what their insurance model is or how well it can handle adverse events) but I like how the company has been run in the last few years (management has bought back around 25% of shares in the last 3 years while shares were trading below book value).

One of the most difficult things for newbies like me is trying to figure out what is a proper valuation for a company. One approach is to look at historical market value to the present but one can never be sure if there is a rational reason current valuation may be low. Such is the case with many insurance companies today.

One of the peculiar things I notice about the insurance industry, at least mid-cap reinsurers, is how the market has been marking down their valuations over the last 5 or so years. This is somewhat surprising given how these insurance companies aren't correlated with the economy and aren't exposed very much to the troubled real estate industry.

The following chart, courtesy Morningstar, plots the price to book value of a random selection of mid-cap reinsurers against the S&P 500 ratio. These companies aren't necessarily comparable given some difference in their risk profiles of their clients. Nevertheless it presents an overview of valuation compression. (As usual, click the picture for a larger one.)

As one can see from the various charts, price to book values that ranged above 1.3 have dropped slightly below 1. Also note that valuation, in many cases, started compressing long before the onset of the financial crisis and the recession.

The question is why?

Is the market irrationally depressed about this industry or is it predicting something? It's worth investigating given how a lot of wealth can be created by the investor, as well as the company itself, buying back shares below book value. (Do note that Bermuda-based insurers tend to have no moat and are very risky so anyone looking into these companies should be careful.)

One possibility for the valuation contraction is that the industry hasn't seen any major hurricanes or other adverse events in a while. Is the market predicting that some of the book value is going to get wiped out when a storm arrives?

I also wonder if the market is concerned that the return on investment (from float) is going to be low over the next 5 to 10 years. I am kind of bearish and expect bond yields to stay low for a while. Given how many of these insurers have their assets invested in low-yielding government bonds and other "safe" instruments, I wonder if their profits are going to decline. From what I understand, a lot of insurers didn't do well during the 1940's and 1950's because bond yields stayed low. In fact, many insurers in Japan had serious problems in the early 2000's because their returns on invested assets ended up being far lower than anyone had imagined in the 80's or early 90's. Is the American insurance industry going to face a similar, albeit less severe, problem?

Anyone have any idea what is going on here?

Comments

  1. What is the trend of the MRH's combined ratio?

    Insurance is a cyclical business. It's cyclical in premium mispricing. Buffett spent a lot ink on this topic in his BRK chairman letters throughout the years. This may not be the reason of your specific cases though.

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  2. Pricing is soft and investment profits will probably be anemic. But that could be a wonderful environment for insurance, and reinsurance, companies oriented to the underwriting. The yield hogs ROIC  will start to suffer and pricing will finally recover more than 5 years.

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  3. Sivaram VelauthapillaiSeptember 26, 2010 at 3:04 AM

    Thanks for the ideas John Y and PlanMaestro. I've started looking for historical data to see if this is for cyclical reasons.

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