Invest Like Buffett: Risk reduction

During the Berkshire-Hathaway annual shareholders meeting a week ago, a questioner asked how Berkshire’s reinsurance unit priced Super Cat (super catastrophic) policies re-insuring other insurance carriers against immense losses.  Warren Buffett fielded the question from the audience and passed it to Ajit Jain, Berkshire’s Vice Chairman of reinsurance operations.  The two-part answer was instructive.

Say No:

Both Jain and Buffett said they say ‘no’ to far more opportunities than they price or accept.  In fact, Warren Buffett and Charlie Munger have stated numerous times over the years they believe they’re successful because they say no to most things.  Warren went farther saying that he and Charlie didn’t have the record they do because of any great skill they have, but because of their ability to say no to as often as they do.

This ability to say no is important to Dividend Farmers.  The financial world and media covering it are a frenzy of day-trading, impulse buying, and “act now” advice and direction.  When MSNBC, Bloomberg, Forbes, your broker, brother-in-law, and a universe of actors are telling you this is the next Apple or Amazon you shouldn’t miss, it’s a challenge to hold fire saving your investment money for select opportunities.  But that’s exactly what Warren Buffett and Ajit Jain counseled 40,000+ attendees.  Considering the record of the men involved, that’s good advice. 

Risk Mitigation:

Beyond saying no, Jain ventured into the process his team goes through in pricing Super Cat insurance.  They start with as much historical data as they can find.  They want to know all they can about the likelihood of an event, how, where, and why it may occur, and the magnitude of the consequences if it does.  Jain and team are conducting risk analysis coupled with an expected cost estimate.

Risk Assessment Matrix

The data helps them define the hazard e.g., a typhoon in a specific region, as well as the estimated probability said typhoon will happen during a given time frame.  They’re using a process analogous to the risk assessment matrix I previously blogged about. 

In the Berkshire analysis, the hazard generates a combination of likelihood and severity resulting in a risk level.  Once the is risk identified, Jain and company determine what price can be applied to account for that risk plus Berkshire’s much discussed margin of safety by baking expected cost into the equation.

Expected cost is the probability of an event happening times the cost of the event if it does.  For example, if the probability of an event happening is 1%, but the cost of the event, should it happen, be $1,000,000, the expected cost of the event is $10,000 (.01 x 1,000,000 = 10,000). 

Estimating the expected cost of a risk (part science, part art) allows Berkshire’s reinsurance group to apply a price that accounts for this cost while ensuring Berkshire remains financially healthy.  This is the margin of safety. 

In my million dollar example, an insurer may price the policy at $500 per year knowing there’s an estimated 1% chance of paying out $1,000,000 and a 99% chance of collecting $500.  If the insurer has the capacity to pay $1,000,000 in the unlikely event of such a claim, it can pocket $500 frequently with little effort and do so repeatedly while using that $500 as investment cash as it waits on possible claims payout.  This no interest ‘loan’ is what Warren frequently refers to as float. 

Economic Moat

In the case of Berkshire’s reinsurance division, the dollar figures are considerably greater allowing the firm to take on risks and expected costs no other entity has the capacity to accept.  This financial strength allows Berkshire’s reinsurance arm to capture premium business at premium prices with few competitors to drive down the price.  Talk about a financial moat!

DIY Investor Application:

Investment Research

Although this example stems from Berkshire-Hathaway and its super cat business, the principle is applicable to us DIY investors.  If I begin by reviewing as much data as possible about a prospective investment opportunity, I’m off to a good start.  Doing so helps me gain a sense of how likely the company is to provide a desired return.  The higher the desired return, the lower the likelihood it is to happen, in general, and vice versa. 

I’m establishing an expected payout (probability of return x return) against which I weigh an expected cost to invest (probability of cost x cost).   For example, if I believe the probability of a return is 80% and the return is $5 a share in dividends, my expected payout is $4 per share per year.  If my cost of investing is $50 a share and the probability of that cost happening is 100% (I buy the share) my expected cost is $50 a share with an expected return of $4 a share in a given year.  This represents an 8% return on my money which is solid.

On the risk side, if I estimate the chance of losing my $50 share is low, say 1%, then my expected cost of losing my money is .01 x $50 or 50 cents.  Against this I have an expected return of $4 which is 8 times greater than my expected cost when investing.  Probability is on my side and my risk, although not zero, is quite low.  As long as I’m capable of losing my $50 without going broke, I’ll gladly accept $4 a year in returns for the very low possibility I’ll lose the $50. 

This is the same kind of bet Ajit Jain and Warren Buffett make with super cat insurance policies and do so successfully.  If I’m going to be a better investor, learning from those who have proven highly successful themselves offers a template I’m not going to ignore.

The thoughts expressed here are those of the author, who is not a financial professional.  Opinions should not be considered investment advice.  They are presented for discussion and entertainment purposes only.  For specific investment advice or assistance, please contact a registered investment advisor, licensed broker, or other financial professional.