Notes starting from May 5, 2009

Updated: May 28, 2009.

Not a Black Swan

A Black Swan event is an unusual event. It is NOT always unfavorable.

The October 2008 meltdown was NOT a black swan event. It fell easily within the likely outcomes based on the high initial valuations ten years ago.

What was a Black Swan event or, actually, a series of Black Swan events were the continued S&P500 price increases at the end of the 1990s.

Monte Carlo Models

Not everything that has confidence limits is a Monte Carlo model. A Monte Carlo model has a randomness generator built into it. Probabilities are extracted from historical data or, too often, from outright guesses. Then a Monte Carlo model converts that information into understandable outcomes.

The Scenario Surfer and the Investment Strategy Tester are Monte Carlo models.

The Year 15 SWR and Year 30 SWR Retirement Risk Evaluators and the Stock Returns Predictor are not. They use historical sequences directly to supply the randomness. There do not include the intermediate stages of statistical data extraction, characterization and random number generation.

Free Lunches for Everyone

There are “free lunches” available all over the place for those who will look for them. Opinion? I say: FACT. From 2007.

Free Lunches for Everyone

Denial Remains Expensive

I added the Dividend Blend and Income approaches since writing this article. Adding them, readers had five great choices. You should have avoided the worst of the 2008 meltdown. From October 2006 and July 2008.

Denial Is Expensive
Five Great Choices

Thresholds and Allocations

Bear Market rallies are commonplace.

History suggests that we are in a Bear Market rally, not a recovery. If so, the downside could be brutal. Historically, P/E10 falls between 5 and 8 before hitting bottom. The history does not have enough events for us to rely on that information statistically. History is suggestive, not thoroughly convincing.

P/E10 fell almost to 11 this time. Today, it is 16.

My sensitivity studies show that the best thresholds and allocations have a broad maximum. [I discovered this in my early Current Research.] Although I have identified current P/E10 thresholds and allocations at 10-18-30 and 100-80-20-0%, consider taking a little money out of the stock market early. Consider extending the full P/E10 range of the allocation shift from 16 through 21 as opposed to restricting yourself to the single value P/E10=18. Consider a current allocation of 50% or 60% instead of 80%.

Now is a good time to practice on the Scenario Surfer. Learn how you react to sharp changes in valuations.

It is also a good time to visit Ed Easterling’s Crestmont Research web site. Read his articles about the stock market.

Crestmont Research

Was It Or Wasn’t It?

Was the run up in the late 1990s a Black Swan event? How about the October 2008 meltdown?

Was It Or Wasn’t It?

The Safe Withdrawal Rate Solution

We now know the solution to the Safe Withdrawal Rate problem.

The Safe Withdrawal Rate Solution

The Multiply-by-20 Rule

In case you missed it: you now need to save 20 times your annual retirement needs, not 25. It works in all kinds of markets. Rob Bennett brought out this point in a recent Letter to the Editor. Not any portfolio will do, however. You need to follow strategies developed at this site.

April 14, 2009 Letters to the Editor

Financial Planners

Financial Planners operate under severe constraints. How many could have gotten away with having investors at low stock allocations over the last ten years? Very few. Yet, that would have been great advice.

If you use a financial planner, work with him. Learn about investing. Learn about how he is matching your investments with your goals. And have him look for hidden flaws. Risk assessment is a weak point in investment training. You need to contribute your own insights.

It is a serious mistake to put everything into a financial planner’s hands. You need to contribute. It is your money. He cannot do his best without your participation.

For more, read Rob Bennett’s Letter to the Editor.

April 14, 2009 Letters to the Editor

Two of My Favorites

Here are two of my favorite articles.

Investment Traps
Elements of Skill

Two More Outstanding RobCasts

Rob Bennett has posted two outstanding RobCasts:

Podcast #103 -- Cash on the Sidelines Often Disappears Into Nothingness

Podcast #104 -- Probability Investing

Rob Bennett’s RobCast Page Thirteen

The Destructive Implications of the Bailout - Understanding Equilibrium

Here is an important article about today’s economy. It is Dr. John P. Hussman’s commentary for May 18, 2009.

The Destructive Implications of the Bailout - Understanding Equilibrium

How TIPS Could Go Sour

The definition of inflation is always controversial. In my opinion, the Government has done a credible job. However, I have spotted a Hidden Flaw for investors.

Inflation includes housing prices and “equivalent rents.” Today, we are seeing housing price deflation balanced out by serious inflation in gasoline, food and other necessities. Put everything into a single number and it does not look too bad for those who are just starting out. They can buy a house at a cheaper price and at a low mortgage interest rate.

But to a retiree, it is a disaster. He owns his home, which is worth less. His own cost of living has gone through the roof. Yet, his TIPS, which were meant to protect him, show a net inflation adjustment close to zero.

Everything has been stacked against the retiree in spite of best intentions.

Read Rob Bennett's letter in response to this NOTE: The Housing Market Isn't Efficient Either.

May 20, 2009 Letters to the Editor

Risk and Monte Carlo Models

Properly used, a Monte Carlo model can help us identify risk. It can mitigate consequences. The Scenario Surfer, for example, identified the possibility of a super bubble following the bubble. It identified the possibility of very high valuations after a run up as in the early 1990s. At the same time, it has consistently warned us to prepare for a sharp price drop from high valuations.

Risk is not simply volatility. Risk is the hidden flaw. Monte Carlo models can help us. But you should never stop looking for a hidden flaw.

More about Monte Carlo Simulations

I posted this answer at Morningstar.

I am not near retirement, anymore, but had been wondering how many used or depended in any significant way on the Monte Carlo simulations?

I have created a couple of Monte Carlo simulations at my web site (the Scenario Surfer and the Investment Strategy Tester). But they are unique and I have used Monte Carlo simulations differently from others.

I think that Monte Carlo simulations are of great value for retirement training, assuming that you sell stock for income, and for identifying hidden flaws in your strategies.

Identifying your personal reaction to sharp price drops is important. Monte Carlo simulations can help.

I think that Monte Carlo simulations have value as a research tool. They extend the range of possibilities beyond the historical data.

The main danger is relying on Monte Carlo simulations for assurance that bad things will not happen. Another danger is using bad inputs. My own models automatically make adjustments for valuations. Others assume a rate of return, which is typically misleading.

Always look for hidden flaws. That is the real definition of risk. It is what you fail to prepare for that can hurt, not simple volatility.

Understanding Risk

Remember to match risk and income streams. That was my thinking behind Understanding Risk. What I called the CALCULATED RATE was what I now identify as the Likely Success rate in the calculators. The HALF FAILURE RATE was roughly equivalent to the Reasonably Safe rate. It is relevant for today.

Understanding Risk

TIPS and Real Estate

We are approaching a period of intense inflation. The best response in the past has been to buy hard assets. At the same time, real estate prices are depressed. Mortgage rates are low.

Take advantage of this. Invest in real estate. Alternatively, invest in TIPS.

Statistical Lessons Learned

Here are some of my key findings regarding statistical estimates.

Statistical Lessons Learned

Notes Index starting from November 23, 2007