Tag Archive | allocation


SmartStops comment:  an excellent article that every investor should read as MPT continues to be deeply entrenched in our systems.  Its shortcomings are proven.  The article concludes with:

The advice that most investment advisors give their clients – At its core, the message is usually something similar to this: “The markets are random and unpredictable, so the best way to invest is to properly diversify and wait for the averages to play out.”

However, what most investors seem to be unaware of is that this whole theory of random movement of market prices was proven false over 50 years ago by one of the most influential mathematicians of the 20th century, Benoit Mandelbrot. The random motion of market prices was a very nice theory, but it just doesn’t match what actually happens in the real world.

Some excerpts from JJ Abodeely, CFA’s article :   Modern Portfolio Theory Is Harming Your Portfolio

              1. MPT and the quantification of investing has further (mis)informed the debate by seeking a easy way to label and quantify “risk.” In 1952, Harry Markowitz chose variance or volatility of prices or returns to define risk. He did so because it was mathematically elegant and computationally simple. However, this idea has serious limitations (most of which Markowitz has since acknowledged).

              On the individual stock level, Vincent notes

Risk is often in the eye of the beholder. While “quants” (who rely heavily on MPT) might view a stock that has fallen in value by   50 percent over a short period of time as quite risky (i.e. it has a high beta), others might view the investment as extremely safe,   offering an almost guaranteed return. Perhaps the stock trades well below the cash on its books and the company is likely to         generate cash going forward. This latter group of investors might even view volatility as a positive; not something that they need to be paid more to accept. On the other hand, a stock that has climbed slowly and steadily for years and accordingly has a       relatively low beta might sell at an astronomical multiple to revenue or earnings. A risk-averse, beta-focused investor is happy to add the stock to his diversified portfolio, while demanding relatively small expected upside, because of the stock’s consistent track record and low volatility. But a fundamentally-inclined investor might consider the stock a high risk investment, even in a diversified portfolio, due to its valuation. There’s a tradeoff between risk and return, but volatility and return shouldn’t necessarily have this same relationship.

2.  After all, if you buy and hold the market you can earn the long-term returns right? Unfortunately, the answer to that is no. The long-term “average” returns are rarely available. In fact, depending on where you are standing, the returns are either much higher, or much lower. Consider this chart from Crestmont Research which shows that even for periods as long as 10 years, average rarely occurs:


3. Consider this chart which you’ve probably seen in one form or another. It shows expected risk and return of various mixes of asset classes and the typical approach to asset allocation which Modern Portfolio Theory has spawned:


So what’s wrong with this picture? Lots of things.

The first is the inputs– namely expected returns and volatilities of various asset classes– most investment programs are built on logic like this:

  • Bonds will return 5% on average over the long-term but be between 0-10% in any given year
  • Stocks will return 10% on average over the long-term but be between -10% and +20% in any given year
  • Some might include other nuance regarding different types of bonds like High Yield or different types of stocks like Emerging Markets
  • Some might include different types of assets like real estate, commodities, or “alternatives”

The problem of course is this is an incomplete description of investment returns:

  • The math contends that returns are randomly and unpredictably distributed around the average
  • This “normal distribution” of returns contends that larger market movements outside of the ranges above will be relatively rare
  • “Average” returns ignore the role of valuation and the importance of when you start investing (buy) and when you finish (sell) even over multi-decade time horizons

The traditional approach to asset allocation is built on false axioms. The phenomenal secular bull market in stocks and bonds from 1982-1999 created the perfect conditions for the nearly religious acceptance of MPT. In a recent post, Expensive Markets Mean Low (or Negative) Prospective Returns, I made the case that valuation matters greatly and currently portend disappointing returns for both stocks and bonds. Traditional asset allocation has no way of dealing with this in a way that successfully protects portfolios from experiencing meaningful and unnecessary drawdowns.

Read JJ Abodeely, CFA’s article :   Modern Portfolio Theory Is Harming Your Portfolio in its entirety.

Position Sizing: Key to Maximizing Returns

In a time when market volatility and equity preservation is of utmost importance, determining the correct number of shares to buy, or “position sizing”, is key to maximizing returns and minimizing risk.

The common investor generally doesn’t spend much time thinking about how many shares to buy or how significant of a position to take.  Instead, most investors use a common methodology of trading the same number of shares each time, which usually translates to a specific dollar amount.  Other, more sophisticated investors, opt to allocate a certain percentage of their portfolio value to a specific position. Following this train of thought, a new position in a portfolio of $100,000 would transcribe either a $10,000, or 10%, investment or a usual position of 50 shares.

Although these methods may work for some, using the volatility of a specific portfolio is likely to be the most effective decision tool.  Measuring a portfolio’s overall volatility enables an investor to decide on what percentage of that portfolio he is willing to risk losing on the new position.  This methodology is better explained through the following example. Read More…

A New Risk Indicator To Sidestep Market Downturns: Is It Better Than VIX?

By Chris Georgopoulos, originally published on 11/14/11

Without question the most popular model to predict market crashes is the VIX, commonly referred to as the “Fear Gauge,” a market index that measures the implied volatility of the S&P 500 index options. Its concept is quite simple, when the uncertainty and fear among investors rises, they commonly run to the S&P 500 options to either hedge or speculate. The increased interest in the options usually leads to higher premiums and as the premiums increase so does the VIX. However, predicting the future isn’t 100% accurate, most of the time it’s not even close. Every forecasting model has its flaws and the VIX is not an exception. There are many problems skeptics have found with the VIX such as; its population study is limited to only the 500 stocks of the S&P 500 and” {the} model is similar to that of plain-vanilla measures, such as simple past volatility” (Wikipedia). A blog post on sensibleinvestments.com summarized the VIX as “simply an indicator of actual volatility in the market but one that is very sensitive to changes in actual volatility particularly if it is on the downside.” Is there a better way?

An elementary statistics theory states that the larger the population size, the greater the likelihood that the sample will be represented. If markets are graded by the performance of popular indexes such as the S&P 500, why limit a forecasting model’s population to only 500 stocks? The economy has become global; interactions from every corner of the world’s businesses affect every other business. If there is a model that forecasts market direction, should it limit itself to just the largest companies? As for only using a month or two of short term option premiums to garner a prediction, as the VIX does, it seems to limit itself to only a single variable. Instead of short term options premiums and limited samples what if we could measure real-time individual stock trend alerts on thousands of domestic and foreign stocks and ETFs? Or simply what if we analyzed the micro components (every stock) to develop a macro forecast of the market based off trends and risk?

By studying the history of risk alerts from SmartStops.net, an intelligent risk management service, two proven alternatives to the VIX were found. SmartStops.net has developed their own proprietary risk model that monitors the trends and risks to over 4,000 of the most popular stocks and ETFs. If the risks grow on any individual investment SmartStops.net alert their subscribers with both long and short term exit triggers. However not only do these alerts help individual and institutional investors manage specific investment risk, the reviews of the alerts themselves have predictive capabilities. By back-testing every alert that SmartStops.net has issued from their inception versus the S&P 500 performance, there is proof of this and the results speak for themselves.

There have only been 7 days for which the amount of Long-Term Exit Triggers (stop alerts) as a percentage of every stock and ETF covered by SmartStops.net has been over 20%. The subsequent market action of the S&P 500 has averaged a negative return for the time periods of 1 week, 1 month, 3 months, 6 months and a year. The 6 month average return is over -7% and when examined from the absolute lows of the S&P 500, the returns average over -19%. If you remove the knee-jerk market reactions caused by “Flash Crash” on 5-6-2010, the returns are even lower.
Another metric offered by SmartStops.net is their SRBI(tm) (SmartStops Risk Barometer Index); this index measures the current percentage of stocks and ETFs that are in “Above Normal Risk” state (ANR) divided by the 100 day average above normal risk percent. By definition, a stock that is listed ANR experienced a risk alert as its last SmartStop alert identifying a downtrend. Conversely, a stock that is listed in a “Normal Risk State” experienced a reentry alert as its last SmartStop alert indicating trading strength and an upward trend. Back-testing historical SRBI data since inception shows that the repercussions to the market when the percentage of downtrends increases to over 40% of all stocks and ETFs covered are profound. Below you will see that there have been only five occasions where this has happened. In each case the S&P returns for the following year were all negative.

Is this a better way?

Before a concrete conclusion can be determined, the predictive capabilities of the VIX must also be analyzed. Read More…

NETFLIX Investors – Did you Protect Yourself?

NETFLIX , NFLX, drops but SmartStops keeps investors and traders from major losses.

This is why Risk Management and Protection are a must in every investor and trader’s arsenal.   SmartStops triggered its short-term protection for Netflix at $74.13 at 9:32AM.  NFLX closes at $60.28 today, 7/25/12.

In the most recent Netflix downtrend SmartStops saved its clients  $42.46 per share!  

See chart at: http://www.smartstops.net/PublicPages/SmartStopsOnDemand.aspx?symbol=NFLX


ETFs And Allocations To Protect Portfolios In The Current Financial Storm

excerpt from article at Seeking Alpha: 

 This is a followup to a previous postings suggesting how investors can take refuge in the oncoming financial storm. If you’ve not done so already, be sure to read my previous post Say It Ain’t So for a description of our dismal macroeconomic picture.

The purpose of this article today is to explore any safe havens for your investments to shelter them from this worldwide slump. What are we protecting against? Problem is, we don’t yet know. And we won’t until the elections play out next year, and events in Europe unfold.

The market may not wait for the politicians. Technical indicators suggest a very large correction in the market can be expected, and fundamental macroeconoomic trends unfortunately offer no consolation.

How severe will the downturn be?

In my view, that will depend in part on what fiscal and monetary policies we pursue, and how international political relations progress. There my crystal ball is a little cloudy.

Scenario one sees a continuation of monetary easing, as pursued by both the Bush and Obama administrations, and largely aped by European governments to a lesser degree.

In this scenario, the policy response will be pure Keynes, with large bouts of government spending to build out our country’s infrastructure and hopefully create jobs. The Fed will assist with gobs of money dished out to offset rapidly deleveraging private expenditures and to support our wobbling real estate market.

for rest of article, click here

Read More…

Chicken or Egg? Risk Tolerance as a Driver of Financial Success

SmartStops would like to draw your attention to this article’s statement:    Overall, by taking more risk Bill can expect to be significantly better off.    As SmartStops will remind you, you can take on more risk by ensuring there is constant active oversight for it.  See other articles on that subject.   

 published originally at:  Advisor One by Geoff Davey, FinaMetrica

Many studies have shown that risk tolerance correlates positively with income and wealth. The correlations are not strong, usually around 0.3, but they seem to be universal.

There is a temptation to think that higher income and/or higher wealth lead to higher risk tolerance. However, there is always a danger in trying to read a cause and effect relationship into a correlation. To know for sure we would need to conduct a longitudinal study measuring risk tolerance, income and wealth as we went along.

Failing that, we can conduct a thought experiment. Suppose that Bill and Bob have different appetites for risk. Presented with a choice between taking a certain $100 and a 50/50 gamble of winning $0 or $X, Bill will take the gamble when X is $250 but Bob won’t take the gamble until it reaches $300. Looking at any single $250 gamble choice, Bill has a 50% chance of being no worse off than Bill.  However, if Bill and Bob are presented with a series of such choices, the longer the series runs the more certain it is that Bill will finish up better off than Bob. With a series of 10, Bill has an 83% chance of being no worse off than Bob and by the time we get to a series of 100 that chance has increased to 98%.  Over 10 choices, Bill will finish with $1,000 but Bob could expect to have $1,250, though he may have nothing or $2500.

Now suppose that Bill and Bob both started with a kitty of $1,000 and that rather than the choices being framed from a base of $100, they were framed from a base of 10% of the kitty at the time. For 10 choices, Bob’s kitty grows to $2,593 but Bill’s grows to an expected average of $3,260 and 62% of the time will be greater than $2,590. At worst Bill will have $1,000 and at best $9,300.

Overall, by taking more risk Bill can expect to be significantly better off.

So how does this relate to real life? Clearly, life’s choices are rarely as simple as in our example and rather than a series of identical choices we face a series of mainly different choices where there are usually more than two alternatives—and those alternatives will often include the possibility of losses. Further, the range of outcomes is often not clear and they must be estimated rather than calculated. Finally, we may make cognitive errors in assessing the situation and in identifying and evaluating the alternatives.

As we know from experience, risky choices take many forms and occur in different contexts including employment, borrowing, insurance and investment. For the riskier alternatives to be considered there would be a commensurately greater expected reward, but this will come with the possibility of an unfavorable outcome. The more risk tolerant amongst us will need less of an incentive to take the riskier alternatives. If we continue that pattern over time, all other things being equal, we should finish up better off.

So my hypothesis is that risk tolerance is a driver of financial success rather than the converse.

If you can’t beat them join them, Best Buy. BBY

by  Chris Georgopoulos, SmartStops contributor

Reading financial articles can be, let’s say boring at times. This article we are going to try to spice it up, let’s play a game of role playing.  Famed speculator, Jesse Livermore once was quoted…

“If I were walking down a railroad track and saw an express train coming at me at 60 miles an hours.  I would be a damned fool not to get off the track and let the train go by. After it had passed, I could always get back on the track, if I desired.” –Reminiscences of a Stock Operator, Edwin Lefevre.  

For this game let’s rename the train, Best Buy stock (BBY: NYSE), the ““I” in walking down the track” we can call the shareholders of Best Buy and the speed of the train, the issues.  The game is scored by the costs of each decision. Whoever has the best return wins!

It is the end of summer 2005, Best Buy is approaching $80/share and the future couldn’t be brighter. The tech bubble burst is ancient history, the housing market is hot, interest rates are low and every house in America is an ATM for consumer spending.  You are on the railroad track…there isn’t a train in sight! 

It is now the beginning of fall 2008; Best Buy has fallen to the mid $40s in defiance of the market making new highs and there are rumors of problems in Mortgage backed securities.  (Note:  Sidestepping risk is now made possible with the release of SmartStops.net  which if had been available would have had you out in the $70 range in 2005).  Your friend has made a fortune flipping speculative properties in south Florida and Las Vegas, but you see he is worried. He still has five houses on the market with almost no personal income… (You know how this story ends)  You can hear a train coming and it sounds like it’s really moving!

Only a few months later, Best Buy is trading under $18/share!   The rumors are true; the housing market has crushed the stock market. It seems nobody thought housing prices would ever go down and the economy is on the verge of total failure. You can now see the train, its moving fast and finally you start to consider if you should actually get off the tracks.

(SmartStops.net   issued two Long-Term exit signals in 2008 the first January 4, 2008 at $46.80 and on September 16, 2008 at $40.68. That’s a  $22 per share savings by sidestepping risk.)

It is two years later; Best Buy is trading back in the mid $40s. Read More…


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