A Dash of Insight

Developing and Evaluating Trading Systems

Improved technology, more power.  We would expect this to be good.

In fact, more power can enable us to do exactly the wrong thing.

This happens all of the time with the world's most powerful computer, the human mind.  A year ago we reviewed analysts who thought the market looked like a replay of the 1987 crash.  This type of analysis crops up all of the time, often using old charts as evidence.  With the power to search among thousands of choices, picking the time frame, and adjusting the scales, the human computer can "prove" nearly anything.

Those developing computer-based trading systems face the same problem.  The modern software makes it easy to include many variables --- too many!

Some Helpful Illustrations

Bill Rempel missed the Kentucky Derby by a few days, but his story highlighting horse race handicappers is excellent.  A group of handicappers were tested, using gradually increasing amounts of information.  The extra data increased their confidence, but not their performance!  (Read the entire discussion.)

Bill discusses Occam's Razor and points out the importance of reducing the number of independent variables:

I use this paring down or pruning technique at work as well as when examining trading strategies or opportunities. My first question, when faced with complex models, has for a long time been “I wonder how many of those variables actually do most of the work?”

This is pretty convincing to us, since Bill sounds just like our own Vince Castelli.  It is easy to develop a model using all of the available data and lots of variables.  You will generate a perfect "post-diction" but not anything useful for prediction.

The result:  Over-fitting and over-confidence, a dangerous brew!

Unfortunately, consumers of system strategies, including a few big-time "gatekeepers" we have met, have become accustomed to seeing eye-popping (and unrealistic) results.  They apply an automatic discount, regardless of the methodology employed.

The TCA Model Applied to the S&P 500

For the purposes of comparison, the chart below shows our TCA Model (Trend, Cycle, Anticipation) as applied to the S&P 500.  Without giving away the store, we can say that the model uses a relatively small number of variables -- some designed to choose between trend and cycle, and others representing indicators for each.  Much of the power comes from advanced techniques for filtering and smoothing data, thereby improving signal to noise.  The chart below is not a back-test, but the signals actually used in trading during the last year.

The overall performance shows a gain of about 6% during a time when the S&P declined by a few percent.  It accomplishes this while reducing risk by staying out of the market for significant periods.

A key point is that the model gets the investor into the market to enjoy the big moves.  The cost?  There are some losses at times of rapid changes or churning.

Finding the big moves is very important.  Some traders have trouble joining in when the market has already made a move.  They are reluctant to "chase."  It is difficult to show gains when missing the big rallies.

Anyone interested in trading systems should join us as regular readers of The Rempel Report, where he updates and reports on several interesting trading systems.  One of these is similar to our own sector rotation approach.

TCA-ETF Update

Each Thursday (a day late this week) we share with the investment community a recent report from our ETF ratings.  We have been doing this in real time for eight months.  Our purpose is partly to gain visibility for the approach (free report available on request), but also as information for other ETF traders, and most importantly to provide a laboratory for others trying to develop trading systems.  We discuss the issues surrounding system development in many of the articles in this series.

As we noted last week, we have expanded the ETF universe, and we seek more additions.  Adding more targets is helpful, as long as they can be shown to have characteristics suitable for one's model.

The current ratings show some dramatic changes from recent weeks, and include one of the new ETF's, KOL.

This looks good, too Good

Readers of "A Dash" do not need us to tell them the old common-sense idea, "If it sounds too good to be true...."

Or so we would think.

Meanwhile, those watching financial television are bombarded with self-serving ads from brokerage firms suggesting that the intelligent viewer can design his/her own trading system with their free software.

Other ads offer a pre-packaged approach, like Robert Taylor and the Xyber9 system.  We can't find the specific claims on the website, but the TV ads talk about accuracy in the 80's.  It is a great marketing program, with references to a Nobel Prize nomination and the Harvard Business Review.

So we wonder....

Analyzing Trading Systems

A standard method for analyzing a system includes some back testing.  Everyone does it, so the question is not "whether?" but "how?".

When we were developing and analyzing trading systems in the late 80's, there was an interesting phenomenon.

Every system we saw "predicted" the Crash of '87.

We should say "post-dicted."  Most of us now understand why, since we have all read Fooled by Randomness ( on our recommended reading list if you missed it).   If a system developer did not forecast the Crash, that system would never have seen the light of day.  It certainly was not presented to trading firms like ours.

The founder of  our group, who assembled a team of top options traders at the Chicago Board Options Exchange (CBOE), was Ralph Katz.  In the days before computer-generated option prices, Ralph could glance at a complicated page of quotes and tell you which specific prices were out of line.  Ralph understood immediately why the system development process might be wrong.  He would insist that the system developer go to a different time period, (e.g., Did the system capture the Gulf War Decline?),  one not contemplated by the original developer.

Ralph's approach is now used by the best system testers.

Analyzing Systems

When you get a system that seems "too good", it is time to take a close look.  CXO Advisory Group, one of our featured sites, does a great job of determining "guru grades."   Taylor's idea of using gravitational pull to predict stock performance was intellectually unsatisfying for us, so we asked CXO for an opinion.  They identified the strange definition of "trend" used by Taylor and concluded as follows:

In summary, Robert Taylor's accuracy rate probably derives not from forecasting   ability but from defining targets that are very hard to miss. The accuracy rate   seems high only if one ignores the peculiar way he defines trends.

Consumers Do Not Understand

The key to building a successful investment management business is marketing, and that seems to include making big claims.  The consumer is looking for a home run.  This usually means looking at what worked last year, and chasing that performance.

In a very helpful and honest article, Barry Ritholtz described the process of presenting his methods on a road show.  (Thanks to Barry for taking the time to send the pointer for an article we remembered.)  Barry wrote as follows:

Money raisers and some GPs have long ago figured this out. You have a few choices: you can answer the investors' questions honestly -- or to quote Ray Davies, you can give the people what they want (or think they want):

"We expect gains of 35-45%, with minimal risk or leverage. Our black box algorithms  have been backtested, and generate better numbers than that, but we would rather under-promise and outperform."

Read the entire article for the full flavor of this process.  Based upon our own experience, it is a very realistic account.  This method of choosing managers has led many to illusory low-risk returns based upon very high leverage and minimal true advantage (alpha).

If the big fund of fund managers are using this approach, imagine the challenge for the individual investor.

A Dash of Realism

The best investment managers, those that we admire greatly like Warren Buffett and Bill Miller, have periods where their style does not seem to be working.  That says more about the market than it does about the manager.

Any investor who wants to trade equities with little turnover (meaning low transaction costs) needs to understand what results qualify as strong.  Beating the market by several points a year is excellent, and it probably comes with some volatility.

TCA-ETF Update

Each Thursday we have been providing the rankings of the top ETF's in our universe along with a (slightly delayed) account of our actual trades.  We define a "cycle" as beginning with the last day where we were completely out of the market.  The current cycle, the third we have reported, shows results that lag the S&P (we were a little slow getting back in -- the TCA does not follow the "Gong Model" which was faster) and a little better than the Nasdaq.  There are many attractive sectors right now, including foreign ETF's and energy holdings.

 

The Use and Abuse of Data: Two Excellent Commentaries

In the current issue of Barron's Mike Santoli has some special insight for those trying to interpret the many historical analogies making the rounds.  He writes:

• Every time the U.S. unemployment rate has risen by at least 0.3% in a month, as it did in December, a recession has occurred. So a recession is a sure thing. 

• Prior to the onset of recession, there's typically at least a 25% one-year rise in weekly unemployment claims. The increase in claims in December was less than 7%. So a recession is not imminent. 

• But, then: The average decline in the S&P 500 from a pre-recession peak to a trough since 1945 has been 25%, just a few percent more than the index had lost from its 2007 peak to its intraday low Wednesday of last week. So, maybe the market has mostly discounted a typical recession scenario? 

• Hold on, because a bearishly inclined forecaster suggests that in recessions, 70% of the prior bull market's upside is undone, implying another 20% or so downside risk from today's levels. Scared yet?

• Not so fast, because every one of the 23 times since 1987 that the ratio of bears to bulls in the weekly American Association of Individual Investors poll has exceeded two (as now), the market was up 12 months later, by an average of 21%.

 

Such evidence of history's malleability is almost enough to make us all post-modern, and deny that any objective reality exists. More to the point, it's a little different every time, and the key is to figure out that difference.

These observations are excellent and the thoughtful followers of "A Dash" should read the entire column.  He reaches a conclusion that will be familiar to our readers:

But stocks have already been repriced to reflect expectations that published estimates are too high. The current S&P 500 forecast could be chopped by 10% and still market valuations wouldn't appear extreme at current prices. But the market's real-time response to muted corporate outlooks will deliver the true verdict on whether the market has built in enough fear.

The pricing of stocks compared to expected earnings and bond yields is our definition of a negativity bubble.

Barry Ritholtz, citing the Santoli column, offers some great advice for interpreting data.  He provides a list of questions--really good ones-- that anyone should ask.  Once again, readers should check out the entire article.

Applying the Ritholtz Advice

As we read Barry's advice, we immediately thought of many current "recession indicators".  We tried to illuminate this  problem with an earlier article on the problems inherent in forecasting unlikely events.  Let us try to apply the advice in this context, using several questions from the list.

• Do we have enough historical examples?  For recessions, the answer is clearly "no."  There are not that many of them, especially in recent years.  It is easy to tinker with a system to achieve a perfect retrospective model.
• Causation or correlation?  For recessions, many of the economic variables are concurrent or lagging indicators.  Most analysts look at directional movement versus absolute levels.  For example, unemployment claims are not close to prior recession levels.  They have moved higher, from some extremely low levels.
• Coincidence.  Are the factors really related?  The so-called Leading Economic Indicators come to mind.  Our own analysis finds little relationship between these indicators and payroll employment growth.  Other items, like the inverted yield curve, reflect unusual circumstances in the demand for US Treasuries, the "conundrum."
• Differentiating elements in other time periods.  This one is obvious.  Many of the recession forecasts reach deep into history.  Do we really think that markets and economic management from the Taft administration or the Great Depression are similar to current conditions?  What about corporate improvements in inventory control?  Is it possible that using computers makes a difference?
• Compare interest rates, inflation, dividend yield, P/E contraction or expansion, sentiment, overall market trend, business cycles -- across different eras. Might that account for potentially different outcomes?  Yes!  Circumstances in the early 70's, with very high interest rates, were different from now.  Another example: The Fed interest rate actions in the bubble era were much slower than they are now.
• Consider things in terms of probabilities, not outcomes.  Excellent!  We wonder how anyone can state with 100% certainty that we are "now in a recession."  Or the opposite.  If a recession occurs, something that no one knows yet, the actual dating of the beginning by the NBER will be the prior peak.  It might include the current period.  If there is a bounce in the economy, it will not.  Many of those so certain about a recession  have been (mis-)predicting the economy for years.  There is no statute of limitations.  The media points out that these people saw the problem early, as if it were praiseworthy to miss major market gains.
  

Conclusion

These two excellent articles are good resources.  Any time one sees a simple historical analogy, it would be wise to check out Barry's list of questions. 

Using Gambling to Learn about Investing

At "A Dash" we have tried to draw a clear distinction between investing and gambling.  We believe that the analysis of gambling situations frequently provides more data, allowing a long-run analysis.  The techniques used are the same that investors should use in evaluating stocks and sectors.

The Danger

Those buying stocks, whether their time frame is short-term or long-term, frequently focus on the return rather than the risk.  This can take two distinct forms:

1. Believing in the apparent consistency of returns.  This has been costly for investors in mortgage securities, either directly or through hedge funds that leveraged these instruments.
2. Swinging for the fences.  The investor looks at the potential gain rather than the risk.

The Gambling Lesson

Seeing the risk/reward error is extremely difficult when one already has an investment position.  The  gambling comparison can help one take a completely different perspective -- one where there is no  psychic stake in the outcome.

Accrued Interest  provides several lessons on this theme in an excellent post today.  The points are difficult to summarize, so we recommend reading the entire article.

Tom Murcko at InvestorGuide.com also provides a thoughtful comparison  of investing and gambling,  including a good intellectual framework.

Our own comparison is also helpful.

Conclusion

Looking for understanding from different, but analogous situations, is a strong method for improving investment performance.

Many approaches are working well, but investors need to choose with a realistic assessment of risks.

ETF Update: Are you missing the rally?

How has your portfolio been doing?   If you are not happy with the answer, it might be time to ask why.

Best Use of ETF's

We know that many investors and fund managers have been caught in the negativity bubble.  They focus on a macro-economic debate, mostly between economists and non-economists.  Regular readers know that we have tried to expose this.

Meanwhile, the market is conveying a very different message, as noted in Dr. Brett Steenbarger's must-read article, "Why Aren't Stocks Forecasting Recession?"

Those following a disciplined investment method, adjusting for market cap size and style, have captured the move.  My friend and RealMoney colleague, Steve Birenberg of Northlake Capital Management, graciously provides occasional updates for his system.  On September 5th, he wrote on RealMoney (subscription required and worth it) as follows:

For the third consecutive month there were no changes to my Market Cap and Style models. The signals remain large cap and growth. Client portfolios own the S&P 500 Spyder (SPY) and the iShares Russell 1000 Growth (IWF) to take advantage of the current signals. The large cap signal from the Market Cap model remains one of the strongest readings in the monthly data I have going back to 1980. All ten factors covering a breadth of economic, interest rate, and stock market technical indicators are flashing a large cap signal. On their own, each factor has in the past shown predictive ability for anticipating relative performance of large caps vs. small caps as measured by the S&P 500 and Russell 2000. With the weight of the evidence from a broad array of previously accurate indicators lined up so solidly in favor of large caps, I feel very good about the prospects for large cap outperformance to continue for at least a few more months.

Our Own Method

Our own TCA-ETF model has captured another dimension, the decline of the dollar.  The effect is described in a good column from MarketWatch.  Since we use an iShares universe that includes foreign ETF's, we capture all of these effects through computer-based technical analysis.  This is the complete set of rankings, showing our actual holdings, entry dates, and returns through yesterday.   (you can click to enlarge)

This is a complete set of sector ratings.  The IEZ position was closed and IXC purchased because of the relative rankings.  The sectors marked with an asterisk are in what we call "The Penalty Box," stopped out for violating specific criteria.

The Sector Message

The most important conclusion from the rankings is that almost forty sectors qualify as a "buy" based upon our analysis.  The positive expectancy is broad-based.

The next message is that certain themes -- especially foreign ETF's, energy, and basic materials, show the greatest strength.

Why Not All Top Sectors

Our investment discipline attends to risk considerations and diversification, so we have limits on sector concentration.  Overweighting some groups is an element in beating the market, but risk control is important.

Stops and Exits

Part of risk control is the use of "stops."  This is a tricky topic, worthy of a separate analysis, so it will be part of a future weekly update.  All good things have an end, and exits are important.  The perceptive Adam Warner highlights the risk in one of our key holdings.

Fundamentals

Some investors focused on fundamentals have enjoyed similar gains.  Unlike our partnerships, our individual accounts include no foreign ETF's but there is considerable overlap in holdings.  Many US corporations have significant earnings from abroad and strong earnings prospects.

At "A Dash" we view fundamentals in terms of forward earnings prospects versus alternative investments.  The market is recognizing that bonds and real estate have weak prospects relative to stocks.  This is another way of saying "Fed Model," a valuation topic familiar to regular readers.

Implications for Investors

There are many traps for the investor.  Spending a lot of time reading pundits who start with the conclusion and then find the evidence is the single biggest trap.  Amazingly, some of these sites are the most popular and highest-rated on the Internet.  Go figure.

Another trap comes from the financial media.  The stories seem always to focus on the worries.  That seems to get reader attention.  Few provide good information on the multi-year growth of earnings -- far outstripping stock performance.

Meanwhile, the online brokerage commercials are a huge trap.  They lead the investor to think that his/her own market "feel" can beat the experts.  Some even encourage one to develop and backtest a trading system.  The main purpose of our TCA-ETF series is to describe the challenges in system development and testing, including dealing with the inevitable losing streaks.  Most people trying this at home will make all of the common mistakes and get terrible results, as described here.

A thoughtful reader can learn to do better.

Will Rogers and the Yield Curve

Regular readers of "A Dash" know that we encourage intellectual integrity and consistency.  When one is watching the markets all of the time, the "pundit polka" (as we called it in Wisconsin) is easy to spot.

A helpful and regular commenter, Josh Stern,  noted and found humorous my Will Rogers piece written for RealMoney a few days ago.  With this scant encouragement, I promised to share it with readers of "A Dash."

The Comment

Will Rogers is well remembered for saying "...I never met a man I didn't like."

I found myself reminded of this as I read all of the criticisms of the Fed and this week's rate cut.  A guy in one of the Hollywood Squares on CNBC this morning was complaining that the 10-year note has moved up 20 basis points, "taking back half of the Fed rate cut."

Reality check:  LIBOR (cited here on Columnist Conversation as a big credit market issue quite recently) has declined nicely, the TED spread has come in, the prime rate (important for business and also many home equity loans) is down 50 bps.  While the 10-year is up a bit, mortgage rates are not (as Gary D. Smith reported in his excellent trading diary on RealMoney Silver).  [Readers of "A Dash" know that Gary has been one of the hottest market observers for several years, and provides a lot of his thinking and data on his website, Between the Hedges].

The CNBC guy did not like 10-year rates over 5% (drag on stock valuations and profits).  He did not like them below 4.5% (shows panic, a flight to quality).  He did not like the yield curve when it was inverted (predicted recession) and he does not like it now, since it is sloped "for the wrong reasons."

This guy never saw a yield curve he liked.  Aha!  That is what made me think of Will Rogers.  He is the anti-Will.  If an analyst is going to cite an indicator, it should -- well -- indicate something!  Both ways.  Positive and negative.  I wish that the interviewers of such guests would hand over a piece of paper and invite the expert to draw a bullish yield curve.

More wisdom from Will:   "Heroing is one of the shortest-lived professions there is."

Update

I got a couple of emails saying that mortgage rates had gone up slightly, although my research showed that it depended on the market and the lender.  Mortgages trade with the ten-year, but those rates did not really decline on the "flight to quality" buying and they only bounced a little.  The main point is how a pundit who is determined to be bearish can torture evidence to get the desired result.

Mark Hulbert noted the same thing in his column today.  The research cited by many to push recession predictions into the 30-40% range would now imply about a 10% chance.  He notes that those citing this indicator in the past have fallen silent.  Quelle surprise!

Reader Challenge

Use the search function at your favorite investment blogs.  Enter "inverted yield curve" to determine the blogger's prior position.  Then watch for an update.  We invite suggestions for other search terms to try.