Schulenberg & Associates, Inc. (Stock Market Timing Newsletter)

Schulenberg and Associates, Inc. (since 1981): Originators of the Thermodynamic Approach to Stock Market Timing and the Stock Strategist™ Newsletter

Schulenberg and Associates, Inc. is a company that specializes in innovative software products and solutions, and with a special emphasis on the design of mathematical algorithms. Over the past quarter century we have concentrated our efforts on five major areas: (1) the generation of stock, ETF, and mutual fund timing signals, (2) research on innovative solutions to problems in nonlinear mathematical modeling and number factorization, (3) the development of large-scale database applications, (4) the creation of support tools for Space Shuttle flight software development, and (5) software products for Spanish language education, machine translation, and corpus linguistics.

Our experience with stock market timing and equity modeling began in 1987 when we added neural network capabilities to our EDES™ (Empirical Data Expert System) program. Development of our Stock Strategist ™ software began in 2000, and we started publishing our daily Newsletter and market timing reports in October 2004. On 9/27/06 we began utilizingTimerTrac™ to conduct independent verification of our stock market signals.

After graduating from the University of California at Berkeley (math/physics), Craig W. Schulenberg began his programming career at the MIT Instrumentation Laboratory in Cambridge, Massachusetts (now the Charles Stark Draper Laboratory). While a member of the Apollo team he was responsible for integrating the flight software load file for Apollo 11 (LUMINARY), and for the programming and testing of the Lunar Module (LM) onboard guidance computer software for the lunar ascent (P12), aborts during the lunar descent (P70,P71), and the final phases of the lunar landing itself (P66,P67). Some additional biographical information can be found in Gary B. Smith's archived Real Money™ articles: On the Comp, a Bounce Then a Leg Down? and The Dow Nears Its Jump Zone.

Schulenberg Stock Strategist™ (SSS) "Maxwell-Boltzmann" Stock Market Timing Models

The basis for the Stock Strategist™ is an entirely new approach to viewing the stock market, that is, from a thermodynamic standpoint. In thermodynamics, the Maxwell-Boltzmann distribution describes the relationship between the absolute temperature of a gas and the percentage of molecules that will have speeds within specified limits. This relationship works both ways: given a distribution of molecular speeds you can determine the temperature of a gas, and given the temperature of a gas you can determine the molecular speed distribution. We utilize an analogous concept in determining the effective temperature of the stock market. We call this value the MTI (Market Timing Indicator), although the acronym might also be considered to stand for "Market Temperature Indicator". Instead of gas molecules we consider an ensemble of over 8500 stocks and ETFs; instead of looking at the number of gas molecules within specified speed ranges we consider the distribution of "long" holdings within a spectrum of specially designed stock portfolios (with unusual buy and sell criteria). In a way, this is Technical Analysis ... but firmly rooted in the fundamental forces that underlie the stock market.

Our current QQQQ timing model was finalized at the end of January 2005, after incorporation of logic to take account of crude oil prices. Since 2/1/05 we have been tracking actual performance gains in trading QQQQ both long and short. Our signals are generated each evening, and trading profits are calculated on the assumption that all trades are made the next morning at the open price for QQQQ. In addition to QQQQ we generate daily buy and sell signals for over 1,500 stocks and ETFs, as well as 1,100 mutual funds.

Signal Verification (Tracking by TimerTrac™)

We utilize Timertrac™ to monitor our actual QQQQ signal performance. Timertrac™ is an independent market timing signal certification service that provides direct comparisons of the actual performance of hundreds of market timing signals. The tracking of our QQQQ signal began on 9/27/06. In addition, each week we submit a market analysis to TimerTrac for incoporation into their Broadcast emails. The expanded texts of our weekly TimerTrac Broadcasts are available (Broadcasts). If you would like to receive their bi-weekly Broadcast emails, then you should contact TimerTrac at the link shown above; it's free, and it summarizes the current thinking of a number of market timing organizations -- not just us.

The following graph shows that our QQQQ signal is perhaps even more useful when trading IWM (the Russell 2000 ETF). The actual trading performance for the past 12 months is shown in the following graph, and is compared against the Russell 2000 Index:

As of 9/308 we have added 5 more "Voted" Signals, so that in addition to QQQQ we now have customized high accuracy models for SPY, DIA, IWM, MDY, and SMH. For the actual performance of all 6 of our Voted Signals (from 9/4/08 to the present), please click on the following TimerTrac medallion:

Newsletter Subscriptions

A subscription to the Strategist Newsletter™ provides 13 daily reports that address the full range of investment approaches: a QQQQ day-trading signal, short-term (S/T) signals for 1,000 stocks and ETFs, intermediate-term (I/T) signals for 1,600 stocks and ETFs, daily buy/hold/sell signals for over 1,100 mutual funds, and 67 different stock and ETF Portfolios (short-term, intermediate-term, and aggressive). Also, four different Allocation (Hedging) Vectors are provided that will help you safely allocate capital between long positions, short positions, and cash. Newsletter subscriptions are for a 3-month period.

SWReg™ accepts all standard credit cards.

Our Major Market Timing Innovations
Grail System™ Stock Timing Models The MTI (Market Timing/Temperature Indicator) that is generated by the thermal model in our Preprocessor is used to develop customized short-term timing models for 1,000 stocks and ETFs. These Grail System™ models utilize the MTI value, multiple neural networks, as well as both traditional and proprietary technical indicators (based on price and volume), in order to generate daily buy/sell signals. These highly accurate signals are tuned to the intrinsic (natural) characteristics of each individual stock (average maximum drawdown and trading frequency). The intrinsic values (AMD-Average Maximum Drawdown, and trading frequency) are determined by performing an analysis of the entire price history for a given stock, using Monte-Carlo techniques to evaluate hundreds of thousands of possible trades. The objective is to maximize the annualized gain, and the only restriction imposed is that any trade must be held for at least 4 trading days. When this analysis is complete, the natural trading frequency and associated Average Maximum Drawdown are then available. This data is then fed into the optimization process for each of our custom models so that our model values (AMD and trading frequency) can be 'coaxed' to converge to these natural values. This process produces a stock timing model that reflects the natural rhythm of the stock or ETF, and since it is MTI-based, it quickly reacts to the overall temperature of the stock market. The back-tested performance of our most accurate short-term model, the one for QQQQ, can be seen in the voteqqqq Report.
Generalized Candlesticks (the RaDiSH Transform™) Although our short-term signals (Grail System™) are based on our Market Timing (Temperature) Indicator (MTI), and are thus thermally-based, they do not operate on a sufficiently reactive time scale to be able to predict the daily movement of a single equity like QQQQ (since the temperature of the stock market can't change very much in a single day). Instead, we turn to an elegant generalization of Japanese Candlesticks. By applying our proprietary transform (RaDiSH Transform™) we can convert the four daily prices (High, Low, Open, Close) plus volume, into a set of 5 dimensionless and time-invariant numbers. Then, by using this data to train a neural network we can predict the average price that a given stock 'may' exhibit on the next trading day (the sum of the High and Low prices divided by 2). Finally, by looking at the actual Open price of QQQQ, together with this estimated average price for the next day, we can calculate the probability that QQQQ will Close higher than its Open. This gives us a QQQQ day-trading signal that is probably about as accurate as is theoretically possible. A sample Prediction Table report can be seen here.
ETF Decomposition of Mutual Funds Our Mutual Fund Timing Indicator (MFTI) was developed using our Stock Market Timing Indicator (MTI) as a basis, and this works very well to identify those protracted periods when mutual funds (as an investment class) are in either a 'buy' or a 'sell' state. However, the task of developing buy/sell/hold signals for individual mutual funds requires a different approach. Simply looking at the recent price history of a fund shows its current performance, but offers little insight as to how the fund will perform over the next month or two. Our solution is to try to determine the current holdings of the mutual fund, and then to use our intermediate-term buy/sell/hold (and short-term buy/sell) signals to calculate a weighted signal for the entire fund. Our approach is to decompose each mutual fund into a weighted sum of 5 different ETFs (basis vectors) that are chosen from a large set of 175 ETFs. Monte-Carlo methods are then used to determine the 5 'best' ETFs, and their associated weightings, that reproduce the recent price history of the mutual fund most accurately. These decompositions are often uncannily accurate, and correlation coefficients (R**2) of 0.9900 or better are routinely achieved. While these decompositions can never exactly reflect the current holdings of a mutual fund, they nonetheless give us an analytical way of assigning a net Score (and a buy, sell, or hold recommendation) for over 1,100 funds on a daily basis. A sample mutual fund decomposition report can be seen here.
Differential Signals -- Comparing Two Indices By employing an interesting mathematical device we can utilize our Grail System™ techniques to generate models for new 'signals' that predict the relative performance of one index against another. We actually utilize ETFs for this purpose, and the objective is to predict whether QQQQ (the Nasdaq 100) will outperform (or underperform) the S&P 500 (SPY), the DOW (DIA), or the Russell 2000 (IWM) over the near-term. A '+/-' value for the $NQ-RU signal, for example, would mean that a simultaneous Long of QQQQ and a Short of IWM (i.e., a hedged situation) would likely be profitable; a '-/+' signal would suggest a profitable QQQQ Short while going Long on IWM. Other available indicators are $NQ-SP (QQQQ vs. SPY) and $NQ-DW (QQQQ vs. DIA). These indicators provide invaluable supporting evidence for our current QQQQ signal, and may be of considerable benefit to traders in stock futures. A recent Differential Signals report can be seen here.
Trading Links
For Predictive, Insightful, Global Intelligence: Stratfor.com
For up-to-the-minute market news and analysis: Briefing.com
For information on stocks, ETFs, and mutual funds: Yahoo.com
For information on stocks, ETFs, and mutual funds: MSN/Money
For details and ratings of specific mutual funds: Morningstar.com

Our Major Market Timing Innovations

Grail System™ Stock Timing Models

The MTI (Market Timing/Temperature Indicator) that is generated by the thermal model in our Preprocessor is used to develop customized short-term timing models for 1,000 stocks and ETFs. These Grail System™ models utilize the MTI value, multiple neural networks, as well as both traditional and proprietary technical indicators (based on price and volume), in order to generate daily buy/sell signals. These highly accurate signals are tuned to the intrinsic (natural) characteristics of each individual stock (average maximum drawdown and trading frequency).

The intrinsic values (AMD-Average Maximum Drawdown, and trading frequency) are determined by performing an analysis of the entire price history for a given stock, using Monte-Carlo techniques to evaluate hundreds of thousands of possible trades. The objective is to maximize the annualized gain, and the only restriction imposed is that any trade must be held for at least 4 trading days. When this analysis is complete, the natural trading frequency and associated Average Maximum Drawdown are then available. This data is then fed into the optimization process for each of our custom models so that our model values (AMD and trading frequency) can be 'coaxed' to converge to these natural values. This process produces a stock timing model that reflects the natural rhythm of the stock or ETF, and since it is MTI-based, it quickly reacts to the overall temperature of the stock market. The back-tested performance of our most accurate short-term model, the one for QQQQ, can be seen in the voteqqqq Report.

Generalized Candlesticks (the RaDiSH Transform™)

Although our short-term signals (Grail System™) are based on our Market Timing (Temperature) Indicator (MTI), and are thus thermally-based, they do not operate on a sufficiently reactive time scale to be able to predict the daily movement of a single equity like QQQQ (since the temperature of the stock market can't change very much in a single day). Instead, we turn to an elegant generalization of Japanese Candlesticks. By applying our proprietary transform (RaDiSH Transform™) we can convert the four daily prices (High, Low, Open, Close) plus volume, into a set of 5 dimensionless and time-invariant numbers. Then, by using this data to train a neural network we can predict the average price that a given stock 'may' exhibit on the next trading day (the sum of the High and Low prices divided by 2). Finally, by looking at the actual Open price of QQQQ, together with this estimated average price for the next day, we can calculate the probability that QQQQ will Close higher than its Open. This gives us a QQQQ day-trading signal that is probably about as accurate as is theoretically possible. A sample Prediction Table report can be seen here.

ETF Decomposition of Mutual Funds

Our Mutual Fund Timing Indicator (MFTI) was developed using our Stock Market Timing Indicator (MTI) as a basis, and this works very well to identify those protracted periods when mutual funds (as an investment class) are in either a 'buy' or a 'sell' state. However, the task of developing buy/sell/hold signals for individual mutual funds requires a different approach. Simply looking at the recent price history of a fund shows its current performance, but offers little insight as to how the fund will perform over the next month or two. Our solution is to try to determine the current holdings of the mutual fund, and then to use our intermediate-term buy/sell/hold (and short-term buy/sell) signals to calculate a weighted signal for the entire fund.

Our approach is to decompose each mutual fund into a weighted sum of 5 different ETFs (basis vectors) that are chosen from a large set of 175 ETFs. Monte-Carlo methods are then used to determine the 5 'best' ETFs, and their associated weightings, that reproduce the recent price history of the mutual fund most accurately. These decompositions are often uncannily accurate, and correlation coefficients (R**2) of 0.9900 or better are routinely achieved. While these decompositions can never exactly reflect the current holdings of a mutual fund, they nonetheless give us an analytical way of assigning a net Score (and a buy, sell, or hold recommendation) for over 1,100 funds on a daily basis. A sample mutual fund decomposition report can be seen here.

Differential Signals -- Comparing Two Indices

By employing an interesting mathematical device we can utilize our Grail System™ techniques to generate models for new 'signals' that predict the relative performance of one index against another. We actually utilize ETFs for this purpose, and the objective is to predict whether QQQQ (the Nasdaq 100) will outperform (or underperform) the S&P 500 (SPY), the DOW (DIA), or the Russell 2000 (IWM) over the near-term. A '+/-' value for the $NQ-RU signal, for example, would mean that a simultaneous Long of QQQQ and a Short of IWM (i.e., a hedged situation) would likely be profitable; a '-/+' signal would suggest a profitable QQQQ Short while going Long on IWM. Other available indicators are $NQ-SP (QQQQ vs. SPY) and $NQ-DW (QQQQ vs. DIA). These indicators provide invaluable supporting evidence for our current QQQQ signal, and may be of considerable benefit to traders in stock futures. A recent Differential Signals report can be seen here.

Schulenberg and Associates, Inc.: Thermodynamic Stock, ETF, and Mutual Fund Timing Signals and Portfolios

Stock Market Timing

Other ProductsFactorization Suite EDES/Model™

Schulenberg and Associates, Inc. (since 1981): Originators of the Thermodynamic Approach to Stock Market Timing and the Stock Strategist™ Newsletter

Schulenberg Stock Strategist™ (SSS) "Maxwell-Boltzmann" Stock Market Timing Models

Our Major Market Timing Innovations

Grail System™ Stock Timing Models

Generalized Candlesticks (the RaDiSH Transform™)

ETF Decomposition of Mutual Funds

Differential Signals -- Comparing Two Indices

Trading Links

For Predictive, Insightful, Global Intelligence: Stratfor.com

For up-to-the-minute market news and analysis: Briefing.com

For information on stocks, ETFs, and mutual funds: Yahoo.com

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Last Changed: 4/06/2009