MarketModel Advisors, LLC celebrates 5 years of providing proprietary research related to stock market indices, primarily the "fair value" of the SP500.  Clients of MarketModel include Hedge Funds, Independent Market Professionals, and Wealth Managers. MarketModel Advisors also applies this research as a Commodity Pool Operator (CPO), managing a hedge fund since Dec 2015.

MarketModel is founded by Mike Valletutti, CTA. Following the 1987 market crash he began developing methods for determining market valuation and trading strategies while studying statistics & probabilities, time series analysis, probability modeling, and statistical experiments at Georgia Tech.

“My passion was the stock market, having witnessed the ‘87 crash as a Sophomore at GT,” Michael comments, “Merging together the circumstances and opportunities following the crash and my early passion for the market, I came up with some economic and technical rules that performed well when applied to historical data. And then I worked for over 15 years testing and refining the model.”

"What's the market worth?" Probably the most asked question, with many different opinions.

Traditional Technical Analysis methods use price to determine price.  Fundamental models rely on aggregate company financials and relative yield.  MarketModel is unique in that it looks at other macroeconomic inputs to help determine a value for the stock market. Long-only wealth managers are able to make finer portfolio adjustments to their equity allocations during periods of market under or over valuations.

Michael is registered as an active CTA with the National Futures Association (NFA) and is soliciting funds from accredited investors.

Model Background

The goal of active management is deliver better risk-adjusted returns than passive investing.

Model Theory

The fundamental theory is that macroeconomic conditions lead stock market prices. If true, producing accurate, forward-looking economic forecasts (i.e. ATL Fed GDPNow) could provide clues to the future direction of the major stock indices (i.e. SP500).  Often times, stock market prices are controlled by sentiment - greed and fear - which can lead to disconnects between price's "fair value". The model wants to buy the market when price is a discount to fair value, and short the market when price is a premium to fair value.

The model isn't a crystal ball. Trade signals are based on Probabilities and Statistical methods, producing different trades with differing probability of success. Overall, model is right 2 out of 3 trades.

More recently, research has been focused on limiting maximum exposure to the stock market.  Today's markets are faster than ever, and high velocity of price movements is normal.  Typical equity allocation strategies are too heavily invested in equities (i.e. 80% long).  Worse yet, most hedge fund strategies use leverage in an attempt to outperform the index.  These strategies will suffer with the increased velocity of price.

The model is not a HFT or intraday scalping algorithm, only changing the position about 2-3x a month, on average. The model is a pure directional bet on whether the SP500 will rise or fall, which during bull or bear markets, is able to profit from not only the major trend but also sell into the minor counter-trends. The result is a system designed to beat the SP index by profiting when the market loses during pullbacks.

Application of Theory - Strategy Choice

Once you have a system that produces an estimated fair value for the stock market, the next step is to decide which strategy fits the desired results. The model produces not only a prediction of direction of SP500, but also a probability strength of signal.

One could create a hedged strategy where Shorting SP is utilized, which makes profits possible during a market decline. This hedge fund approach is best combined with another long-only portfolio.

Another option is to supplement the long-only strategy, using the model to change equity weighting allocations, making better timed buys and sells. Scaling between 15% long to 150% long at MAX BULL. Selling means taking profits, not shorting the market.

The graph shows 1999-2012 backtesting results of these two different applications of the model theory (Long/Short or Long-Only) as compared to passive index investing in the SP500.


Underweight SPX Trading Fund, LP
MAX Drawdown -6.7%
completes 2 years Nov 2017
Hedges Long-only strategies

Fund Results (2 years)

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First 12 month period, fund was above backtested average return of 8% net of fees, as notated in the green box on the graph. In December 2015, Macro Fair Value had started to roll over, and the fund was positioned correctly short ES futures. With only one failed hedge trade in March, the fund had strong monthly profits trading the long side, including up to Election night.

Fund then faded the Trump Election rally to suffer its first multi-month drawdown, as noted in red box on the graph. SP500 Price following the Election had spiked too far ahead of Macro Fair Value, and it took a quarter before Macro caught up to price. After this lag, Macro Fair Value led Price again for most of the rest of 2017.

Since drawdown, Macro Fair Value has mostly led SP500 price, supporting the bull trend. As noted in the blue box, the fund has started to get back to historical win rate with 2 wins for every 1 loss. Lack of volatility in 2017, however, didn't allow the fund's scaling strategy to add to position sizes, resulting in less than average monthly returns. None of the hedging short trades worked in 2017.


A significant strategic advantage of the fund is identifying which SPX prices have the best odds of a defined short-term low during a market decline. The fund favors high cash balances, only scaling to full size when price falls to this MAX BULL support level.

During market volatility, the fund can add short-term profits, sometimes significant. These MAX BULL signals occur during deep discounts between Macro Fair Value price and the actual SP500 price, and often coincide with extremely negative sentiment indicators. Normally these trades only last a few days - a panic selloff that reverses as price bounces back to an improving Macro Fair Value.

These trades allow the fund to use its cash reserves for high risk opportunities, but limiting them to extreme, pre-defined price points. This scaling strategy allows the fund to have less than 50% exposure ("underweight SPX") to the market, on average.

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Michael J. Valletutti Biography


Georgia Institute of Technology
BIE: Bachelors of Engineering - Industrial
MSIE: Masters of Science - Probability & Statistics
Develops initial macro model


Commodity Trading Advisor (CTA) – NFA Registered
Collects nightly market data for input into model
Tracks and refines model with virtual money


Chairman and CEO, Applied Global Technologies (AGT)
Co-founder, Video Managed Services and Technology
$25M Small Business, 100+ employees
Private Equity Event


Founder, MarketModel Advisors, LLC
Twitter @marketmodel
Shared model trades via email subscription service


Commodity Pool Operator (CPO) - NFA Firm Registered
Underweight SPX Trading Fund, LP

Information about Modeling

What is a model?

Backward Testing

A simple example of a market model is comparing today's price to the historical average of price over, for example, the 50 past days. The rule would be to BUY when today's price is above the past average, and SELL if below. This rule could be easily backtested and other rules could be applied to produce win/loss ratio and profit/loss delta. Other rules could be applied and tested, but not so many that the rules only work for the test data. Known as curve-fitting, too many of today’s rules are created to fit just one set of past data, which will not work for new data. In simple terms, the rules were so stringent that they could only work once.

Forward Testing

The next method for a model is to forward test, which measures the results against future data. Since 2006, Michael has been applying the model in real-time to the daily trade of the SP500. In fact, between 2006-2010, he posted the daily model signals on the web and also paper-traded the positions. The results were consistent with the historical testing, and produced very good returns in both bull and bear markets. In fact, the model's best year was during the 2008 financial crisis.

Testing with Real Money

By 2012, Michael’s confidence in his own MarketModel led him to establish a futures account and commit to trading the model signals, following the direction and probability signals of the model. Michael's trading diary moved to social media via Twitter @marketmodel, where the nightly model signals were posted, along with trading results.

Here are the returns for the model's subscription years:

The model uses SP500 futures instead of the SPX cash because of the use of leverage provided by futures. Use of leverage is typically associated with high risk, however in our case, we are simply choosing to not to tie up $1M is cash buying and selling shares of the SPX. Leverage allows for the scaling from underweight SP500 to up to 1x leveraged (100% long or short).

The model's use of leverage allows for scaling into very large account balances. For example, a $1B account could invest alongside the model within the SP futures market easily within the avg volume and open interest of today's market.  The investment decisions are almost entirely systematic, based on the model's signals.

Get Info

MarketModel Advisors LLC, CPO
NFA ID 0491458

Long/Short Hedge Fund: Underweight SPX Trading Fund, LP

Michael J. Valletutti, CTA
NFA ID 0267975

Follow on LinkedIn where I publish bigger Macro ideas few times a year

Wealth Managers

Clients expect firms have proprietary info that gives their wealth managers an edge over passive indexing.
MarketModel will help fund your research budget, at no upfront cost.

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