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- 2001: Volume 10, No. 2
Forecasted Moving Averages:
Creating Leading Indicators Through Intermarket Analysis

By Louis B. Mendelsohn

Moving averages, one of the most popular and widely-used technical indicators, help traders identify the trend direction of financial markets. Moving averages form the basis of a myriad of single-market trend following trading strategies. These include the popular 50-day and 200-day simple moving average crossover approaches used to highlight the underlying trend direction of broad market indexes such as the Dow Jones Industrial Average and the Nasdaq Composite Index.

Moving averages, calculated according to precise mathematical formulae, are an objective (quantitative) way to ascertain the current trend direction of a market, and formulate an expectation about its future direction. For example, todayís five-day simple moving average of closes is calculated by adding up the values of the most recent five daysí closing prices and dividing by five. This same approach can be used to calculate simple moving averages of different lengths, such as a 10-day, 50-day, or 200-day moving average. Even intraday moving averages can be computed for various time intervals.

Moving averages filter out the random "noise" in past price data by "smoothing" or "averaging" out the fluctuations in price movement. However, because moving averages are calculated solely on past single-market price data up through and including the current periodís price, moving averages have a serious drawback which lessens their effectiveness as a trend forecasting tool. They are a "lagging" technical indicator.

This means that trades based upon the analysis of moving averages typically get into and out of the market late, compared to the point at which the marketís price actually makes a top or bottom and changes trend direction. Depending on the marketís price movement, and the type and size of moving average utilized, this lag effect can be substantial, causing the difference between trading success and failure in todayís highly volatile, global financial markets.

Figure 1 depicts a chart of daily prices of the March 2001 U.S. Dollar Index futures contract, with its actual 10-day simple moving average lagging behind the market at major turning points.

Figure 1:

Chart of daily prices of the U.S. Dollar Index with its actual 10-day simple moving average. Notice how the moving average lags behind the market.
Source: VantagePoint Intermarket Analysis Software

Moving Average Crossovers Lead to Whipsaws
This lag—the Achillesí heel of moving averages—has challenged technical analysis researchers for years in a futile effort to eliminate it, while still retaining the beneficial "smoothing" effects of moving averages. To this end, numerous types of moving averages have been devised, each with its own mathematical construction, effectiveness at discerning the underlying market trend and ability to minimize the lag effect.

Additionally, in order to improve their effectiveness, moving averages are often incorporated into more complex technical indicators, such as moving average crossover strategies. One such approach, for instance, involves the calculation of two simple moving averages of different lengths, such as a five-day and a 10-day average. When the short moving average value is greater than the long moving average value, the underlying trend is assumed to be up. When the short moving average value is less than the long moving average value, the trend is assumed to be down.

Figure 2 shows the New York Light Crude Oil March 2001 futures contract with its actual 5-day and 10-day simple moving averages superimposed on the daily price chart. Notice that both the short and long averages lag behind the turning points in the market.

Figure 2:

Chart of daily prices of the New York Light Crude Oil futures contract with its actual five-day and 10-day simple moving averages. Notice how the short average is more responsive than the long average, but still lags behind the market at major turning points.
Source: VantagePoint Intermarket Analysis Software

An inherent assumption behind moving averages is that a trend once underway tends to persist. Therefore, until the long moving average is penetrated by the short moving average, for instance, in the direction opposite from the prevailing trend, the trend is assumed to remain intact.

Traditional moving average crossover strategies are effective at identifying the current market direction in strongly trending markets. But, in non-trending, sideways markets, and even in trending markets when using very short moving averages which may be overly sensitive to abrupt price fluctuations, these approaches are subject to whipsaws. This results in erroneous trading signals at market tops and bottoms. So, while traders can often make money in trending markets using moving averages, it is the choppy markets, increasingly more common today, that cause substantial trading losses.

In a further effort to overcome this deficiency, different variations on crossover strategies have been created. One popular approach compares an actual price, such as the daily close, with a moving average value. Other commonly-used approaches attempt to minimize whipsaws and filter out faulty signals by using bands surrounding the moving averages, utilizing three or more moving averages, or combining moving averages with other single-market technical indicators for additional confirmation.

With todayís unprecedented intraday and interday market volatility, caused in no small measure by the globalization of the financial markets and resulting effects of related markets on one another, it is no longer sufficient to use single-market lagging indicators such as moving averages. Since they are constructed only on past single-market price data—the price for today, for yesterday, and so onómoving averages always lag behind turning points in the market. More importantly, moving averages, calculated in this manner, lag behind what is about to happen in the market.

Now, knowing that a market made a top or bottom several days ago is no longer an effective way to make trading decisions, if it ever was. Even a one day lag, in todayís fast-paced, globally interconnected markets, is too long to wait for this information.

It is imperative that traders adopt an intermarket perspective and incorporate intermarket data into their current trading strategies, in order to develop effective leading indicators that correspond to how todayís global financial markets really exist.

A New Way to Forecast Moving Averages
The purpose of technical analysis is to identify the underlying market trend and forecast (or at the very least extrapolate) its future course, for the purpose of making profitable trading decisions. Therefore, it seems logical that this goal could best be achieved through applying leading indicators which utilize both single-market and intermarket data, rather than by continuing to rely upon trend following indicators such as traditional moving averages that are computed solely on past single-market data.

Theoretically, a predicted moving average value for a future date, if it were 100 percent accurate, would have, by definition, no lag whatsoever. But this is not possible. So, something else must be done to bring this widely-used trend following indicator into the 21st century of trend forecasting.

One innovative solution to this dilemma that I have been perfecting since the late 1980s transforms moving averages into a leading indicator by using both single-market and intermarket price, volume and open interest futures data as inputs into the design of neural networks which are then trained to make short term forecasts of moving averages.

Neural networks are a mathematical technology from the field of artificial intelligence, which can be trained to find reoccurring patterns and relationships within both single-market and intermarket data, applicable to market forecasting. These forecasted moving averages are then incorporated into predictive moving average crossover strategies that identify market trend direction of individual financial markets with very high accuracy.

For instance, to forecast the short term trend direction of the Nasdaq-100 Index for the next several days, neural networks can be trained on past single-market data on the Nasdaq-100 Index itself, in addition to intermarket data from various related markets. My firmís software program, VantagePoint, analyzes nine related markets to forecast several moving averages of different lengths and of different forecast time horizons on the Nasdaq-100 Index. This includes a five-day average for two days in the future and a 10-day average for four days in the future. The related markets include the Dow Jones Industrial Average, Dow Jones Utility Average, 30-year Treasury bonds, S&P 500 Index, S&P 100, U.S. Dollar Index, New York Stock Exchange Composite Index, CRB Index and New York light crude oil. Intermarket predictive information and current charts on other markets tracked by VantagePoint can be found at www.ProfitTaker.com.

Figure 3 shows a crossover of a predicted 10-day simple moving average for four days in the future with todayís actual 10-day moving average for the Nasdaq-100 Index. Notice that the predicted moving average, because it is forecasted in advance, does not lag behind the market, while the actual 10-day average lags behind both the market and the predicted average.

Figure 3:

Chart of daily prices of the Nasdaq-100 Index with a 10-day actual and predicted moving average crossover. Notice the difference in lag between the actual and predicted moving averages.
Source: VantagePoint Intermarket Analysis Software

Each day as the neural networks are updated with the most recent single-market and intermarket data, new moving average forecasts are made and the difference in value between each predicted and actual moving average of the same length is determined.

In this simple example, when the predicted moving average crosses the actual moving average from above to below (the difference goes from positive to negative), the market trend is expected to turn down within the forecast time horizon.

When the difference reaches a maximum negative value and starts to narrow (indicating that the downward trend is beginning to lose strength), this is an early warning that the market is poised to make a bottom and turn up.

Rather than wait for the crossover itself to occur, trading decisions can be based on a narrowing in the difference. For instance, when the difference reaches a maximum negative value and starts to narrow, you can act on this information in a number of ways depending on your account size, risk propensity, trading style and objectives. Here are just three possible scenarios that can be pursued (assuming that you are in a short position):

  • If the difference reaches a maximum negative value and narrows by even a small amount, you can close out your short position and stand aside. Then you can wait for the difference to narrow further before going long.
  • If the difference reaches a maximum negative value and narrows by even a small amount, you can tighten your stop and stay in your short position until the next day.
  • If the difference reaches a maximum negative value and narrows by a minimum amount, you can close out your short position and go long. This strategy is the most aggressive of the three since it involves reversing positions at the earliest indication that the current market trend is expected to make a bottom and change direction.

With the Nasdaq currently in a major bear market, and with so much cash sitting on the sidelines in money market funds ready to be pumped back into equities at the right time, it is imperative to have intermarket-based leading indicators that can give you an early warning that the Nasdaq is making a bottom. This is a golden money-making opportunity waiting to happen. Yet, many traders involved in trading the QQQs, Nasdaq-100 futures, or individual tech stocks, having lost a lot of money in 2000 and early 2001 relying on single-market trend following lagging indicators, will make lame "coulda", "woulda", "shoulda" excuses to justify their "paralysis of analysis" and inability to pull the trigger when this opportunity is at hand. Thatís what separates the winners from the losers in this financial competition in which only the strong survive.

There Is No Financial Crystal Ball
By employing leading indicators, utilizing both single-market and intermarket data, such as forecasted moving averages, early warnings of imminent changes in trend direction become apparent days before they show up on traditional price charts or can be identified by single-market trend following indicators which lag the market.

Admittedly, it is impossible to create leading trend forecasting indicators that can forecast future market direction with 100 percent accuracy. This elusive Holy Grail is the financial market equivalent of a desert mirage. In reality, no more than 80 to 85 percent predictive accuracy can ever be achieved, given the randomness and unpredictable events that are inherent in todayís globally interdependent financial markets, as well as due to the daunting task of creating effective forecasting tools that can stay current with rapidly evolving, complex financial markets.

As the futures and equities markets become even more intertwined, futures contracts on individual stocks make their U.S. debut, and more traders incorporate intermarket analysis into their trading strategies, powerful leading indicators, such as the predictive moving average crossover strategies briefly discussed in this article, which expand upon the concepts of popular trend following indicators, are a must for serious traders. This will allow them to seize trading opportunities based on predictive information derived from the hidden relationships and complex patterns between related global markets.


Louis Mendelsohn is president and chief executive officer of Market Technologies Corporation, Wesley Chapel, Florida, a trading software development firm founded in 1979, that specializes in quantitative trend forecasting. His firmís software, VantagePoint, uses neural networks to perform intermarket analysis and predict market trends with nearly 80 percent accuracy for interest rates, currencies, stock indexes and energies. Mr. Mendelsohnís recent book, Trend Forecasting with Technical Analysis: Unleashing the Hidden Power of Intermarket Analysis to Beat the Market (MarketPlace Books) is available at Market Technologies Corporationís website, www.ProfitTaker.com. Mr. Mendelsohn can be reached by e-mail at Louis@ProfitTaker.com or by phone at 813-973-0496 or 800-732-5407.


CRB TRADER is published bi-monthly by Commodity Research Bureau, 209 West Jackson Boulevard, 2nd Floor, Chicago, IL 60606. Copyright © 1934 - 2002 CRB. All rights reserved. Reproduction in any manner, without consent is prohibited. CRB believes the information contained in articles appearing in CRB TRADER is reliable and every effort is made to assure accuracy. Publisher disclaims responsibility for facts and opinions contained herein.

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