The modern trading desktop offers easy access to a wide variety of technical indicators. It is not uncommon for practitioners of technical analysis to have ready access to hundreds of indicators, along with the ability to apply them quickly and in unending combinations on price charts.
"Selected success" (below) shows an intraday price chart of the CME Group’s S&P 500 E-mini contract (ES) with three well-known indicators: Moving average convergence-divergence (MACD), money flow and the relative strength index (RSI). The TradeStation EasyLanguage program that created the signals can be found at futuresmag.com/PriceCode. It shows how straightforward it is to construct systems that in the past would have required extensive programming and technical knowledge.
Each indicator is different, but all can be used to measure overbought/oversold levels. When these levels are reached in combination, a long or short signal is generated. Some implementers will wait for a cross-over to occur — when overbought/oversold levels initiate a reversion to the mean. The approach shown here generates a signal when all three indicators simultaneously reach individual overbought/oversold levels.
Such a price chart of successful trade signals can lure the trader into a perception that the right combination of technical indicators has been found — one that will provide a generally successful trading strategy. But the simple visual inspection of price charts can give a false sense of success.
"Reality bites" (below), taken three days after the first chart, shows the same indicator set producing an unsuccessful trade signal. Both of these indicator charts illustrate a common problem with the use of technical indicators and highlight how indicators that work splendidly in one market context — for example, during a day of rotational price action — will fail miserably when the market enters a trend. The obvious next step for the trader is to attempt to distinguish between rotational and trending markets, often looking to additional indicators that can make the initial attempt more robust.
Because simple visual inspection can be misleading in determining the efficacy of a trade strategy, technical traders are encouraged to backtest. Again, modern trading platforms make it easy to develop strategy ideas and conduct backtests on historical data quickly and without specialized programming knowledge.
"Ups and downs" (below) shows an equity curve of a three-year backtest of the MACD, money flow and RSI indicator strategy. A strategy that makes use of the indicator combination for entry, and employing an initial four-point stop loss (moderate for the ES contract) and trailing stop position management is easy to write and execute on historical data. The backtest equity curve illustrates the importance of historical testing as well as some of the pitfalls of strategy backtesting in general.
For example, if a backtest period consisting of the last 200 trades had been used — the circled part of the equity curve — the trader might have been lured into believing he had found a highly successful strategy.
Strategy development addresses the mixed results shown by advocating the use of in- and out-of-sample data to minimize curve fitting and generate more accurate hypothetical results. Veteran strategy developers advocate lengthy periods of historical backtest, far exceeding a three-year test. The well-known systems technical strategist William Eckhardt describes backtest periods lasting decades before becoming convinced of any strategy (see "William Eckhardt: The man who launched a thousand systems," March 2011). The depicted equity curve illustrates the inherent difficulty of verifying new trade strategies.
Price level trading
Experienced traders know the importance of using key price levels as support and resistance against which to trade. Traders, regardless of time frame, look for relevant price levels as a guide. Price level trading, in addition to specific price patterns to guide trade entry decisions, often makes up the core of a well-developed technical trading strategy.
To that end, let’s exchange the often overly busy price chart of technical indicators with a simplified view of the market that consists of just a small number of key price levels. "Level headed" (below) shows an example where only three price levels are the focus: The previous day’s high and low, and the current day’s open. The price chart is a favorite among day-traders, as the previous day’s price extremes define levels that may be respected in the next day’s trading, offering levels against which to fade, or define levels of new price discovery, offering levels where breakouts may occur. The day session open serves as an important intraday price level, similar to the way interday swing traders concentrate on the day session closing price.
When just a few key price levels are the focus, the price chart is cleared of the noise from traditional technical indicators. With just a small number of price levels to focus on, the trader can begin to consider price action theories that may form the basis of a comprehensive trading approach.
Here’s one example where the open can serve as the basis for a simple trade strategy. In this model, if price moves below the open on a bearish day, then reversion to the open can make for a well-defined short entry. Similarly, if price moves above the open on a bullish day, then reversion to the open can make for a well-defined long entry.
To determine what constitutes a bearish or bullish day, we use the NYSE Breadth indicator, which measures the number of advancing issues minus the number of declining issues. If Breadth>N, then bullish; if Breadth
This simple model has a rational basis to it as well. Namely, on a bearish day, retracement to the open offers an opportunity for those who missed an initial move down to make a well-placed sale. Similarly, on a bullish day, retracement to the open offers an opportunity for those who missed the initial rally to get on a well-placed purchase. Although exceptionally simple, this kind of analysis may be more thoughtful than that which relies on a combination of technical indicators to blindly generate buy and sell orders, where many times the indicator calculations are not well understood by the user.
Price level backtest
The open price level strategy is simple to backtest. "Grinding higher" (below) shows a three-year equity curve using one CME ES contract and the short side of the open strategy just described. The same caveats as described earlier with the technical-indicator-based strategy backtest apply equally well here, and a much more in-depth performance study must be conducted to demonstrate that the open price level strategy is viable going forward.
That said, the initial results across the same, admittedly limited, time window are certainly more predictable than the indicator combo strategy. The equity curve has many of the attributes the technical trader aspires to with a mechanical system: Regular and continuous profits with limited drawdown. The TradeStation EasyLanguage code for the open price level strategy is posted here ( code1, code2), so further analysis can be conducted easily.
The comparison of a technical indicator combination strategy vs. a simple price level approach provides an interesting result, and may be something the trader will want to investigate in looking at new methods of trading.
Michael Gutmann was a software engineer and manager at Intel Corp. for 20 years. He trades his system daily and recently published the second edition of "The Very Latest E-Mini Trading: Using Market Anticipation to Trade Electronic Futures, 2nd Edition." He can be reached via www.anticipationtrading.com.