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StockChart’s SCTR Really Knows how to Rank Technical

SCTR – Technical Analysis

The SCTR no longer gets the performance pictured here, even when backtested on the dates shown.  This article is retained as a warning for why we no longer allow comparisons between split-adjusted Closing prices and constants, or ranking of split adjusted closing prices.  The stocks with higher split adjusted closes in the past turned out to have lower SCTR scores.  It’s certainly not obvious, but the evil is in the part where we subtract close from open, and where we compare close – 1.  Replacing close with rawclose everywhere gets our checker to stop complaining, but kills the performance.  This isn’t to say that some variation of the SCTR might not work.  Just not the one pictured here.

Equities Lab has historically focused our screening efforts on identifying companies with strong fundamentals that are undervalued in the market, and investing in that value. However, as time goes on we want to push both our own investment philosophies and our system capabilities. After looking around for a bit I stumbled up the SCTR, the StockCharts Technical Rank.

Originally the brain child of Mr. John Murphy, an author and contributor on StockCharts, this score is based on six different indicators weighted according to term.

Alright, let’s talk about the actual screen.


This entire screen is based on one thing – the SCTR formula. Here we are simply looking for companies that are ranked in the top 90% percent of the market based on that formula that also have a market cap of greater than $1 billion.

Here is an in depth look at the PPO Histogram. Click on the photo below to learn exactly how to calculate it.

  • Long Term (60%)
    • The first variable, long term, is exactly what it sounds like. It is looking for technical indicators that span over a longer period of time.
    • Containing two sub variables
      • Percent difference between close and 200 day moving average
      • Change of close over the past 6 months
  • Medium Term (30%)
    • The second of the variables, medium term, looks for technical indicators in a period of time less than 6 months.
    • Containing two sub variables
      • Percent different between close and the 50 day moving average
      • Change of close over the past month
  • Short Term (10%)
    • The final variable looks for technical indicators that appear in time span of a month or less
    • Containing two sub variables
      • The slope of the PPO histogram over a three day period
      • 14 day RSI

I know the editor of the SCTR looks complicated, but it’s actually incredibly simple. I went into this screen thinking that is was going to take a few hours to properly put the indicator together, but in reality, I was able to knock it out in less than 30 minutes.

Back to the Screen

In its raw form this screen returns a large number of potential companies – even though we are isolating the top performers in our editor.


There are over 200 matches for this screen. There’s no way I’m going to go through and analyze each of these companies, and I don’t have enough capital to comfortably invest in each one of these.

That’s where max holdings come into play. You can add a max number of positions you’d like to hold in the trading rules tab. Once you add a max, an order_by tab will be created automatically. This tab will rank the companies based on whatever you decide and the screen will only return up to the number of companies that you stated earlier.


We are going to order these results by their income statement score added to num times large charge multiplied by negative 1.

  • Income Statement Score
    • A formula created by the founders of Equities Lab to attribute a score based on values that are found within the income statement.
  • Num Times Large Change * –1
    • Num Times Large Charge counts the number of times a company’s share price has done a short term 10% movement in either direction over a 6 month period. Since we are looking for lower volatility companies we are going to multiply that number by -1 in order to give companies that didn’t have big movements a higher ranking.


This is a much more reasonable number of companies for me to analyze. There are also a few companies that I recognize, which gives me hope for how this screen will actually perform over the past 20 years.

Time to run the backtest


When trading on a quarterly rebalance since 1995 you would have returned over 22% annually – totaling to over 11,000% in that time frame.


The benchmarked S&P 500 has been crushing it since the crash in 2008. 2015 was pretty flat, but overall, the SPY would have been a good investment at the end of the crash. I say this because it has become moderately difficult to find a screen that consistently beats the market over the past few years. This screen not only beats the market these past few years, but has beaten the market every year since 1999. That’s what I call consistency.



We also want to make sure this screen has a winrate that is higher than 50%. They don’t all have to be homeruns, but we’d like the majority to be positive. We have set the great return and bad returns values to .01 and -.01 respectively to illustrate a clear picture of how well this screen does. Finally, checking the report we generate about the backtest we have a sharpe ratio of double the S&P 500.

In Review

StockCharts has created a wonderful score that is honestly the first incredibly successful technical indicator that can be traded with longer term investing in mind. After testing this formula and screen extensively, I believe that this screen deserves to be located on our “Featured Screens” list within the Equities Lab system, and that is where this screen now lives.

Tyler McCain
Tyler McCain
A student of finance at Georgia State University, Tyler has had a passion for the world of finance for as long as he can remember. Joining the Equities Lab team in 2015 he attempts to juggle the perfect mix of school, work, and giving back to the community. When he isn't working at Equities Lab he can often be found helping teach programs at the Rosen Family Foundation - a non-profit that teaches financial literacy to middle and high school students.

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