Apologies for the length on this ahead of time.
I was doing my third dive through the Wiki this weekend and started tearing apart piece by piece the discussions on using Relative Strength and accompanying ATR with it. I understand there are several out there for ToS, TradingView, and TC2000, or you can just flat out join OneOption and have it right at your fingertips. However, there was mention in the Wiki that these (except 1OP) are still not perfect as they require some tweaking to get correct. I also wanted to present methods that may help traders who might not use any of these charting platforms as well. I want to present a method that might fix some of these issues.
For those who are confused on what I am talking about, check out this Wiki Post and discussion thread:
https://www.reddit.com/RealDayTrading/comments/rp5rmx/a_new_measure_of_relative_strength/ The Cole’s Notes version is that the % change of a stock vs. $SPY is not enough usually to truly measure RS or RW. One must consider the average movement of $SPY over X number of periods (aka the ATR for simplicity --- I know the ATR is not exactly this but it is close), compare $SPY’s raw % change to that number to get something
HSeldon2020 coined as the “Power Index”. Again, layman’s terms are that it measures the force of the move vs. the average movement of $SPY. This Power Index is what we use to create an expectation of the stock’s movement during a normal 1hr trading window. If $SPY’s Power Index rating is +2.0 with an ATR of $0.50, $SPY moved $1.00…for easy numbers, let’s call this 0.5% raw change. Therefore, we would expect AAPL, which may have an ATR of $0.25 to have moved $0.50 in the same timespan to mirror $SPY, also equalling a 0.5% raw change. However, if AAPL moves $1.00 in this same time, it means AAPL has an expected move of +2.0 ($0.50) on the Power Index, but it has moved +4.0 ($1.00), then we have a clear signal of institutional interest. The post signs off with a recommendation for a rolling S that penalizes candle bursts and comments that it might not be possible. I don’t use any of the above platforms, so I apologize if someone has done this before, but here is my version that may be better or worse than others that requires two indicators working together. Please let me know what you think. This is on TrendSpider, fwiw.
Let’s use a picture-perfect example to illustrate, an $AMZN short on Friday November 18th around noon. I have highlighted this day on the chart with a white line. You will notice that $AMZN is below all major simple moving averages (5=blue, 21=pink, 50=yellow, 100=purple, and 200=red). It also has a raw 5-day weakness to $SPY (5-day Rate of Change indicator) of -6.73% (white is stock) while $SPY is -0.57% (orange is $SPY), meaning on a raw percent drop, AMZN is 11X weaker than $SPY. But we know from above this can be misleading.
https://i.postimg.cc/tC3NDWDf/AMZNDaily.png Since we are day traders, we are usually only focused on immediate price action of the last several days. If we zoom into the hourly chart at around the time of our entry, we can see a 16-period raw ROC (16 1hr candles in a true 4am-8pm trading day) of AMZN is -2.88 and $SPY is +0.51. Again, this can be misleading, but it does give an accurate measurement of the % change of the underlying vs. the market.
https://i.postimg.cc/6qwyQ2R2/AMZNHourly.png Now that we have identified that on a Raw % basis, AMZN is moving down at a faster rate then $SPY, we can look to our “execution chart” where we take our trade based on the price action and confirmation on the 5min chart. Everyone is familiar with the ATR here, however, not many are familiar with Normalized ATR. Normalized ATR turns the ATR into a percentage that can then be used to directly compare across tickers. It also comes with a moving average so you can see what the smoothed movement is to avoid any large candles skewing the data one way. When we apply a 12-period NATR (teal line on indicator) with a 12-period SMA (orange line on indicator) we can use this SMA-smoothed line as a true representation of the average volatility/expected movement of the stock over the past trading hour (12 5min candles in an hour). Let’s pretend we take this descending wedge breakout at the 11:45am candle close. This gives at the time of entry an expected move on $AMZN of 0.362% per hour, but we are seeing 0.67% movement currently.
This is where the “Power Index” (aka Normalized ATR) really helps us. We know the ROC of $SPY is -0.22, but that doesn’t mean much when we compare it to $AMZN of -0.67 when we don’t really know the expected move. The “Power Index” of $SPY shows that we can expect a move of 0.165% within the past 1 hour but have only seen -0.22% change, showing some volatility, with a Power Index of 1.33. $AMZN, however, at this time has moved over 1.8X its expected range for this given period. This confirms its relative weakness using both a raw% movement and an expected “Power Index” rating.
https://i.postimg.cc/CLRVqMNz/AMZN5min.png I can hear a lot of you now saying, “so what
MADEUPDINOSAURFACTS, what is the practical application to this?” Well, the practical application comes when you apply the Normalized ATR first to $SPY and the sector ETF ($XLY in this case) to make sure the stock is actually weak and not just being dragged down by its own sector. In this example $XLY has a Normalized ATR value of .249 and a ROC of -0.48 on 12 period 5min chart, giving it a Power Index of +1.92. Comparing that to $AMZN, which has a value of +1.85, with $SPY at +1.33 we can then say that $AMZN is roughly equal to its sector baseline and the trade will likely work when $SPY goes down, but it will only go down as much as $$XLY.
Practically thinking, I can find a way to scan for this at least using the ROC indicator and NATR by scanning for stocks that have an NATR > than $SPY and their sector ETF, and then a ROC greater than the NATR. This first filters out those choppy trades that move sideways because they are trading within their expected range, second, gives a way to filter out sectors that are moving less than the market in either direction, and third, gives a way to filter in trades that are both more powerful than the market and sector they are in --- highlighting clear institutional movement within the stock. To round it all out then, $AMZN probably was not a great trade using this criterion since the sector ETF was weaker than $AMZN and was likely dragging it down with it but not because of it. You can see on the chart; the breakout was short lived and required some quick profit taking before it started chugging back towards entry.
Conversely, if we take a quick look at one more trade, $LW, from yesterday, that considers RS vs. $$SPY and RS vs. the current sector. We can see clear 5-day and 1-day RS, with a 5-day at 7.04 and $SPY at -0.15, while the 1hr 16-period ROC at the time of entry 3.11 vs. 0.02 on $SPY. Drilling down to the 5min chart we can see a descending wedge (flag/pennant or whatever I guess) forming with a breakout. However, the breakout was not confirmed around 12:30pm when $LW became stronger than its NATR and the market. At 12:25 close $LW had a positive ROC of 0.25 and an NATR of 0.202, giving it a power rating of 1.23. $SPY at that time was trading within its own range, with a ROC of -0.02 and an NATR of 0.132, giving it a power rating of 0.15. $XLP, the ETF for $LW, was also trading within its range with a ROC of -0.02 and an NATR of 0.121, giving it a power rating of 0.165. Therefore, $LW once the confirmation occurred, was 8.2X stronger than $$SPY and 7.45X stronger than its sector of $XLP. For total trade honesty, after the entry signal and total move higher, $XLP increased 0.358%, $$SPY moved 0.492%, and $LW moved 1.59% at their peaks by the end of the day, clearly illustrating $LW’s strength to the market. See below for entry candle on $LW across the 3 tickers.
LW daily:
https://i.postimg.cc/fR0tBNwb/LWDaily.png LW Hourly:
https://i.postimg.cc/MTtvvZY9/LWHourly.png LW 5min:
https://i.postimg.cc/wxf1zvMv/LW5min.png SPY 5min:
https://i.postimg.cc/fLHRM2wF/SPY5min.png XLY 5min:
https://i.postimg.cc/66mpSmb4/XLY5min.png Please let me know what you think and If this is as close to the “Power Index” as we can get or if you all have found something better? I am going to keep using this to see how it works in real time.
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