Percent Relative Strength

This is a very similar idea to one we have already published. The concept of having a start date from which the relative strength can be computed. Which facilitates the ability to run scans that match what you see on the chart. You can get details here: https://www.hahn-tech.com/thinkorswim-scan-relative-strength/

So we have a request for a chart study and a custom watchlist column. The code is very much the same for each. The only thing I will add is to change the background color based on values above or below zero.

Here is the code for the chart study:

declare lower;
input correlationTicker = "SPX";
input startDate = 20180928;
def beginTracking = DaysFromDate(startDate) == 0;
def correlationClose = close(symbol = correlationTicker);
def correlationPrctChange = 100 * (correlationClose / correlationClose[1] - 1);
def plottedPrctChange = 100 * (close / close[1] - 1);
def correlationDiff = plottedPrctChange - correlationPrctChange;
rec data = CompoundValue(1, if beginTracking then correlationDiff else if DaysFromDate(startDate) > 0 then data[1] + correlationDiff else 0, 0);
plot signal = data;
AddVerticalLine(beginTracking, "Start", Color.YELLOW, 2);

IMPORTANT NOTE ABOUT PUTTING THIS INTO A WATCHLIST

The values do not compute correctly. Some tickers are close but others are way off. I spent way too much time digging into the details. Screenshot below includes some comments to show just one of the many glitches. I am afraid that Watchlists on Thinkorswim are severely broken. Someone else is going to have to report it because I just don’t have time.

I’ll post the code anyway just in case at some point in the future they fix whatever problem they have. (an ambitious viewer might just take both of these code sections and submit them to TDA support asking them to fix their problem….)

Here is the code for the watchlist:

declare lower;
input correlationTicker = "SPX";
input startDate = 20180928;
def beginTracking = DaysFromDate(startDate) == 0;
def correlationClose = close(symbol = correlationTicker);
def correlationPrctChange = 100 * (correlationClose / correlationClose[1] - 1);
def plottedPrctChange = 100 * (close / close[1] - 1);
def correlationDiff = plottedPrctChange - correlationPrctChange;
rec data = CompoundValue(1, if beginTracking then correlationDiff else if DaysFromDate(startDate) > 0 then data[1] + correlationDiff else 0, 0);
plot signal = data;
signal.AssignValueColor(if signal <> 0 then Color.BLACK else color.CURRENT);
AssignBackgroundColor(if signal > 0 then Color.GREEN else Color.RED);