Well, that's the fun part of PCA. I just throw 'em all in and let PCA sort 'em out (by extracting the most important info).
To allow visualization, let's limit ourselves for now to three dimensions (axes = 233 day, 144 day, and 89 day standard deviation). We can first graph all our data points, with the colors of the points representing the date (using a rainbow gradient, where blue is old and red is most recent)
Now our three axes, representing each date's 233, 144, and 89 day standard deviation, create a 3D space that's mostly empty. Intuitively, we can reduce the above graph to 2 dimensions without losing much info (think of a "plane of best fit" going across the above graph diagonally):
With PCA, it's up to you to interpret what each new axis represents (in this case, some aspect of volatility extracted from the 3 standard deviation measures we began with). If we imagine pulling every point in the above graph down onto the horizontal axis, we get the most important relative measure of volatility for each date. If we pull every point to the left, onto the vertical axis, we get the second most important relative measure of volatility for each date. Importantly, the second most important measure of volatility is uncorrelated to the first:
Uncorrelated (by definition), but as we see below when we order the PCs by date, not independent!
PC1 appears to predict what's going to happen to PC2 six months in advance. This general pattern doesn't change if I increase dimensionality from 3 (used here for visualization) to many more by including lots of other Fibonacci standard deviations, or even throwing in other measures of volatility, like the average magnitude of day-over-day %changes (and not the standard deviation thereof).
I'm not sure what PC2 is measuring, but if we consider PC1 a "fundamental" measure of volatility, once it goes negative, it appears to be good for the gold price (and signal an end to a correction) whenever PC2 follows it into negative territory.
As an aside, also note that PC1 is at an all-time low. Has a bubble ever ended with such low volatility?