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Beginner here, so apologies for the rather naïve question, I try to find answers elsewhere but mostly I found opinions (often contradicting and rarely with an explanantion). Maybe I'm using the wrong terminology in my searches, or maybe it's such a basic concept that it's not discussed... Anyhow..

I started exploring the quant world recently and I would like to apply some automated trading strategies to long term investments (i.e. trades on a weekly basis rather than daily or intra-day), so I tend to download and visualize data using weekly aggregation (i.e. 1 candle/1 HLOC = 1 week)

Many technical indicators have been optimized for daily data and their parameters are the result of that optimization (e.g. 200d for trend using SMA, 20d/2SD for Bollinger bands, 12d/26d/9d for MACD, etc.)

SO the key questions I have are:

  • Should I be scaling the parameter to fit the data while preserving the original time reference? Using the examples above, 200d SMA -> 40w SMA, Bollinger bands 4w/2SD, etc
  • Should non-temporal parameter such as SD be adjusted too? According to Bollinger himself, changing the period should lead so adjustments of the SD

For consistent price containment: If the average is lengthened the number of standard deviations needs to be increased; from 2 at 20 periods, to 2.1 at 50 periods. Likewise, if the average is shortened the number of standard deviations should be reduced; from 2 at 20 periods, to 1.9 at 10 periods.

Although he also states

Bollinger Bands can be used on bars of any length, 5 minutes, one hour, daily, weekly, etc. The key is that the bars must contain enough activity to give a robust picture of the price-formation mechanism at work.

Source

So I assume I can keep SD at 2

  • What about the MACD? The Moving Averages period are not multiples of 5, 12d/26d -> 2.4w/5.2w, do I round them? What about the "signal"? That is derived from the MACD line, should that be scaled too?

Any guidance would be greatly appreciated

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Understandably, there is no factual (academical) evidence that SMA's, MACDs and Bollinger bands are optimized following your above described user-defined specifications (I haven't found anything yet). While eg. SMA200 might work well in the US equity market, it can be a different story elsewhere. However, when dealing with a long-term investment horizon, it makes sense to use an SMA with a 200 day lookback window, since it needs to be robust against short-term volatility and only be sensitive to large price shocks that alters the price process to new lows/highs. The same can probably be said about MACD and Bollinger bands.

When that is said, there exists no perfect solution to your answer. However, I believe that you can effectively rescale your technical indicators, since the error of rescaling will not impact your long-term investment horizon (of course, with "long-term" I believe that you're holding your asset for a minimum of 1 week). As an example let's look at Bank of America (ticker: BAC). Fitting a SMA with 200 days on daily adjusted close prices and a SMA with 40 weeks on weekly prices gives you the corresponding graph: BAC SMA200 vs SMA40

There isn't much of a difference, however, the difference might be more apparent for volatile stocks. Again, we can determine the difference of the MACD indicators by comparing the daily estimated version against its weekly counterpart: BAC MACD daily vs weekly

Here, I've allowed to be a bit less concise and thus the signal line has a lookback window of 9 days for the daily and 2 weeks (ie. 2 data-points) for the weekly MACD indicator. Again, 12 days becomes 2 weeks and 26 becomes 5 weeks. There might be a bit of a visual difference between the MACD indicators, and you're the only one who can determine whether it will affect your trading strategy. I encourage you to try different parameters and compare with what you seem fit (eg. MACD(12,26,9) on daily data).

For Bollinger bands, the scaling in SD does not affect the intuition behind the bands, as long as it is "adequately" chosen. As written in your source:

The default parameters of 20 periods for the moving average and standard deviation calculations, and two standard deviations for the width of the bands are just that, defaults. The actual parameters needed for any given market/task may be different.

which also holds for weekly pricing data. Try to compare your fitted weekly Bollinger bands with that of the daily Bollinger bands and determine whether your weekly Bollinger bands are justified.

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Welcome, hello.

Since your time frame is 1 week, rather than the typical 1 day that these parameters are "tuned" for; you would need to change your time, yes. If you want to "capture" 200 days of space, then that is the equivalent of looking at 5 candles on your weekly chart.

However, something to note is the SMA (or any indicator related) of the 200 day versus the 40 week will be somewhat different since the 200d SMA is an average over 200 individual days (and their respective closes prices), rather than the average over 40 sets of 5 days (and their respective close prices at the end of the week).

If you have the means, you can utilize the value of the 200d SMA at the close of the week (this would avoid the need for scaling altogether).

As for the standard deviation, leaving it as 2 is fine since you are capturing the same period of time. If you were capturing more data, then the SD would need to be adjusted accordingly.

Finally, MACD can either be adjusted and rounded or you can simply use the approach that would avoid scaling (that I mentioned before).

Hope this helped.

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