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@spiderbyte87: Your drawings look a bit strange to me, but maybe I simply misunderstood them. When looking at both of your graphs, it looks like short term volatility is always higher than long term volatility. Maybe you have just added the fast ATR to the slow ATR and not superposed it.
I agree that risk is tied to short term volatility. Therefore it is generally a good idea to enter a position when volatility is low. However, in order to get decent returns, then you would look at expected (implied) volatility. To have a better than 1:1 reward-to-risk ratio the volatility should expand.
A traditional way of looking at acceptable entry conditions is the Bollinger Squeeze. It compares the width of a Bollinger Band to the width of a Keltner Channel. Let us assume a lookback period of 20 bars, then
-> the average true range tells us something about the intrabar volatility, that is the size of an intra bar move
-> the standard deviation tells us something about how far the average data point is away from the mean of all data points
In case that the 20 bars are representing a consolidation (price going nowhere), the standard deviation will be small. In case that the 20 bars are representing a trending move, the standard deviation will be high. The standard deviation does in fact represent the higher timeframe volatility over 20 bars, while the ATR represents the 1-bar volatility. Of course, if 1-bar volatility is high, this typically has an impact on the higher timeframe volatility as well, but this is not all. The trendiness also increases the standard deviation.
Attached is a chart showing the case. I have identified two groups of 4 bars. For both groups the average true range ATR(4) - which is only related to the bar size - is 0.242 for the last bar of the group. The squeeze is a quick and dirty way of comparing N-bar volatility (SD) to intrabar volatility. The problem is that the formula for the standard deviation does not take into account all data points, but only the closes. Ideally a standard deviation should be calculated from the opens, highs, lows and closes, and not just the closes. To release the pain a bit, I have calculated the standard deviation from the bar medians and not the closes.
Fast ATR definitely drops below slow ATR, but those are times when I would not consider taking a trade. The idea is that as price becomes more rangebound, risk is reduced. I know this is an obvious point, but I like to have it spelled out in numbers so the emotional guesswork is taken out of the picture.
Fat Tails, can you provide a visual walkthrough of a trade using what you're talking about so I can get a better understanding?
After testing this I've found that this produces a biased ratio relative to volatility and volume. To reverse the bias, you can do the following:
Instead of using the difference between the fast and slow ATR to produce risk, use the difference between the median of the fast and slow ATR. This way the risk reward ratio follows volatility in such a way it favors higher volatility over lower volatility.
It isn't a bad thing to have a bias though, just something to be aware of. Mean reverting systems prefer low volatility, and trend following systems prefer high volatility. Knowing this, we can deduce that we need to find a way objectively identify low and high volatility. I'll use the position of the fast ATR relative to the slow ATR. Above = high volatility (trend), below = low volatility (reversion). The problem is that price isn't normalized so the bias will always be skewed by volume. The obvious work-around for this is to base the ATR calculation on only the RTH session (assuming that's the session you trade).
You could also just pick a bias and only trade a certain way (trend vs. reversion), but I want to milk as much out of the market as possible, so I'll continue to look for a way to do both.
I'm in the middle of a cross-country move so I'll post up some charts when I get where I'm going.
You cannot use the difference between the fast and the slow ATR to produce risk. In that case if your fast ATR and your slow ATR are equal, this would result in a zero risk. The risk depends on the absolute amount of the expected (implied) volatility, not any difference.
What you look for, is a situation where the risk is small compared to a potential return. This would be the case when price has been sitting in a base (consolidation) for a while. You can detect is by comparing intra-bar volatility (short term volatility as measured via the ATR) with directional volatility (long term volatility as measured via the standard deviation over a period).
When the standard deviation is small compared to the average true, this indicates a situation when "The Squeeze" is on. Visually this can be shown with Bollinger Bands and a Keltner Channel. When the Bollinger Bands (based on the standard deviation) are inside the Keltner Channel (based on the average true range), this indicates a situation, where the directional (longer term) volatility is low compared to the intra-bar volatiity.
Prices have been moving back and forth for a while which resulted in a base. The chart attached below shows four such consolidations which can be identified by the Bollinger Bands sitting inside the Keltner Channel or by the Squeeze indicator below, which directly compares standard deviation and average true range.
Now there are two types of consolidations.
(1) high volatility base: intra-bar volatility is high, directional volatility is comparatively low
(2) low volatility base: intra-bar volatility is low, directional volatility is even lower
To trade a breakout of one of those consolidations, you would need to set your stop outside the base. Therefore your risk is proportional to intra-bar volatility. If you trade the high volatility base, you have a higher risk, compared to trading the low volatility base. The returns achieved by trading both setups are similar. Therefore the low volatility base is the better choice for a trade setup.
-> risk is not tied to the difference between short term and long term volatility
-> risk is directly tied to short term volatility
-> you want to enter a trade when short term volatility is low
-> you want to enter a trade when price has been sitting in a base and volatility is expected to rise
The term "The Bollinger Band Squeeze", which has been coined as a trade setup is misleading, because for that squeeze you will both find low volatility and high volatility setups. Only the low volatility setups should be taken.
Well I think I've figured it out. I'm sure FatTails will tell me otherwise, but I think I have a system for optimizing R:R based on volatility and max preferred trade risk.
After playing with some ideas, I've come up with a novel approach. This is going to take some explaining, but I'm sure you nerds out there will like it..
The idea is to find the happy medium between too tight a stop or too loose a stop based on volatility. This, of course, must take into account the your risk of ruin or 'preferred max risk' per trade. Attached is a spreadsheet that I developed which takes into account your max "preferred" stop and the short and long term volatility of the market. Using standard deviations, I've found that the highest probability can be obtained. If you follow how it works, you'll see that the close the ATR is to the "normal" average for your high timeframe, the better the R:R becomes. It is designed this way in order to look favorably on trades that are more probable of being successful and to tighten the stop for those that are not (volatility wise).
I won't get into the math behind it until my next post.
If you combine this stop strategy with good entry analysis, you potentially have a very well-rounded system IMHO.
BTW FatTails mentioned directional volatility. I am interested in that as well, but I need help determining how to calculate it without adding too much to the complexity.
My next post will have an example trade to demonstrate how to use the spreadsheet. (not gonna cherry pick, just going to find a normal trade for me and see if it works.. the point isn't to be right, just for the R:R to be right)
Thanks ill have to open it in excel on my laptop and reupload.. I still have to put together a guide to using it anyway, shouldn't have jumped the gun i was just so excited to share my work.. Holy crap it's not easy to type on an ipad! Ok back to my rig tomorrow to write up a guide
In order for this to work you need to be working on two timeframes. These are dependent on your account size and the way you trade. We're only using one chart so use your lower timeframe with a lookback that fits your higher timeframe.
You'll only have one chart for everything, so use this equation to figure out the indicator period for your higher timeframe period: (#days_lookback*60*24) / #lower_TF_minute_value
Just three indicators:
1. BBandofATR(Median of **your instrument and value**, 1, **your higher timeframe period**)
Leave the lower and middle band transparent. Use a color of your choice for the upper band.
2. BBandofATR(Median of **your instrument and value**, 2, 14)
Leave the lower band transparent. Color the middle band the same as #1's band. Optionally you can color the upper band something different and use it as a filter (only trade when it's below the middle line on the chart).
And you're done! Now all you have to do is enter the values in the three similarly colored lines into the spreadsheet (top to bottom) and you will get stop, target, and contract values back. You can change the number of contracts and the max preferred risk per trade if you want. Right now only 5 instruments (click the upper left to change) can be used with the spreadsheet, but more can be easily added.
The arrows didn't line up right when I saved it for some reason, but you get the point.
I should mention that this will ONLY get as close as possible to your preferred risk and will go over if the volatility profile deems that to be the best option. This is done by calculating the dollar amount risk for all possible position sizes (in my case 1-5 contracts) and looking for the one with the smallest deviation from the trader's preferred risk.
How to determine preferred risk is a topic for another thread, but Big Mike mentioned risk of ruin and I tend to agree however without a proper dataset I would advise .05-.5% for day traders and 1-3% for swing traders dependent on account size.
Writing this on the ipad so gonna be quick.. Will have an update to this in the next couple of days. I made some major changes so the guide will have to be rewritten. Im also moving the spreadsheet over to the elite section because i dont want this in the public domain since it's gone from theoretical to practical (actually using it live now).
