Notes regarding correlation cofficient

written by Yuri Shramenko yurips@verizon.net

website: www.TechEdgeTrading.com

 

 

I'd like to comment on this:

"The correlation as so far is a necessary palliative. Actually this is a big-big problem for me how to estimate the effectiveness of the projection line"
I'd like to present how I deal with this issue, and my purpose is to present an alternative for evaluating forecasts. In no way am I asking for something to be "fixed". I also want to respond to your comment:
"I believe that it makes sense to create a back test system that will simulate the trader's behavior."
Here I'd like to show how I use Forecasts in trading - that is, prior to "turning them over" to a tech-based trading-system.
- This doesn't mean I'm saying this is the ideal way, or that I'm recommending it. This works for me.
- I doubt if the process I use can be automated  
- If your goal is to create one forecast from which you trade directly I'd recommend skipping this post
 
I don't use forecast correlations at all. The forecasts I use on a regular basis I developed two years ago by manually reviewing ("eyeballing") the forecast - I zoom in no more then two months on the X axis so I can clearly see the relationship of the forecast line to the out-of-sample prices. (Summer 2005 I added an ADX (trend strength) forecast to my arsenal, that won't be coverd here)
I am looking for two things:
- is the forecast calling the turning-points within a couple of days
- by relative comparison to other forecasted swings, is the forecast identifying when larger swings will occur
- I am not looking for anything else!
If it looks good, then I review the exact same forecast on different time periods of the same market (cross-validation testing). What that means is I use TMIN and TMAX to select different years to load, then rerun the forecast using the same length training interval, target, and criteria. Then of course I manually review again. Then I select another financial market.
While this is a slow process, and somewhat subjective, when you find a forecast that passes all your tests you can re-use it for years.
Hint: if you're using an RPO and you'd like to try this approach out, DO NOT use a '1' as the first parm of the RPO. Using '1' is best if your aim is to find a day-to-day high correlation.
 
The next two images below show both why I ignore correlation and how I manually evaluate. This first image had a low correlation - yet its picking the turning-points just fine. My guess is the low correlation reading is for two reasons, the first being the sideways price action in the last week of May and the second, and main reason being the lack of upwards amplitude during the correction in early June. Yet to my eye this is fine, to yours it may be unusable, and to correlation it was a pretty bad forecast.

 

 
The second reason I ignore correlations is that Inversions happen in all astro-sourced forecasts. Obviously an inversion will wreak havoc on a correlation reading. Its an out-of-scope topic that happens. While Inversions obviously aren't ideal, here's whats good about them for me:
- since I use a tech-based system to trade them, I rarely get filled. For example, the below forecast has an upswing starting around June 18. As there was no upswing and I use a "price-confirmation" entry technique (ie price has to be rising thru a SwingLine) I don't get filled, hence no loss
- At the close of trading on June 21 I know I'm most likely in an inversion. I have a choice now - I can remove the "Long Only" filter on my tech-based system and go short and/or I can wait for the next turning point in the last week of March
- its noteworhty that the forecast did accurately call the start and end of the swing; to some an inversion is a bad thing; to others it still gives the start and end times of swings, a good thing; it may also provide the relative amplitude of the anticipated swing, another good thing

 
Here's a forecast with a negative correlation, it would be dismissed immediately as unusable.

 
 
But if I zoom in on the first month it looks different. How much data past the LBC you use is relevant in the correlation calc.
 

 
In the same forecast, zooming in on June, the two circled areas show why the correlation reading may be poor. The forecast is just not tracking day-by-day. Also look at June 21. The High of the day correlated with an upswing, the Close and Low didn't. For correlation purposes, which is right? If my objective in using a forecast:
- has nothing to with tracking price day-by-day
- but rather with figuring out the approximate start and end days of swings and their relative amplitudes
Then I'm happy (possibly ecstatic) with this forecast.
 

 
The forecast I use most is usally off a few days in the exact start and end times of swings.
So I always run other models whose only purpose is to tell me about non-directional turning-points. Non-directional means I don't care if the market moves up or down before or after the trend-change date. What I care about is:
- if the market was moving up I expect it move down after the trend change date
- if the market was moving down I expect it move up after the trend change date
- beforehand I have no directional bias
Some people have a very hard time understanding "non-directional".
 
Below is an image of one of my turning-point models for financial markets. Its run in ULE  - it does not do any training, it just plots a vertical grey line when the event is due. The EfficiencyTest does a fine job of evalating turning-point events - llok for a "V" shape around culmination. If you have MT's Statistic Expert you can evaluate a few thousand events to see if they are useful in predicting trend-change times (in Step 3 check only "Mixed")
As you can see most each vertical line coincides with a trend-change in the market (I call the below model "Lunar Occultation Index"). What I do is wait for when a forecasted swing is predicted and then "fine-tune" the anticipated start of that swing with turning-point models like below (then i turn it over to the tech-based trading-system).
 

 
Below is another trend-change model for the EurUsd (shown below is the dollar index).
Note that the only thing it forecasts is the time of anticipated trend-changes. Some are up, others are down (no-directional turning-points). To some "non-directional" makes it unusable, to others its incredibly valuable information.

 
If what you're looking for is one forecast model that you can trade directly from, and you're attempting to find that model based on high correlation readings, it may take you a long time to find it! In the mean time, you may already have at your disposal  techniques that allow you trade profitably, but may not recognize these models because of the way you're evaluating them.
 
It may be worthwhile to:
- manually review forecasts to see if you're catching the start and end of swings; if you're missing short counter-moves the correlation of that model will be low, but you have to seriously consider asking yourself this question: "If I know the start and end days of large market swings within a couple of days - is there any way, any way at all, that I could put that information to use?".  
- create separate models whose only purpose is to provide the dates of anticipated trend-changes
- find a simple technical-analysis based swing-trading system that confirms your forecasted swing has occured, sets an initial stop-loss, and uses a trailing-stop to capure the bulk of the swing if it occurs
 
Yuri Shramenko
www.TechEdgeTrading.com