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As I understand, the figures you are showing are histograms/sample PDFs of the prices of the prior day? Am I correct? Is volume somehow wrapped up in this?
If #1 is correct, then you are forecasting the next day's price based on the median of the prior day's prices and the standard deviation of the prior day's prices. So, days with much volatility (big standard deviations) will cause your forecast line to have a steeper slope. Correct?
How is this "chaos?" +1 for using sampled PDFs and not parameterized statistics, but I don't get how this incorporates some chaotic model. To me, this looks like some sort of support/resistance idea characterized by statistics (which would be pretty cool).
Can you help answer these questions from other members on NexusFi?
Please confirm that you are not a vendor and that you have nothing for sale, no products, no services and are not related or affiliated with any company who does have anything for sale, products or services, with regards to trading.
thank you for your interest. i will try to answer them
1) It is not based on sample PDFs and volume is not considered. It is made up frequency of traded price.
2) The prediction is not based on standard deviations, but the formation of equilibrium and its destruction.
3) You can use the most frequently traded price as a form of Support/Resistance but the concept is slightly more complex. It is chaos in the sense that we acknowledged that price movement is random but there is global determinism and local randomness in the movement and we are able to discern this global determinism to make our forecast.
So, the pyramid shaped objects are histograms of the previous day's prices frequency content? So, you're taking the FFT (or something similar)? Of tick data? Minute? Closing prices? Care to elaborate?
Okay. Similar language was used to describe chaos theory's predecessor - catastrophe theory. You're drawing lines from the extreme ends of the frequency distribution. Somehow the horizontal distance must be important, too. Correct?
Is this all based on some heuristic on the frequency distribution, or some underlying (quantitative) theory? Can you elaborate?
attached is the price forecast for S&P500 as can be seen, heavy resistance for S&P500 as shown in the picture, there are a few balance points above current price.
if price breaks below 115900, it will move to 115850.
the triangles are only drawn once we have identified our equilibrium, for a triangle to be drawn we need a point of origin (which could be the high, low or balance point), the forecast price (image pt) will be found once we connect a point of origin to another balance point.
A Balance point is simply the most frequently traded price for a interval. The high is the high price for a interval and the same applies to the low.
Raw tick data is used.
Finding equilibrium can be done after market hours or in real time.
Horizontal distance is of no importance, we need to find equilibrium by looking at the display of raw prices using non-fixed time intervals.
The theory is based on chaos and similar to sierpinski triangle.
Thanks for sharing your way of looking at the market.
If I understand you correctly the histogram you're using is basicly a TPO (Time Price Opportunity) profile that shows how much time price spent at a given price rather than how much volume traded there. Is that right?
How do you decide when the trend has changed? Would you perhaps be willing to post some charts about your method from between November 8 and November 15 or so, when there were large shifts in the prevailing trend?