Friday, January 15, 2021
Copyright © 2021 Fred Duckworth
Numerical Price Prediction is an approach to trading foreign currency pairs that I came up with based on five biblical principles:
- The first being to test everything and hold fast to only those things which prove to be valid and reliable.
- The second was a belief that, as in life, when you have a system operating at peak performance, more often than not, it's at least in part due to the interactions between its various components evidencing strong, healthy relationships.
- The third is the fact that the best of plans are typically established in the presence of a multitude of counselors.
- The fourth is the necessity of being able to rightly interpret the signs of the times.
- And the fifth is that, once again, as with life itself, positive outcomes are usually the result of having made good choices.
The first principle led me to reject the use of almost all common indicators, such as MACD, RSI, CCI, stochastic oscillators and the like; along with any approaches involving harmonic patterns, Elliot waves, pivot points, Fibonacci ratios and whatnot.
Instead, I attempted to rightly interpret the signs of the times by devising a methodology similar to that used by meteorologist to predict the weather—one based as much as possible on statistical analysis and mathematical probability.
The idea was to gather and evaluate precise, up-to-date, quantitative data and use it to calculate the odds of price reaching designated values within a given time period by patterning the system's elements after the equations, wave functions, and computer models used in weather forecasting.
But, instead of monitoring wind velocity and direction, cloud formations, humidity, temperature, and barometric pressure; I evaluate the synergy (or "relationships") between such factors as typical price ranges, reoccurring chart patterns, horizontal support and resistance, trend lines and market structure (which is to say, "a multitude of counselors that proved to be valid and reliable" over several weeks and months) all in multiple time frames—with the result being a graphical depiction (computer model) of current conditions that I could then use to help me make precise, well-timed trades (or in other words, "good choices based on rightly interpreting the signs of the times").
The system incorporates the idea of cycle theory, which holds that cyclical forces, both long and short, drive price movements, and can be used to anticipate turning points. It's also compatible with Edgar Peters' fractal market hypothesis, which views financial markets as fractal in the sense that they follow cyclical and replicable patterns—ones consisting of fragmented shapes that break down into parts which then replicate the shape of the whole.
I used these cycles to generate what some call "baselines" by conducting a thorough analysis to first uncover the cyclical waves formed in the wake of price action, followed by the defining of their general frequencies and magnitudes; and then finally plotting centered moving averages that came as close as possible to approximating the zero amplitude of the corresponding waves/cycles.
So, the notion that there are no "best" moving averages to use when trading is not one to which I subscribe. Again, at the heart of my system is the use of carefully selected baselines which I calculated in the manner explained above. (By baselines, I mean painstakingly selected moving averages able to rightly discern whether price is rising, falling, or maintaining its altitude within a particular time frame.)
However, it is not enough, in my opinion, to stop at merely determining which are the best moving averages to use when trading charts of a given time frame. To trade with the clarity and precision I desired required me to carry out one final step in which I assigned a specific temporal value to each individual baseline and its corresponding or associated price-range envelope—to answer the question: What moving average best conveys in which direction and by how much price moves every five minutes? Or every thirty minutes? Or every four hours? Or even every day?
Determining the specific moving average that best represented price movement for each of the major time intervals along with their corresponding price range envelopes seemed to be the final step I needed to carry out in order to complete the development of my trading system to my full satisfaction.
And yet, even after this "final" step, their emerged still another aspect to interpreting price action that proved deserving of my consideration which I had not envisioned at all—the concept of "temporal" support and resistance.
In other words, not only do I believe there is a certain amount of
distance beyond which exchange rates will typically resist separating themselves from the central tendencies of key price distributions, it seems to me I have also observed that there is generally a limit to the amount of
time exchange rates will advance in one particular direction without deviation. I refer to these limitations as
temporal support and resistance, and they have proven to be a welcome enhancement to my system.
As of today, when putting this system into practice, I switch back and forth between 240-, 60-, 15-, 5-, and 1-minute charts to get different perspectives, even though all of these time frames are basically configured with the same relative/corresponding measures.
I rely on the three-day baseline to convey the overall day-to-day market bias. However, this is not an actionable measure in a practical since in that it evidences far too much lag. So then, the highest time frame that is of any actual use in helping me decide in which direction to trade from a longer-term perspective is the
16-hour baseline (two-thirds of a day). I look to this measure in conjunction with 8-hour price flow (i.e.,
the slope of the 8-hour price range envelope). However, for a more immediate/finely tuned measure of price flow, I turn to the
four-hour price range envelope.
As for where I watch for reversals, generally speaking, I anticipate them taking place at intraday statistical support/resistance, which is to say, at the
four-hour price range support or resistance levels, and/or at the
six-hour temporal support or resistance levels. (In this sense, the system incorporates aspects of mean reversion or regression toward the mean.) If these levels don’t hold however, I go to my backup, which is the
eight-hour price range envelope.
The highest time frame of interest to me with respect to executing reversal-related trades is the
four-hour baseline. To me, calculating reversal-related entry levels using the 16-hour and/or three-day measures would be like trying to perform surgery with a sledgehammer. From my perspective, attempting to operate in this manner with any kind of precision at all is virtually impossible.
However, for more immediate reversals, I’m interested in the one-hour trend. Yet, this measure evidences too much fluctuation to be trusted and must therefore be confirmed by the two-hour baseline. So then, perhaps what I am really looking for are reversals in the
two-hour trend, using the
one-hour baseline to help me recognize when such reversals have taken place (based on the slopes of the two measures and their positional relationships to one another).
At the "microscopic" level, I track the slopes of the
20- and
40-minute baselines, and I also monitor the
20-,
40- and
120-minute temporal (statistical)
support/resistance levels. These measures are good for pinpointing pullback entry levels in the intraday trend and for detecting early indications of reversals in two-hour and four-hour sentiment/bias/price flow.