My initial inspiration came from three scriptural passages…
- Prove all things; hold fast that which is good.
- “When evening comes, you say, ‘It will be fair weather, for the sky is red,’ and in the morning, ‘Today it will be stormy, for the sky is red and overcast.’ You know how to interpret the appearance of the sky, but you cannot interpret the signs of the times.
- He said to the crowd: “When you see a cloud rising in the west, immediately you say, ‘It’s going to rain,’ and it does. And when the south wind blows, you say, ‘It’s going to be hot,’ and it is. Hypocrites! You know how to interpret the appearance of the earth and the sky. How is it that you don’t know how to interpret this present time?
So, what I'm trying to do is use a methodology based as much as possible on statistical analysis and mathematical probability.
The idea is to make market forecasts using an approach similar to that employed by meteorologist when predicting the weather...that is to say, by evaluating precise, up-to-date quantitative information (depicted visually) and then calculating the odds of rates reaching designated values within a given time period.
But instead of monitoring air mass (i.e., humidity, wind speed and direction, barometric pressure, temperature, etc.) I’m evaluating the synergy between such factors as fractals, typical price ranges, trend lines, and support/resistance levels in multiple timeframes. This is meant to simulate the equations, wave functions, and computer models used in weather forecasting.
It all results in a graphical depiction of price patterns (i.e., waves, cycles, and envelopes) that I can then use to help me make precise, well-timed trades...