This is a continuation of my series on forecasting techniques. The idea behind the Simple Mean method is to somehow extend historical mean to the future. In this case a forecast equals to last value plus average change.
The oscillator version of the stationary extrapolated levels indicator. The methodology behind the extrapolated levels where to minimize the risk of making a decision based only on a forecast, therefore the indicator plotted levels in order to determine possible reversal points, signals where generated when the detrended series crossed over/under...
Beta Peek/Valey based forecast
The idea behind this indicator is to extrapolate a stationary time series and find the peeks of the extrapolated result. The highest and lowest of the extrapolated data represent really precise support and resistance if the data and its extrapolation are barelly equal with an error lower than the average.
For completeness here is a naive method with seasonality. The idea behind naive method with seasonality is to take last value from same season and treat it as a forecast. Its counterpart, naive method without seasonality, involves taking last mean value, i.e forecast = sma(x, p) .
Forecast 7 SMA's 6 periods
This script is an upgrade of the existing Triple MA Forecast from Yatrader2
To allow the user to display 7 different SMAs and look 6 candles ahead
Best to use on high timeframe, if on low timeframe change the forecast maximum to lower
This was made to...
update: added weekly and monthly pivots, the offset is a average approximation so there may be inconsistency on the date forecasted to be end of week/month.
(using diferent sessions or limited time intervals is not possible).
This is my original indicator that was inspired by "Mayer Multiple" and "Chande Forecast Oscillator" (CFO).
I decided to search truth of trend power with SMA and LinReg and found it in a somewhere of the middle. Also, I added a limit area, where you need to keep a more attention, because it can show a potential reversal.
You can change parametrs with a your own...
This is a scaled version of a Forecast Oscillator, which may be used as a standalone indicator or as a filter. Scaling allows to reduce data to a standard interval, say, 0..1 or -1..1. Oftentimes, it also makes data more contrastive.
Holt's Forecasting method
Holt (1957) extended simple exponential smoothing to allow the forecasting of data with a trend. This method involves a forecast equation and two smoothing equations (one for the level and one for the trend):
Forecast equation: ŷ = l + h * b
Level equation: l = alpha * y + (1 - alpha) * (l + b)
Trend equation: b = beta * (l - l)...