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ORTI Double Channel BB V2 (Static Timeframe Multi-Period MA)

The "ORTI Double Channel BB V2 (Static Timeframe Multi-Period MA)" is private scrypt, based in a previous study, but with some better functions .

This is a redesigned and recalculated set of the common plotted lines with the typical two "Standard Deviations" (positively and negatively) away from the original calculation of a "Simple Moving Average" of the security's price.

But now, with the option to convert the "Simple Moving Average" to adapt into 9 different kinds of "Moving Averages", to have a much more robust indicator which in turn would serve both as "Bollinger Bands" and by any of the most used "Moving Averages", a hybrid basically.

Although, this time I added four channels to result in two kind of standard deviations to have more clear signals about volatility with the additional channel of positive and negative measurement.

The following options to convert the "Simple Moving Average" ( SMA ) to:
Exponential Moving Average ( EMA )
Weighted Moving Average ( WMA )
Arnaud Legoux Moving Average ( ALMA )
Hull Moving Average ( HMA )
Volume-weighted Moving Average ( VWMA )
• Least Square Moving Average ( LSMA )
Smoothed Moving Average ( SMMA )
Double Exponential Moving Average ( DEMA )

The cherry on the top, for this private version: is when you want to get a predetermined count in "natural temporalities" as minutes, hours or days, in any graph you could get a static average, and this count will be automatically respected. For example, a "Moving Average" could be configurated to know a trend per day, week or month... or whatever comes to mind, and at every single chart that you move through (5m, 15m, 1h, 4h, etc), you will see the same average to make your own "trend analysis" into a micro/macro market view.

As in traditional "Bollinger Bands", the "Standard Deviations" are still a measure of volatility , when markets become more volatile, bands widen, during the less volatile periods, the bands contract.

A common fact in trading is that, prices vary most of the time and there is a lot of truth in this assertion, since the markets consolidate mainly as bullish and bearish . Market trends are sometimes very rare, so trading them may not be as easy as you might think. If we look at prices in this way, we can define the trend as a deviation from the norm (rank).

Usually, most Traders use “Moving Averages” to identify commercial areas and analyze markets. A “Moving Average” helps the Trader isolate the trend a lot and can also indicate when a trend may be receding.

The importance of using any of the “Moving Averages” in the “Bollinger Bands”, becomes a reality and reveals the average price of a marketable instrument in a given period of time. However, there are different ways to calculate the averages, and that is why there are different types of “Moving Averages”. They are called "in motion" because, as the price moves, new data is added to the calculation, thus changing the average.

The base of the “Bollinger Bands” measures and represents the deviation or volatility of the price and this is the reason why they can be very useful to identify a trend. Even the use of two sets of “Bollinger Bands”, one generated with the parameter "one Standard Deviation" and the other with the typical configuration of "two Standard Deviations", can help us to see the price in a different way.

Another great advantage of “Bollinger Bands” is that, they adjust dynamically as volatility increases and decreases. As a result, the “Bollinger Bands” automatically expand and contract in synchronization with the price action, creating an envelope of precise trends.

Note: The previous calculation example is not the default, the parameters can be adjusted according to the criteria of the merchant.

As everyone knows, and as you can find on the internet, the "Moving Averages" are one of the most commonly used technical indicators in Stock, Futures , Forex and Crypto trading. Market analysts and traders, use "Moving Averages" to help identify trends in price fluctuations, smoothing out the noise and short-lived spikes (from news and earnings announcements, for example) for individual securities or indexes.

They are calculated by adding recent closing prices and then dividing that by the number of time periods in the calculation average. A simple, or arithmetic, a "Moving Average" that is calculated by adding the closing price of the security for several time periods and then dividing this total by that same number of periods. Short-term averages respond quickly to changes in the price of the underlying, while long-term averages are slow to react.

There are different types of "Moving Averages", calculated in different ways and over different time periods, which reveal different information for traders. The type of "Moving Average" and measurement period used determine the strategies a trader implements. So, many traders watch for short-term averages to cross above longer-term averages to signal the beginning of an uptrend. Short-term averages can act as levels of support when the price experiences a pullback.

As is usual, traders and market analysts commonly use several periods in creating "Moving Averages" to plot on their charts. For identifying significant, long-term support and resistance levels and overall trends, but they only consider the 50-day, 100-day and 200-day moving averages as the most common. Based on historical statistics, these longer-term moving averages are considered more reliable trend indicators and less susceptible to temporary fluctuations in price.

There is such popular trading patterns that use "Simple Moving Averages" include the “death cross” and a “golden cross”. A “death cross” occurs when the short period "Moving Average" crosses below the long period "Moving Average" and this is considered a bearish signal that further losses are in store; the “golden cross” occurs when a short-term "Moving Average" breaks above a long-term moving average, this can signal further gains are in store, that is interpreted as bearish .

The 5-, 10-, 20-, and 50-day moving averages are often used to spot near-term trend changes. Changes in direction by any of these shorter-term "Moving Averages" are watched as possible early clues to longer-term trend changes. Crossovers of the 50-day moving average by either the 10-day or 20-day "Moving Averages" are regarded as significant. The 10-day "Moving Average", plotted on an hourly chart, is frequently used to guide traders in intraday trading.

For more technical information: https://www.investopedia.com/

But why we have to use in our TECHNICAL ANALYSISthe same Moving Averages (10, 20, 30, 50, 100 and 200) for all time frame OHLC charts (1m, 5m, 15m, 1h, 4h, 1d, 1w and 1m)? That does not make any sense.

This is when you must go back to (statistic) basics: reliability and validity are a very important aspects of selecting a survey instrument. Reliability refers to the extent that the instrument yields the same results over multiple trials. Validity refers to the extent that the instrument measures what it was designed to measure.

Content validity measures the extent to which the items that comprise the scale accurately represent or measure the information that is being assessed. Are the real traders answering this question, that are asked representative of the possible data that they are trying to read? Well, I think maybe not.

Such as correlations, to verify the relevance of the “timeframe” questions, we could start at… Operation hours, the first data that has you should find may be is correlated with questions from: Does your trend indicator has a straight relationship of time under your time-analisys examination to determine if validity is present? If the scores are highly correlated, it is called convergent validity, then if convergent validity exists and validity is supported.

Criterion-related validity has to do with how well works the counting from the instrument, as a known outcome they are expected in a real, natural and measurable lapse time. Such as correlations are used to determine if criterion-related validity your counting data, would must be at: minutes, days, weeks, months, etc.

That is when we start with the rhythm, as in music. If your trading day in operation at Forex is made up of 24-hours, during 5-days of the week, there you have your first clue. Now, what did you want and have to measure? Well, first of all you need a daily, weekly and monthly count to begin with all your indicators.

For some reason, there are a lot of questions about time and calendars which all are answered by reference to astrology, because the original purpose of astrology was to create a reliable method of measuring the passage of time, the clock by which we live our lives: 12 Hours. It is very interesting!

Even though there are really 24 hours in a day, but therefore you would think we should have 12-time units in our day, not 24, each of which is twice as long as our current hour. But the only reason we would think like this is because we have forgotten about the way ancient astrology divides the time lapses into smaller units.

And now, the next step is when you should refresh your elementary school classes, that mathematics that I'm pretty sure you so hated: relation of prime numbers, compound numbers, divisible numbers and multiples.

You may think about the relationship that exists between the time period and the operative session, as well as the chart that you are consulting; so then, you must find the ideal configuration of those numbers that are only divisible between themselves and 1, or the numbers that besides being divisible by themselves and the unit and are also divisible by other numbers.

For example: for an hourly chart, if a day is divided into 24-hours in base of the number 12, is because it has a larger number of integer factors: 12/6=2, 12/4=3, 12/3=4, 12/2=6. Son then, all of your other indicators should find this relation.

This is when you must start questioning yourself, if you are really working with an adequate configuration of Moving Averages and Oscillators?

Another example:
Relative Strength Index (14)
Stochastic %K (14, 3, 3)
Commodity Channel Index (20)
Average Directional Index (14)
• Momentum (10)
MACD Level (12, 26, 9)
Stochastic RSI Fast (3, 3, 14, 14)
• Williams Percent Range (14)
Ultimate Oscillator (7, 14, 28)

// --------------------------------------------------------------------------------
// ORTI Double Channel BB V2 (Static Timeframe Multi-Period MA)
// --------------------------------------------------------------------------------
// Author: Eduardo Ortí
// Email: ortiemm@protonmail.com
// --------------------------------------------------------------------------------
Dec 23
Notas de prensa: “Short title” modified.
Jan 02
Notas de prensa: Measurement upgraded for Minutes, Hours and Days.
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