Moving Average Momentum SignalsBest for trade execution in lower timeframe (1m,5m,15m) with momentum confirmation in higher timeframes (2h,4h,1d)
This indicator relies on three key conditions to determine buy and sell signals: the price's deviation from a short-term moving average, the change in the moving average over time (past 10 candles), and the price's deviation from a historical price (40 candles). The strategy aims to target moments where the asset's price is likely to experience a reversal or momentum shift.
Conditions
Price deviation from short-term Moving Average (MA): Current candle close minus the 10-period MA (price action past 10 candles)
Change in Moving Average over time: Current 10-period MA minus the 10-period MA from 10 candles ago (price action past 20 candles)
Price deviation from historical price: Current close minus the close from 40 candles ago (price action past 40 candles)
Signal Generation Logic
Buy Signal: Triggered when all three conditions are positive. Confirmed if the previous signal was a sell or if there were no previous signals
Sell Signal: Triggered when all three conditions are negative. Confirmed if the previous signal was a buy or if there were no previous signals
Usage and Strategy
After back testing, I observed the higher timeframes were a good indication of momentum/sentiment that you can take note of while trading intraday on the lower time frames (time intervals stated above). Background highlights are also displayed for easier visualization of bullish/bearish skew in terms of the volume of signals generated.
Komut dosyalarını "美元未来10天走势预测" için ara
Statistics • Chi Square • P-value • SignificanceThe Statistics • Chi Square • P-value • Significance publication aims to provide a tool for combining different conditions and checking whether the outcome is significant using the Chi-Square Test and P-value.
🔶 USAGE
The basic principle is to compare two or more groups and check the results of a query test, such as asking men and women whether they want to see a romantic or non-romantic movie.
–––––––––––––––––––––––––––––––––––––––––––––
| | ROMANTIC | NON-ROMANTIC | ⬅︎ MOVIE |
–––––––––––––––––––––––––––––––––––––––––––––
| MEN | 2 | 8 | 10 |
–––––––––––––––––––––––––––––––––––––––––––––
| WOMEN | 7 | 3 | 10 |
–––––––––––––––––––––––––––––––––––––––––––––
|⬆︎ SEX | 10 | 10 | 20 |
–––––––––––––––––––––––––––––––––––––––––––––
We calculate the Chi-Square Formula, which is:
Χ² = Σ ( (Observed Value − Expected Value)² / Expected Value )
In this publication, this is:
chiSquare = 0.
for i = 0 to rows -1
for j = 0 to colums -1
observedValue = aBin.get(i).aFloat.get(j)
expectedValue = math.max(1e-12, aBin.get(i).aFloat.get(colums) * aBin.get(rows).aFloat.get(j) / sumT) //Division by 0 protection
chiSquare += math.pow(observedValue - expectedValue, 2) / expectedValue
Together with the 'Degree of Freedom', which is (rows − 1) × (columns − 1) , the P-value can be calculated.
In this case it is P-value: 0.02462
A P-value lower than 0.05 is considered to be significant. Statistically, women tend to choose a romantic movie more, while men prefer a non-romantic one.
Users have the option to choose a P-value, calculated from a standard table or through a math.ucla.edu - Javascript-based function (see references below).
Note that the population (10 men + 10 women = 20) is small, something to consider.
Either way, this principle is applied in the script, where conditions can be chosen like rsi, close, high, ...
🔹 CONDITION
Conditions are added to the left column ('CONDITION')
For example, previous rsi values (rsi ) between 0-100, divided in separate groups
🔹 CLOSE
Then, the movement of the last close is evaluated
UP when close is higher then previous close (close )
DOWN when close is lower then previous close
EQUAL when close is equal then previous close
It is also possible to use only 2 columns by adding EQUAL to UP or DOWN
UP
DOWN/EQUAL
or
UP/EQUAL
DOWN
In other words, when previous rsi value was between 80 and 90, this resulted in:
19 times a current close higher than previous close
14 times a current close lower than previous close
0 times a current close equal than previous close
However, the P-value tells us it is not statistical significant.
NOTE: Always keep in mind that past behaviour gives no certainty about future behaviour.
A vertical line is drawn at the beginning of the chosen population (max 4990)
Here, the results seem significant.
🔹 GROUPS
It is important to ensure that the groups are formed correctly. All possibilities should be present, and conditions should only be part of 1 group.
In the example above, the two top situations are acceptable; close against close can only be higher, lower or equal.
The two examples at the bottom, however, are very poorly constructed.
Several conditions can be placed in more than 1 group, and some conditions are not integrated into a group. Even if the results are significant, they are useless because of the group formation.
A population count is added as an aid to spot errors in group formation.
In this example, there is a discrepancy between the population and total count due to the absence of a condition.
The results when rsi was between 5-25 are not included, resulting in unreliable results.
🔹 PRACTICAL EXAMPLES
In this example, we have specific groups where the condition only applies to that group.
For example, the condition rsi > 55 and rsi <= 65 isn't true in another group.
Also, every possible rsi value (0 - 100) is present in 1 of the groups.
rsi > 15 and rsi <= 25 28 times UP, 19 times DOWN and 2 times EQUAL. P-value: 0.01171
When looking in detail and examining the area 15-25 RSI, we see this:
The population is now not representative (only checking for RSI between 15-25; all other RSI values are not included), so we can ignore the P-value in this case. It is merely to check in detail. In this case, the RSI values 23 and 24 seem promising.
NOTE: We should check what the close price did without any condition.
If, for example, the close price had risen 100 times out of 100, this would make things very relative.
In this case (at least two conditions need to be present), we set 1 condition at 'always true' and another at 'always false' so we'll get only the close values without any condition:
Changing the population or the conditions will change the P-value.
In the following example, the outcome is evaluated when:
close value from 1 bar back is higher than the close value from 2 bars back
close value from 1 bar back is lower/equal than the close value from 2 bars back
Or:
close value from 1 bar back is higher than the close value from 2 bars back
close value from 1 bar back is equal than the close value from 2 bars back
close value from 1 bar back is lower than the close value from 2 bars back
In both examples, all possibilities of close against close are included in the calculations. close can only by higher, equal or lower than close
Both examples have the results without a condition included (5 = 5 and 5 < 5) so one can compare the direction of current close.
🔶 NOTES
• Always keep in mind that:
Past behaviour gives no certainty about future behaviour.
Everything depends on time, cycles, events, fundamentals, technicals, ...
• This test only works for categorical data (data in categories), such as Gender {Men, Women} or color {Red, Yellow, Green, Blue} etc., but not numerical data such as height or weight. One might argue that such tests shouldn't use rsi, close, ... values.
• Consider what you're measuring
For example rsi of the current bar will always lead to a close higher than the previous close, since this is inherent to the rsi calculations.
• Be careful; often, there are na -values at the beginning of the series, which are not included in the calculations!
• Always keep in mind considering what the close price did without any condition
• The numbers must be large enough. Each entry must be five or more. In other words, it is vital to make the 'population' large enough.
• The code can be developed further, for example, by splitting UP, DOWN in close UP 1-2%, close UP 2-3%, close UP 3-4%, ...
• rsi can be supplemented with stochRSI, MFI, sma, ema, ...
🔶 SETTINGS
🔹 Population
• Choose the population size; in other words, how many bars you want to go back to. If fewer bars are available than set, this will be automatically adjusted.
🔹 Inputs
At least two conditions need to be chosen.
• Users can add up to 11 conditions, where each condition can contain two different conditions.
🔹 RSI
• Length
🔹 Levels
• Set the used levels as desired.
🔹 Levels
• P-value: P-value retrieved using a standard table method or a function.
• Used function, derived from Chi-Square Distribution Function; JavaScript
LogGamma(Z) =>
S = 1
+ 76.18009173 / Z
- 86.50532033 / (Z+1)
+ 24.01409822 / (Z+2)
- 1.231739516 / (Z+3)
+ 0.00120858003 / (Z+4)
- 0.00000536382 / (Z+5)
(Z-.5) * math.log(Z+4.5) - (Z+4.5) + math.log(S * 2.50662827465)
Gcf(float X, A) => // Good for X > A +1
A0=0., B0=1., A1=1., B1=X, AOLD=0., N=0
while (math.abs((A1-AOLD)/A1) > .00001)
AOLD := A1
N += 1
A0 := A1+(N-A)*A0
B0 := B1+(N-A)*B0
A1 := X*A0+N*A1
B1 := X*B0+N*B1
A0 := A0/B1
B0 := B0/B1
A1 := A1/B1
B1 := 1
Prob = math.exp(A * math.log(X) - X - LogGamma(A)) * A1
1 - Prob
Gser(X, A) => // Good for X < A +1
T9 = 1. / A
G = T9
I = 1
while (T9 > G* 0.00001)
T9 := T9 * X / (A + I)
G := G + T9
I += 1
G *= math.exp(A * math.log(X) - X - LogGamma(A))
Gammacdf(x, a) =>
GI = 0.
if (x<=0)
GI := 0
else if (x
Chisqcdf = Gammacdf(Z/2, DF/2)
Chisqcdf := math.round(Chisqcdf * 100000) / 100000
pValue = 1 - Chisqcdf
🔶 REFERENCES
mathsisfun.com, Chi-Square Test
Chi-Square Distribution Function
Volatility System by W. WilderVolatility System (Volatility Stops) Similarity
Most traders adjust their stops over time in the direction of the trend in order to lock in profits. Apart from moving averages, one of the most popular techniques is trailing stops using a multiple of Average True Range. There are several variations:
The original Volatility System(Volatility Stops), introduced by Welles Wilder in his 1978 book: New Concepts in Technical Trading Systems
Chandelier exits introduced by Alexander Elder in Come Into My Trading Room (2002) trail the stops from Highs or Lows rather than Closing Price
Average True Range Trailing Stops are similar to the above, but include a ratchet mechanism to prevent stops moving down during an up-trend or rising during a down-trend, as ATR increases
WillTrend intoduced by Larry Williams in 1988
Comparison of systems
All the systems under consideration have one common ingredient - ATR. ATR was developed by Welles Wilder and described in his book in 1978, also in this book the Volatility System was described, which in the future became known as Volatility Stops.
In fact, Wilder is the father of such systems due to the presence of ATR in the calculation of this type of indicator.
The main difference of Volatility System
Followers such as Larry Williams and Alexander Elder made minor changes to the value based on the ATR, mainly focusing on changing the base to which this value is added or subtracted.
Larry Williams uses the square root of 5 as a multiplier and calculates the ATR with a period of 66, and Alexander Elder uses a multiplier of 2.5-3.5 applying it to the ATR with a period of 22. Both authors changed the original value for ATR and multiplier calculations. Alexander Elder is closest to the original Welles Wilder calculation, which used a multiplier of 2.8.-3.1 applying it to an ATR with a period of 7.
As a reference, Elder took the Highest High(22) from which he subtracts ATR*Multiplier in an uptrend or the Lowest Low(22) to which he adds ATR*Multiplier to obtain the turning point (SAR).
Larry Williams uses the average price of extremes (Highest High(10) + Lowest Low(10)) / 2 as a reference base to which he adds or subtracts the ATR*Multilpyer values.
Both systems differ from the original, because Wilder used Significan Close(SIC) in his calculations. SIC is the maximum closing price during an uptrend and the minimum closing price during a downtrend, which
does not go beyond the current trade, as in other systems. To calculate the base when a trend changes, bars that are outside the current trend will be used when calculating WillTrend and Chandelier Exit, in contrast to the Volatility System, which takes SIC values only within the current trade. This is the main difference from subsequent developments of similar systems.
Improvements made
The original Volatility System is present as an indicator on TradingView, but it is an improved version with the addition of a ratchet and works differently from the original Weilder system.
List of improvements:
Added the ability to remove the ratchet. You need to turn off the "Trail one way" checkbox in the setting menu. When this function is turned off, the system will operate in the author-inventor mode. On some instruments, the original system works much better than the improved ratchet system, which cannot be turned off.
Added the ability to use Highest High and Lowest Low as a base instead of the closing price.
Volatility Stops Formula Description
Welles Wilder's system uses Closing Price and incorporates a stop-and-reverse feature (as with his Parabolic SAR).
Determine the initial trend direction
Calculate the Significant Close ("SIC"): the highest close reached in an up-trend or the lowest close in a down-trend
Calculate Average True Range ("ATR") for the selected period (7 days in this example)
Multiply ATR by the Multiple (3.0 in this example, best values author describes as 2.8-3.1)
The first stop is calculated in day 7 and plotted for day 8
If an up-trend, the first stop is SIC - 3 * ATR, otherwise SIC + 3 * ATR for a down-trend
Repeat each day until price closes below the stop (or above in a down-trend)
Set SIC equal to the latest Close, reverse the trend and continue.
Chandelier Exit Description
Chandelier Exits subtract a multiple of Average True Range ("ATR") from the highest high for the selected period. Using the default settings as an example:
Highest High in last 22 days - 3 * ATR for 22 days
In a down-trend the formula is reversed:
Lowest Low in last 22 days + 3 * ATR for 22 days
The time period must be long enough to capture the highest point of the recent up-trend: too short and the stops move downward; too long and the high may be taken from a previous down-trend.
It is not essential to use the same period for up and down trends; down-trends are notoriously faster than up-trends and may benefit from a shorter time period.
The multiple of 3 may be varied, but most traders settle between 2.5 and 3.5.
WillTrend Description
Larry Williams is prefer to used the Square Root from 5 as a multiplayer for ATR. SQRT(5) = 2.236
WillTrend subtract a multiple of Average True Range ("ATR") from the Middle Price (Highest High for the selected period + Lowest Low for the selected period / 2).
(Highest High in last 10 days + Lowest Low in last 10 days) / 2 - 2.236 * ATR for 66 days
In a down-trend the formula is reversed:
(Highest High in last 10 days + Lowest Low in last 10 days) / 2 + 2.236 * ATR for 66 days
itradesize /\ Silver Bullet x Macro x KillzoneThis indicator shows the best way to annotate ICT Killzones, Silver Bullet and Macro times on the chart. With the help of a new pane, it will not distract your chart and will not cause any distractions to your eye, or brain but you can see when will they happen.
The indicator also draws everything beforehand when a proper new day starts.
You can customize them how you want to show up.
Collapsed or full view?
You can hide any of them and keep only the ones you would like to.
All the colors can be customized, texts & sizes or just use shortened texts and you are also able to hide those drawings which are older than the actual day.
You should minimize the pane where the script has been automatically drawn to therefore you will have the best experience and not show any distractions.
The script automatically shows the time-based boxes, based on the New York timezone.
Killzone Time windows ( for indices ):
London KZ 02:00 - 05:00
New York AM KZ 07:00 - 10:00
New York PM KZ 13:30 - 16:00
Silver Bullet times:
03:00 - 04:00
10:00 - 11:00
14:00 - 15:00
Macro times:
02:33 - 03:00
04:03 - 04:30
08:50 - 0910
09:50 - 10:10
10:50 - 11:10
11:50 - 12:50
[imba]lance algo🟩 INTRODUCTION
Hello, everyone!
Please take the time to review this description and source code to utilize this script to its fullest potential.
🟩 CONCEPTS
This is a trend indicator. The trend is the 0.5 fibonacci level for a certain period of time.
A trend change occurs when at least one candle closes above the level of 0.236 (for long) or below 0.786 (for short). Also it has massive amout of settings and features more about this below.
With good settings, the indicator works great on any market and any time frame!
A distinctive feature of this indicator is its backtest panel. With which you can dynamically view the results of setting up a strategy such as profit, what the deposit size is, etc.
Please note that the profit is indicated as a percentage of the initial deposit. It is also worth considering that all profit calculations are based on the risk % setting.
🟩 FEATURES
First, I want to show you what you see on the chart. And I’ll show you everything closer and in more detail.
1. Position
2. Statistic panel
3. Backtest panel
Indicator settings:
Let's go in order:
1. Strategies
This setting is responsible for loading saved strategies. There are only two preset settings, MANUAL and UNIVERSAL. If you choose any strategy other than MANUAL, then changing the settings for take profits, stop loss, sensitivity will not bring any results.
You can also save your customized strategies, this is discussed in a separate paragraph “🟩HOW TO SAVE A STRATEGY”
2. Sensitive
Responsible for the time period in bars to create Fibonacci levels
3. Start calculating date
This is the time to start backtesting strategies
4. Position group
Show checkbox - is responsible for displaying positions
Fill checkbox - is responsible for filling positions with background
Risk % - is responsible for what percentage of the deposit you are willing to lose if there is a stop loss
BE target - here you can choose when you reach which take profit you need to move your stop loss to breakeven
Initial deposit- starting deposit for profit calculation
5. Stoploss group
Fixed stoploss % checkbox - If choosed: stoploss will be calculated manually depending on the setting below( formula: entry_price * (1 - stoploss percent)) If NOT choosed: stoploss will be ( formula: fibonacci level(0.786/0.236) * (1 + stoploss percent))
6. Take profit group
This group of settings is responsible for how far from the entry point take profits will be and what % of the position to fix
7. RSI
Responsible for configuring the built-in RSI. Suitable bars will be highlighted with crosses above or below, depending on overbought/oversold
8. Infopanels group
Here I think everything is clear, you can hide or show information panels
9. Developer mode
If enabled, all events that occur will be shown, for example, reaching a take profit or stop loss with detailed information about the unfixed balance of the position
🟩 HOW TO USE
Very simple. All you need is to wait for the trend to change to long or short, you will immediately see a stop loss and four take profits, and you will also see prices. Like in this picture:
🟩 ALERTS
There are 3 types of alerts:
1. Long signal
2. Short signal
3. Any alert() function call - will be send to you json with these fields
{
"side": "LONG",
"entry": "64.454",
"tp1": "65.099",
"tp2": "65.743",
"tp3": "66.388",
"tp4": "67.032",
"winrate": "35.42%",
"strategy": "MANUAL",
"beTargetTrigger": "1",
"stop": "64.44"
}
🟩 HOW TO SAVE A STRATEGY
First, you need to make sure that the “MANUAL” strategy is selected in the strategy settings.
After this, you can start selecting parameters that will show the largest profit in the statistics panel.
I have highlighted what you need to pay attention to when choosing a strategy
Let's assume you have set up a strategy. The main question is how to preserve it?
Let’s say the strategy turned out with the following parameters:
Next we need to find this section of code:
// STRATS
selector(string strategy_name) =>
strategy_settings = Strategy_settings.new()
switch strategy_name
"MANUAL" =>
strategy_settings.sensitivity := 18
strategy_settings.risk_percent := 1
strategy_settings.break_even_target := "1"
strategy_settings.tp1_percent := 1
strategy_settings.tp1_percent_fix := 40
strategy_settings.tp2_percent := 2
strategy_settings.tp2_percent_fix := 30
strategy_settings.tp3_percent := 3
strategy_settings.tp3_percent_fix := 20
strategy_settings.tp4_percent := 4
strategy_settings.tp4_percent_fix := 10
strategy_settings.fixed_stop := false
strategy_settings.sl_percent := 0.0
"UNIVERSAL" =>
strategy_settings.sensitivity := 20
strategy_settings.risk_percent := 1
strategy_settings.break_even_target := "1"
strategy_settings.tp1_percent := 1
strategy_settings.tp1_percent_fix := 40
strategy_settings.tp2_percent := 2
strategy_settings.tp2_percent_fix := 30
strategy_settings.tp3_percent := 3
strategy_settings.tp3_percent_fix := 20
strategy_settings.tp4_percent := 4
strategy_settings.tp4_percent_fix := 10
strategy_settings.fixed_stop := false
strategy_settings.sl_percent := 0.0
// "NEW STRATEGY" =>
// strategy_settings.sensitivity := 20
// strategy_settings.risk_percent := 1
// strategy_settings.break_even_target := "1"
// strategy_settings.tp1_percent := 1
// strategy_settings.tp1_percent_fix := 40
// strategy_settings.tp2_percent := 2
// strategy_settings.tp2_percent_fix := 30
// strategy_settings.tp3_percent := 3
// strategy_settings.tp3_percent_fix := 20
// strategy_settings.tp4_percent := 4
// strategy_settings.tp4_percent_fix := 10
// strategy_settings.fixed_stop := false
// strategy_settings.sl_percent := 0.0
strategy_settings
// STRATS
Let's uncomment on the latest strategy called "NEW STRATEGY" rename it to "SOL 5m" and change the sensitivity:
// STRATS
selector(string strategy_name) =>
strategy_settings = Strategy_settings.new()
switch strategy_name
"MANUAL" =>
strategy_settings.sensitivity := 18
strategy_settings.risk_percent := 1
strategy_settings.break_even_target := "1"
strategy_settings.tp1_percent := 1
strategy_settings.tp1_percent_fix := 40
strategy_settings.tp2_percent := 2
strategy_settings.tp2_percent_fix := 30
strategy_settings.tp3_percent := 3
strategy_settings.tp3_percent_fix := 20
strategy_settings.tp4_percent := 4
strategy_settings.tp4_percent_fix := 10
strategy_settings.fixed_stop := false
strategy_settings.sl_percent := 0.0
"UNIVERSAL" =>
strategy_settings.sensitivity := 20
strategy_settings.risk_percent := 1
strategy_settings.break_even_target := "1"
strategy_settings.tp1_percent := 1
strategy_settings.tp1_percent_fix := 40
strategy_settings.tp2_percent := 2
strategy_settings.tp2_percent_fix := 30
strategy_settings.tp3_percent := 3
strategy_settings.tp3_percent_fix := 20
strategy_settings.tp4_percent := 4
strategy_settings.tp4_percent_fix := 10
strategy_settings.fixed_stop := false
strategy_settings.sl_percent := 0.0
"SOL 5m" =>
strategy_settings.sensitivity := 15
strategy_settings.risk_percent := 1
strategy_settings.break_even_target := "1"
strategy_settings.tp1_percent := 1
strategy_settings.tp1_percent_fix := 40
strategy_settings.tp2_percent := 2
strategy_settings.tp2_percent_fix := 30
strategy_settings.tp3_percent := 3
strategy_settings.tp3_percent_fix := 20
strategy_settings.tp4_percent := 4
strategy_settings.tp4_percent_fix := 10
strategy_settings.fixed_stop := false
strategy_settings.sl_percent := 0.0
strategy_settings
// STRATS
Now let's find this code:
strategy_input = input.string(title = "STRATEGY", options = , defval = "MANUAL", tooltip = "EN:\nTo manually configure the strategy, select MANUAL otherwise, changing the settings won't have any effect\nRU:\nЧтобы настроить стратегию вручную, выберите MANUAL в противном случае изменение настроек не будет иметь никакого эффекта")
And let's add our new strategy there, it turned out like this:
strategy_input = input.string(title = "STRATEGY", options = , defval = "MANUAL", tooltip = "EN:\nTo manually configure the strategy, select MANUAL otherwise, changing the settings won't have any effect\nRU:\nЧтобы настроить стратегию вручную, выберите MANUAL в противном случае изменение настроек не будет иметь никакого эффекта")
That's all. Our new strategy is now saved! It's simple! Now we can select it in the list of strategies:
The Ultimate Buy and Sell IndicatorThis indicator should be used in conjunction with a solid risk management strategy that does not over-leverage positions and uses stop-losses. You can not rely 100% on the signals provided by this indicator (or any other for that matter).
With that said, this indicator can provide some excellent signals.
It has been designed with a large number of customization options intended for advanced traders, but you do not HAVE to be an advanced user to simply use the indicator. I have tried to make it easy to understand, and this section will provide you with a better understanding of how to use it.
NOTE:
While NOT REQUIRED, I would recommend also finding my indicator called, "Ultimate RSI", which is designed to work together with this indicator (visually). They both contain the same settings and allow you to visualize changes made in this indicator that can not be displayed on the main chart.
This indicator creates it's own candles(bars), so you have to go into your main settings and turn off the "body, border and wick" color settings. Using a dark background is also recommended.
How does it work?
The indicator mainly relies on the RSI indicator with Bollinger Bands for signals. (Though not entirely)
First, there are something that I call "Watch Signals", which are various Bollinger Band crossing events. This could be the price crossing Bollinger Bands or the RSI crossing Bollinger Bands.
There are separate watch signals for buys and sells. Buy watch signals are colored orange to match the BUY signal candle color and Fuchsia (kind of a bright purple) to match SELL signal candles.
In order for most buy or sell signals to be created, there must first be a watch signal. There is a lookback period (or length) for watch signals to be used, and after that many candles (bars) have passed, they will be ignored. You can set a length to look back as well as a time to wait before creating any.
What this means is that if there has previously been (for instance) a sell signal. You can tell it to wait 10 bars before creating any buy watch signals. You can then also tell it that it should look back 10 bars from the current one in order to find any buy watch signals. This means that if you had it set up that way 10 to wait and 10 to validate, it would start allowing buy watch signals 11 bars after a sell, and then once you hit 20 bars, it will start leaving a gap (invisible to you) as the 10 bar lookback period starts moving forward with each new bar. This is useful in order to keep signals more spaced apart as some bad signals come quickly after another one.
Example: You may get a sell signal where the Bollinger bands are tight, then the price easily drops down into the lower band creating a buy watch signal, then you get a "fake" or short pump up and it says buy, but then drops dramatically afterwards. The wait period can ensure that the sell stays in effect longer before a buy is considered by blocking any buy watch signals for a period of time.
After you get a watch signal, the system then looks for various other things to happen to create buy or sell signals. This could be the RSI crossing the (slow) RSI Basis line (from its Bollinger bands), it could be the price crossing its basis line, it could be MACD crosses, it could even be RSI crossing certain levels. All of these are options. If you like the MACD strategy and want it to give you buy and sell signals from just MACD crosses, simply select that option for signals.
It is also able to use the first of any of the options that takes place.
I included an option to force alternating buy and sell signals, rather than showing groups of, or subsequent buy, buy, buy signals, for instance.
Moving on....
You can change the moving average that is used to calculate the RSI. The standard moving average for RSI is the RMA (aka SWMA). Changes to this can dramatically change your signals. You also have the option to change the moving average type used in the Bollinger bands calculation. You can change the length of these as well. The same goes for the Bollinger bands over the Price chart. I added an ATR option for the RSI Bollinger bands to play with, as well. You are able to adjust the standard deviation (multiplier) of the bands as well, which will of course affect the signals.
The ways you can play with signals are nearly infinite, so have fun figuring it out.
The indicator allows for moving averages to be shown as well, with a variety of types to choose from. The standard numbers are 5, 10, 20, 50, 100 and 200, with the addition of a custom moving average of your choice. You can also change the color of this one. You can choose to show them all or any of them you want to show, in any combination, although the TYPE of moving average (SMA, EMA, WMA, etc.) will apply to all of them.
You may also notice the Bollinger Bands over the Price are colored, and become more or less transparent.
The color is derived from the trend of the RSI or the RSI basis (your choice). It looks back at the value however many bars you want and compares the values and that's how it determines if it is trending up or down. Since RSI is a directional momentum indicator, this can be quite useful. If you see the bands are getting darker, this will explain why.
The indicator has a lookback period for determining the widest the bands (which measure volatility) have been over that period of time. This is the baseline. It then will make the bands disappear (by making them more transparent) if the volatility is low. This indicates that a change in volatility is coming and that price isn't really changing much compared to the past (default 500) bars. If they become bright, this is because price has started trending in a direction and volatility is increasing.
I should also note that the candles are colored based on RSI levels.
If you use the Ultimate Companion indicator, you will be able to see the RSI levels (zones) that the colors are based on. As RSI moves into a new range, the candle color will change.
I have created a yellow zone where the candles turn yellow. This is when RSI is between (default) 45 and 55, indicating there is basically no momentum and price is going sideways. This is a good place to get trapped in bad trades, and there is a Yellow RSI Filter to block signals in this area to keep you from entering bad trades.
Green candles indicate values over 55 (getting brighter as RSI rises) and red candles are RSI values under 45 (getting brighter as RSI values get lower). If you see white, this means RSI is either over 80 or under 20. A sharp reversal is almost always imminent at this stage.
When we talk about Buy and Sell Signals, they draw a green or red triangle and it literally says BUY or SELL. There is an option to color the background for added visibility. These signals do not "repaint", what this means is that they can be late. To account for this, I have included a background color that will flash as a warning that a buy or sell could be imminent, although it may fail to break through and set a buy or sell signal. This is simply an advanced warning. The reason is that sometimes a candle may be very large and you won't be told to buy or sell during the candle until the move is completely over and now you're getting in on the next one. That's not a great feeling, so I made it repaint the background color and not repaint the completed signal. You get the best of both worlds.
This indicator also uses complex logic to handle things.
When there is a buy signal, it enters into a state of having been bought, or a "bought state". The same for sells. If Force alternating signals is off, you could have more than one buy in a bought state, or more than one sell in a sell state. There is an option to color the background green during the full duration of a bought state, or red during the full duration of a sold state.
I have added divergence.
This shows that the lows or highs of RSI and PRICE are different. If RSI is making higher highs but the price is not, then the price is likely to follow this bullish divergence, if the opposite happens, it's bearish. It will draw a line on the chart connecting the highs and lows and call it bearish or bullish. You can adjust this as well.
I have an RSI High/Low filter. If the RSI basis (or average) is very high or low, you can block signal from this area since the price is likely to continue in that direction before actually reversing.
You can change the settings of the MACD if you choose to use it for signals, and if you want to see it, you'll have to run that indicator below the chart and match the settings to see what is going on, just like the RSI.
Going back to Watch Signals. You can also choose to require more than one watch signal if you choose. You can skip watch signals, so it will ignore the first or second one, whatever you want to do. You can color the background to show you where watch signals have been skipped.
Regarding the wait period for creating watch signals after a sell or after a buy, you can also color the background to see where these were blocked by the wait period.
Lastly you can choose which type of watch signals to use, or keep them from being shown on the chart. This allows you to study the history of how the asset you are trading behaves and customize the behavior of signals based on your study of it.
Everything in the settings area has tooltips, which will explain what that thing does to help you along this journey.
I hope this indicator (and perhaps Ultimate RSI alongside this) will help you take your trading to the next level.
RAINBOW AVERAGES - INDICATOR - (AS) - 1/3
-INTRODUCTION:
This is the first of three scripts I intend to publish using rainbow indicators. This script serves as a groundwork for the other two. It is a RAINBOW MOVING AVERAGES indicator primarily designed for trend detection. The upcoming script will also be an indicator but with overlay=false (below the chart, not on it) and will utilize RAINBOW BANDS and RAINBOW OSCILLATOR. The third script will be a strategy combining all of them.
RAINBOW moving averages can be used in various ways, but this script is mainly intended for trend analysis. It is meant to be used with overlay=true, but if the user wishes, it can be viewed below the chart. To achieve this, you need to change the code from overlay=true to false and turn off the first switch that plots the rainbow on the chart (or simply move the indicator to a new pane below). By doing this, you will be able to see how all four conditions used to detect trends work on the chart. But let's not get ahead of ourselves.
-WHAT IS IT:
In its simplest form, this indicator uses 10 moving averages colored like a rainbow. The calculation is as follows:
MA0: This is the main moving average and can be defined with the type (SMA, EMA, RMA, WMA, SINE), length, and price source. However, the second moving average (MA1) is calculated using MA0 as its source, MA2 uses MA1 as the data source, and so on, until the last one, MA9. Hence, there are 10 moving averages. The first moving average is special as all the others derive from it. This indicator has many potential uses, such as entry/exit signals, volatility indication, and stop-loss placement, but for now, we will focus on trend detection.
-TREND DETECTION:
The indicator offers four different background color options based on the user's preference:
0-NONE: No background color is applied as no trend detection tools is being used (boring)
1-CHANGE: The background color is determined by summing the changes of all 10 moving averages (from two bars). If the sum is positive and not falling, the background color is GREEN. If the sum is negative and not rising, the background color is RED. From early testing, it works well for the beginning of a movement but not so much for a lasting trend.
2-RAINBW: The background color is green when all the moving averages are in ascending order, indicating a bullish trend. It is red when all the moving averages are in descending order, indicating a bearish trend. For example, if MA1>MA2>MA3>MA4..., the background color is green. If MA1 threshold, and red indicates width < -threshold.
4-DIRECT: The background color is determined by counting the number of moving averages that are either above or below the input source. If the specified number of moving averages is above the source, the background color is green. If the specified number of moving averages is below the source, the background color is red. If all ten MAs are below the price source, the indicator will show 10, and if all ten MAs are above, it will show -10. The specific value will be set later in the settings (same for 3-TSHOLD variant). This method works well for lasting trends.
Note: If the indicator is turned into a below-chart version, all four color options can be seen as separate indicators.
-PARAMETERS - SETTINGS:
The first line is an on/off switch to plot the skittles indicator (and some info in the tooltip). The second line has already been discussed, which is the background color and the selection of the source (only used for MA0!).
The line "MA1: TYP/LEN" is where we define the parameters of MA0 (important). We choose from the types of moving averages (SMA, EMA, RMA, WMA, SINE) and set the length.
Important Note: It says MA1, but it should be MA0!.
The next line defines whether we want to smooth MA1 (which is actually MA0) and the period for smoothing. When smoothing is turned on, MA0 will be smoothed using a 3-pole super smoother. It's worth noting that although this only applies to MA0, as the other MAs are derived from it, they will also be smoothed.
In the line below, we define the type and length of MAs for MA2 (and other MAs except MA0). The same type and length are used for MA1 to MA9. It's important to remember that these values should be smaller. For example, if we set 55, it means that MA1 is the average of 55 periods of MA0, MA2 will be 55 periods of MA1, and so on. I encourage trying different combinations of MA types as it can be easily adjusted for ur type of trading. RMA looks quirky.
Moving on to the last line, we define some inputs for the background color:
TSH: The threshold value when using 3-TSHOLD-BGC. It's a good idea to change the chart to a pane below for easier adjustment. The default values are based on EURUSD-5M.
BG_DIR: The value that must be crossed or equal to the MA score if using 4-DIRECT-BGC. There are 10 MAs, so the maximum value is also 10. For example, if you set it to 9, it means that at least 9 MAs must be below/above the price for the script to detect a trend. Higher values are recommended as most of the time, this indicator oscillates either around the maximum or minimum value.
-SUMMARY OF SETTINGS:
L1 - PLOT MAs and general info tooltip
L2 - Select the source for MA0 and type of trend detection.
L3 - Set the type and length of MA0 (important).
L4 - Turn smoothing on/off for MA0 and set the period for super smoothing.
L5 - Set the type and length for the rest of the MAs.
L6 - Set values if using 4-DIRECT or 3-TSHOLD for the trend detection.
-OTHERS:
To see trend indicators, you need to turn off the plotting of MAs (first line), and then choose the variant you want for the background color. This will plot it on the chart below.
Keep in mind that M1 int settings stands for MA0 and MA2 for all of the 9 MAs left.
Yes, it may seem more complicated than it actually is. In a nutshell, these are 10 MAs, and each one after MA0 uses the previous one as its source. Plus few conditions for range detection. rest is mainly plots and colors.
There are tooltips to help you with the parameters.
I hope this will be useful to someone. If you have any ideas, feedback, or spot errors in the code, LET ME KNOW.
Stay tuned for the remaining two scripts using skittles indicators and check out my other scripts.
-ALSO:
I'm always looking for ideas for interesting indicators and strategies that I could code, so if you don't know Pinescript, just message me, and I would be glad to write your own indicator/strategy for free, obviously.
-----May the force of the market be with you, and until we meet again,
True Trend Average BandsThis is the indicator I am most proud of. After reading Glenn Neely's book "Mastering Eliott Waves" / "Neowave" and chatting with @timwest who got acknowledged by Neely, we came up with the idea of an moving average which does calculate the real average price since a trend started. Addionally I adapted a method from Neely Neowave and Tim Wests TimeAtMode to not force a timeframe on a chart but instead let the charts data decide which timeframe to use, to then calculate the real average price since the trend started.
It took me a while to get this right and coded, so take a moment and dive deeper and you might learn something new.
We assume that the price is in multiple trends on multiple timeframes, this is caused by short term traders, long term traders and investors who trade on different timeframes. To find out in which timeframe the important trends are, we have to look out for significant lows and highs. Then we change the timeframe in the chart to a value so that we have 10 to 20 bars since the significant low/high. While new bars are printed, and we reach more than 20 bars, we have to switch to a higher timeframe so we have 10 to 20 bars again. In the chart you see two significant trends: a downtrend on the 3 week timeframe and an uptrend from the 2 month timeframe. Based on the logic I have described, these are the two important timeframes to watch right now for the spx (there is another uptrend in the yearly chart, which is not shown here).
Now that we understand how to find the important timeframes, let's look what the magic in this script is that tells us the real average price since a trend started.
I developed a new type of moving average, which includes only the prices since a trend started. The difference to the regular sma is that it will not include prices which happened before the significant low or high happened. For example, if a top happened in a market 10 days ago, the regular sma20 would be calculated by 10 bars which happened before the top and 10 bars which happened after the top. If we want to know the average price of the last 10 bars we manually have to change the ma20 to the ma10 which is annoying manual work, additionally even if we use the ma10 in this case, and we look at yesterday's bar the ma10 will include 9 bars from after the top and one bar before the top, so the ma10 would only show the real average price for the current bar which is not what we want.
To come up with a solution to this problem, the True Trend Average searches for the lowest/highest bar in a given period (20 bars). Then starts to calculate the average value since the low/high. For example: if the price reaches a new 20 day high and then trades below it, the day of the high will be the sma1, the day after it's the sma2, ... up to the maximum look back length.
This way, we always know what the average price would have been if someone sold/bought a little bit every bar of his investment since the high/low.
Why is this even important? Let's assume we missed selling the top or buying the low, and think it would have been at least better to buy/sell a little bit since the new trend started. Once the price reaches the true trend average again, we can buy/sell, and it would be as good as selling/buying a little bit every day. We find prices to buy the dip and sell the bounce, which are as good as scaling in/out.
There is a lot more we can learn from these price levels but I think it is better to let you figure out yourself what you can learn from the information given by this indicator. Think about how market participants who accumulate or distribute feel when prices are above or below certain levels.
Now that we understand this new type of moving average, let's look into the lines we see in the chart:
The upper red band line shows the true trend average high price since the last significant top within 20 bars.
The lower red band line shows the true trend average hl2 price since the last significant top within 20 bars.
The lower green band line shows the true trend average low price since the last significant low within 20 bars.
The upper green band line shows the true trend average hl2 price since the last significant low within 20 bars.
The centerline is the average between the upper red band and the lower green band.
The teal lines show 1 standard deviation from the outer bands.
Before today only a few people had access to this indicator, now that it is public and open source, I am curious if you will find it useful and what you will do with it. Please share your findings.
/edit: The chart only shows the 3week timeframe so here are the other two trends from the 2month and 1year timeframe
[blackcat] L1 Old Duck HeadLevel 1
Background
The old duck head is a classic form formed by a series of behaviors such as bankers opening positions, washing dishes, and pulling over the top of the duck head.
Function
A form of stock candles:
(1) Moving averages using 5, 10 and 60 parameters. When the 5-day and 10-day moving averages crossed the 60-day moving average, a duck neck was formed.
(2) The high point when the stock price fell back formed a duck head.
(3) When the stock price fell back soon, the 5-day and 10-day moving averages again turned up to form a duckbill.
(4) Duck nose refers to the hole formed when the 5-day moving average crosses the 10-day moving average and the two lines cross again.
Market significance:
(1) When the dealer starts to collect chips, the stock price rises slowly, and the 5-day and 10-day moving averages cross the 60-day moving average, forming a duck neck.
(2) When the stock price of the banker shakes the position and starts to pull back, the high point of the stock price forms the top of the duck's head.
(3) When the dealer builds a position again to collect chips, the stock price rises again, forming a duck bill.
Operation method:
(1) Buy when the 5-day and 10-day moving averages cross the 60-day moving average and form a duck neck.
(2) Buy on dips near the sesame point of trading volume near the duckbill.
(3) Intervene when the stock price crosses the top of the duck's head in heavy volume.
The top of the duck’s head should be a little far away from the 60-day moving average, otherwise it means that the dealer is not willing to open a position at this old duck’s head, and the bottom of the old duck’s head must be heavy. Small is better, nothing is the strongest! There must be a lot of sesame dots under the nostrils of the duck, otherwise it means that the dealer has poor control. There must be ventilation under the duck bill, the higher the ventilation, the better!
Remarks
Feedbacks are appreciated.
Variety N-Tuple Moving Averages w/ Variety Stepping [Loxx]Variety N-Tuple Moving Averages w/ Variety Stepping is a moving average indicator that allows you to create 1- 30 tuple moving average types; i.e., Double-MA, Triple-MA, Quadruple-MA, Quintuple-MA, ... N-tuple-MA. This version contains 2 different moving average types. For example, using "50" as the depth will give you Quinquagintuple Moving Average. If you'd like to find the name of the moving average type you create with the depth input with this indicator, you can find a list of tuples here: Tuples extrapolated
Due to the coding required to adapt a moving average to fit into this indicator, additional moving average types will be added as they are created to fit into this unique use case. Since this is a work in process, there will be many future updates of this indicator. For now, you can choose from either EMA or RMA.
This indicator is also considered one of the top 10 forex indicators. See details here: forex-station.com
Additionally, this indicator is a computationally faster, more streamlined version of the following indicators with the addition of 6 stepping functions and 6 different bands/channels types.
STD-Stepped, Variety N-Tuple Moving Averages
STD-Stepped, Variety N-Tuple Moving Averages is the standard deviation stepped/filtered indicator of the following indicator
Last but not least, a big shoutout to @lejmer for his help in formulating a looping solution for this streamlined version. this indicator is speedy even at 50 orders deep. You can find his scripts here: www.tradingview.com
How this works
Step 1: Run factorial calculation on the depth value,
Step 2: Calculate weights of nested moving averages
factorial(depth) / (factorial(depth - k) * factorial(k); where depth is the depth and k is the weight position
Examples of coefficient outputs:
6 Depth: 6 15 20 15 6
7 Depth: 7 21 35 35 21 7
8 Depth: 8 28 56 70 56 28 8
9 Depth: 9 36 34 84 126 126 84 36 9
10 Depth: 10 45 120 210 252 210 120 45 10
11 Depth: 11 55 165 330 462 462 330 165 55 11
12 Depth: 12 66 220 495 792 924 792 495 220 66 12
13 Depth: 13 78 286 715 1287 1716 1716 1287 715 286 78 13
Step 3: Apply coefficient to each moving average
For QEMA, which is 5 depth EMA , the calculation is as follows
ema1 = ta. ema ( src , length)
ema2 = ta. ema (ema1, length)
ema3 = ta. ema (ema2, length)
ema4 = ta. ema (ema3, length)
ema5 = ta. ema (ema4, length)
In this new streamlined version, these MA calculations are packed into an array inside loop so Pine doesn't have to keep all possible series information in memory. This is handled with the following code:
temp = array.get(workarr, k + 1) + alpha * (array.get(workarr, k) - array.get(workarr, k + 1))
array.set(workarr, k + 1, temp)
After we pack the array, we apply the coefficients to derive the NTMA:
qema = 5 * ema1 - 10 * ema2 + 10 * ema3 - 5 * ema4 + ema5
Stepping calculations
First off, you can filter by both price and/or MA output. Both price and MA output can be filtered/stepped in their own way. You'll see two selectors in the input settings. Default is ATR ATR. Here's how stepping works in simple terms: if the price/MA output doesn't move by X deviations, then revert to the price/MA output one bar back.
ATR
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis we usually use it to measure the level of current volatility .
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA , we can call it EMA deviation. And added to that, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
See how this compares to Standard Devaition here:
Adaptive Deviation
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
For this indicator, I used a manual recreation of the quantile function in Pine Script. This is so users have a full inside view into how this is calculated.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is widely used indicator in many occasions for technical analysis . It is calculated as the RMA of true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range
See how this compares to ATR here:
ER-Adaptive ATR
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
For Pine Coders, this is equivalent of using ta.dev()
Bands/Channels
See the information above for how bands/channels are calculated. After the one of the above deviations is calculated, the channels are calculated as output +/- deviation * multiplier
Signals
Green is uptrend, red is downtrend, yellow "L" signal is Long, fuchsia "S" signal is short.
Included:
Alerts
Loxx's Expanded Source Types
Bar coloring
Signals
6 bands/channels types
6 stepping types
Related indicators
3-Pole Super Smoother w/ EMA-Deviation-Corrected Stepping
STD-Stepped Fast Cosine Transform Moving Average
ATR-Stepped PDF MA
Tendies Heist Auto Compounding ExampleThis is an example of how we can use compounding to control our position size. This example shows how we can automatically add and reduce position size based on account equity. The "initial capital" in properties is the starting account equity. At default its set to 100,000. If our max position size is set to 25 then the very first position that's taken has a position size of 10, IF our leverage is set to 10,000. Account equity divided by leverage equals position size. So in that example 100,000 divided by 10,000 in leverage gives us a max position size of 10. However the max position size was set to 25 meaning we would need 250k in equity for it to open a position size of 25 with the leverage set at 10k. Now if the initial capital was set to 100,000 and the max position size was set to 5 and leverage remained at 10,000, all though 100,000 divided by 10,000 equals 10 it will ONLY open a position size of 5, because the max position size in this example was set at 5. Since this works for strategies you may look through the trade log on the posted back test and check out the position size, you can see in this back test the default 100k is used for the initial capital and the default 10k was used for the leverage. You will be able to see as this logic loses money it takes contracts away and as it gains money it adds contracts. I'm using trading view's basic strategy logic example to provide an example of how the compounding logic works.
Note, don't forget to add the syntax below to your strategy.entry call for this logic to work.
qty = size
Tendies Heist LLC 2021
Combo Backtest 123 Reversal & D_Three Ten OscThis is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
TradeStation does not allow the user to make a Multi Data Chart with
a Tick Bar Chart and any other type a chart. This indicator allows the
user to plot a daily 3-10 Oscillator on a Tick Bar Chart or any intraday interval.
Walter Bressert's 3-10 Oscillator is a detrending oscillator derived
from subtracting a 10 day moving average from a 3 day moving average.
The second plot is an 16 day simple moving average of the 3-10 Oscillator.
The 16 period moving average is the slow line and the 3/10 oscillator is
the fast line.
For more information on the 3-10 Oscillator see Walter Bressert's book
"The Power of Oscillator/Cycle Combinations"
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal & D_Three Ten Osc This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
TradeStation does not allow the user to make a Multi Data Chart with
a Tick Bar Chart and any other type a chart. This indicator allows the
user to plot a daily 3-10 Oscillator on a Tick Bar Chart or any intraday interval.
Walter Bressert's 3-10 Oscillator is a detrending oscillator derived
from subtracting a 10 day moving average from a 3 day moving average.
The second plot is an 16 day simple moving average of the 3-10 Oscillator.
The 16 period moving average is the slow line and the 3/10 oscillator is
the fast line.
For more information on the 3-10 Oscillator see Walter Bressert's book
"The Power of Oscillator/Cycle Combinations"
WARNING:
- For purpose educate only
- This script to change bars colors.
D_Three Ten Osc Strategy Backtest This indicator allows the user to plot a daily 3-10 Oscillator on a Tick Bar Chart or any intraday interval.
Walter Bressert's 3-10 Oscillator is a detrending oscillator derived
from subtracting a 10 day moving average from a 3 day moving average.
The second plot is an 16 day simple moving average of the 3-10 Oscillator.
The 16 period moving average is the slow line and the 3/10 oscillator is
the fast line.
For more information on the 3-10 Oscillator see Walter Bressert's book
"The Power of Oscillator/Cycle Combinations"
You can change long to short in the Input Settings
Please, use it only for learning or paper trading. Do not for real trading.
D_Three Ten Osc Strategy This indicator allows the user to plot a daily 3-10 Oscillator on a Tick Bar
Chart or any intraday interval.
Walter Bressert's 3-10 Oscillator is a detrending oscillator derived
from subtracting a 10 day moving average from a 3 day moving average.
The second plot is an 16 day simple moving average of the 3-10 Oscillator.
The 16 period moving average is the slow line and the 3/10 oscillator is
the fast line.
For more information on the 3-10 Oscillator see Walter Bressert's book
"The Power of Oscillator/Cycle Combinations"
Sladkaya BulochkaAccording to the statistics of Thomas Bulkovski collected over several years on the 1-minute chart (21 million candles), there is a statistically significant periods, where the higher the probability of reversal rates on short-term timeframe.
By reversal, on average, had in mind the movement to 5 candles.
This three periods, they remain unchanged, depending on the hour:
- the first minute of each hour (10:01, 11:01, etc.)
- the first minute after the hour (10:31, 11:31)
- 51 minutes each hour (10:51, 11:51)
------------------------------------------------------
По статистике Томаса Булковски, собранной за несколько лет на 1-минутном графике (21 миллион свечей), есть статистически значимые периоды, где более высока вероятность разворота цены на краткосрочных ТФ.
Под разворотом, в среднем, имелось в виду движение на 5 свечей.
Это три периода, они неизменны в зависимости от часа:
- первая минута каждого часа (10:01, 11:01 и т.д.)
- первая минута после получаса (10:31, 11:31)
- каждая 51 минута часа (10:51, 11:51)
HL BREAKOUTThe base of the indicator is the breakout of historic High and lows.
There are 3 basic configurations
1° The High length that measure the latest 10 bars and make the "higher high"
2° The Low length taht measure the latest 10 bars and make the "lower low"
3° The Breakout PIPs administrator that defines how much pips are needed from the latest higher high to be defined as a level breakout.
So the strategy is super easy. The indicators show you the 10...20.. or whatever you need old bars high and lows.
When a breakout of that levels occurs and the candle "close" above or below and the close are more than "X" amount of PIPs a marker show up. The marker are the signals of buy and sell
I test some configurations, and work in all timeframes but.
I suggest
10, 10, 0.0003 for timeframes from 1m to 15m
and 10, 10, 0.0005 for timeframes higher than 15m
Maybe you need to test other configurations for 4h 1 day, etc the basics are the same in all timeframes, the main difference is the amount of pips that will be considered as "breakout" the higher timeframe the higher amount you need to prevent false positives.
Last words: 0.000X are for the PIPs for currencies that have 4 or 5 decimals like euro and other, if you use in YEN change it to a configuration of 2 digits decimal. Just that.
Have "fun" !
D_Three Ten Osc on the IntradayHi
Let me introduce my D_Three Ten Osc script.
This indicator allows the
user to plot a daily 3-10 Oscillator on a Tick Bar Chart or any intraday interval.
Walter Bressert's 3-10 Oscillator is a detrending oscillator derived
from subtracting a 10 day moving average from a 3 day moving average.
The second plot is an 16 day simple moving average of the 3-10 Oscillator.
The 16 period moving average is the slow line and the 3/10 oscillator is
the fast line.
For more information on the 3-10 Oscillator see Walter Bressert's book
"The Power of Oscillator/Cycle Combinations"
D_Three Ten Osc on the DailyHi
Let me introduce my D_Three Ten Osc script.
This indicator allows the
user to plot a daily 3-10 Oscillator on a Tick Bar Chart or any intraday interval.
Walter Bressert's 3-10 Oscillator is a detrending oscillator derived
from subtracting a 10 day moving average from a 3 day moving average.
The second plot is an 16 day simple moving average of the 3-10 Oscillator.
The 16 period moving average is the slow line and the 3/10 oscillator is
the fast line.
For more information on the 3-10 Oscillator see Walter Bressert's book
"The Power of Oscillator/Cycle Combinations"
VWAP For Loop [BackQuant]VWAP For Loop
What this tool does—in one sentence
A volume-weighted trend gauge that anchors VWAP to a calendar period (day/week/month/quarter/year) and then scores the persistence of that VWAP trend with a simple for-loop “breadth” count; the result is a clean, threshold-driven oscillator plus an optional VWAP overlay and alerts.
Plain-English overview
Instead of judging raw price alone, this indicator focuses on anchored VWAP —the market’s average price paid during your chosen institutional period. It then asks a simple question across a configurable set of lookback steps: “Is the current anchored VWAP higher than it was i bars ago—or lower?” Each “yes” adds +1, each “no” adds −1. Summing those answers creates a score that reflects how consistently the volume-weighted trend has been rising or falling. Extreme positive scores imply persistent, broad strength; deeply negative scores imply persistent weakness. Crossing predefined thresholds produces objective long/short events and color-coded context.
Under the hood
• Anchoring — VWAP using hlc3 × volume resets exactly when the selected period rolls:
Day → session change, Week → new week, Month → new month, Quarter/Year → calendar quarter/year.
• For-loop scoring — For lag steps i = , compare today’s VWAP to VWAP .
– If VWAP > VWAP , add +1.
– Else, add −1.
The final score ∈ , where N = (end − start + 1). With defaults (1→45), N = 45.
• Signal logic (stateful)
– Long when score > upper (e.g., > 40 with N = 45 → VWAP higher than ~89% of checked lags).
– Short on crossunder of lower (e.g., dropping below −10).
– A compact state variable ( out ) holds the current regime: +1 (long), −1 (short), otherwise unchanged. This “stickiness” avoids constant flipping between bars without sufficient evidence.
Why VWAP + a breadth score?
• VWAP aggregates both price and volume—where participants actually traded.
• The breadth-style count rewards consistency of the anchored trend, not one-off spikes.
• Thresholds give you binary structure when you need it (alerts, automation), without complex math.
What you’ll see on the chart
• Sub-pane oscillator — The for-loop score line, colored by regime (long/short/neutral).
• Main-pane VWAP (optional) — Even though the indicator runs off-chart, the anchored VWAP can be overlaid on price (toggle visibility and whether it inherits trend colors).
• Threshold guides — Horizontal lines for the long/short bands (toggle).
• Cosmetics — Optional candle painting and background shading by regime; adjustable line width and colors.
Input map (quick reference)
• VWAP Anchor Period — Day, Week, Month, Quarter, Year.
• Calculation Start/End — The for-loop lag window . With 1→45, you evaluate 45 comparisons.
• Long/Short Thresholds — Default upper=40, lower=−10 (asymmetric by design; see below).
• UI/Style — Show thresholds, paint candles, background color, line width, VWAP visibility and coloring, custom long/short colors.
Interpreting the score
• Near +N — Current anchored VWAP is above most historical VWAP checkpoints in the window → entrenched strength.
• Near −N — Current anchored VWAP is below most checkpoints → entrenched weakness.
• Between — Mixed, choppy, or transitioning regimes; use thresholds to avoid reacting to noise.
Why the asymmetric default thresholds?
• Long = score > upper (40) — Demands unusually broad upside persistence before declaring “long regime.”
• Short = crossunder lower (−10) — Triggers only on downward momentum events (a fresh breach), not merely being below −10. This combination tends to:
– Capture sustained uptrends only when they’re very strong.
– Flag downside turns as they occur, rather than waiting for an extreme negative breadth.
Tuning guide
Choose an anchor that matches your horizon
– Intraday scalps : Day anchor on intraday charts.
– Swing/position : Month or Quarter anchor on 1h/4h/D charts to capture institutional cycles.
Pick the for-loop window
– Larger N (bigger end) = stronger evidence requirement, smoother oscillator.
– Smaller N = faster, more reactive score.
Set achievable thresholds
– Ensure upper ≤ N and lower ≥ −N ; if N=30, an upper of 40 can never trigger.
– Symmetric setups (e.g., +20/−20) are fine if you want balanced behavior.
Match visuals to intent
– Enabling VWAP coloring lets you see regime directly on price.
– Background shading is useful for discretionary reading; turn it off for cleaner automation displays.
Playbook examples
• Trend confirmation with disciplined entries — On Month anchor, N=45, upper=38–42: when the long regime engages, use pullbacks toward anchored VWAP on the main pane for entries, with stops just beyond VWAP or a recent swing.
• Downside transition detection — Keep lower around −8…−12 and watch for crossunders; combine with price losing anchored VWAP to validate risk-off.
• Intraday bias filter — Day anchor on a 5–15m chart, N=20–30, upper ~ 16–20, lower ~ −6…−10. Only take longs while score is positive and above a midline you define (e.g., 0), and shorts only after a genuine crossunder.
Behavior around resets (important)
Anchored VWAP is hard-reset each period. Immediately after a reset, the series can be young and comparisons to pre-reset values may span two periods. If you prefer within-period evaluation only, choose end small enough not to bridge typical period length on your timeframe, or accept that the breadth test intentionally spans regimes.
Alerts included
• VWAP FL Long — Fires when the long condition is true (score > upper and not in short).
• VWAP FL Short — Fires on crossunder of the lower threshold (event-driven).
Messages include {{ticker}} and {{interval}} placeholders for routing.
Strengths
• Simple, transparent math — Easy to reason about and validate.
• Volume-aware by construction — Decisions reference VWAP, not just price.
• Robust to single-bar noise — Needs many lags to agree before flipping state (by design, via thresholds and the stateful output).
Limitations & cautions
• Threshold feasibility — If N < upper or |lower| > N, signals will never trigger; always cross-check N.
• Path dependence — The state variable persists until a new event; if you want frequent re-evaluation, lower thresholds or reduce N.
• Regime changes — Calendar resets can produce early ambiguity; expect a few bars for the breadth to mature.
• VWAP sensitivity to volume spikes — Large prints can tilt VWAP abruptly; that behavior is intentional in VWAP-based logic.
Suggested starting profiles
• Intraday trend bias : Anchor=Day, N=25 (1→25), upper=18–20, lower=−8, paint candles ON.
• Swing bias : Anchor=Month, N=45 (1→45), upper=38–42, lower=−10, VWAP coloring ON, background OFF.
• Balanced reactivity : Anchor=Week, N=30 (1→30), upper=20–22, lower=−10…−12, symmetric if desired.
Implementation notes
• The indicator runs in a separate pane (oscillator), but VWAP itself is drawn on price using forced overlay so you can see interactions (touches, reclaim/loss).
• HLC3 is used for VWAP price; that’s a common choice to dampen wick noise while still reflecting intrabar range.
• For-loop cap is kept modest (≤50) for performance and clarity.
How to use this responsibly
Treat the oscillator as a bias and persistence meter . Combine it with your entry framework (structure breaks, liquidity zones, higher-timeframe context) and risk controls. The design emphasizes clarity over complexity—its edge is in how strictly it demands agreement before declaring a regime, not in predicting specific turns.
Summary
VWAP For Loop distills the question “How broadly is the anchored, volume-weighted trend advancing or retreating?” into a single, thresholded score you can read at a glance, alert on, and color through your chart. With careful anchoring and thresholds sized to your window length, it becomes a pragmatic bias filter for both systematic and discretionary workflows.
Full Session ATR Range (Live) - with Position ToggleBelow is a publication-ready text for the "Full Session ATR Range (Live) - with Position Toggle" indicator, written in a professional yet accessible style suitable for a trading community (e.g., TradingView or a blog). The text highlights the indicator's features, usage, and benefits, while avoiding overly technical jargon for a broad audience.
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### Introducing the Full Session ATR Range (Live) Indicator with Position Toggle
Enhance your trading strategy with the **Full Session ATR Range (Live) Indicator**, a powerful tool designed to provide real-time insights into market volatility and session dynamics. This customizable indicator, now available with a position toggle feature, compares the current session's range to a 10-day Average True Range (ATR), helping traders gauge market activity and anticipate potential movements.
#### Key Features
- **Live Range Tracking**: Displays the current session's range (high minus low) alongside a 10-day ATR, updated in real-time during market hours.
- **Session Mode Flexibility**: Includes an auto-toggle option to switch between Electronic Trading Hours (ETH) and Regular Trading Hours (RTH), adapting to your preferred trading session. Manually select ETH or RTH, or let the indicator auto-detect based on market hours.
- **Comprehensive Metrics**: Offers a detailed breakdown including:
- Range/Avg %: Percentage of the current range relative to the 10-day ATR.
- Points Left: Remaining points to reach the average range.
- 100% Range Up/Dn: Potential upper and lower targets based on the ATR difference.
- **Position Customization**: Adjust the table's location on your chart with options like top-left, top-right, middle-center, or bottom-right for optimal visibility.
- **Visual Appeal**: Features a customizable background and text color to match your chart theme.
#### How It Works
The indicator calculates the 10-day ATR using daily data and tracks the current session's range, resetting at the start of each day or session change. During market hours (e.g., 6 AM - 8 PM CDT, adjustable), it updates live, providing actionable insights. When the market is closed, it displays historical ATR while marking live metrics as "n/a" to avoid confusion. The ETH/RTH toggle ensures the range reflects either the full extended session or the core trading hours, tailored to your strategy.
#### Why Use It?
Whether you're a day trader monitoring intraday volatility or a swing trader assessing longer-term trends, this indicator helps you:
- Identify overextended or underactive sessions compared to historical norms.
- Plan entries and exits with targets based on the 100% Range Up/Dn levels.
- Stay informed with a clean, adjustable display that fits your workflow.
#### Installation & Customization
1. Add the indicator to your TradingView chart.
2. Adjust the ATR length (default: 10 days) and table position via the input settings.
3. Choose your session mode (Auto, ETH, or RTH) and customize colors to suit your style.
4. Test during market hours for live updates—note that static values may appear outside trading sessions.
#### Feedback & Support
This indicator is designed for flexibility and ease of use. Share your feedback or request enhancements by commenting below or contacting the developer. Happy trading!
Mig Trade Model - Kill Zones
Key features:
Liquidity Hunt Detection: Spots aggressive moves that "hunt" stops beyond recent swing highs/lows.
Consolidation Filter: Requires 1-3 small-range candles after a hunt before confirming with a strong candle.
Bias Application: Uses daily open/close to auto-detect bias or allows manual override.
Kill Zone Restriction: Limits signals to London (default: 7-10 AM UTC) and NY (default: 12-3 PM UTC) sessions for better relevance in active markets.
This strategy is inspired by smart money concepts (SMC) and ICT (Inner Circle Trader) methodologies, aiming to capture venom-like "stings" in price action where liquidity is grabbed before reversals.
How It Works
ATR Calculation: Uses a user-defined ATR length (default: 14) to measure volatility, which scales candle body and range thresholds.
Bias Determination:
Auto: Compares daily close to open (bullish if close > open).
Manual: User selects "Bullish" or "Bearish."
Strong Candles:
Bullish: Green candle with body > 2x ATR (configurable).
Bearish: Red candle with body > 2x ATR.
Small Range Candles:
Candles where high-low < 0.5x ATR (configurable).
Liquidity Hunt:
Bullish Hunt: Strong bearish candle making a new low below the past swing low (default: 10 bars).
Bearish Hunt: Strong bullish candle making a new high above the past swing high.
Signal Generation:
After a hunt, counts 1-3 small-range candles.
Confirms with a strong candle in the opposite direction (e.g., strong bullish after bearish hunt).
Resets if >3 small candles or an opposing strong candle appears.
Kill Zone Filter:
Checks if the current bar's time (in UTC) falls within London or NY Kill Zones.
Only allows final "Buy" (bullish entry) or "Sell" (bearish entry) if bias matches and in Kill Zone.
Plots:
Yellow circle (below): Bullish liquidity hunt.
Orange circle (above): Bearish liquidity hunt.
Blue diamond (below): Raw bullish signal.
Purple diamond (above): Raw bearish signal.
Green triangle up ("Buy"): Filtered bullish entry.
Red triangle down ("Sell"): Filtered bearish entry.
Inputs
Bias: "Auto" (default), "Bullish", or "Bearish" – Controls signal direction based on daily trend.
ATR Length: 14 (default) – Period for ATR calculation.
Swing Length for Liquidity Hunt: 10 (default) – Bars to look back for swing highs/lows.
Strong Candle Body Multiplier (x ATR): 2.0 (default) – Threshold for strong candle bodies.
Small Range Multiplier (x ATR): 0.5 (default) – Threshold for small-range candles.
London Kill Zone Start/End Hour (UTC): 7/10 (default) – Customize London session hours.
NY Kill Zone Start/End Hour (UTC): 12/15 (default) – Customize New York session hours.
Usage Tips
Timeframe: Best on lower timeframes (e.g., 5-15 min) for intraday trading, especially forex pairs like EURUSD or GBPUSD.
Timezone Adjustment: Inputs are in UTC. If your chart is in a different timezone (e.g., EST = UTC-5), adjust hours accordingly (e.g., London: 2-5 AM EST → 7-10 UTC).
Risk Management: Use with stop-loss (e.g., beyond the hunt low/high) and take-profit based on ATR multiples. Not financial advice—backtest thoroughly.
Customization: Tweak multipliers for different assets; higher for volatile cryptos, lower for stocks.
Limitations: Relies on historical data; may generate false signals in ranging markets. Combine with other indicators like volume or support/resistance.
This indicator is for educational purposes. Always use discretion and proper risk management in live trading. If you find it useful, feel free to share feedback or suggestions!
Orthogonal Projections to Latent Structures (O-PLS)Version 0.1
Orthogonal Projections to Latent Structures (O-PLS) Indicator for TradingView
This indicator, named "Orthogonal Projections to Latent Structures (O-PLS)", is designed to help traders understand the relevance or predictive power of various market variables on the future close price of the asset it's applied to. Unlike standard correlation coefficients that show a simple linear relationship, O-PLS aims to separate variables into "predictive" (relevant to Y) and "orthogonal" (irrelevant noise) components. This Pine Script indicator provides a simplified proxy of the relevance score derived from O-PLS principles.
Purpose of the Indicator
The primary purpose of this indicator is to identify which technical factors (such as price, volume, and other indicators) have the strongest relationship with the future price movement of the current trading instrument. By providing a "relevance score" for each input variable, it helps traders focus on the most influential data points, potentially leading to more informed trading decisions.
Inputs
The indicator offers the following user-definable inputs:
* **Lookback Period:** This integer input (default: 100, min: 10, max: 500) determines the number of past bars used to calculate the relevance scores for each variable. A longer lookback period considers more historical data, which can lead to smoother, less reactive scores but might miss recent shifts in variable importance.
* **External Asset Symbol:** This symbol input (default: `BINANCE:BTCUSDT`) allows you to specify an external asset (e.g., `BINANCE:ETHUSDT`, `NASDAQ:TSLA`) whose close price will be included in the analysis as an additional variable. This is useful for cross-market analysis to see how other assets influence the current chart.
* **Plot Visibility Checkboxes (e.g., "Plot: Open Price Relevance", "Plot: Volume Relevance", etc.):** These boolean checkboxes allow you to toggle the visibility of individual relevance score plots on the chart, helping to declutter the display and focus on specific variables.
Outputs
The indicator provides two main types of output:
Relevance Score Plots: These are lines plotted in a separate pane below the main price chart. Each line corresponds to a specific market variable (Open Price, Close Price, High Price, Low Price, Volume, various RSIs, SMAs, MFI, and the External Asset Close). The value of each line represents the calculated "relevance score" for that variable, typically scaled between 0 and 10. A higher score indicates a stronger predictive relationship with the future close price.
Sorted Relevance Table : A table displayed in the top-right corner of the chart provides a clear, sorted list of all analyzed variables and their corresponding relevance scores. The table is sorted in descending order of relevance, making it easy to identify the most influential factors at a glance. Each variable name in the table is colored according to its plot color, and the external asset's name is dynamically displayed without the "BINANCE:" prefix.
How to Use the Indicator
1. **Add to Chart:** Apply the "Orthogonal Projections to Latent Structures (O-PLS)" indicator to your desired trading chart (e.g., ETH/USDT).
2. **Adjust Inputs:**
* **Lookback Period:** Experiment with different lookback periods to see how the relevance scores change. A shorter period might highlight recent correlations, while a longer one might show more fundamental relationships.
* **External Asset Symbol:** If you trade BTC/USDT, you might add ETH/USDT or SPX as an external asset to see its influence.
3. **Analyze Relevance Scores:**
* **Plots:** Observe the individual relevance score plots over time. Are certain variables consistently high? Do scores change before significant price moves?
* **Table:** Refer to the sorted table on the latest confirmed bar to quickly identify the top-ranked variables.
4. **Incorporate into Strategy:** Use the insights from the relevance scores to:
* Prioritize certain indicators or price actions in your trading strategy. For example, if "Volume" has a high relevance score, it suggests volume confirmation is critical for future price moves.
* Understand the influence of inter-market relationships (via the External Asset Close).
How the Indicator Works
The indicator works by performing the following steps on each bar:
1. **Data Fetching:** It gathers historical data for various price components (open, high, low, close), volume, and calculated technical indicators (SMA, RSI, MFI) for the specified `lookback` period. It also fetches the close price of an `External Asset Symbol` .
2. **Standardization (Z-scoring):** All collected raw data series are standardized by converting them into Z-scores. This involves subtracting the mean of each series and dividing by its standard deviation . Standardization is crucial because it brings all variables to a common scale, preventing variables with larger absolute values from disproportionately influencing the correlation calculations.
3. **Correlation Calculation (Proxy for O-PLS Relevance):** The indicator then calculates a simplified form of correlation between each standardized input variable and the standardized future close price (Y variable) . This correlation is a proxy for the relevance that O-PLS would identify. A high absolute correlation indicates a strong linear relationship.
4. **Relevance Scaling:** The calculated correlation values are then scaled to a range of 0 to 10 to provide an easily interpretable "relevance score" .
5. **Output Display:** The relevance scores are presented both as time-series plots (allowing observation of changes over time) and in a real-time sorted table (for quick identification of top factors on the current bar) .
How it Differs from Full O-PLS
This indicator provides a *simplified proxy* of O-PLS principles rather than a full, mathematically rigorous O-PLS model. Here's why and how it differs:
* **Dimensionality Reduction:** A full O-PLS model would involve complex matrix factorization techniques to decompose the independent variables (X) into components that are predictive of Y and components that are orthogonal (unrelated) to Y but still describe X's variance. Pine Script's array capabilities and computational limits make direct implementation of these matrix operations challenging.
* **Orthogonal Components:** A true O-PLS model explicitly identifies and removes orthogonal components (noise) from the X data that are unrelated to Y. This indicator, in its simplified form, primarily focuses on the direct correlation (relevance) between each X variable and Y after standardization, without explicitly modeling and separating these orthogonal variations.
* **Predictive Model:** A full O-PLS model is ultimately a predictive model that can be used for regression (predicting Y). This indicator, however, focuses solely on **identifying the relevance/correlation of inputs to Y**, rather than building a predictive model for Y itself. It's more of an analytical tool for feature importance than a direct prediction engine.
* **Computational Intensity:** Full O-PLS involves Singular Value Decomposition (SVD) or Partial Least Squares (PLS) algorithms, which are computationally intensive. The indicator uses simpler statistical measures (mean, standard deviation, and direct correlation calculation over a lookback window) that are feasible within Pine Script's execution limits.
In essence, this Pine Script indicator serves as a practical tool for gaining insights into variable relevance, inspired by the spirit of O-PLS, but adapted for the constraints and common use cases of a TradingView environment.
