PowerOfStocks_5EMAThis indicator is based of Subhashish Pani's (power of stocks) 5 EMA Strategy.
It plots 5 EMA and Buy/Sell signals with Target & Stoploss levels.
What is Subhashish Pani's (power of stocks) 5 EMA Strategy :-
His strategy is very simple to understand. for intraday use 5 minutes timeframe for selling. You can sell futures, sell call or buy Puts in selling strategy.
What this strategy tries to do is , it tries to catch the tops, so when you sell at top & it turns out to be a reversal point then you can get good profit.
this will hit stop losses often, but stop losses are small and minimum target should be 1:3. but if you stay with the trend you can get big profits.
According to Subhashish Pani this strategy has 60% success rate.
Strategy for Selling (Short future/Call/stock or buy Put)
When ever a Candle closes completely above 5 ema (no part of candle should be touching the 5ema), then that candle should be considered as Alert Candle.
If the next candle is also completely above 5 ema and it has not broken the low of previous alert candle, Then the previous Alert Candle should be ignored and the new candle should be considered as new Alert Candle.
so if this goes on then continue shifting the Alert Candle, but whenever the next candle breaks the low of the Alert Candle we should take the Short trade (Short future/Call/stock or buy Put).
Stoploss will be above high of the Alert Candle and minimum target will be 1:3.
Strategy for Buying (Buy future/Call/stock or sell Put)
When ever a Candle closes completely below 5 ema (no part of candle should be touching the 5ema), then that candle should be considered as Alert Candle.
If the next candle is also completely below 5 ema and it has not broken the high of previous alert candle, Then the previous Alert Candle should be ignored and the new candle should be considered as new Alert Candle.
so if this goes on then continue shifting the Alert Candle, but whenever the next candle breaks the high of the Alert Candle we should take the Long trade (Buy future/Call/stock or sell Put).
Stoploss will be below low of the Alert Candle and minimum target will be 1:3.
Buy/Sell with extra conditions :
it just adds 1 more condition to buying/selling
1. checks if closing of current candle is lower than alert candles closing for Selling & checks if closing of current candle is higher than alert candles closing for Buyling.
This can sometimes save you from false moves but by using this, you can also miss out on big moves as you'll enter trade after candle closing instead of entering at break of high/low.
Note :- According to Subhashish Pani Timeframe for intraday buying should be 15 minutes Timeframe.
If you haven't understood the strategy by reading above description, then search for "Subhashish Pani's (power of stocks) 5 EMA Strategy" on youtube to get a deeper understanding.
Note:- This is not only for Intraday trading , you can use this strategy for Positional/Swing trading as well. If you use this on Monthly Timeframe then it can be very good for Long Term Investing as well.
Rules will be same for all types of trades & Timeframes.
Cerca negli script per "profit"
Position Tool█ OVERVIEW
This script is an interactive measurement tool that can be used to evaluate or keep track of trades. Like the long and short position drawing tools, it calculates a risk reward ratio and a risk-adjusted position size from the entry, stop and take profit levels, but it also does much more:
• It can be used to configure long or short trades.
• All monetary values can be expressed in any number of currencies.
• The value of tick/pip movement (which varies with the position's size) is displayed in the currency you have selected.
• The CAGR ( Compound Annual Growth Rate ) for the trade can be displayed.
• It does live tracking of the position.
• You can configure alerts on entries and exits.
█ HOW TO USE IT
Load the indicator on an active chart (see here if you don't know how).
When you first load this script on a chart, you will enter an interactive selection mode where the script asks you to pick three points in price and time on your chart by clicking on the chart. Directions will appear in a blue box at the bottom of the screen with each click of the mouse. The first selection is the entry point for the trade you are considering, which takes into account both the time and level you choose, the next are the take profit and stop levels. Once you have selected all three points, the script will draw trade zones and labels containing the trade metrics. The script determines if the trade is a long or short from the position of the take profit and stop loss levels in relation to the entry price. If the take profit level is above the entry price, the stop must be below and vice versa, otherwise an error occurs.
You can change levels by dragging the handles that appear when you select the indicator, or by entering new values in the script's settings. The only way to re-enter interactive mode is to re-add the indicator to your chart.
Once you place the position tool on a chart, it will appear at the same levels on all symbols you use. If your scale is not set to "Scale price chart only", the position tool's levels will be taken into account when scaling the chart, which can cause the symbol's bars to be compressed. If your scale is set to "Scale price chart only", the position tool will still be there, but it will not impact the scale of the chart's bars, so you won't see it if it sits outside the symbol's price scale.
If you select the position tool on your chart and delete it, this will also delete the indicator from the chart. You will need to re-add it if you want to draw another position tool. You can add multiple instances of the indicator if you need a position tool on more than one of your charts.
█ FEATURES
Display
The position tool displays the following information for entries:
• The entry's price level with an '@' sign before it.
• Open or Closed P&L : For an open trade, the "Open P&L" displays the difference in money value between the entry level and the chart's current price.
For a closed trade, the "Closed P&L" displays the realized P&L on the trade.
• Quantity : The trade size, which takes into account the risk tolerance you set in the script's settings.
• RR : The reward to risk ratio expresses the relationship of the distance between the entry and the take profit level vs the entry and the stop level.
Example: A $100 stop with a $100 target will have a ratio of 1:1, whereas a $200 target with the same stop will have a 2:1 ratio.
• Per tick/pip : Represents the money value of a tick or pip movement.
• CAGR : The Compound Annual Growth Rate will be displayed on the main order label on trades that exceed one day in duration.
This value is calculated the same way as in our CAGR Custom Range indicator.
If the trade duration is less than one day, the metric will not be present in the display.
The stop and take profit levels display:
• Their price level with an '@' sign before it.
• Their distance from the entry in money value, percentage and ticks/pips.
• The projected end money value of the position if the level is reached. These values are calculated based on the trade size and the currency.
Currency adjustments
This indicator modifies the trade label's colors and values based on the final Profit and Loss (P&L), which considers the dynamic exchange rate between base and conversion currencies in its calculations when the conversion currency is a specified value other than the default. Depending on the cross rate between the base and account currencies, this process can yield a negative P&L on an otherwise successful simulated trade.
For instance, if your account is in currency XYZ, you might buy 10 Apple shares at $150 each, with the XYZ to USD exchange rate being 2:1. This purchase would cost you 3000 units of XYZ. Suppose that later on, the shares appreciate to $170 each, and you decide to sell. One might expect this trade to result in profit. However, if the exchange rate has now equalized to 1:1, the return on selling the shares, calculated in XYZ, would only be 1700 units, resulting in a loss of 1300 units XYZ.
The indicator will mark the P&L and the target labels in red in such cases, regardless of whether the market price reached the profit target, as the trade produced a net loss due to reduced funds after currency conversion. Conversely, an otherwise unsuccessful position can result in a net profit in the account currency due to conversion rate fluctuations. The final losses or gains appear in the label metrics, and the corresponding color coding reflects the trade's success or failure.
Settings
The settings in the "Trade sizing" section are used to calculate the position size and the monetary value of trades. Two types of risk can be chosen from the menu; a percentage based risk calculation, or a fixed money value. The risk is used to calculate the quantity of units to purchase to achieve that level of risk exposure. Example: An account size of $1000 and 10% risk will have a projected end amount of $900 if the stop loss is hit. The quantity is a product of this relationship; a projected number of units to allow for the equivalent of $100 of risk exposure over the change in price from the entry to the stop value.
The "Trade levels" allow you to manually set the entry, take profit and stop levels of an existing position tool on your chart.
You can control the appearance of the tool and the values it displays in the settings following these first two sections.
Alerts
Three alerts that will trigger when you configure an alert on this indicator. The first will send an alert when the entry price is breached by price action if that price has not already been breached in the previous price history. This is dependant on the entry location you select when placing the indicator on the chart. The other two alerts will trigger when either the stop loss or the take profit level is breached to signal that a trade exit has occurred.
█ NOTES FOR Pine Script™ CODERS
• Interactive inputs are implemented for input.time() and input.price() . These specialized input functions allow users to interact with a script.
You can create one interactive input for both time and price values by using the same `inline` argument in a pair of input.time() and input.price() function calls.
• We use the `cagr()` function from our ta library.
• The script uses the runtime.error() function to throw an error if the stop and limit prices are not placed on opposing sides of the entry price.
• We use the `currency` parameter in a request.security() call to convert currencies.
Look first. Then leap.
[D] Dudu 95 Strategy Template ver.1.1.Hello Guys! Nice to meet you all!
This is my Second script after changing My Profile Name!
I updated my strategy template before - I added some filter conditions (EMA, ADX, DMI).
If there's something to update, I will update this script!
Thank you!
-----
I made this based on the open source strategies by jason5480, kevinmck100, myncrypto.
Thank you All!
### Filter
1. Can Choose whether to use filter.
2. Filters Based on ATR, EMA, ADX, and DMI are ready to use.
### StopLoss
1. Can Choose Stop Loss Type: Percent, ATR, Previous Low / High.
2. Can Chosse inputs of each Stop Loss Type.
### Take Profit
1. Can set Risk Reward Ratio for Take Profit.
- To simplify backtest, I erased all other options except RR Ratio.
- You can add Take Profit Logic by adding options in the code.
2. Can set Take Profit Quantity.
### Risk Manangement
1. Can choose whether to use Risk Manangement Logic.
- This controls the Quantity of the Entry.
- e.g. If you want to take 3% risk per trade and stop loss price is 6% below the long entry price,
then 50% of your equity will be used for trade.
2. Can choose How much risk you would take per trade.
### Plot
1. Added Labels to check the data of entry / exit positions.
2. Changed and Added color different from the original one. (green: #02732A, red: #D92332, yellow: #F2E313)
[DuDu95] SSL 4C MACD Laugerre RSI StrategyHello Guys! Nice to meet you all!
Before I start, my nickname has changed to 'DuDu95'!!
This is the Strategy introduced by youtube channel.
I made this based on the open source indicator by kevinmck100, vkno422, KivancOzbilgic. Thank you All!
### Entry Logic
1. Long Entry Logic
- close > SSL Hybrid baseline upper k (keltner channel)
- macd signal > 0 and current MACD value > previous MACD value
- Laguerre RSI < overbought Line.
2. short Entry Logic
- close < SSL Hybrid baseline lower k (keltner channel)
- macd signal < 0 and current MACD value < previous MACD value
- Laguerre RSI > overbought Line.
### Exit Logic
1. Long Exit Logic
- close < SSL Hybrid baseline lower k (keltner channel)
- macd signal < 0
2. short Entry Logic
- close > SSL Hybrid baseline upper k (keltner channel)
- macd signal > 0
### StopLoss
1. Can Choose Stop Loss Type: Percent, ATR, Previous Low / High.
2. Can Chosse inputs of each Stop Loss Type.
### Take Profit
1. Can set Risk Reward Ratio for Take Profit.
- To simplify backtest, I erased all other options except RR Ratio.
- You can add Take Profit Logic by adding options in the code.
2. Can set Take Profit Quantity.
### Risk Manangement
1. Can choose whether to use Risk Manangement Logic.
- This controls the Quantity of the Entry.
- e.g. If you want to take 3% risk per trade and stop loss price is 6% below the long entry price,
then 50% of your equity will be used for trade.
2. Can choose How much risk you would take per trade.
### Plot
1. Added Labels to check the data of entry / exit positions.
2. Changed and Added color different from the original one. (green: #02732A, red: #D92332, yellow: #F2E313)
[fpemehd] Strategy TemplateHello Guys! Nice to meet you all!
This is my fourth script!
This is the Strategy Template for traders who wants to make their own strategy.
I made this based on the open source strategies by jason5480, kevinmck100, myncrypto. Thank you All!
### StopLoss
1. Can Choose Stop Loss Type: Percent, ATR, Previous Low / High.
2. Can Chosse inputs of each Stop Loss Type.
### Take Profit
1. Can set Risk Reward Ratio for Take Profit.
- To simplify backtest, I erased all other options except RR Ratio.
- You can add Take Profit Logic by adding options in the code.
2. Can set Take Profit Quantity.
### Risk Manangement
1. Can choose whether to use Risk Manangement Logic.
- This controls the Quantity of the Entry.
- e.g. If you want to take 3% risk per trade and stop loss price is 6% below the long entry price,
then 50% of your equity will be used for trade.
2. Can choose How much risk you would take per trade.
### Plot
1. Added Labels to check the data of entry / exit positions.
2. Changed and Added color different from the original one. (green: #02732A, red: #D92332, yellow: #F2E313)
Strategy PnL LibraryLibrary "Strategy_PnL_Library"
TODO: This is a library that helps you learn current pnl of open position and use it to create your own dynamic take profit or stop loss rules based on current level of your profit. It should only be used with strategies.
inTrade()
inTrade: Checks if a position is currently open.
Returns: bool: true for yes, false for no.
notInTrade()
inTrade: Checks if a position is currently open. Interchangeable with inTrade but just here for simple semantics.
Returns: bool: true for yes, false for no.
pnl()
pnl: Calculates current profit or loss of position after the commission. If the strategy is not in trade it will always return na.
Returns: float: Current Profit or Loss of position, positive values for profit, negative values for loss.
entryBars()
entryBars: Checks how many bars it's been since the entry of the position.
Returns: int: Returns a int of strategy entry bars back. Minimum value is always corrected to 1 to avoid lookback errors.
pnlvelocity()
pnlvelocity: Calculates the velocity of pnl by following the change in open profit compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl velocity.
pnlacc()
pnlacc: Calculates the acceleration of pnl by following the change in profit velocity compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl acceleration.
pnljerk()
pnljerk: Calculates the jerk of pnl by following the change in profit acceleration compared to previous bar. If the strategy is not in trade it will always return na.
Returns: float: Returns a float value of pnl jerk.
pnlhigh()
pnlhigh: Calculates the highest value the pnl has reached since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float highest value the pnl has reached.
pnllow()
pnllow: Calculates the lowest value the pnl has reached since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float lowest value the pnl has reached.
pnldev()
pnldev: Calculates the deviance of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float deviance value of the pnl.
pnlvar()
pnlvar: Calculates the variance value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float variance value of the pnl.
pnlstdev()
pnlstdev: Calculates the stdev value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float stdev value of the pnl.
pnlmedian()
pnlmedian: Calculates the median value of the pnl since the start of the current position. If the strategy is not in trade it will always return na.
Returns: float: Returns a float median value of the pnl.
Trend Breakout high/low #1What is the Trend Breakout high/low #1?
This script uses the high/low of each fixed time period as a conditional judgment, and when the high/low is broken as a buy/sell signal, trying to capture a trend.
How to use this script?
Start date and Stop date: You can choose the date of the test.
Trading cycle: Selected time period is used as the basis for determining the high/low and is limited to one trade only.
Stop range: This value will calculate the stop loss range. Set 50-100 that is better
Fixed mode: Fixed of lots per transaction.
---Additional Functions---
Reversal mode: Reversing the buy and sell signals, may be useful in certain situations.
Wighted mode: Increased profitability under certain conditions
When win & When lose:Judgment when there is an ongoing loss/profit as a condition, may be useful in certain situations.
Use closing price: Use the closing price breakout high/low as a conditional judgment, but this function sometimes fails.
Notes:
Trading cycle and your chart time period can't be set too close,that will result repainting.
Stop range can't be set too small,that will result repainting either.
SuperTrend Entry(My goal creating this indicator) : Provide a way to enter the market systematically, automatically create Stop Loss Levels and Take Profit Levels, and provide the position size of each entry based on a fix Percentage of the traders account.
The Underlying Concept :
What is Momentum?
The Momentum shown is derived from a Mathematical Formula, SUPERTREND. When price closes above Supertrend Its bullish Momentum when its below Supertrend its Bearish Momentum. This indicator scans for candle closes on the current chart and when there is a shift in momentum (price closes below or above SUPERTREND) it notifies the trader with a Bar Color change.
Technical Inputs
- If you want to optimize the rate of signals to better fit your trading plan you would change the Factor input and ATR Length input. Increase factor and ATR Length to decrease the frequency of signals and decrease the Factor and ATR Length to increase the frequency of signals.
Quick TIP! : You can Sync all VFX SuperTrend Indicators together! All VFX SuperTrend indicators display unique information but its all derived from that same Momentum Formula. Keep the Factor input and ATR Length the same on other VFX SuperTrend indicators to have them operating on the same data.
Display Inputs
- The indicator has a candle overlay option you can toggle ON or OFF. If toggled ON the candles color will represent the momentum of your current chart ( bullish or bearish Momentum)
your able to change the colors that represent bullish or bearish to your preference
- You can toggle on which shows the exact candle momentum switched sides
your able to change the colors that represent a bullish switch or bearish switch to your preference
- The trader can specify which point you would like your stop loss to reference. (Low and High) Which uses the Low of the Momentum signal as the reference for your Stop Loss during buy signals and the High as the reference during sell signals. Or (Lowest Close and Highest Close) which uses the Lowest Close of the Momentum signal as the reference for your Stop Loss during buys and the Highest Close as the reference during sells.
- The colors that represent your Stop Loses and Take Profits can also be changed
Risk Management Inputs
- Your Risk MANAGMENT section is used to set up how your Stop Loss and Take Profit are calculated
- You have the option to take in account Volatility when calculating your Stop Loss. A adjusted ATR formula is used to achieve this. Increase Stop Loss Multiplier from 0 to widen stops.
- Increase Take Profit Multiplier from 0 to access visual Take Profit Levels based on your Stop Loss. This will be important for traders that Prefer trading using risk rewards. For Example: If the the Take Profit Multiplier is 3 a Take Profit level 3 times the size or your stop loss from your entry will be shown and a price number corresponding to that Take Profit Level becomes available.
- Enter your current Account size, Bet Percentage and Fixed Spread to get your Position Size for each trade
-Toggle on the Current Trade Chart and easily get the size of your Position and the exact price of your Take Profit and Stop Loss.
You can increase the Size of the Current Trade Chart= Tiny, Small, Normal, Large, Huge and change the Position of the Current
trade Chart to your preference, (Top- Right, Center, Left) (Middle- Right, Center, Left) (Bottom- Right, Center, Left).
How it can be used ?
- Enter Trades and always know where your stop is going to be
- Eliminate the need to manual calculate Position Size
- Get a consistent view of the current charts momentum
- Systematical enter trades
- Reduce information overload
SSL + Wave Trend StrategyStrategy incorporates the following features:
Risk management:
Configurable X% loss per stop loss
Configurable R:R ratio
Trade entry:
Based on strategy conditions below
Trade exit:
Based on strategy conditions below
Backtesting:
Configurable backtesting range by date
Trade drawings:
Each entry condition indicator can be turned on and off
TP/SL boxes drawn for all trades. Can be turned on and off
Trade exit information labels. Can be turned on and off
NOTE: Trade drawings will only be applicable when using overlay strategies
Alerting:
Alerts on LONG and SHORT trade entries
Debugging:
Includes section with useful debugging techniques
Strategy conditions
Trade entry:
LONG
C1: SSL Hybrid baseline is BLUE
C2: SSL Channel crosses up (green above red)
C3: Wave Trend crosses up (represented by pink candle body)
C4: Entry candle height is not greater than configured threshold
C5: Entry candle is inside Keltner Channel (wicks or body depending on configuration)
C6: Take Profit target does not touch EMA (represents resistance)
SHORT
C1: SSL Hybrid baseline is RED
C2: SSL Channel crosses down (red above green)
C3: Wave Trend crosses down (represented by orange candle body)
C4: Entry candle height is not greater than configured threshold
C5: Entry candle is inside Keltner Channel (wicks or body depending on configuration)
C6: Take Profit target does not touch EMA (represents support)
Trade exit:
Stop Loss: Size configurable with NNFX ATR multiplier
Take Profit: Calculated from Stop Loss using R:R ratio
Credits
Strategy is based on the YouTube video "This Unique Strategy Made 47% Profit in 2.5 Months " by TradeSmart.
It combines the following indicators to determine trade entry/exit conditions:
Wave Trend: Indicator: WaveTrend Oscillator by @LazyBear
SSL Channel: SSL channel by @ErwinBeckers
SSL Hybrid: SSL Hybrid by @Mihkel00
Keltner Channels: Keltner Channels Bands by @ceyhun
Candle Height: Candle Height in Percentage - Columns by @FreeReveller
NNFX ATR: NNFX ATR by @sueun123
Risk Management Strategy TemplateThis strategy is intended to be used as a base template for building new strategies.
It incorporates the following features:
Risk management:
Configurable X% loss per stop loss
Configurable R:R ratio
Trade entry:
Calculated position size based on risk tolerance
Trade exit:
Stop Loss currently configurable ATR multiplier but can be replaced based on strategy
Take Profit calculated from Stop Loss using R:R ratio
Backtesting:
Configurable backtesting range by date
Trade drawings:
TP/SL boxes drawn for all trades. Can be turned on and off
Trade exit information labels. Can be turned on and off
NOTE: Trade drawings will only be applicable when using overlay strategies
Debugging:
Includes section with useful debugging techniques
Strategy conditions
Trade entry:
LONG
C1: Price is above EMA line
C2: RSI is crossing out of oversold area
SHORT
C1: Price is below EMA line
C2: RSI is crossing out of overbought area
Trade exit:
Stop Loss: Stop Loss ATR multiplier is hit
Take Profit: R:R multiplier * Stop Loss is hit
The idea is to use RSI to catch pullbacks within the main trend.
Note that this strategy is intended to be a simple base strategy for building upon. It was not designed to be traded in its current form.
CFB-Adaptive CCI w/ T3 Smoothing [Loxx]CFB-Adaptive CCI w/ T3 Smoothing is a CCI indicator with adaptive period inputs and T3 smoothing. Jurik's Composite Fractal Behavior is used to created dynamic period input.
What is Composite Fractal Behavior ( CFB )?
All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets.
Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration.
Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action.
The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit!
This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic.
CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate
Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included:
Bar coloring
Signals
Alerts
Future PreviewFuture Preview
Calculate real-time future order profit with open price, leverage and commission fee. Simple and straight forward. If you need any additional feature, please leave a comment below. I am glad to help.
Usage:
When adding Future Preview to chart, it will ask order open time and open price on the chart by clicking with left mouse on the desired value. These value can be changed lately, as well as the leverage and commission fee. Default leverage is 10 and default commission fee is 0.06% (taker).
There will be two horizontal lines. The solid longer line is the open price line, it shows the order open price. The shorter line moving with real-time price is the current price line, it shows the current price. There will be preview data shows on top or below the price line. Open price line is red for short order and green for long order. The current price line is red when the order is losing and it is green when it profiting. The back ground color follows the color of current price line. Background color transparency and gain/loss color can be changed in options.
There will be one horizontal line on the left if the option of showing open time is on (default is on). It shows the time stamp when current order opened.
After adding Future Preview to chart, there is option to add Taking Profit(TP) or Stop Loss(SL) to the chart.
Font size can be changed in option
MPF EMA Cross Strategy (8~13~21) by Market Pip FactoryThis script is for a complete strategy to win maximum profit on trades whilst keeping losses at a minimum, using sound risk management at no greater than 1.5%
The 3x EMA Strategy uses the following parameters for trade activation and closure.
1/ Daily Time Frame for trend confirmation
2/ 4 Hourly Time Frame for trend confirmation
3/ 1 Hourly Time Frame for trend confirmation AND trade execution
4/ 3x EMAs (Exponential Moving Averages)
* EMA#1 = 8 EMA (Red Color)
* EMA#2 = 13 EMA (Blue Color)
* EMA#3 = 21 EMA (Orange Color)
5/ Fanning of all 3x EMAs and CrossOver/CrossUnder for Trend Confirmation
6/ Price Action touching an 8 EMA for trade activation
7/ Price Action touching a 21 EMA for trade cancellation BEFORE activation
* For LONG trades: 8 EMA would be ABOVE 21 EMA
* For SHORT trades: 8 EMA would be BELOW 21 EMA
* For trade Cancellation, price action would touch the 21 EMA before trade is activated
* For trade Entry, price action would touch 8 EMA
Once trigger parameter is identified, entry is found by:
a) Price action touches 8 EMA (Candle must Close for confirmed Trade preparation)
b) Trade preparation can be cancelled before trade is activated if price action touches 21 EMA
c) Trailing Stop Loss can be used (optional) by counting back 5 candles from current candle
CLOSURE of a Trade is identified by:
e) 8 EMA crossing the 21 EMA, then close trade, no matter LONG or SHORT
f) Trail Stop Loss
IMPORTANT:
g) No more than ONE activated trade per EMA crossover
h) No more than ONE active trade per pair
NOTE: This strategy is to be used in conjunction with Cipher Twister (my other indicator) to reduce trades on
sideways price action and market trends for super high win ratio.
NOTE: Enabling of LONGs and SHORTs Via Cipher Twister is done by using the previous
green or red dot made. Additionally, when the trend changes, so do the dot's validity based
on being above or below the 0 centerline.
----------------------------
Strategy and Bot Logic
----------------------------
.....::: FOR SHORT TRADES ONLY :::.....
The Robot must use the following logic to enable and activate the SHORT trades:
Parameters:
$(crossunder)=8EMA,21EMA=Bearish $(crossover)=8EMA,21EMA=Bullish $entry=SELL STOP ORDER (Short)
$EMA#1 = 8 EMA (Red Color) $EMA#2 = 13 EMA (Blue Color) $EMA#3 = 21 EMA (Orange Color)
Strategy Logic:
1/ Check Daily Time Frame for trend confirmation if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=daily and trend=$(crossunder) then goto 2/ *Means: crossunder = ema21 > ema8
$(chart)=daily and trend=$(crossover) then stop (No trades) *Means: crossover = ema8 > ema21
NOTE: This function is switchable. 0=off and 1=on(active). Default = 1 (on)
2/ Check 4 Hourly Time Frame for trend confirmation if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=4H and trend=$(crossunder) then goto 3/ *Means: crossunder = ema21 > ema8
$(chart)=4H and trend=$(crossover) then stop (No trades) *Means: crossover = ema8 > ema21
NOTE: This function is switchable. 0=off and 1=on(active). Default = 1 (on)
3/ 1 Hourly Time Frame for trend confirmation AND trade execution if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=1H and trend=$(crossunder) then goto 4/ *Means: crossunder = ema21 > ema8
$(chart)=1H and trend=$(crossover) then stop (No trades) *Means: crossover = ema8 > ema21
4/ Trade preparation:
* if Next (subsequent) candle touches 8EMA, then set STOP LOSS and ENTRY
* $stoploss=3 pips ABOVE current candle HIGH
* $entry=3 pips BELOW current candle LOW
5/ Trade waiting (ONLY BEFORE entry is hit and trade activated):
* if price action touches 21 EMA then cancel trade and goto 1/
Note: Once trade is active this function does not apply !
6/ Trade Activation:
* if price activates/hits ENTRY price, then bot activates trade SHORTs market
7/ Optional Trailing stop:
* if active, then trailing stop 3 pips ABOVE previous HIGH of previous 5th candle
or * Move Stop Loss to Break Even after $X number of pips
NOTE: This means count back and apply accordingly to the 5th previous candle from current candle.
NOTE: This function is switchable. 0=off and 1=on(active). Default = 0 (off)
8/ Trade Close ~ Take Profit:
* Only TP when
$(chart)=1H and trend=$(crossover) then close trade ~ Or obviously if Stop Loss is hit if 7/ is activated.
----------END FOR SHORT TRADES LOGIC----------
.....::: FOR LONG TRADES ONLY :::.....
The Robot must use the following logic to enable and activate the LONG trades:
Parameters:
$(crossunder)=8EMA,21EMA=Bearish $(crossover)=8EMA,21EMA=Bullish $entry=BUY STOP ORDER (Long)
$EMA#1 = 8 EMA (Red Color) $EMA#2 = 13 EMA (Blue Color) $EMA#3 = 21 EMA (Orange Color)
Strategy Logic:
1/ Check Daily Time Frame for trend confirmation if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=daily and trend=$(crossover) then goto 2/ *Means: crossover = ema8 > ema21
$(chart)=daily and trend=$(crossunder) then stop (No trades) *Means: crossunder = ema21 > ema8
NOTE: This function is switchable. 0=off and 1=on(active). Default = 1 (on)
2/ Check 4 Hourly Time Frame for trend confirmation if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=4H and trend=$(crossover) then goto 3/ *Means: crossover = ema8 > ema21
$(chart)=4H and trend=$(crossunder) then stop (No trades) *Means: crossunder = ema21 > ema8
NOTE: This function is switchable. 0=off and 1=on(active). Default = 1 (on)
3/ 1 Hourly Time Frame for trend confirmation AND trade execution if:
(look back up to 50 candles - find last cross of EMAs)
$(chart)=1H and trend=$(crossover) then goto 4/ *Means: crossover = ema8 > ema21
$(chart)=1H and trend=$(crossunder) then stop (No trades) *Means: crossunder = ema21 > ema8
4/ Trade preparation:
* if Next (subsequent) candle touches 8EMA, then set STOP LOSS and ENTRY
* $stoploss=3 pips BELOW current candle LOW
* $entry=3 pips ABOVE current candle HIGH
5/ Trade waiting (ONLY BEFORE entry is hit and trade activated):
* if price action touches 21 EMA then cancel trade and goto 1/
Note: Once trade is active this function does not apply !
6/ Trade Activation:
* if price activates/hits ENTRY price, then bot activates trade LONGs market
7/ Optional Trailing stop:
* if active, then trailing stop 3 pips BELOW previous LOW of previous 5th candle
or * Move Stop Loss to Break Even after $X number of pips
NOTE: This means count back and apply accordingly to the 5th previous candle from current candle.
NOTE: This function is switchable. 0=off and 1=on(active). Default = 0 (off)
8/ Trade Close ~ Take Profit:
* Only TP when
$(chart)=1H and trend=$(crossunder) then close trade ~ Or obviously if Stop Loss is hit if 7/ is activated.
----------END FOR LONG TRADES LOGIC----------
IMPORTANT:
* If an existing trade is already open for that same pair, & price action touches 8EMA, do NOT open a new trade..
* bot must continuously check if a trade is currently open on the pair that triggers
* New trades are to be only opened if there is no active trade opened on current pair.
* Only 1 trade per pair rule !
* 5 simultaneous open trades (not same pairs) default = 5 but value can be changed accordingly.
* Maximum risk management must not exceed 1.5% on lot size
*** Some features are not yet available autoated, they will be added in due course in subsequent version updates ***
5 Minute Scalping StrategyTaking entrys based on the 1 minute timeframe MACD
only taking longs when all emas are in the correct order and there is a bigger than usual MACD downtick and the RSI is above 51
only taking shorts when all emas are in the opposite order and there is a bigger than usual uptick on the MACD and the RSI is bellow 49
bigger than usual ticks are defined by bollinger bands around the Macd and the ticks have to be higher than 35 and lower than -10
you can change whatever setting you like to make the strategy more profitible. pls share when you find a more profitible setting than me
the stoploss doesnt work correct if it would be hit in the same candle you enter the trade. pls share when you have a solution for this
the stratagy is profitible when i backtested it for the last month, but i dont know how it will play out in the future, so you enter the signals at your own risk
Oversold RSI with tight SL Strategy (by Coinrule)This is one of the best strategies that can be used to get familiar with technical indicators and start to include them in your trading bot rules.
ENTRY
1. This trading system uses the RSI ( Relative Strength Index ) to anticipate good points to enter positions. RSI is a technical indicator frequently used in trading. It works by measuring the speed and change of price movements to determine whether a coin is oversold (indicating a good entry point) or overbought (indicating a point of exit/entry for a short position). The RSI oscillates between 0 and 100 and is traditionally considered overbought when over 70 and oversold when below 30.
2. To pick the right moment to buy, the strategy enters a trade when the RSI falls below 30 indicating the coin is oversold and primed for a trend reversal.
EXIT
The strategy then exits the position when the price appreciates 7% from the point of entry. The position also maintains a tight stop-loss and closes the position if the price depreciates 1% from the entry price. The idea behind this is to cut your losing trades fast and let your winners ride.
The best time frame for this strategy based on our backtesting data is the daily. Shorter time frames can also work well on certain coins, however in our experience, the daily works best. Feel free to experiment with this script and test it on a variety of your coins! With our backtesting data a trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange by volume. In the example shown, this strategy made a handsome net profit of 39.31% on Chainlink with 61.54% of trades being profitable.
EHMA Range StrategyThis script is a modified version of @borserman's script for the Exponential Hull Moving Average
All credit for the EHMA goes to him :)
In addition to the EHMA, this script works with a range around the EHMA (which can be modified), in an attempt to be robust against fake signals. Many times a bar will close below a moving average, only to reverse again the next bar, which eats away at your profits. Especially on shorter timeframes, but also on choppy longer timeframes this can make a strategy unattractive to use.
With the range around the EHMA, the strategy only enters a long/exit-short position if a bar crosses above the upper range. Vice versa, it only enters a short/exit-long position if a bar crosses below the lower range. This avoids positions if bars behave choppy within the EHMA range & only enters a position if the market is confident in it's direction. Having said that, fakeouts are still possible, but a lot less frequent. Having backtested this strategy vs the regular EHMA strategy (and having experimented with various settings), this version seems to be a lot more robust & profitable!
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as good as in historical backtesting.
This post and the script don’t provide any financial advice.
EMA bands + leledc + bollinger bands trend following strategy v2The basics:
In its simplest form, this strategy is a positional trend following strategy which enters long when price breaks out above "middle" EMA bands and closes or flips short when price breaks down below "middle" EMA bands. The top and bottom of the middle EMA bands are calculated from the EMA of candle highs and lows, respectively.
The idea is that entering trades on breakouts of the high EMAs and low EMAs rather than the typical EMA based on candle closes gives a bit more confirmation of trend strength and minimizes getting chopped up. To further reduce getting chopped up, the strategy defaults to close on crossing the opposite EMA band (ie. long on break above high EMA middle band and close below low EMA middle band).
This strategy works on all markets on all timeframes, but as a trend following strategy it works best on markets prone to trending such as crypto and tech stocks. On lower timeframes, longer EMAs tend to work best (I've found good results on EMA lengths even has high up to 1000), while 4H charts and above tend to work better with EMA lengths 21 and below.
As an added filter to confirm the trend, a second EMA can be used. Inputting a slower EMA filter can ensure trades are entered in accordance with longer term trends, inputting a faster EMA filter can act as confirmation of breakout strength.
Bar coloring can be enabled to quickly visually identify a trend's direction for confluence with other indicators or strategies.
The goods:
Waiting for the trend to flip before closing a trade (especially when a longer base EMA is used) often leaves money on the table. This script combines a number of ways to identify when a trend is exhausted for backtesting the best early exits.
"Delayed bars inside middle bands" - When a number of candle's in a row open and close between the middle EMA bands, it could be a sign the trend is weak, or that the breakout was not the start of a new trend. Selecting this will close out positions after a number of bars has passed
"Leledc bars" - Originally introduced by glaz, this is a price action indicator that highlights a candle after a number of bars in a row close the same direction and result in greatest high/low over a period. It often triggers when a strong trend has paused before further continuation, or it marks the end of a trend. To mitigate closing on false Leledc signals, this strategy has two options: 1. Introducing requirement for increased volume on the Leledc bars can help filter out Leledc signals that happen mid trend. 2. Closing after a number of Leledc bars appear after position opens. These two options work great in isolation but don't perform well together in my testing.
"Bollinger Bands exhaustion bars" - These bars are highlighted when price closes back inside the Bollinger Bands and RSI is within specified overbought/sold zones. The idea is that a trend is overextended when price trades beyond the Bollinger Bands. When price closes back inside the bands it's likely due for mean reversion back to the base EMA in which this strategy will ideally re-enter a position. Since the added RSI requirements often make this indicator too strict to trigger a large enough sample size to backtest, I've found it best to use "non-standard" settings for both the bands and the RSI as seen in the default settings.
"Buy/Sell zones" - Similar to the idea behind using Bollinger Bands exhaustion bars as a closing signal. Instead of calculating off of standard deviations, the Buy/Sell zones are calculated off multiples of the middle EMA bands. When trading beyond these zones and subsequently failing back inside, price may be due for mean reversion back to the base EMA. No RSI filter is used for Buy/Sell zones.
If any early close conditions are selected, it's often worth enabling trade re-entry on "middle EMA band bounce". Instead of waiting for a candle to close back inside the middle EMA bands, this feature will re-enter position on only a wick back into the middle bands as will sometimes happen when the trend is strong.
Any and all of the early close conditions can be combined. Experimenting with these, I've found can result in less net profit but higher win-rates and sharpe ratios as less time is spent in trades.
The deadly:
The trend is your friend. But wouldn't it be nice to catch the trends early? In ranging markets (or when using slower base EMAs in this strategy), waiting for confirmation of a breakout of the EMA bands at best will cause you to miss half the move, at worst will result in getting consistently chopped up. Enabling "counter-trend" trades on this strategy will allow the strategy to enter positions on the opposite side of the EMA bands on either a Leledc bar or Bollinger Bands exhaustion bar. There is a filter requiring either a high/low (for Leledc) or open (for BB bars) outside the selected inner or outer Buy/Sell zone. There are also a number of different close conditions for the counter-trend trades to experiment with and backtest.
There are two ways I've found best to use counter-trend trades
1. Mean reverting scalp trades when a trend is clearly overextended. Selecting from the first 5 counter-trend closing conditions on the dropdown list will usually close the trades out quickly, with less profit but less risk.
2. Trying to catch trends early. Selecting any of the close conditions below the first 5 can cause the strategy to behave as if it's entering into a new trend (from the wrong side).
This feature can be deadly effective in profiting from every move price makes, or deadly to the strategy's PnL if not set correctly. Since counter-trend trades open opposite the middle bands, a stop-loss is recommended to reduce risk. If stop-losses for counter-trend trades are disabled, the strategy will hold a position open often until liquidation in a trending market if th trade is offsides. Note that using a slower base EMA makes counter-trend stop-losses even more necessary as it can reduce the effectiveness of the Buy/Sell zone filter for opening the trades as price can spend a long time trending outside the zones. If faster EMAs (34 and below) are used with "Inner" Buy/Zone filter selected, the first few closing conditions will often trigger almost immediately closing the trade at a loss.
The niche:
I've added a feature to default into longs or shorts. Enabling these with other features (aside from the basic long/short on EMA middle band breakout) tends to break the strategy one way or another. Enabling default long works to simulate trying to acquire more of the asset rather than the base currency. Enabling default short can have positive results for those high FDV, high inflation coins that go down-only for months at a time. Otherwise, I use default short as a hedge for coins that I hold and stake spot. I gain the utility and APR of staking while reducing the risk of holding the underlying asset by maintaining a net neutral position *most* of the time.
Disclaimer:
This script is intended for experimenting and backtesting different strategies around EMA bands. Use this script for your live trading at your own risk. I am a rookie coder, as such there may be errors in the code that cause the strategy to behave not as intended. As far as I can tell it doesn't repaint, but I cannot guarantee that it does not. That being said if there's any question, improvements, or errors you've found, drop a comment below!
Oversold RSI with Tight Stop-Loss Strategy (by Coinrule)KRAKEN:LINKUSD
This is one of the best strategies that can be used to get familiar with technical indicators and start to include them in your rules on Coinrule .
ENTRY
1. This trading system uses the RSI (Relative Strength Index) to anticipate good points to enter positions. RSI is a technical indicator frequently used in trading. It works by measuring the speed and change of price movements to determine whether a coin is oversold (indicating a good entry point) or overbought (indicating a point of exit/entry for a short position). The RSI oscillates between 0 and 100 and is traditionally considered overbought when over 70 and oversold when below 30.
2. To pick the right moment to buy, the strategy enters a trade when the RSI falls below 30 indicating the coin is oversold and primed for a trend reversal.
EXIT
The strategy then exits the position when the price appreciates 7% from the point of entry. The position also maintains a tight stop-loss and closes the position if the price depreciates 1% from the entry price. The idea behind this is to cut your losing trades fast and let your winners ride.
The best time frame for this strategy based on our back testing data is the daily. Shorter time frames can also work well on certain coins, however in our experience, the daily works best. Feel free to experiment with this script and test it on a variety of your coins! With our back testing data a trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange by volume. In the example shown, this strategy made a handsome net profit of 52.6% on Chainlink with 66.67% of trades being profitable.
You can execute this strategy on your favorite exchanges with Coinrule .
Ranged Volume DCA Strategy - R3c0nTraderUpdate: Republishing this as Public Open-Source script.
Credits:
Thank you "EvoCrypto" for granting me permission to use "Ranged Volume" to create this strategy.
Thank you "junyou0424" for granting me permission to use "DCA Bot with SuperTrend Emulator" which I used for adding bot inputs, calculations, and strategy
What does this do?
This script is mainly used for backtesting a Ranged Volume strategy to see how a 3Commas bot would perform.
I created this script out of necessity and I wanted a way to test a 3Commas DCA bot with a strategy based on “Volume.”
I came across "EvoCrypto’s" "Ranged Volume" study and strategy in TradingView and I liked it. I wanted to configure it so it can be used for DCA bot backtesting. I used parts from "junyou0424’s" "DCA Bot with SuperTrend Emulator" to add the following:
1. The Start Time and End Time
2. Price deviation to open safety orders (%)
3. Target Take Profit (%)
4. Trailing deviation
5. Base Order and Safety Order
6. Safety order volume scale
7. Safety order step scale
8. Max safety orders
In addition to the above, I also added chart indicators for "Take Profit" as well as "Safety Order"
Pre-requisites:
You can use this script without a 3Commas account and see how 3Commas DCA Bot and Ranged Volume strategy would perform vs. a non-DCA strategy. However, I highly recommend signing up for their free account and going through their training. This would give you a base understanding on the settings you will see in this strategy and why you will need to know them.
That said these are the pre-requisites I suggest you have:
1. Base Knowledge of 3Commas DCA bots
2. Base knowledge of settings such as “Max safety trades count”, “safety order volume scale” and “safety order step scale”. If these are alien to you, I suggest you read up on these.
3. Knowledge of setting up a Single-pair 3Commas bot for receiving custom TradingView signal.
4. A paper-bot to test your ideas. (Do not use a real money bot until you have tested it sufficiently with a paper-bot. You alone are responsible for your results!)
5. Add the study I created called "R3c0nTrader’s Ranged Volume Study” which adds a separate chart in its own pane showing the volume spikes. It will also generate the “buy” signals for your bot. NOTE: The study also has the same color scheme as this strategy and having the colors in both the strategy and the study will make things easier to see. If you use EvoCrypto’s Ranged Volume Study instead, just keep in mind that the colors won’t match, and you will have to manually match them.
6. Make your buy signals from your strategy are the same as in your study! To do this, use the same “Volume Range Length” you entered in the STRATEGY and enter that value for the “Volume Range Length” in the STUDY. Also ensure you have the same settings for “Heikin Ashi” (On or Off).
Comparisons of Ranged Volume Strategy vs Ranged Volume DCA Strategy
BTCUSD
Beware of Strategies that claim super high profits. This can easily be done by lowering the initial capital to something unrealistic. If I did that with this strategy and set the initial capital $100 and base order size to $100, I get a net profit of 2,864% which is not realistic.
How to Use
1. On the “Inputs” tab:
a. Set your Start and End Time to backtest against.
b. Set your “Volume Range Length” (number of bars to look back)
c. “Heikin Ashi Colors” – Usually I leave this enabled
d. “Show Bar Colors” – Leave enabled
e. “Show Break-Out” – Leave enabled
f. “Show Range” – Leave enabled
g. Set your other inputs which are those settings you would find in your 3Commas bot that you want to test (e.g., Price deviation to open safety orders, Target Take Profit, Base order, Safety order, etc.).
h. Quick Example for BTCUSD on 2hr chart:
i. Price deviation to open safety orders (%) = 6
ii. Target Take Profit (%) = 14
iii. Trailing deviation = 0
iv. Base order = 100
v. Safety order = 200
vi. Safety order volume scale = 2
vii. Safety order step scale = 1.4
viii. Max safety order = 5
2. On the “Properties” tab, set your initial capital, base currency, etc.
a. Initial capital – Default is 10,000 (Please use realistic values here. The amount here should be able to cover ALL your safety orders if they were triggered. Ideally, you should have funds left over and not use all trade capital.)
b. Base currency – Select your currency
c. Order Size - Not used. Use the “Inputs” tab to change your base order size.
d. Leave “Pyramiding” set to 999. This acts as a ceiling to the “Max safety orders” on the “Inputs” tab. It must always be higher than your “Max safety orders.” For example, if you set your “Max safety orders” to “4” and “Pyramiding” to “4” then it effectively means you have “3” “Max safety orders” and not “4” because it is counting each successive entry including the initial order.
e. “Commission” - Optional
f. “Verify price for limit orders” – Leave at zero. This does not change anything that I can tell.
g. Optional - Enter a value for “Commission”
h. Slippage – Optional. Slippage does not occur in backtesting but does occur in real trading but it can be simulated. Example use case for tracking performance of a real money bot: You enter the start date and time of your bot’s trade into this strategy and you notice some values are a little off due to slippage (average price, take profit, safety orders are not lining up) then you would go back here and increase the slippage until those lines up close enough with your actuals.
i. Margin for long positions – I don’t use this honestly.
j. Margin for short positions – I don’t use this honestly.
k. Recalculate “After order is filled” and “On every tick” – I don’t use this honestly.
3. “Style” tab
a. Ranged Volume Bar Coloring - You must disable bar coloring in any studies you added or this may not work properly
i. Color 0 – Default Yellow; appears when a volume breakout occurs
ii. Color 1 – Default Red; appears when a volume breakdown occurs
iii. Color 2 – Light Blue; appears when Close is higher than the Open
iv. Color 3 – Dark Blue; appears when the Close is lower than the Open
b. Take profit – Default Green; take profit line
c. Safety order – Default Light Blue; safety order line
d. No Safety Orders left – Default Red; when a trade runs out of safety orders, the line turns red and there is no safety orders left underneath to catch any further falling price movements.
e. Avg Position Price – Default Orange; your average position price for any given trade.
f. Take Profit Plot Area – Default Green; creates a highlighted area for your take profit
g. SO Plot Area – Default Light Blue; creates a highlighted area for your safety orders
h. Trades on chart – Show or hide your trades on the chart
i. Signal labels – Show or hide the trade signal labels on the chart
j. Quantity – Show or hide the trade quantity on the chart
Explanation of Chart lines and colors on chart
SOPR Candles OscillatorThe Spent Output Profit Ratio (SOPR) is computed by dividing the realized value (in USD) divided by the value at creation (USD) of a spent output. Or simply: price sold / price paid. This metric was created by Renato Shirakashi.
The indicator provides insight into macro market sentiment, profitability and losses taken over a particular time-frame. It reflects the degree of realized profit for all coins moved on-chain.
SOPR is measured by taking the ratio between the fiat value at the time of UTXO creation, and the fiat value when the UTXO is spent.
In this indicator, I have essentially created an index that measures SOPR value on any given day. This is visually displayed as an oscillator.
SOPR values greater than 0 implies that the coins moved that day are, on average, selling at a profit (price sold is greater than the price paid).
SOPR value less than 0 implies that the coins moved that day are, on average, selling at a loss (price sold is less than the price paid).
You have the ability to see the SOPR of BTC , ETH and LTC. You can also smooth the SOPR using an EMA or SMA of your choice. I have added colored bars to the chart to make it easier to visualize SOPR and it's relation to price action.
Thank you to both TradingView and Glassnode for adding all the on-chain data.
Villa Dinamic Pivot Supertrend StrategyThis strategy works better on AUD/USD in the 15 min timeframe. It uses the Pivot Supertrend to enter trades based on different filters such as:
- Simple EMA filter: that the 3 EMAs should be in order
- DEMA angle: you can choose the DEMA Angle threshold and the look back to check the angle to just trade trades with DEMA at a certain angle
- Simple DEMA filter: just check if close is above or below DEMA
- Take Every Supertrend Signal: this means to take every normal supertrend signal to not just wait for a pivot supertrend signal to enter a trade (specially on long pivot supertrend periods)
- Stop Loss at Supertrend: this means that the stop loss will be at the Normal Supertrend, if false the stop loss will be placed at the ATR level selected.
- 2 Steps Take Profit: this means if you want to close a percentage of position as soon as the normal supertrend crosses the entry price, you can select the % on the "2 Steps TP qty" input
- Stop Loss ATR Multiplier: if Stop Loss at Supertrend is off this will be the stoploss based on the atr
- Take Profit ATR Multiplier: if Stop Loss at Supertrend is off this will be the takeprofit based on the atr (you have to keep in mind that the ratio between this two will make the Risk to reward ratio of the take profit when the Stop Loss at Supertrend)
- Testing: to avoid overfitting, you can select date ranges for backtesting and forwardtesting and select which testing you wanna do
Loft Strategy V4This strategy is an advanced version of the Loft Strategy V1, I shared earlier. (Loft Strategy V1 consists of a kalman filter (by alexgrover ) and a "stop and reverse" line which is following and the kalman filter. If the price goes in the same direction as the position side, the "stop and reverse" line approaches the kalman filter as set on the "Approach Decrease Step" parameter.)
In addition to the previous version, it includes a martingale like deviation and multiple take-profit.
Here it is some parameters definitions of the strategy:
Kalman Filter: The higher this parameter, the faster and more aggressive the filter. Otherwise the filter goes very smoothly
Beginning Approach: First approximation as a percentage of stop-n-reverse line
Final Approach: Minimum approximation of stop-n-reverse line
Approach Decrease Step: If the price moves in the same direction as the strategy, the approach percentage is reduced by this parameter. Otherwise nothing do
Base Order Quantity: Initial capital of position
Max Safe Order Attempt: This parameter determines the maximum number of times the strategy will raise the bet after losing in a row.
Safe Order Deviation: if the last trade is loss, multiply the bet by this parameter (aka. martingale factor)
Profit Deviation: if last trade in loss, multiply the take-profit points
Max Order Quantity: Maximum capital allowed for a position
TP1, TP2, TP3 : Take profit spots in percentage
QT1, QT2, QT3: Amount of take-profit spots
Stop Loss: Maximum stop loss allowed for a trade
Long Entry, Short Entry: Only long side, only short side or both side
Safe Stop After TP2: If the price reaches the TP2 point, move the stop-loss point to the entry price.
Safe Stop After TP1: If the price reaches TP1, move the stop-loss point to the stop-n-reverse line.
Uptrend and Oversold Index Swing Trading System 8H--- Foreword ---
The Overbought and Oversold Index Swing Trading System or short: I11L Hypertrend primarily uses money management Strategies, EMA and SMA and my momentum Ideas for trying to produce satisfactory Alpha over a timespan of multiple years.
--- How does it Work? ---
It uses 20 different EMA's and SMA's to produce a score for each Bar.
It will credit one Point If the EMA is above the SMA.
A high score means that there is a strong Uptrend.
Spotting the strong Uptrend early is important.
The I11L Hypertrend System trys to spot the "UPTREND" by checking for a crossover of the Score(EMA) / Score(SMA).
A low score means that there is a strong Downtrend.
Its quite common to see a reversal to the mean after a Downtrend and spotting the bottom is important.
The System trys to spot the reversal, or "OVERSOLD" state by a crossunder of the Score(EMA) / Score(SMA).
--- What can i customize? ---
-> Trading Mode: You can choose between two different trading modes, Oversold and Overbought(trend) and Random Buys to check if your systems Profitfactor is actually better then market.
-> Work with the total equity: The system uses the initial capital per default for Backtesting purposes but seeing the maximum drawdown in a compounding mode might help!
-> Use a trailing SL: A TSL trys to not lose too much if the trade goes against your TP
-> Lookbackdistance for the Score: A higher Lookbackdistance results in a more lagging indicator. You have to find the balance between the confirmation of the Signal and the frontrunning.
-> Leverage: To see how your strategie and your maximum Drawdown with the total equity mode enabled would have performed.
-> Risk Capital per Trade unleveraged: How much the underlying asset can go against your position before the TSL hits, or the SL if no TSL is set.
-> TPFactor: Your risk/reward Ratio. If you risk 3% and you set the ratio to 1.2, you will have a TP at 3 * 1.2 = 3.6%
-> Select Date: Works best in the 8H Timeframe for CFD's. Good for getting a sense of what overfitting actually means and how easy one can fool themself, find the highest Profitfactor setting in the first Sector (Start - 2012) and then see if the second Sector (2012 - Now) produces Alpha over the Random Buy mode.
--- I have some questions about the System ---
Dear reader, please ask the question in the comment Section and i will do my best to assist you.
