Coral Trend Pullback Strategy (TradeIQ)Description:
Strategy is taken from the TradeIQ YouTube video called "I Finally Found 80% Win Rate Trading Strategy For Crypto".
Check out the full video for further details/clarification on strategy entry/exit conditions.
The default settings are exactly as TradeIQ described in his video.
However I found some better results by some tweaking settings, increasing R:R ratio and by turning off confirmation indicators.
This would suggest that perhaps the current confirmation indicators are not the best options. I'm happy to try add some other optional confirmation indicators if they look to be more effective.
Recommended timeframe: 1H
Strategy 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: Coral Trend is bullish
C2: At least 1 candle where low is above Coral Trend since last cross above Coral Trend
C3: Pullback happens and price closes below Coral Trend
C4: Coral Trend colour remains bullish for duration of pullback
C5: After valid pullback, price then closes above Coral Trend
C6: Optional confirmation indicators (choose either C6.1 or C6.2 or NONE):
C6.1: ADX and DI (Single indicator)
C6.1.1: Green line is above red line
C6.1.2: Blue line > 20
C6.1.3: Blue trending up over last 1 candle
C6.2: Absolute Strengeh Histogram + HawkEye Volume Indicator (Two indicators combined)
C6.2.1: Absolute Strengeh Histogram colour is blue
C6.2.2: HawkEye Volume Indicator colour is green
SHORT
C1: Coral Trend is bearish
C2: At least 1 candle where high is below Coral Trend since last cross below Coral Trend
C3: Pullback happens and price closes above Coral Trend
C4: Coral Trend colour remains bearish for duration of pullback
C5: After valid pullback, price then closes below Coral Trend
C6: Optional confirmation indicators (choose either C6.1 or C6.2 or NONE):
C6.1: ADX and DI (Single indicator)
C6.1.1: Red line is above green line
C6.1.2: Blue line > 20
C6.1.3: Blue trending up over last 1 candle
C6.2: Absolute Strengeh Histogram + HawkEye Volume Indicator (Two indicators combined)
C6.2.1: Absolute Strengeh Histogram colour is red
C6.2.2: HawkEye Volume Indicator colour is red
NOTE: All the optional confirmation indicators cannot be overlayed with Coral Trend so feel free to add each separately to the chart for visual purposes
Trade exit:
Stop Loss: Calculated by recent swing low over previous X candles (configurable with "Local High/Low Lookback")
Take Profit: Calculated from R:R multiplier * Stop Loss size
Credits
Strategy origin: TradeIQ's YouTube video called "I Finally Found 80% Win Rate Trading Strategy For Crypto"
It combines the following indicators for trade entry conditions:
Coral Trend Indicator by @LazyBear (Main indicator)
Absolute Strength Histogram | jh by @jiehonglim (Optional confirmation indicator)
Indicator: HawkEye Volume Indicator by @LazyBear (Optional confirmation indicator)
ADX and DI by @BeikabuOyaji (Optional confirmation indicator)
Strategy
Ultra Moving Average Rating Trend StrategyThis is a technical analysis strategy based initially on the rating strategy, but fully adapted and converted to moving average rating.
In this case we are using: Ichimoku, SMA, EMA, ALMA, SMMA, LSMA, VWMA, DEMA, HMA, KAMA FRAMA, VIDYA, JMA, TEMA, ZLEMA, TRIMA and T3 moving averages.
With all of them together I am making an index.
Rules for entry and exit:
If % percentage of all the moving averages is telling to go long , we go long or exit short. And viceversa for short.
If there are any questions, please let me know !
HHLL Strategy This is simple Highest high and Lowest low strategy.
Buy when break HH+offset
Sell when break LL+offset
Offset = (HH-LL)/2
SUPPORT RESISTANCE STRATEGY [5MIN TF]A SUPPORT RESISTANCE BREAKOUT STRATEGY for 5 minute Time-Frame , that has the time condition for Indian Markets
The Timing can be changed to fit other markets, scroll down to "TIME CONDITION" to know more.
The commission is also included in the strategy .
The basic idea is when ,
1) Price crosses above Resistance Level ,indicated by Red Line, is a Long condition.
2) Price crosses below Support Level ,indicated by Green Line , is a Short condition.
3) Candle high crosses above ema1, is a part of the Long condition .
4) Candle low crosses below ema1, is a part of the Short condition .
5) Volume Threshold is an added confirmation for long/short positions.
6) Maximum Risk per trade for the intraday trade can be changed .
7) Default qty size is set to 50 contracts , which can be changed under settings → properties → order size.
8) ATR is used for trailing after entry, as mentioned in the inputs below.
// ═════════════════════════//
// ————————> INPUTS <————————— //
// ═════════════════════════//
→ L_Bars ———————————> Length of Resistance / Support Levels.
→ R_Bars ———————————> Length of Resistance / Support Levels.
→ Volume Break ———————> Volume Breakout from range to confirm Long/Short position.
→ Price Cross Ema —————> Added condition as explained above (3) and (4).
→ ATR LONG —————————> ATR stoploss trail for Long positions.
→ ATR SHORT ————————> ATR stoploss trail for Short positions.
→ RISK ————————————> Maximum Risk per trade intraday.
The strategy was back-tested on TCS ,the input values and the results are mentioned under "BACKTEST RESULTS" below.
// ═════════════════════════ //
// ————————> PROPERTIES<——————— //
// ═════════════════════════ //
Default_qty_size ————> 50 contracts , which can be changed under
Settings
↓
Properties
↓
Order size
// ═══════════════════════════════//
// ————————> TIME CONDITION <————————— //
// ═══════════════════════════════//
The time can be changed in the script , Add it → click on ' { } ' → Pine editor→ making it a copy [right top corner} → Edit the line 27.
The Indian Markets open at 9:15am and closes at 3:30pm.
The 'time_cond' specifies the time at which Entries should happen .
"Close All" function closes all the trades at 3pm , at the open of the next candle.
To change the time to close all trades , Go to Pine Editor → Edit the line 92 .
All open trades get closed at 3pm , because some brokers don't allow you to place fresh intraday orders after 3pm .
// ═══════════════════════════════════════════════ //
// ————————> BACKTEST RESULTS ( 100 CLOSED TRADES )<————————— //
// ═══════════════════════════════════════════════ //
INPUTS can be changed for better Back-Test results.
The strategy applied to NSE:TCS ( 5 min Time-Frame and contract size 50) gives us 60% profitability , as shown below
It was tested for a period a 6 months with a Profit Factor of 1.8 ,net Profit of 30,000 Rs profit .
Sharpe Ratio : 0.49
Sortino Ratio : 1.4
The graph has a Linear Curve with Consistent Profits.
The INPUTS are as follows,
1) L_Bars —————————> 4
2) R_Bars —————————> 4
3) Volume Break ————> 5
4) Price Cross Ema ——> 100
5) ATR LONG ——————> 2.4
6) ATR SHORT —————> 2.6
7) RISK —————————> 2000
8) Default qty size ——> 50
NSE:TCS
Save it to favorites.
Apply it to your charts Now !!
Thank You ☺ NSE:TCS
PIVOT STRATEGY [INDIAN MARKET TIMING]
A Back-tested Profitable Strategy for Free!!
A PIVOT INTRADAY STRATEGY for 5 minute Time-Frame , that also explains the time condition for Indian Markets
The Timing can be changed to fit other markets, scroll down to "TIME CONDITION" to know more.
The commission is also included in the strategy .
The basic idea is when ,
1) Price crosses above ema1 ,indicated by pivot highest line in green color .
2) Price crosses below ema1 ,indicated by pivot lowest line in red color .
3) Candle high crosses above pivot highest , is the Long condition .
4) Candle low crosses below pivot lowest , is the Short condition .
5) Maximum Risk per trade for the intraday trade can be changed .
6) Default_qty_size is set to 60 contracts , which can be changed under settings → properties → order size .
7) ATR is used for trailing after entry, as mentioned in the inputs below.
// ═════════════════════════//
// ————————> INPUTS <————————— //
// ═════════════════════════//
Leftbars —————> Length of pivot highs and lows
Rightbars —————> Length of pivot highs and lows
Price Cross Ema —————> Added condition
ATR LONG —————> ATR stoploss trail for Long positions
ATR SHORT —————> ATR stoploss trail for Short positions
RISK —————> Maximum Risk per trade for the day
The strategy was back-tested on RELIANCE ,the input values and the results are mentioned under "BACKTEST RESULTS" below .
// ═════════════════════════ //
// ————————> PROPERTIES<——————— //
// ═════════════════════════ //
Default_qty_size ————> 60 contracts , which can be changed under settings
↓
properties
↓
order size
// ═══════════════════════════════//
// ————————> TIME CONDITION <————————— //
// ═══════════════════════════════//
The time can be changed in the script , Add it → click on ' { } ' → Pine editor→ making it a copy [right top corner} → Edit the line 25 .
The Indian Markets open at 9:15am and closes at 3:30pm .
The 'time_cond' specifies the time at which Entries should happen .
"Close All" function closes all the trades at 3pm, at the open of the next candle.
To change the time to close all trades , Go to Pine Editor → Edit the line 103 .
All open trades get closed at 3pm , because some brokers don't allow you to place fresh intraday orders after 3pm .
NSE:RELIANCE
// ═══════════════════════════════════════════════ //
// ————————> BACKTEST RESULTS ( 128 CLOSED TRADES )<————————— //
// ═══════════════════════════════════════════════ //
INPUTS can be changed for better back-test results.
The strategy applied to NIFTY ( 5 min Time-Frame and contract size 60 ) gives us 60% profitability y , as shown below
It was tested for a period a 6 months with a Profit Factor of 1.45 ,net Profit of 21,500Rs profit .
Sharpe Ratio : 0.311
Sortino Ratio : 0.727
The graph has a Linear Curve with consistent profits .
The INPUTS are as follows,
1) Leftbars ————————> 3
2) Rightbars ————————> 5
3) Price Cross Ema ——————> 150
4) ATR LONG ————————> 2.7
5) ATR SHORT ———————> 2.9
6) RISK —————————> 2500
7) Default qty size ——————> 60
NSE:RELIANCE
Save it to favorites.
Apply it to your charts Now !!
↓
FOLLOW US FOR MORE !
Thank me later ;)
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
Pro Trading Art Open Range Breakout StrategyThis strategy is based on Selected Candle High Low Breakout with buffer point.
You can select specific candle from input tab by giving time of that candle.
Default Settings:
Start Hour : Hour of starting candle means from this input you can specify opening candle. Default is 9.
Start Minute: Minute of starting candle. Default is 15. Means Default opening candle is 9:15
Stop Hour : Means After this time no new trade will execute.
End Hour & End Minute & Close All Trade : Means when you specify End Hour and Minute and Close all trade is true then strategy will close all trade on specified time.
Buffer : With the help of this option you can add some point in High and low of Opening Candle
Trade Mode : You can specify Target and Stop Loss in point or Percent
Stop Loss Point or Percent : This will work according to Trade Mode
Target Point Or Percent : This will work according to Trade Mode
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.
Accumulation Stage Identifier and Strategy around for TradingIn the psychology of trading at any market condition, there are four stage usually occurs on any tickers.
Stage 1 -> Neglect phase or consolidation phase
It occurs when the company does not produce the expected result and waiting for next result.
It can extend for days, weeks, months and years. Never give entry at this stage though that blue-chip told to be cheaper in price.
Stage 2 -> Accumulation
It occurs when the company's earning and sales consistently grows.
It can extend for days, weeks, months but should not expect the continues increase in price, as there will be potential pull-back which can be considered as opportunity to accumulate.
If the company fundamental is good, just give some space at the time of pullback.
Most of the time, the pullback volume will be low to compare to volume at the time of increase.
Usually, the stock that is going through accumulation stage will definitely trade above 200SMA and short term MA will be greater than long term moving average.
Continues the highest high and highest low along with volume.
Stage 3 -> Distribution
It occurs when the company's earning and sales stagnated due to certain reason.
It can extend for days, weeks while the price and volume highly volatile.
High volume while the price low
Typically, the stock that is going through distribution stage will certainly trade below 200SMA and short term MA will be lesser than long term moving average.
Continues the lowest high and lowest low along with volume.
Stage 4 -> Capitalization
Price reaches the 52W low while volume spikes on big down.
In each stage, the price & volume are perfect indicator to highlight the situation and the trader with proper discipline and patients can certainly reap the fruitful outcome of accumulation stage.
Based on this explanation, here is the strategy that is created with 50,90 & 200 Simple moving average and price volume trends (PVT) indicator applied on MACD to signal whenever the PVT convergence and divergence.
Note:
As the indicator designed to signal on the ticker that trade above 200 moving average, it is good to use this strategy on companies that are fundamental strong.
Whenever, there is pull back happens, the strategy might signal for exit, however, here comes the traders patient based on the conviction on the particular chosen stocks.
White being patient is good, disciplinary in following the strategy also important. Hence, consider the action when the stock goes opposite direction from your expectation.
Hope this strategy would help you find the profit.
Happy investing.
VWAP Push StrategyThis strategy is unfortunately not finished yet.
A pretty simple strategy. If price broke through VWAP and had three consecutive candles following the breakthroughs trend, the high of the third candle will be drawn. If this happened after a crossover of the vwap and price breaks through the high of the third candle, strategy will go long. Short will be the same after crossing under the vwap. A long or short will be closed after crossing the vwap in the opposite direction, so the vwap is kind of a trailing stop.
Unfortunately, I could not manage to stop the script from entering multiple times into one drawn high or low. Of course, if a high was crossed the script should wait for a new formed high before entering a new long. If someone would find a solution to this, it would be great, because I think it is a nice strategy .
Should work great scalping 5min charts (when scripting, I used the SPX for reference).
Consolidation Breakout [Indian Market Timing]OK let's get started ,
A Day Trading (Intraday) Consolidation Breakout Indication Strategy that explains time condition for Indian Markets .
The commission is also included in the strategy .
The basic idea is ,
1) Price crosses above upper band , indicated by a color change (green) is the Long condition .
2) Price crosses below lower band , indicated by a color change (red) is the Short condition .
3) ATR is used for trailing after entry
// ═══════════════════════════════//
// ————————> TIME CONDITION <————————— //
// ═══════════════════════════════//
The Indian Markets open at 9:15am and closes at 3:30pm.
The time_condition specifies the time at which Entries should happen .
"Close All" function closes all the trades at 2:57pm.
All open trades get closed at 2:57pm , because some brokers dont allow you to place fresh intraday orders after 3pm.
NSE:NIFTY1!
// ═══════════════════════════════════════════════ //
// ————————> BACKTEST RESULTS ( 114 CLOSED TRADES )<————————— //
// ═══════════════════════════════════════════════ //
LENGTH , MULT (factor) and ATR can be changed for better backtest results.
The strategy applied to NIFTY (3 min Time-Frame and contract size 5) gives us 60% profitability , as shown below
It was tested for a period a 8 months with a Profit Factor of 2.2 , avg Trade of 6000Rs profit and Sharpe Ratio : 0.67
The graph has a Linear Curve with consistent profits.
NSE:NIFTY1!
Save it favorites.
Apply it to your charts Now !!
Thank me later ;)
X48 - Strategy | MA Type Cross + TPSL | Future&Spot | V.2Thank You For Open Source Code, This Strategy Ref. By 1.Simple Strategy Like MA Crossover For Long/Short or Spot Trade, 2. CDC Action Zone V.2 for BarPaint
This Strategy Mixing With MA Crossover Strategy and BarPaint By CDC Action Zone and TP/SL by Varbara
### How To Use Strategy : Setting EMA/SMA Crossover EMA/SMA, Any Value If You Want
For Long Position : Cross Up
For Short Position : Cross Down
Can Use With Spot Trade : Cross Up = Buy, Cross Down = Sell
TP/SL When Your OrderSize Change From any % Of Your TP/SL Value
### In Strategy Setting
Intitial Capital = Ex. 200
Order Size = Should Be Money Management Not Use 100% of Capital Ex. 10% of Capital (200$) = Order Size 20$
StopLoss and Take Profit = If You Run Trend TF 4H+ or 1D+ You Can Change TP% = 1,000% for nonlimit and Stop Loss 5 - 20% from your order size
Ex. Stoploss 15% = OrderSize / 100 x %SL = 20$/100 x 15% = 3$ Loss from order size 20$ (if you not set stop loss.)
Base Currency = (Your Currency) # Ex. USD
Commission = (Your Trading Fee) # Ex. Future Fee Can Check At Binance Fee Rate > www.binance.com > Choose Your Fee Type, Ex. USD M Future (Regular User) = 0.02 (Maker), 0.04 (Taker)
Commission Symbol Type = % # (Ref. By Binance Fee Rate)
### Notice ####
Default Setting It's Realistic From Normal Life Ex. Capital 200$ / Ordersize 20$ (10%)/ Commission 0.1% (Buy+Sell) / Slippage = 2 / TP = 1000% (nonlimit) / SL = 15%/OrderSize
Low Risk But High Return, Good Luck
### Bot Auto Trade by X4815162342 ###
if you wanna try my bot auto trade X48-3in1-bot : Contact My Line ID : x4815x
Full Command Alert For This Strategy If You Wanna See It's
'{"ex":"'+markettype+'","side": "'+longcommand+'", "amount": "@{{strategy.order.contracts}}", "symbol": "{{ticker}}", "passphrase": "'+passphrase+'","leverage":"'+str.tostring(leveragex)+'"}'
'{"ex":"'+markettype+'","side": "'+shortcommand+'", "amount": "@{{strategy.order.contracts}}", "symbol": "{{ticker}}", "passphrase": "'+passphrase+'","leverage":"'+str.tostring(leveragex)+'"}'
But Easy Than Full Command Just Use Thisssssss !! Strategy Be Manage Auto Long and Short or TPSL Position
You Don't Do Anything Just Use This Message to Alerts Message
{{strategy.order.alert_message}}
### If you don't use bot but just looking for strategy test ####
Just Pass Bot Setting Function It's Nothing Effect For Strategy !!!!!!
Let's Enjoy With Your Strategy BackTest 😁
Remember Beware Max drawdown%. I'm Recommend Lower Than 10% It's Very Good.
Monthly Returns of a Strategy in a ChartIt's a simple example of how you can present your strategy's monthly performance in a chart.
You maybe know that there is no support of these kind of charts in TradingView so this chart is actually a table object under the hood.
Table visual appearance is customizable, you can change:
Location
Bar Width / High
Colors
Thanks to @MUQWISHI for hard work, for helping me coding it.
It's not about the strategy itself but the way you display returns on your chart. So pls don't critique my choice of the strategy and its performance 🙂
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 well as in historical backtesting.
This post and the script don’t provide any financial advice.
Triple RSI strategyThis strategy is commonly used both in forex and stock markets for reversal trading. when the rsi line reaches and crosses simultaneously at 3 rsi setups i.e at 7, 14, and 21, a signal is generated.
This strategy works best in 1-hour timeframe. It provides over 60 to 80 percent accuracy in 1-hour timeframe.
In the stock market, this strategy provides an excellent entry point, if one is seeking small profits.
One can expect to make around 10 to 50 pips in the forex market easily. However, I advise seeking support from price action from the lower timeframe in the forex market.
I hope you like it.
Follow for more strategies and scripts like this.
Fast v Slow Moving Averages Strategy (Variable) [divonn1994]This is a simple moving average based strategy that takes 2 moving averages, a Fast and a Slow one, plots them both, and then decides to enter a 'long' position or exit it based on whether the two lines have crossed each other. It goes 'long when the Fast Moving Average crosses above the Slow Moving Average. This could indicate upwards momentum in prices in the future. It then exits the position when the the Fast Moving Average crosses back below. This could indicate downwards momentum in prices in the future. This is only speculative, though, but sometimes it can be a very good indicator/strategy to predict future action.
I've tried some strategy settings and I found different promising strategies. Here are a few:
BTCUSD ( BitStamp ) 1 Day Timeframe : EMA, Fast length 25 bars, Slow length 62 bars => 28,792x net profit (default)
BTCUSD ( BitStamp ) 1 Day Timeframe : VWMA, Fast length 21 bars, Slow length 60 bars => 15,603x net profit
BTCUSD ( BitStamp ) 1 Day Timeframe : SMA, Fast length 18 bars, Slow length 51 bars => 19,507x net profit
BTCUSD ( BitStamp ) 1 Day Timeframe : RMA, Fast length 20 bars, Slow length 52 bars => 5,729x net profit
BTCUSD ( BitStamp ) 1 Day Timeframe : WMA, Fast length 29 bars, Slow length 60 bars => 19,869x net profit
Features:
-You can choose your preferred moving average: SMA , EMA , WMA , RMA & VWMA .
-You can change the length average for each moving average
-I made the background color Green when you're currently in a long position and Red when not. I made it so you can see when you'd be actively in a trade or not. The Red and Green background colors can be toggled on/off in order to see other indicators more clearly overlayed in the chart, or if you prefer a cleaner look on your charts.
-I also have a plot of the Fast moving average and Slow moving average together. The Opening moving average is Purple, the Closing moving average is White. White on top is a sign of a potential upswing and purple on top is a sign of a potential downswing. I've made this also able to be toggled on/off.
Let me know if you think I should change anything with my script, I'm always open to constructive criticism so feel free to comment below :)
VXD Cloud Edition for Python-Binance-bots.VXD Cloud Edition for Python-Binance-bots.
to overcome sideways market conditions this cloud configured for low timeframe.
every TA is same as VXD Cloud Edition but custom alert message for bots.
Risk:Reward Calculation
Risk of Ruin Setting can now selected between Fixed $ or %
if Buy your Stoploss will be Swing low
if Sell your Stoploss will be Swing high and can be setting at Pivot Setting
then Auto Position Sizing and TP line will be calculated form there and will show in Orange color line (Draw Position Box is available)
Tailing SL when price greater than RR=1
Alert Setting
{{strategy.order.alert_message}}
Python-Bot
github.com
There are 2 mode : one-way mode and hedge mode is different script in my Github profile.
read README.MD and there's video tutorial in thai language.
Pls study app.py and it's script before deploy for your own safty and your own risk, I'm NOT responsible for your loss.
Close v Open Moving Averages Strategy (Variable) [divonn1994]This is a simple moving average based strategy that works well with a few different coin pairings. It takes the moving average 'opening' price and plots it, then takes the moving average 'closing' price and plots it, and then decides to enter a 'long' position or exit it based on whether the two lines have crossed each other. The reasoning is that it 'enters' a position when the average closing price is increasing. This could indicate upwards momentum in prices in the future. It then exits the position when the average closing price is decreasing. This could indicate downwards momentum in prices in the future. This is only speculative, though, but sometimes it can be a very good indicator/strategy to predict future action.
What I've found is that there are a lot of coins that respond very well when the appropriate combination of: 1) type of moving average is chosen (EMA, SMA, RMA, WMA or VWMA) & 2) number of previous bars averaged (typically 10 - 250 bars) are chosen.
Depending on the coin.. each combination of MA and Number of Bars averaged can have completely different levels of success.
Example of Usage:
An example would be that the VWMA works well for BTCUSD (BitStamp), but it has different successfulness based on the time frame. For the 12 hour bar timeframe, with the 66 bar average with the VWMA I found the most success. The next best successful combo I've found is for the 1 Day bar timeframe with the 35 bar average with the VWMA.. They both have a moving average that records about a month, but each have a different successfulness. Below are a few pair combos I think are noticeable because of the net profit, but there are also have a lot of potential coins with different combos:
It's interesting to see the strategy tester change as you change the settings. The below pairs are just some of the most interesting examples I've found, but there might be other combos I haven't even tried on different coin pairs..
Some strategy settings:
BTCUSD (BitStamp) 12 Hr Timeframe : 66 bars, VWMA=> 10,387x net profit
BTCUSD (BitStamp) 1 Day Timeframe : 35 bars, VWMA=> 7,805x net profit
BNBUSD (Binance) 12 Hr Timeframe : 27 bars, VWMA => 15,484x net profit
ETHUSD (BitStamp) 16 Hr Timeframe : 60 bars, SMA => 5,498x net profit
XRPUSD (BitStamp) 16 Hr Timeframe : 33 bars, SMA => 10,178x net profit
I only chose these coin/combos because of their insane net profit factors. There are far more coins with lower net profits but more reliable trade histories.
Also, usually when I want to see which of these strategies might work for a coin pairing I will check between the different Moving Average types, for example the EMA or the SMA, then I also check between the moving average lengths (the number of bars calculated) to see which is most profitable over time.
Features:
-You can choose your preferred moving average: SMA, EMA, WMA, RMA & VWMA.
-You can also adjust the previous number of calculated bars for each moving average.
-I made the background color Green when you're currently in a long position and Red when not. I made it so you can see when you'd be actively in a trade or not. The Red and Green background colors can be toggled on/off in order to see other indicators more clearly overlayed in the chart, or if you prefer a cleaner look on your charts.
-I also have a plot of the Open moving average and Close moving average together. The Opening moving average is Purple, the Closing moving average is White. White on top is a sign of a potential upswing and purple on top is a sign of a potential downswing. I've made this also able to be toggled on/off.
Please, comment interesting pairs below that you've found for everyone :) thank you!
I will post more pairs with my favorite settings as well. I'll also be considering the quality of the trades.. for example: net profit, total trades, percent profitable, profit factor, trade window and max drawdown.
*if anyone can figure out how to change the date range, I woul really appreciate the help. It confuses me -_- *
VIDYA Trend StrategyOne of the most common messages I get is people reaching out asking for quantitative strategies that trade cryptocurrency. This has compelled me to write this script and article, to help provide a quantitative/technical perspective on why I believe most strategies people write for crypto fail catastrophically, and how one might build measures within their strategies that help reduce the risk of that happening. For those that don't trade crypto, know that these approaches are applicable to any market.
I will start off by qualifying up that I mainly trade stocks and ETFs, and I believe that if you trade crypto, you should only be playing with money you are okay with losing. Most published crypto strategies I have seen "work" when the market is going up, and fail catastrophically when it is not. There are far more people trying to sell you a strategy than there are people providing 5-10+ year backtest results on their strategies, with slippage and commissions included, showing how they generated alpha and beat buy/hold. I understand that this community has some really talented people that can create some really awesome things, but I am saying that the vast majority of what you find on the internet will not be strategies that create alpha over the long term.
So, why do so many of these strategies fail?
There is an assumption many people make that cryptocurrency will act just like stocks and ETFs, and it does not. ETF returns have more of a Gaussian probability distribution. Because of this, ETFs have a short term mean reverting behavior that can be capitalized on consistently. Many technical indicators are built to take advantage of this on the equities market. Many people apply them to crypto. Many of those people are drawn down 60-70% right now while there are mean reversion strategies up YTD on equities, even though the equities market is down. Crypto has many more "tail events" that occur 3-4+ standard deviations from the mean.
There is a correlation in many equities and ETF markets for how long an asset continues to do well when it is currently doing well. This is known as momentum, and that correlation and time-horizon is different for different assets. Many technical indicators are built based on this behavior, and then people apply them to cryptocurrency with little risk management assuming they behave the same and and on the same time horizon, without pulling in the statistics to verify if that is actually the case. They do not.
People do not take into account the brokerage commissions and slippage. Brokerage commissions are particularly high with cryptocurrency. The irony here isn't lost to me. When you factor in trading costs, it blows up most short-term trading strategies that might otherwise look profitable.
There is an assumption that it will "always come back" and that you "HODL" through the crash and "buy more." This is why Three Arrows Capital, a $10 billion dollar crypto hedge fund is now in bankruptcy, and no one can find the owners. This is also why many that trade crypto are drawn down 60-70% right now. There are bad risk practices in place, like thinking the martingale gambling strategy is the same as dollar cost averaging while also using those terms interchangeably. They are not the same. The 1st will blow up your trade account, and the 2nd will reduce timing risk. Many people are systematically blowing up their trade accounts/strategies by using martingale and calling it dollar cost averaging. The more risk you are exposing yourself too, the more important your risk management strategy is.
There is an odd assumption some have that you can buy anything and win with technical/quantitative analysis. Technical analysis does not tell you what you should buy, it just tells you when. If you are running a strategy that is going long on an asset that lost 80% of its value in the last year, then your strategy is probably down. That same strategy might be up on a different asset. One might consider a different methodology on choosing assets to trade.
Lastly, most strategies are over-fit, or curve-fit. The more complicated and more parameters/settings you have in your model, the more likely it is just fit to historical data and will not perform similar in live trading. This is one of the reasons why I like simple models with few parameters. They are less likely to be over-fit to historical data. If the strategy only works with 1 set of parameters, and there isn't a range of parameters around it that create alpha, then your strategy is over-fit and is probably not suitable for live trading.
So, what can I do about all of this!?
I created the VIDYA Trend Strategy to provide an example of how one might create a basic model with a basic risk management strategy that might generate long term alpha on a volatile asset, like cryptocurrency. This is one (of many) risk management strategies that can reduce the volatility of your returns when trading any asset. I chose the Variable Index Dynamic Average (VIDYA) for this example because it's calculation filters out some market noise by taking into account the volatility of the underlying asset. I chose a trend following strategy because regressions are capturing behaviors that are not just specific to the equities market.
The more volatile an asset, the more you have to back-off the short term price movement to effectively trend-follow it. Otherwise, you are constantly buying into short term trends that don't represent the trend of the asset, then they reverse and loose money. This is why I am applying a trend following strategy to a 4 hour chart and not a 4 minute chart. It is also important to note that following these long term trends on a volatile asset exposes you to additional risk. So, how might one mitigate some of that risk?
One of the ways of reducing timing risk is scaling into a trade. This is different from "doubling down" or "trippling down." It is really a basic application of dollar cost averaging to reduce timing risk, although DCA would typically happen over a longer time period. If it is really a trend you are following, it will probably still be a trend tomorrow. Trend following strategies have lower win rates because the beginning of a trend often reverses. The more volatile the asset, the more likely that is to happen. However, we can reduce risk of buying into a reversal by slowly scaling into the trend with a small % of equity per trade.
Our example "VIDYA Trend Strategy" executes this by looking at a medium-term, volatility adjusted trend on a 4 hour chart. The script scales into it with 4% of the account equity every 4-hours that the trend is still up. This means you become fully invested after 25 trades/bars. It also means that early in the trade, when you might be more likely to experience a reversal, most of your account equity is not invested and those losses are much smaller. The script sells 100% of the position when it detects a trend reversal. The slower you scale into a trade, the less volatile your equity curve will be. This model also includes slippage and commissions that you can adjust under the "settings" menu.
This fundamental concept of reducing timing risk by scaling into a trade can be applied to any market.
Disclaimer: This is not financial advice. Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
Strategy BackTest Display Statistics - TraderHalaiThis script was born out of my quest to be able to display strategy back test statistics on charts to allow for easier backtesting on devices that do not natively support backtest engine (such as mobile phones, when I am backtesting from away from my computer). There are already a few good ones on TradingView, but most / many are too complicated for my needs.
Found an excellent display backtest engine by 'The Art of Trading'. This script is a snippet of his hard work, with some very minor tweaks and changes. Much respect to the original author.
Full credit to the original author of this script. It can be found here: www.tradingview.com
I decided to modify the script by simplifying it down and make it easier to integrate into existing strategies, using simple copy and paste, by relying on existing tradingview strategy backtester inputs. I have also added 3 additional performance metrics:
- Max Run Up
- Average Win per trade
- Average Loss per trade
As this is a work in progress, I will look to add in more performance metrics in future, as I further develop this script.
Feel free to use this display panel in your scripts and strategies.
Thanks and enjoy :)
Smoothed Heikin Ashi Trend on Chart - TraderHalai BACKTESTSmoothed Heikin Ashi Trend on chart - Backtest
This is a backtest of the Smoothed Heikin Ashi Trend indicator, which computes the reverse candle close price required to flip a Heikin Ashi trend from red to green and vice versa. The original indicator can be found in the scripts section of my profile.
This particular back test uses this indicator with a Trend following paradigm with a percentage-based stop loss.
Note, that backtesting performance is not always indicative of future performance, but it does provide some basis for further development and walk-forward / live testing.
Testing was performed on Bitcoin , as this is a primary target market for me to use this kind of strategy.
Sample Backtesting results as of 10th June 2022:
Backtesting parameters:
Position size: 10% of equity
Long stop: 1% below entry
Short stop: 1% above entry
Repainting: Off
Smoothing: SMA
Period: 10
8 Hour:
Number of Trades: 1046
Gross Return: 249.27 %
CAGR Return: 14.04 %
Max Drawdown: 7.9 %
Win percentage: 28.01 %
Profit Factor (Expectancy): 2.019
Average Loss: 0.33 %
Average Win: 1.69 %
Average Time for Loss: 1 day
Average Time for Win: 5.33 days
1 Day:
Number of Trades: 429
Gross Return: 458.4 %
CAGR Return: 15.76 %
Max Drawdown: 6.37 %
Profit Factor (Expectancy): 2.804
Average Loss: 0.8 %
Average Win: 7.2 %
Average Time for Loss: 3 days
Average Time for Win: 16 days
5 Day:
Number of Trades: 69
Gross Return: 1614.9 %
CAGR Return: 26.7 %
Max Drawdown: 5.7 %
Profit Factor (Expectancy): 10.451
Average Loss: 3.64 %
Average Win: 81.17 %
Average Time for Loss: 15 days
Average Time for Win: 85 days
Analysis:
The strategy is typical amongst trend following strategies with a less regular win rate, but where profits are more significant than losses. Most of the losses are in sideways, low volatility markets. This strategy performs better on higher timeframes, where it shows a positive expectancy of the strategy.
The average win was positively impacted by Bitcoin’s earlier smaller market cap, as the percentage wins earlier were higher.
Overall the strategy shows potential for further development and may be suitable for walk-forward testing and out of sample analysis to be considered for a demo trading account.
Note in an actual trading setup, you may wish to use this with volatility filters, combined with support resistance zones for a better setup.
As always, this post/indicator/strategy is not financial advice, and please do your due diligence before trading this live.
Original indicator links:
On chart version -
Oscillator version -
Update - 27/06/2022
Unfortunately, It appears that the original script had been taken down due to auto-moderation because of concerns with no slippage / commission. I have since adjusted the backtest, and re-uploaded to include the following to address these concerns, and show that I am genuinely trying to give back to the community and not mislead anyone:
1) Include commission of 0.1% - to match Binance's maker fees prior to moving to a fee-less model.
2) Include slippage of 10 ticks (This is a realistic slippage figure from searching online for most crypto exchanges)
3) Adjust account balance to 10,000 - since most of us are not millionaires.
The rest of the backtesting parameters are comparable to previous results:
Backtesting parameters:
Initial capital: 10000 dollars
Position size: 10% of equity
Long stop: 2% below entry
Short stop: 2% above entry
Repainting: Off
Smoothing: SMA
Period: 10
Slippage: 10 ticks
Commission: 0.1%
This script still remains to shows viability / profitablity on higher term timeframes (with slightly higher drawdown), and I have included the backtest report below to document my findings:
8 Hour:
Number of Trades: 1082
Gross Return: 233.02%
CAGR Return: 14.04 %
Max Drawdown: 7.9 %
Win percentage: 25.6%
Profit Factor (Expectancy): 1.627
Average Loss: 0.46 %
Average Win: 2.18 %
Average Time for Loss: 1.33 day
Average Time for Win: 7.33 days
Once again, please do your own research and due dillegence before trading this live. This post is for education and information purposes only, and should not be taken as financial advice.
3ngine Global BoilerplateABOUT THE BOILERPLATE
This strategy is designed to bring consistency to your strategies. It includes a macro EMA filter for filtering out countertrend trades,
an ADX filter to help filter out chop, a session filter to filter out trades outside of desired timeframe, alert messages setup for automation,
laddering in/out of trades (up to 6 rungs), trailing take profit , and beautiful visuals for each entry. There are comments throughout the
strategy that provide further instructions on how to use the boilerplate strategy. This strategy uses `threengine_global_automation_library`
throughout and must be included at the top of the strategy using `import as bot`. This allows you to use dot notation
to access functions in the library - EX: `bot.orderCurrentlyExists(orderID)`.
HOW TO USE THIS STRATEGY
1. Add your inputs
There is a section dedicated for adding your own inputs near the top of the strategy, just above the boilerplate inputs
2. Add your calculations
If your strategy requires calculations, place them in the `Strategy Specific Calculations` section
3. Add your entry criteria
Add your criteria to strategySpecificLongConditions (this gets combined with boilerplate conditions in longConditionsMet)
Add your criteria to strategySpecificShortConditions (this gets combined with boilerplate conditions in shortConditionsMet)
Set your desired entry price (calculated on every bar unless stored as a static variable) to longEntryPrice and shortEntryPrice. ( This will be the FIRST ladder if using laddering capabilities. If you pick 1 for "Ladder In Rungs" this will be the only entry. )
4. Plot anything you want to overlay on the chart in addition to the boilerplate plots and labels. Included in boilerplate:
Average entry price
Stop loss
Trailing stop
Profit target
Ladder rungs
Swing Failure Reversal StrategyThis strategy is using Swing Failure Patterns as a reversion indicator.
The strategy automatically adapts itself to the timeframe of the current chart.
Swing Failure Pattern occurs when the price trend fails to set new highs in uptrend or meet new lows in a downtrend. This pattern helps traders decide when to enter and exit the market. Usually, traders enter in the downtrend i.e. lower price highs and lower price lows, and exit in the uptrend situation i.e. higher price highs and higher price lows. Thus, traders go against the current trend. This helps the traders take advantage of early trend reversal indicators.
Types of Failure Swing :
Failure Swing Top: This occurs when the stock price goes higher whereas the RSI fails to make a higher high and falls below the recent fail point. The Fail Point is where the RSI line is below the recent swing low. This Failure Swing indicates a short position.
Failure Swing Bottom: This occurs when the stock price gets lower whereas RSI fails to make a lower low and rises over the recent fail point. Fail point is the point where the RSI line is above the recent swing high. This Failure Swing indicates a long position.
