EMA20 Cross Strategy with countertrades and signalsEMA20 Cross Strategy Documentation
Overview
The EMA20 Cross Strategy with Counter-Trades and Instant Signals is a Pine Script (version 6) trading strategy designed for the TradingView platform. It implements an Exponential Moving Average (EMA) crossover system to generate buy and sell signals, with optional trend filtering, session-based trading, instant signal processing, and visual/statistical feedback. The strategy supports counter-trades (closing opposing positions before entering new ones) and operates with a fixed trade size in EUR.
Features
EMA Crossover Mechanism:
Uses a short-term EMA (configurable length, default: 1) and a long-term EMA (default: 20) to detect crossovers.
A buy signal is generated when the short EMA crosses above the long EMA.
A sell signal is generated when the short EMA crosses below the long EMA.
Instant Signals:
If enabled (useInstantSignals), signals are based on the current price crossing the short EMA, rather than waiting for the candle close.
This allows faster trade execution but may increase sensitivity to price fluctuations.
Trend Filter:
Optionally filters trades based on the trend direction (useTrendFilter).
Long trades are allowed only when the short EMA (or price, for instant signals) is above the long EMA.
Short trades are allowed only when the short EMA (or price) is below the long EMA.
Session Filter:
Restricts trading to specific market hours (sessionStart, default: 09:00–17:00) if enabled (useSessionFilter).
Ensures trades occur only during active market sessions, reducing exposure to low-liquidity periods.
Customizable Timeframe:
The EMA calculations can use a higher timeframe (e.g., 5m, 15m, 1H, 4H, 1D, default: 1H) via request.security.
This allows the strategy to base signals on longer-term trends while operating on a shorter-term chart.
Trade Management:
Fixed trade size of €100,000 per trade (tradeAmount), with a maximum quantity cap (maxQty = 10,000) to prevent oversized trades.
Counter-trades: Closes short positions before entering a long position and vice versa.
Trades are executed with a minimum quantity of 1 to ensure valid orders.
Visualization:
EMA Lines: The short EMA is colored based on the last signal (green for buy, red for sell, gray for neutral), and the long EMA is orange.
Signal Markers: Displays buy/sell signals as arrows (triangles) above/below candles if enabled (showSignalShapes).
Background/Candle Coloring: Optionally colors the chart background or candles green (bullish) or red (bearish) based on the trend (useColoredBars).
Statistics Display:
If enabled (useStats), a label on the chart shows:
Total closed trades
Open trades
Win rate (%)
Number of winning/losing trades
Profit factor (gross profit / gross loss)
Net profit
Maximum drawdown
Configuration Inputs
EMA Short Length (emaLength): Length of the short-term EMA (default: 1).
Trend EMA Length (trendLength): Length of the long-term EMA (default: 20).
Enable Trend Filter (useTrendFilter): Toggles trend-based filtering (default: true).
Color Candles (useColoredBars): Colors candles instead of the background (default: true).
Enable Session Filter (useSessionFilter): Restricts trading to specified hours (default: false).
Trading Session (sessionStart): Defines trading hours (default: 09:00–17:00).
Show Statistics (useStats): Displays performance stats on the chart (default: true).
Show Signal Arrows (showSignalShapes): Displays buy/sell signals as arrows (default: true).
Use Instant Signals (useInstantSignals): Generates signals based on live price action (default: false).
EMA Timeframe (emaTimeframe): Timeframe for EMA calculations (options: 5m, 15m, 1H, 4H, 1D; default: 1H).
Strategy Logic
Signal Generation:
Standard Mode: Signals are based on EMA crossovers (short EMA crossing long EMA) at candle close.
Instant Mode: Signals are based on the current price crossing the short EMA, enabling faster reactions.
Trade Execution:
On a buy signal, closes any short position and opens a long position.
On a sell signal, closes any long position and opens a short position.
Position size is calculated as the minimum of €100,000 or available equity, divided by the current price, capped at 10,000 units.
Filters:
Trend Filter: Ensures trades align with the trend direction (if enabled).
Session Filter: Restricts trades to user-defined market hours (if enabled).
Visual Feedback
EMA Lines: Provide a clear view of the short and long EMAs, with the short EMA’s color reflecting the latest signal.
Signal Arrows: Large green triangles (buy) below candles or red triangles (sell) above candles for easy signal identification.
Chart Coloring: Highlights bullish (green) or bearish (red) trends via background or candle colors.
Statistics Label: Displays key performance metrics in a label above the chart for quick reference.
Usage Notes
Initial Capital: €100,000 (configurable via initial_capital).
Currency: EUR (set via currency).
Order Processing: Orders are processed at candle close (process_orders_on_close=true) unless instant signals are enabled.
Dynamic Requests: Allows dynamic timeframe adjustments for EMA calculations (dynamic_requests=true).
Platform: Designed for TradingView, compatible with any market supported by the platform (e.g., stocks, forex, crypto).
Example Use Case
Scenario: Trading on a 5-minute chart with a 1-hour EMA timeframe, trend filter enabled, and session filter set to 09:00–17:00.
Behavior: The strategy will:
Calculate EMAs on the 1-hour timeframe.
Generate buy signals when the short EMA crosses above the long EMA (and price is above the long EMA).
Generate sell signals when the short EMA crosses below the long EMA (and price is below the long EMA).
Execute trades only during 09:00–17:00.
Display green/red candles and performance stats on the chart.
Limitations
Instant Signals: May lead to more frequent signals, increasing the risk of false positives in volatile markets.
Fixed Trade Size: Does not adjust dynamically based on market conditions beyond equity and max quantity limits.
Session Filter: Simplified and may not account for complex session rules or holidays.
Statistics: Displayed on-chart, which may clutter the view in smaller charts.
Customization
Adjust emaLength and trendLength to suit different market conditions (e.g., shorter for scalping, longer for swing trading).
Toggle useInstantSignals for faster or more stable signal generation.
Modify sessionStart to align with specific market hours.
Disable useStats or showSignalShapes for a cleaner chart.
This strategy is versatile for both manual and automated trading, offering flexibility for various markets and trading styles while providing clear visual and statistical feedback.
"profit factor" için komut dosyalarını ara
NAS100 and gold Smart Scalping Strategy PRO [Enhanced v2]It works on both Gold, Platinum and USTEC100. Profit factor between 6-9. Great Profit making with risk management
S4_IBS_Mean_Rev_3candleExitOverview:
This is a rules-based, mean reversion strategy designed to trade pullbacks using the Internal Bar Strength (IBS) indicator. The system looks for oversold conditions based on IBS, then enters long trades , holding for a maximum of 3 bars or until the trade becomes profitable.
The strategy includes:
✅ Strict entry rules based on IBS
✅ Hardcoded exit conditions for risk management
✅ A clean visual table summarizing key performance metrics
How It Works:
1. Internal Bar Strength (IBS) Setup:
The IBS is calculated using the previous bar’s price range:
IBS = (Previous Close - Previous Low) / (Previous High - Previous Low)
IBS values closer to 0 indicate price is near the bottom of the previous range, suggesting oversold conditions.
2. Entry Conditions:
IBS must be ≤ 0.25, signaling an oversold setup.
Trade entries are only allowed within a user-defined backtest window (default: 2024).
Only one trade at a time is permitted (long-only strategy).
3. Exit Conditions:
If the price closes higher than the entry price, the trade exits with a profit.
If the trade has been open for 3 bars without showing profit, the trade is forcefully exited.
All trades are closed automatically at the end of the backtest window if still open.
Additional Features:
📊 A real-time performance metrics table is displayed on the chart, showing:
- Total trades
- % of profitable trades
- Total P&L
- Profit Factor
- Max Drawdown
- Best/Worst trade performance
📈 Visual markers indicate trade entries (green triangle) and exits (red triangle) for easy chart interpretation.
Who Is This For?
This strategy is designed for:
✅ Traders exploring systematic mean reversion approaches
✅ Those who prefer strict, rules-based setups with no subjective decision-making
✅ Traders who want built-in performance tracking directly on the chart
Note: This strategy is provided for educational and research purposes. It is a backtested model and past performance does not guarantee future results. Users should paper trade and validate performance before considering real capital.
Trend Scanner ProTrend Scanner Pro, Robust Trend Direction and Strength Estimator
Trend Scanner Pro is designed to evaluate the current market trend with maximum robustness, providing both direction and strength based on statistically reliable data.
This indicator builds upon the core logic of a previous script I developed, called Best SMA Finder. While the original script focused on identifying the most profitable SMA length based on backtested trade performance, Trend Scanner Pro takes that foundation further to serve a different purpose: analyzing and quantifying the actual trend state in real time.
It begins by testing hundreds of SMA lengths, from 10 to 1000 periods. Each one is scored using a custom robustness formula that combines profit factor, number of trades, and win rate. Only SMAs with a sufficient number of trades are retained, ensuring statistical validity and avoiding curve fitting.
The SMA with the highest robustness score is selected as the dynamic reference point. The script then calculates how far the price deviates from it using rolling standard deviation, assigning a trend strength score from -5 (strong bearish) to +5 (strong bullish), with 0 as neutral.
Two detection modes are available:
Slope mode, based on SMA slope reversals
Bias mode, based on directional shifts relative to deviation zones
Optional features:
Deviation bands for visual structure
Candle coloring to reflect trend strength
Compact table showing real-time trend status
This tool is intended for traders who want an adaptive, objective, and statistically grounded assessment of market trend conditions.
5EMA_BB_ScalpingWhat?
In this forum we have earlier published a public scanner called 5EMA BollingerBand Nifty Stock Scanner , which is getting appreciated by the community. That works on top-40 stocks of NSE as a scanner.
Whereas this time, we have come up with the similar concept as a stand-alone indicator which can be applied for any chart, for any timeframe to reap the benifit of reversal trading.
How it works?
This is essentially a reversal/divergence trading strategy, based on a widely used strategy of Power-of-Stocks 5EMA.
To know the divergence from 5-EMA we just check if the high of the candle (on closing) is below the 5-EMA. Then we check if the closing is inside the Bollinger Band (BB). That's a Buy signal. SL: low of the candle, T: middle and higher BB.
Just opposite for selling. 5-EMA low should be above 5-EMA and closing should be inside BB (lesser than BB higher level). That's a Sell signal. SL: high of the candle, T: middle and lower BB.
Along with we compare the current bar's volume with the last-20 bar VWMA (volume weighted moving average) to determine if the volume is high or low.
Present bar's volume is compared with the previous bar's volume to know if it's rising or falling.
VWAP is also determined using `ta.vwap` built-in support of TradingView.
The Bolling Band width is also notified, along with whether it is rising or falling (comparing with previous candle).
What's special?
We love this reversal trading, as it offers many benifits over trend following strategies:
Risk to Reward (RR) is superior.
It _Does Hit_ stop losses, but the stop losses are tiny.
Means, althrough the Profit Factor looks Nahh , however due to superior RR, end of day it ended up in green.
When the day is sideways, it's difficult to trade in trending strategies. This sort of volatility, reversal strategies works better.
It's always tempting to go agaist the wind. Whole world is in Put/PE and you went opposite and enter a Call/CE. And turns out profitable! That's an amazing feeling, as a trader :)
How to trade using this?
* Put any chart
* Apply this screener from Indicators (shortcut to launch indicators is just type / in your keyboard).
* It will show you the Green up arrow when buy alert comes or red down arrow when sell comes. * Also on the top right it will show the latest signal with entry, SL and target.
Disclaimer
* This piece of software does not come up with any warrantee or any rights of not changing it over the future course of time.
* We are not responsible for any trading/investment decision you are taking out of the outcome of this indicator.
ORB 5M + VWAP + Braid Filter + TP 2R o Niveles PreviosORB 5-Minute Breakout Strategy Summary
Strategy Name:
ORB 5M + VWAP + Braid Filter + TP 2R or Previous Levels
Timeframe:
5-minute chart
Trading Window:
9:35 AM to 11:00 AM (New York time)
✅ Entry Conditions:
Opening Range: Defined from 9:30 to 9:35 AM (first 5-minute candle).
Breakout Entry:
Long trade: Price breaks above the opening range high.
Short trade: Price breaks below the opening range low.
Confirmation Filters (All must be met):
Strong candle (green for long, red for short).
VWAP in the direction of the trade.
Braid Filter by Mango2Juice supports the breakout direction (green for long, red for short).
📉 Stop Loss:
Placed at the opposite side of the opening range.
🎯 Take Profit (TP):
+2R (Risk-to-Reward Ratio of 2:1),
or
Closest of the following: previous day’s high/low or premarket levels.
⚙️ Additional Rules:
Only valid signals between 9:35 and 11:00 AM.
Only one trade per breakout direction per day.
Filter out "trap candles" (very small or indecisive candles).
Avoid trading after 11:00 AM.
📊 Performance Goals:
Maintain a high Profit Factor (above 3 ideally).
Focus on tickers with good historical performance under this strategy (e.g., AMZN, PLTR, CVNA).
Smart Fib StrategySmart Fibonacci Strategy
This advanced trading strategy combines the power of adaptive SMA entries with Fibonacci-based exit levels to create a comprehensive trend-following system that self-optimizes based on historical market conditions. Credit goes to Julien_Eche who created the "Best SMA Finder" which received an Editors Pick award.
Strategy Overview
The Smart Fibonacci Strategy employs a two-pronged approach to trading:
1. Intelligent Entries: Uses a self-optimizing SMA (Simple Moving Average) to identify optimal entry points. The system automatically tests multiple SMA lengths against historical data to determine which period provides the most robust trading signals.
2. Fibonacci-Based Exits: Implements ATR-adjusted Fibonacci bands to establish precise exit targets, with risk-management options ranging from conservative to aggressive.
This dual methodology creates a balanced system that adapts to changing market conditions while providing clear visual reference points for trade management.
Key Features
- **Self-Optimizing Entries**: Automatically calculates the most profitable SMA length based on historical performance
- **Adjustable Risk Parameters**: Choose between low-risk and high-risk exit targets
- **Directional Flexibility**: Trade long-only, short-only, or both directions
- **Visualization Tools**: Customizable display of entry lines and exit bands
- **Performance Statistics**: Comprehensive stats table showing key metrics
- **Smoothing Option**: Reduces noise in the Fibonacci bands for cleaner signals
Trading Rules
Entry Signals
- **Long Entry**: When price crosses above the blue center line (optimal SMA)
- **Short Entry**: When price crosses below the blue center line (optimal SMA)
### Exit Levels
- **Low Risk Option**: Exit at the first Fibonacci band (1.618 * ATR)
- **High Risk Option**: Exit at the second Fibonacci band (2.618 * ATR)
Strategy Parameters
Display Settings
- Toggle visibility of the stats table and indicator components
Strategy Settings
- Select trading direction (long, short, or both)
- Choose exit method (low risk or high risk)
- Set minimum trades threshold for SMA optimization
SMA Settings
- Option to use auto-optimized or fixed-length SMA
- Customize SMA length when using fixed option
Fibonacci Settings
- Adjust ATR period and SMA basis for Fibonacci bands
- Enable/disable smoothing function
- Customize Fibonacci ratio multipliers
Appearance Settings
- Modify colors, line widths, and transparency
Optimization Methodology
The strategy employs a sophisticated optimization algorithm that:
1. Tests multiple SMA lengths against historical data
2. Evaluates performance based on trade count, profit factor, and win rate
3. Calculates a "robustness score" that balances profitability with statistical significance
4. Selects the SMA length with the highest robustness score
This ensures that the strategy's entry signals are continuously adapting to the most effective parameters for current market conditions.
Risk Management
Position sizing is fixed at $2,000 per trade, allowing for consistent exposure across all trading setups. The Fibonacci-based exit system provides two distinct risk management approaches:
- **Conservative Approach**: Using the first Fibonacci band for exits produces more frequent but smaller wins
- **Aggressive Approach**: Using the second Fibonacci band allows for larger potential gains at the cost of increased volatility
Ideal Usage
This strategy is best suited for:
- Trending markets with clear directional moves
- Timeframes from 4H to Daily for most balanced results
- Instruments with moderate volatility (stocks, forex, commodities)
Traders can further enhance performance by combining this strategy with broader market analysis to confirm the prevailing trend direction.
Daily Breakout + Daily Shadow By RouroThis script is a Pine v5 strategy designed to detect daily candle body breakouts and execute them on any intraday timeframe, while also providing:
Daily Data Retrieval
Using request.security(..., "D", ...) it fetches the OHLC and timestamp of the daily candle, regardless of the chart’s current timeframe.
Calculation of Yesterday’s and Day-Before-Yesterday’s Bodies
b1High and b1Low → the high/low of yesterday’s daily candle body
b2High and b2Low → the high/low of the previous day’s body
Detection of the First Intraday Bar After a New Day
By using ta.change(time("D")), it marks the start of each new trading day.
Drawing the Previous Day’s “Shadow” on the Chart
It overlays a box (box.new) and two wick lines (line.new) with configurable colors and transparency, so you can clearly see the full range of yesterday’s candle on any intraday chart.
Automatic End-of-Day Position Closure
It will automatically close any open position at the start of the next day to avoid unintended rollovers.
Entry Signals
On the very first intraday bar after the daily close:
Long if yesterday’s close broke above the body of the day before yesterday
Short if yesterday’s close broke below the body of the day before yesterday
…which triggers a strategy.entry at the intraday open.
Fully Customizable Stop-Loss and Take-Profit
SL options:
Opposite end of yesterday’s body
Fixed pips from entry
A risk-reward ratio on yesterday’s wick
Optional “safety SL” in fixed pips that overrides the above
TP options:
Fixed pips
Yesterday’s wick extreme (high/low)
Partial exit on the wick (TP1), then second exit (TP2) either:
At a multiplied RR
Or at the daily close (“Close of Day”)
You can also choose to move SL to breakeven after TP1 is hit.
Live Metrics Table
In the upper-right corner it displays in real time:
Start of backtest (date of first trade)
Number of ✅ Winning trades and ❌ Losing trades
Total number of trades
Win rate (%)
Profit Factor
All within a fixed table layout so it never runs out of rows or columns.
Williams %R StrategyThe Williams %R Strategy implemented in Pine Script™ is a trading system based on the Williams %R momentum oscillator. The Williams %R indicator, developed by Larry Williams in 1973, is designed to identify overbought and oversold conditions in a market, helping traders time their entries and exits effectively (Williams, 1979). This particular strategy aims to capitalize on short-term price reversals in the S&P 500 (SPY) by identifying extreme values in the Williams %R indicator and using them as trading signals.
Strategy Rules:
Entry Signal:
A long position is entered when the Williams %R value falls below -90, indicating an oversold condition. This threshold suggests that the market may be near a short-term bottom, and prices are likely to reverse or rebound in the short term (Murphy, 1999).
Exit Signal:
The long position is exited when:
The current close price is higher than the previous day’s high, or
The Williams %R indicator rises above -30, indicating that the market is no longer oversold and may be approaching an overbought condition (Wilder, 1978).
Technical Analysis and Rationale:
The Williams %R is a momentum oscillator that measures the level of the close relative to the high-low range over a specific period, providing insight into whether an asset is trading near its highs or lows. The indicator values range from -100 (most oversold) to 0 (most overbought). When the value falls below -90, it indicates an oversold condition where a reversal is likely (Achelis, 2000). This strategy uses this oversold threshold as a signal to initiate long positions, betting on mean reversion—an established principle in financial markets where prices tend to revert to their historical averages (Jegadeesh & Titman, 1993).
Optimization and Performance:
The strategy allows for an adjustable lookback period (between 2 and 25 days) to determine the range used in the Williams %R calculation. Empirical tests show that shorter lookback periods (e.g., 2 days) yield the most favorable outcomes, with profit factors exceeding 2. This finding aligns with studies suggesting that shorter timeframes can effectively capture short-term momentum reversals (Fama, 1970; Jegadeesh & Titman, 1993).
Scientific Context:
Mean Reversion Theory: The strategy’s core relies on mean reversion, which suggests that prices fluctuate around a mean or average value. Research shows that such strategies, particularly those using oscillators like Williams %R, can exploit these temporary deviations (Poterba & Summers, 1988).
Behavioral Finance: The overbought and oversold conditions identified by Williams %R align with psychological factors influencing trading behavior, such as herding and panic selling, which often create opportunities for price reversals (Shiller, 2003).
Conclusion:
This Williams %R-based strategy utilizes a well-established momentum oscillator to time entries and exits in the S&P 500. By targeting extreme oversold conditions and exiting when these conditions revert or exceed historical ranges, the strategy aims to capture short-term gains. Scientific evidence supports the effectiveness of short-term mean reversion strategies, particularly when using indicators sensitive to momentum shifts.
References:
Achelis, S. B. (2000). Technical Analysis from A to Z. McGraw Hill.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Williams, L. (1979). How I Made One Million Dollars… Last Year… Trading Commodities. Windsor Books.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
This explanation provides a scientific and evidence-based perspective on the Williams %R trading strategy, aligning it with fundamental principles in technical analysis and behavioral finance.
Moving Average Trap Strategy by D. BrigagliaThis is a strategy that follows the 200 periods moving average and fades the cross of ma3, ma5 and ma8. It is designed for profiting by mean reversion while at the same time respecting long term trend. It is designed for long term trending markets such as stocks and stock indices.
In this backtest, the strategy shows the ability to beat the S&P500 index with an average slippage set to 2 ticks. The number of trades is good (350), the profit factor is acceptable (1.67). The drawdowns are also reduced compared to the underlying asset.
Nothing of my content is financial advice.
Nifty36ScannerThis code is written for traders to be able to automatically scan 36 stocks of their choice for MACD , EMA200 + SuperTrend and Half Trend . Traders can be on any chart, and if they keep this scanner/indicator on , it will start displaying stocks meeting scanning criteria on the same window without having to go to Screener section and running it again and again. It will save time for traders and give them real time signals.
Indicators for scanning stocks are:
MACD
EMA200
Supertrend
HalfTrend - originally developed by EVERGET
Combination of EMA200 crossover/under and MACD crossover/under has worked well for me for long time, so using this combination as one of the criteria to
Scan the stocks. Using Everget's Half Trend method confirms the signal given by MACD , EMA200 and Supertrend Crossover.
I have added 36 of my favourite stocks from Nifty 50 lot. Users of this script can use the same stocks or change it by going into the settings of this scanner.
The Code is divided into 3 Sections
Section 1: Accepting input from users as boolean so that they can scan on the basis of one of the criteria or any combination of the criteria.
Section 2: "Screener function" to calculate Buy/ Sell on the basis of scanning criteria selected y the user.
screener=>
= ta.supertrend(2.5,10)
Buy/Sell on the basis of Supertrend crossing Close of the candle
//using ta.macd function to calculate MACD and Signal
= ta.macd(close, 12, 26, 9)
using HalfTrend indicator to calculate Buy/Sell signals , removed all the plotting functions from the code of Half Trend
Bringing Stock Symbols in S series variables
s1=input.symbol('NSE:NIFTY1!', title='Symbol1', group="Nifty50List", inline='0')
Assigning Bull/Bear ( Buy/Sell) signals to each stocks selected
=request.security(s1, tf, screener())
Assign BUY to all the stocks showing Buy signals using
buy_label1:= c1?buy_label1+str.tostring(s1)+'\n': buy_label1
Follow the same process for SELL Signals
Section 3: Plotting labels for the BUY/SELL result on the in terms of label for any stocks meeting the criteria with deletion of any previous signals to avoid clutter on the chart with so many signals generated in each candle
Display Buy siganaling stocks in teh form of label using Label.new function with parameters as follows:
barindex
close as series
color
textcolor
style as label_up,
yloc =price
textalign=left
Delete all the previous labels
label.delete(lab_buy )
STOCKS SELECTION
We have given range f 36 stocks from NIFTY 50 that can be selected at anytime,. User can chose their own 36 stocks using setting button.
INDICATORS SELECTION
1. MACD: It i sone of the most reliable trading strategy with 39.3% Success rate with 1.187 as profit factor for NIFTY Index on Daily time frame
2. EAM200 + Super trend : Combination of EMA200 crossover and Super trend removes any false positives and considered a very reliable way of scanning for Buy/Sell signals
3. HALF TREND: Originally developed as an indicator by Everget and modified as strategy by AlgoMojo, it generates Buy/Sell signals with 40.2% success rate with 1.469 as profit faction, on 15 minutes timeframe.
Open High Low StrategyThis is a very simple, yet effective and to some extend widely followed scalping strategy to capture the underling sentiments of the counter whether it will go up or down.
What is it?
This is Open-High-Low (OLH) strategy.
As you already aware of Candlestick patterns, there is patterns called as Marubozu patterns where the sell wick or buy wick either ceases to exists (or very small). This is exactly in the same principle.
In OLH strategy: The buy signal appears when the Open Price is the Low Price. It means if you draw the candlestick, there is no bottom wick. So after the opening of the candle, the demand drives the price up to the level, some selling may or may not come and closes in green. This indicates a strong upward biasness of the underlying counter.
Similarly, a sell signal appears when the Open price is the High Price. It means there is no upper wick. So there is no buying pressure, since the opening of the candle, sellers are in force and pulls down the price to a closing.
This strategy generates the signal at the close of the candle (technically barstate.isconfirmed). Because until the bar is real-time there is no option to know the final closing or high. So you will see the bar on which it generates the buy or sell signal is actually indicates the previous bar as OLH bar.
To determine the Stop-Loss, it uses the most widely known SL calculation of:
For buy signal, it takes the low of the last 7 candles and substract the ATR (Average True Range) of 14-period.
For sell signal, it takes the high of the last 7 candles and add it to the ATR (Average True Range) of 14-period.
One can plot the SL lines as dotted green and red lines as well to see visually.
Default Risk:Reward is 1:2, Can be customizable.
What is Unique?
Of course the utter simplistic nature of this strategy is it's key point. Very easy and intuitive to understand.
There are awesome strategies in this forum that talks about the various indicators combinations and what not.
Instead of all this, in a 15m NSE:NIFTY chart, it generates a good ~ 47% profit-factor with 1:2 Risk Reward ratio. Means if you loose a trade you will loose 1% of account and if you win you will gain 2%. Means 3 trades (2 profits and 1 loss) in a trading session result 3% overall gain for the day. (Assuming you are ready with 1% draw down of your account per trade, at max).
Disclaimer:
This piece of software does not come up with any warrantee or any rights of not changing it over the future course of time.
We are not responsible for any trading/investment decision you are taking out of the outcome of this indicator.
Vin's Playzone Strategy How it works
Playzone is a very simple system, utilizing just two exponential moving
averages. The 'Zones' in which different 'actions' should be taken is
highlighted with different colors on the chart. Calculations for the zones
are based on the relative position of price to the two EMA lines and the
relationship between the two EMAs
How to use
The basic method for using Playzone is to follow the green/red color.
Buy when bar closes in green.
Sell when bar closes in red.
Using it this way is safe but slow and is expected to have around 35-40%
accuracy, while yielding around 2-3 profit factors. The system works best
on larger time frames.
The more advanced method uses the zones to switch between different
trading system and biases, or in conjunction with other indicators.
example 1:
Buy when Yellow-Green and Bullish Divergence between price and RSI is visible,
if not Buy on Green and vise-versa
example 2:
Set up a long-biased grid and trade long only when actionzone is in green
change the bias to short when actionzone turns to te bearish side(red)
(Look at colors on a larger time frame)
"We let the market tell us what to do, Not to outguess what the market gonna do."
Hull MA of RSI StrategyThis simple strategy base on RSI value of Close Price, High Price, Low Price, Median Price and RSI value smoothed by Hull Moving Average.
1. Optimize parameter on BTC H1 Binance chart
RSI period: 13
Hull MA period: 3
Middle Channel: 55-45
Overbough / Oversold: 70-30
2. Setup
2.1 Long Condition
- RSI of Close Price crossunder Overbought
- Close Price lower than Median Price (HL2)
- RSI of Median Price above Overbought
2.2 Close Long Position
- RSI of Close Price crossover Overbought (Take profit)
or
- RSI of Low Price crossunder upper value of Middle Channel (Stop loss)
2.2 Short Condition
- RSI of Close Price crossover Oversold
- Close Price higher than Median Price (HL2)
- RSI of Median Price below Oversold
2.2 Close Long Position
- RSI of Close Price crossunder Oversold (Take profit)
or
- RSI of High Price crossover lower value of Middle Channel (Stop loss)
3. Idea
- Follow strong momentum of Price to catch Flash Buy/Sell Bar in Crypto Market
- RSI of High Price and Low Price help to regconize setup failure quickly.
- This case study desire to find a balance of Winrate, Profit factor, Sharpe Ratio
High/low crypto strategy with MACD/PSAR/ATR/EWaveToday I am glad to bring you another great creation of mine, this time suited for crypto markets.
MARKET
Its a high and low strategy, designed for crypto markets( btcusd , btcusdt and so on), and suited for for higher time charts : like 1hour, 4hours, 1 day and so on.
Preferably to use 1h time charts.
COMPONENTS
Higher high and lower low between different candle points
MACD with simple moving average
PSAR for uptrend and downtrend
Trenddirection made of a modified moving average and ATR
And lastly elliot wave oscillator to have an even better precision for entries and exits.
ENTRY DESCRIPTION
For entries we have : when the first condition is meet(we have a succession on higher high or lower lows), then we check the macd histogram level, then we pair that with psar for the direction of the trend, then we check the trend direction based on atr levels with MA applied on it and lastly to confirm the direction we check the level of elliot wave oscillator. If they are all on the same page we have a short or a long entry.
STATS
Its a low win percentage , we usually have between 10-20% win rate, but at the same time we use a 1:30 risk reward ratio .
By this we achieve an avg profit factor between 1.5- 2.5 between different currencies.
RISK MANAGEMENT
In this example, the stop loss is 0.5% of the price fluctuation ( 10.000 -> 9950 our sl), and tp is 15% (10.000 - > 11500).
In this example also we use a 100.000 capital account, risking 5% on each trade, but since its underleveraged, we only use 5000 of that ammount on every trade. With leveraged it can be achieved better profits and of course at the same time we will encounter bigger losses.
The comission applied is 5$ and a slippage of 5 points aswell added.
For any questions or suggestions regarding the script , please let me know.
Lagged Donchian Channel + EMAThis strategy is based on a lagged 24 periods Donchian Channel and a 200 periods EMA .
The enter positions are calculated this way :
Bull entry
1. we wait for the close of a candle below the channel and it must be below the 200 EMA
2. the following candle must be a green one and close in the lagged channel
3. we put a long order at the close of the second candle, a stop loss at the low of last 3 candles and a x3 take profit
Bear entry
1. we wait for the close of a candle above the channel and it must be above the 200 EMA
2. the following candle must be a red one and close in the lagged channel
3. we put a short order at the close of the second candle, a stop loss at the high of last 3 candles and a x3 take profit
For both long or short positions :
If the order is not filled, it's cancelled if the price reach 50% of the TP or if the price reach the stop loss level
The position is closed if a new bear/bull condition appears in the other side of the position (if a bear appears when you're long and inversement)
Features :
Position calculator's included with leverage option
Labels of position can be plotted or not
Bull/Bear channels can be plotted with red and green filled
All parameters can be changed for backtesting
Better results have been got with defaults parameters on LTCUSDTPERP in H1 timeframe => profit factor of 2.84 with almost 100 positions.
Hope this strategy will be useful and it would be cool if I could get feedback, comments or better combinations of parameters !!
Don't hesitate to like and leave a comment ;)
@Mysteriown
RSI V Pattern strategyThis strategy based on RSI for swing trading or short term trading
Strategy Rules
=============
LONG
1. ema20 is above ema50 --- candles are colored green on the chart
2. RSI value sharply coming up
previous candle1 low is previous candle2 low and previous candle1 RSI value is less than previous candle2
current candle RSI value is greater than previous candle1 and crossing above 30
above which makes a V shape on RSI indicator, colored in yellow on the chart , price bar is colored in yellow
3. Enter Long when the above V pattern occurs
EXIT LONG
1. when the RSI reaches 70 , close half position and move stop loss to up
2. when RSI reaches high value 90, close 3/4 position
3. when RSI crossing below 10 OR stopLoss hit , whichever happens first , close whole position
Note : take profit levels are colored in blue on RSI and Price candles
I have tested SPY , QQQ on daily chart , performance results are with 80% win rate and more than 3 profit factor
Happy Trading
Monthly MA Close Generates buy or sell signal if monthly candle closes above or below the signal MA.
Long positions only.
Inputs:
-Change timeframe MA
-Change period MA
-Use SMA or EMA
-Display MA
-Use another ticker as signal
-Select time period for backtesting
This script is not necessarily written to maximize profits, but to minimize losses.
Although it can outperform 'Buy & Hold' on some occasions when there is a multiple month bearisch trend.
You can optimise this strategy by changing the signal MA inputs.
I would suggest aiming for the best Profit Factor starting from the monthly ("M") setting.
You can always fine-tune the results at a lower timeframe.
The option to use another ticker for providing signals can give you a more stable and unified results.
For example using AMEX:SPY as signal with default parameters gives better results with NASDAQ:AAPL than if you would use NASDAQ:AAPL itself.
I used the anti-repainting function from PineCoders to prevent repainting.
This script is best used for multi-month trading positions & Daily or 4H setting of your chart.
CDC ActionZone V3 2020## CDC ActionZone V3 2020 ##
This is an update to my earlier script, CDC ActionZone V2
The two scripts works slightly differently with V3 reacting slightly faster.
The main update is focused around conforming the standard to Pine Script V4.
## How it works ##
ActionZone is a very simple system, utilizing just two exponential moving
averages. The 'Zones' in which different 'actions' should be taken is
highlighted with different colors on the chart. Calculations for the zones
are based on the relative position of price to the two EMA lines and the
relationship between the two EMAs
CDCActionZone is your barebones basic, tried and true, trend following system
that is very simple to follow and has also proven to be relatively safe.
## How to use ##
The basic method for using ActionZone is to follow the green/red color.
Buy when bar closes in green.
Sell when bar closes in red.
There is a small label to help with reading the buy and sell signal.
Using it this way is safe but slow and is expected to have around 35-40%
accuracy, while yielding around 2-3 profit factors. The system works best
on larger time frames.
The more advanced method uses the zones to switch between different
trading system and biases, or in conjunction with other indicators.
example 1:
Buy when blue and Bullish Divergence between price and RSI is visible,
if not Buy on Green and vise-versa
example 2:
Set up a long-biased grid and trade long only when actionzone is in
green, yellow or orange.
change the bias to short when actionzone turns to te bearish side
(red, blue, aqua)
(Look at colors on a larger time frame)
## Note ##
The price field is set to close by default. change to either HL2 or OHLC4
when using the system in intraday timeframes or on market that does not close
(ie. Cryptocurrencies)
## Note2 ##
The fixed timeframe mode is for looking at the current signal on a larger time frame
ie. When looking at charts on 1h you can turn on fixed time frame on 1D to see the
current 'zone' on the daily chart plotted on to the hourly chart.
This is useful if you wanted to use the system's 'Zones' in conjunction with other
types of signals like Stochastic RSI, for example.
BitMEX pump catcherWhat is going on here? This strategy is pretty simple. We start by measuring a very long chunk of volume history on BitMEX:XBTUSD 1 hour chart to find out if the current volume is high or low. At 1.0 the indicator is showing we are at 100% of normal historical volume. The blue line is a measure of recent volume! This indicator gets interested when the volume drops below 90% of the regular volume (0.9), and then comes back up over 90%. There's usually a pump of increased price activity during this time. When the 0.9 line is crossed by the blue line, the indicator surveys the last 2 bars of price action to figure out which way we're going, long or short. Green is long. Red is short. To exit the trade we use a 7 period fast ema of the volume crossing under an 11 ema slower period which shows declining interest in the market signifying an end to the pump or dump. The profit factor is quite high with 5x leverage, but historically we see 50% drawdown -- very risky. 1x leverage looks nice and tight with very low drawdown. Play with the inputs to see what matches your own risk profile. I would not recommend taking this into much lower timeframes as trading fees are not included in the profit calculations. Please don't get burned trading on stupid high leverage. This indicator is probably not going to work well on alts, as Bitcoin FOMO build up and behavior is different. This whole indicator is tuned to Bitcoin, and attempts to trade only the meatiest part of the market moves.
Weaknesses: it can sometimes pick to trade the wrong direction if if hits support or resistance and changes direction after a trade is entered. Use a stoploss.
Strengths: It usually gets things right. Historically over 57% right.
Use at your own risk!
Strategy for The Bitcoin Buy/Sell IndicatorThis is the strategy for
Starting with a capital of $3,000 XBT , one might have $15,975 dollar worth of XBT plus whatever the bitcoin has appreciated over the years.
The Sharpe Ratio: 0.586, Net Profit is 532%, 57 closed trades from 2017 till today, Profit factor of 3.745 (aka for every dollar loss, there is 3.745 dollar profit) with 14% drawdown .
Let that sink in.
Adaptive Zero Lag EMA [STUDY]A user has asked for the Study/Indicator version of this Strategy .
If you encounter the error "loop....>100ms" simply toggle the eye icon to hide and unhide the indicator
The following is simply quoted from my previous post for your convenience: (obviously there won't be risk, Stop Loss, or Take profit parameters!)
OPERATING PRINCIPLE
The strategy is based on Ehlers idea that any indicator can be turned into a signal-producing trade system through smoothing and other filtering processes.
In fact, I'm using his Zero Lag EMA ( ZLEMA ) as a baseline indicator as well as some code snippets he has made public (1). God bless open source!
Next, I've provided the option to use an Instantaneous Frequency Measurement (IFM) method, which will adaptively choose the best period for the ZLEMA (2)
I've written other studies that use the differential calculus approximations for IFM, so it was only natural to include them in this strategy.
The primary two are Cosine IFM (3) and In-phase Quadrature IFM (4). You can also find an indicator with both plotted and the ability to average them together, as one IFM prefers long periods and the other short. (5)
BEFORE WE BEGIN
1. This strategy only runs on "normal" FX pairs ( EURUSD , GBPJPY , AUDUSD ...) and will fail on Metals or Commodities.
Cryptos are largely untested.
2. Please run it on these time frames: M15 to D.
Anything outside this range will likely fail.
HOW TO USE AND SUCCEED
1. If the Default settings don't produce good results right off the bat, then lower gain limit to 1 or 2 and threshold to 0.01.
2. Test each setting under adaptive method. If you want to leave it Off, then I'd recommend using some kind of IFM (see my links below) to
discover the most efficient period to use.
3. Once you have the best adaptive method chosen, begin incrementing gain limit until you find a nice balance between profit factor ( PF ) and drawdown.
4. Now, begin incrementing threshold. The goal is to have PF above 2 and a drawdown as low as possible.
5. Finally, change the source! Typically, close is the best option, but I have run into cases where high
yielded the highest returns and win rate.
6. Sit back, relax, and tweak the risk until you're happy with the return and drawdown amounts.
ADVANCED
You may need to adjust take profit (TP) points and stop loss (SL) points to create the best entry possible. Don't be greedy! You'll likely have poor
results if the TP is set to 300 and SL is 50.
If you are trading a pair that has a long Dominant Cycle Period, then you may increase Max Period to allow the IFM
to accept longer periods. Any period above the Max Period will be rejected. This may increase lag time!
Cheers and good luck trading!
-DasanC
(1)www.mesasoftware.com
(2)www.jamesgoulding.com
(3) Cosine IFM
(4) I-Q IFM
(5) Averaging IFM
IFM stands for Instantaneous frequency measurement
Adaptive Zero Lag EMA v2This is my most successful strategy to date! Please enjoy and join the Open Source movement by sharing your code and ideas online!
OPERATING PRINCIPLE
The strategy is based on Ehlers idea that any indicator can be turned into a signal-producing trade system through smoothing and other filtering processes.
In fact, I'm using his Zero Lag EMA (ZLEMA) as a baseline indicator as well as some code snippets he has made public (1). God bless open source!
Next, I've provided the option to use an Instantaneous Frequency Measurement (IFM) method, which will adaptively choose the best period for the ZLEMA (2)
I've written other studies that use the differential calculus approximations for IFM, so it was only natural to include them in this strategy.
The primary two are Cosine IFM (3) and In-phase Quadrature IFM (4). You can also find an indicator with both plotted and the ability to average them together, as one IFM prefers long periods and the other short. (5)
BEFORE WE BEGIN
1. This strategy only runs on "normal" FX pairs (EURUSD, GBPJPY, AUDUSD ...) and will fail on Metals or Commodities.
Cryptos are largely untested.
2. Please run it on these time frames: M15 to D.
Anything outside this range will likely fail.
HOW TO USE AND SUCCEED
1. If the Default settings don't produce good results right off the bat, then lower gain limit to 1 or 2 and threshold to 0.01.
2. Test each setting under adaptive method . If you want to leave it Off , then I'd recommend using some kind of IFM (see my links below) to
discover the most efficient period to use.
3. Once you have the best adaptive method chosen, begin incrementing gain limit until you find a nice balance between profit factor (PF) and drawdown.
4. Now, begin incrementing threshold . The goal is to have PF above 2 and a drawdown as low as possible.
5. Finally, change the source ! Typically, close is the best option, but I have run into cases where high
yielded the highest returns and win rate.
6. Sit back, relax, and tweak the risk until you're happy with the return and drawdown amounts.
ADVANCED
You may need to adjust take profit (TP) points and stop loss (SL) points to create the best entry possible. Don't be greedy! You'll likely have poor
results if the TP is set to 300 and SL is 50.
If you are trading a pair that has a long Dominant Cycle Period , then you may increase Max Period to allow the IFM
to accept longer periods. Any period above the Max Period will be rejected. This may increase lag time!
Cheers and good luck trading!
-DasanC
PS - This code doesn't repaint or have future-leak, which was present in Pinescript v2.
PPS - Believe me! These returns are typical! Sometimes you must push aside the "if it's too good to be true..." mindset that society has ingrained in you.
Do you really believe the most successful pass up opportunities before investigating them? ;)
(1) Ehlers & Ric Zero Lag EMA
(2) Measuring Cycles by Ehlers
(3) Cosine IFM
(4) Inphase Quadrature IFM
(5) Averaging IFM
