Lot Size Calculator by MenolakRugiThe Lot Size Formula in forex trading is a critical tool that offers several key benefits to traders:
🟢Risk Management: By using the formula, traders can control the amount of capital they risk on each trade. This helps prevent excessive losses by aligning the lot size with a predefined risk tolerance, such as 1% or 2% of the account balance.
🟢Consistent Position Sizing: The formula ensures that position sizes are calculated based on the specific trade setup, including the distance to the stop loss. This consistency helps avoid over-leveraging and reduces the emotional aspect of trading.
🟢Adaptability: The lot size can be adjusted according to different currency pairs and market conditions. This flexibility ensures that traders can apply the formula across various trading instruments and environments.
🟢Improved Profit Potential: By managing risk effectively, traders can protect their capital while maximizing profit opportunities. When losses are controlled, traders are able to stay in the market longer and compound their gains over time.
🟢Precision in Trade Planning: Calculating the lot size allows traders to plan their trades more precisely, aligning their strategies with the amount they are willing to risk. This leads to more disciplined and structured trading, reducing impulsive decisions.
In summary, the lot size formula helps maintain a balanced approach to trading, where both risk and reward are carefully managed to increase the chances of long-term success.
在腳本中搜尋"stop loss"
Intramarket Difference Index StrategyHi Traders !!
The IDI Strategy:
In layman’s terms this strategy compares two indicators across markets and exploits their differences.
note: it is best the two markets are correlated as then we know we are trading a short to long term deviation from both markets' general trend with the assumption both markets will trend again sometime in the future thereby exhausting our trading opportunity.
📍 Import Notes:
This Strategy calculates trade position size independently (i.e. risk per trade is controlled in the user inputs tab), this means that the ‘Order size’ input in the ‘Properties’ tab will have no effect on the strategy. Why ? because this allows us to define custom position size algorithms which we can use to improve our risk management and equity growth over time. Here we have the option to have fixed quantity or fixed percentage of equity ATR (Average True Range) based stops in addition to the turtle trading position size algorithm.
‘Pyramiding’ does not work for this strategy’, similar to the order size input togeling this input will have no effect on the strategy as the strategy explicitly defines the maximum order size to be 1.
This strategy is not perfect, and as of writing of this post I have not traded this algo.
Always take your time to backtests and debug the strategy.
🔷 The IDI Strategy:
By default this strategy pulls data from your current TV chart and then compares it to the base market, be default BINANCE:BTCUSD . The strategy pulls SMA and RSI data from either market (we call this the difference data), standardizes the data (solving the different unit problem across markets) such that it is comparable and then differentiates the data, calling the result of this transformation and difference the Intramarket Difference (ID). The formula for the the ID is
ID = market1_diff_data - market2_diff_data (1)
Where
market(i)_diff_data = diff_data / ATR(j)_market(i)^0.5,
where i = {1, 2} and j = the natural numbers excluding 0
Formula (1) interpretation is the following
When ID > 0: this means the current market outperforms the base market
When ID = 0: Markets are at long run equilibrium
When ID < 0: this means the current market underperforms the base market
To form the strategy we define one of two strategy type’s which are Trend and Mean Revesion respectively.
🔸 Trend Case:
Given the ‘‘Strategy Type’’ is equal to TREND we define a threshold for which if the ID crosses over we go long and if the ID crosses under the negative of the threshold we go short.
The motivating idea is that the ID is an indicator of the two symbols being out of sync, and given we know volatility clustering, momentum and mean reversion of anomalies to be a stylised fact of financial data we can construct a trading premise. Let's first talk more about this premise.
For some markets (cryptocurrency markets - synthetic symbols in TV) the stylised fact of momentum is true, this means that higher momentum is followed by higher momentum, and given we know momentum to be a vector quantity (with magnitude and direction) this momentum can be both positive and negative i.e. when the ID crosses above some threshold we make an assumption it will continue in that direction for some time before executing back to its long run equilibrium of 0 which is a reasonable assumption to make if the market are correlated. For example for the BTCUSD - ETHUSD pair, if the ID > +threshold (inputs for MA and RSI based ID thresholds are found under the ‘‘INTRAMARKET DIFFERENCE INDEX’’ group’), ETHUSD outperforms BTCUSD, we assume the momentum to continue so we go long ETHUSD.
In the standard case we would exit the market when the IDI returns to its long run equilibrium of 0 (for the positive case the ID may return to 0 because ETH’s difference data may have decreased or BTC’s difference data may have increased). However in this strategy we will not define this as our exit condition, why ?
This is because we want to ‘‘let our winners run’’, to achieve this we define a trailing Donchian Channel stop loss (along with a fixed ATR based stop as our volatility proxy). If we were too use the 0 exit the strategy may print a buy signal (ID > +threshold in the simple case, market regimes may be used), return to 0 and then print another buy signal, and this process can loop may times, this high trade frequency means we fail capture the entire market move lowering our profit, furthermore on lower time frames this high trade frequencies mean we pay more transaction costs (due to price slippage, commission and big-ask spread) which means less profit.
By capturing the sum of many momentum moves we are essentially following the trend hence the trend following strategy type.
Here we also print the IDI (with default strategy settings with the MA difference type), we can see that by letting our winners run we may catch many valid momentum moves, that results in a larger final pnl that if we would otherwise exit based on the equilibrium condition(Valid trades are denoted by solid green and red arrows respectively and all other valid trades which occur within the original signal are light green and red small arrows).
another example...
Note: if you would like to plot the IDI separately copy and paste the following code in a new Pine Script indicator template.
indicator("IDI")
// INTRAMARKET INDEX
var string g_idi = "intramarket diffirence index"
ui_index_1 = input.symbol("BINANCE:BTCUSD", title = "Base market", group = g_idi)
// ui_index_2 = input.symbol("BINANCE:ETHUSD", title = "Quote Market", group = g_idi)
type = input.string("MA", title = "Differrencing Series", options = , group = g_idi)
ui_ma_lkb = input.int(24, title = "lookback of ma and volatility scaling constant", group = g_idi)
ui_rsi_lkb = input.int(14, title = "Lookback of RSI", group = g_idi)
ui_atr_lkb = input.int(300, title = "ATR lookback - Normalising value", group = g_idi)
ui_ma_threshold = input.float(5, title = "Threshold of Upward/Downward Trend (MA)", group = g_idi)
ui_rsi_threshold = input.float(20, title = "Threshold of Upward/Downward Trend (RSI)", group = g_idi)
//>>+----------------------------------------------------------------+}
// CUSTOM FUNCTIONS |
//<<+----------------------------------------------------------------+{
// construct UDT (User defined type) containing the IDI (Intramarket Difference Index) source values
// UDT will hold many variables / functions grouped under the UDT
type functions
float Close // close price
float ma // ma of symbol
float rsi // rsi of the asset
float atr // atr of the asset
// the security data
getUDTdata(symbol, malookback, rsilookback, atrlookback) =>
indexHighTF = barstate.isrealtime ? 1 : 0
= request.security(symbol, timeframe = timeframe.period,
expression = [close , // Instentiate UDT variables
ta.sma(close, malookback) ,
ta.rsi(close, rsilookback) ,
ta.atr(atrlookback) ])
data = functions.new(close_, ma_, rsi_, atr_)
data
// Intramerket Difference Index
idi(type, symbol1, malookback, rsilookback, atrlookback, mathreshold, rsithreshold) =>
threshold = float(na)
index1 = getUDTdata(symbol1, malookback, rsilookback, atrlookback)
index2 = getUDTdata(syminfo.tickerid, malookback, rsilookback, atrlookback)
// declare difference variables for both base and quote symbols, conditional on which difference type is selected
var diffindex1 = 0.0, var diffindex2 = 0.0,
// declare Intramarket Difference Index based on series type, note
// if > 0, index 2 outpreforms index 1, buy index 2 (momentum based) until equalibrium
// if < 0, index 2 underpreforms index 1, sell index 1 (momentum based) until equalibrium
// for idi to be valid both series must be stationary and normalised so both series hae he same scale
intramarket_difference = 0.0
if type == "MA"
threshold := mathreshold
diffindex1 := (index1.Close - index1.ma) / math.pow(index1.atr*malookback, 0.5)
diffindex2 := (index2.Close - index2.ma) / math.pow(index2.atr*malookback, 0.5)
intramarket_difference := diffindex2 - diffindex1
else if type == "RSI"
threshold := rsilookback
diffindex1 := index1.rsi
diffindex2 := index2.rsi
intramarket_difference := diffindex2 - diffindex1
//>>+----------------------------------------------------------------+}
// STRATEGY FUNCTIONS CALLS |
//<<+----------------------------------------------------------------+{
// plot the intramarket difference
= idi(type,
ui_index_1,
ui_ma_lkb,
ui_rsi_lkb,
ui_atr_lkb,
ui_ma_threshold,
ui_rsi_threshold)
//>>+----------------------------------------------------------------+}
plot(intramarket_difference, color = color.orange)
hline(type == "MA" ? ui_ma_threshold : ui_rsi_threshold, color = color.green)
hline(type == "MA" ? -ui_ma_threshold : -ui_rsi_threshold, color = color.red)
hline(0)
Note it is possible that after printing a buy the strategy then prints many sell signals before returning to a buy, which again has the same implication (less profit. Potentially because we exit early only for price to continue upwards hence missing the larger "trend"). The image below showcases this cenario and again, by allowing our winner to run we may capture more profit (theoretically).
This should be clear...
🔸 Mean Reversion Case:
We stated prior that mean reversion of anomalies is an standerdies fact of financial data, how can we exploit this ?
We exploit this by normalizing the ID by applying the Ehlers fisher transformation. The transformed data is then assumed to be approximately normally distributed. To form the strategy we employ the same logic as for the z score, if the FT normalized ID > 2.5 (< -2.5) we buy (short). Our exit conditions remain unchanged (fixed ATR stop and trailing Donchian Trailing stop)
🔷 Position Sizing:
If ‘‘Fixed Risk From Initial Balance’’ is toggled true this means we risk a fixed percentage of our initial balance, if false we risk a fixed percentage of our equity (current balance).
Note we also employ a volatility adjusted position sizing formula, the turtle training method which is defined as follows.
Turtle position size = (1/ r * ATR * DV) * C
Where,
r = risk factor coefficient (default is 20)
ATR(j) = risk proxy, over j times steps
DV = Dollar Volatility, where DV = (1/Asset Price) * Capital at Risk
🔷 Risk Management:
Correct money management means we can limit risk and increase reward (theoretically). Here we employ
Max loss and gain per day
Max loss per trade
Max number of consecutive losing trades until trade skip
To read more see the tooltips (info circle).
🔷 Take Profit:
By defualt the script uses a Donchain Channel as a trailing stop and take profit, In addition to this the script defines a fixed ATR stop losses (by defualt, this covers cases where the DC range may be to wide making a fixed ATR stop usefull), ATR take profits however are defined but optional.
ATR SL and TP defined for all trades
🔷 Hurst Regime (Regime Filter):
The Hurst Exponent (H) aims to segment the market into three different states, Trending (H > 0.5), Random Geometric Brownian Motion (H = 0.5) and Mean Reverting / Contrarian (H < 0.5). In my interpretation this can be used as a trend filter that eliminates market noise.
We utilize the trending and mean reverting based states, as extra conditions required for valid trades for both strategy types respectively, in the process increasing our trade entry quality.
🔷 Example model Architecture:
Here is an example of one configuration of this strategy, combining all aspects discussed in this post.
Future Updates
- Automation integration (next update)
False Breakouts [TradingFinder] Fake Breakouts Failure🔵 Introduction
Technical indicators are essential tools for analysts and traders in financial markets, helping them predict price movements and make better trading decisions. One of the key concepts in technical analysis that should be carefully considered is the "False Breakout."
This phenomenon occurs when a price temporarily breaks through a significant support or resistance level but fails to hold and quickly returns to its previous range. Understanding this concept and applying it in trading can reduce risks and increase profitability.
🟣 What is a False Breakout?
A Fake Breakout, as the name suggests, refers to a breakout that appears to occur but fails to sustain, leading the price to quickly revert back to its previous range. This situation often happens when inexperienced or non-professional traders, under psychological pressure and eager to enter the market quickly, initiate trades.
This creates opportunities for professional traders to take advantage of these short-term fluctuations and execute successful trades.
🟣 The Importance of Recognizing False Breakouts
Recognizing False Breakouts is crucial for any trader aiming for success in financial markets. False Breakouts typically occur when the market approaches a critical support or resistance level.
In these situations, many traders are waiting to see if the price will break through this level. However, when the price quickly returns to its previous range, it indicates weakness in the movement and the inability to sustain the breakout.
🟣 How to identify False Breakouts?
To identify Fake Breakouts, it is important to carefully analyze price charts and look for signs of a quick price reversal after breaking a key level.
Here are some chart patterns that may help you identify a False Breakout :
1. Pin Bar Pattern : The Pin Bar is a candlestick pattern that indicates a price reversal. This pattern usually appears near support and resistance levels, showing that the price attempted to break through a key level but failed and reversed.
2. Fakey Pattern : This pattern, which consists of several candlesticks, indicates a False Breakout and a quick price return to the previous range. It usually appears near key levels and can signal a trend reversal.
3. Using Multiple Timeframes : One way to identify False Breakouts is by using charts of different timeframes. Sometimes, a breakout on a one-hour chart may be a False Breakout on a daily chart. Analyzing charts across multiple timeframes can help you accurately identify this phenomenon.
🔵 How to Use
Once you identify a False Breakout, you can use it as a trading signal. For this, it is best to look for trading opportunities in the opposite direction of the False Breakout. In other words, if a False Breakout occurs at a resistance level, you might consider selling opportunities, and if it happens at a support level, you might look for buying opportunities.
Here are some key points for trading based on False Breakouts :
1. Patience and Discipline : Patience and discipline are crucial when trading with False Breakouts. Wait for the False Breakout to clearly form before entering a trade.
2. Use Stop Loss : Setting an appropriate stop loss is vital when trading based on False Breakouts. Typically, the stop loss can be placed near the level where the False Breakout occurred.
3. Seek Confirmations : Before entering a trade, look for additional confirmations. These can include other analyses or technical indicators that show the price is likely to return to its previous level.
🔵 Settings
🟣 Logical settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Bac k: You can set the number of swings that will go back for checking.
🟣 Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 Alert Settings
Alert False Breakout : Enables alerts for Breakout.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵Conclusion
False Breakouts, as a key concept in technical analysis, are powerful tools for identifying sudden price changes and using them in trading. Understanding this phenomenon and applying it can help traders perform better in financial markets and avoid potential losses.
To benefit from False Breakouts, traders need to carefully analyze charts and use the appropriate analytical tools. By leveraging this strategy, traders can achieve lower-risk and higher-reward trades.
Multi-Factor StrategyThis trading strategy combines multiple technical indicators to create a systematic approach for entering and exiting trades. The goal is to capture trends by aligning several key indicators to confirm the direction and strength of a potential trade. Below is a detailed description of how the strategy works:
Indicators Used
MACD (Moving Average Convergence Divergence):
MACD Line: The difference between the 12-period and 26-period Exponential Moving Averages (EMAs).
Signal Line: A 9-period EMA of the MACD line.
Usage: The strategy looks for crossovers between the MACD line and the Signal line as entry signals. A bullish crossover (MACD line crossing above the Signal line) indicates a potential upward movement, while a bearish crossover (MACD line crossing below the Signal line) signals a potential downward movement.
RSI (Relative Strength Index):
Usage: RSI is used to gauge the momentum of the price movement. The strategy uses specific thresholds: below 70 for long positions to avoid overbought conditions and above 30 for short positions to avoid oversold conditions.
ATR (Average True Range):
Usage: ATR measures market volatility and is used to set dynamic stop-loss and take-profit levels. A stop loss is set at 2 times the ATR, and a take profit at 3 times the ATR, ensuring that risk is managed relative to market conditions.
Simple Moving Averages (SMA):
50-day SMA: A short-term trend indicator.
200-day SMA: A long-term trend indicator.
Usage: The strategy uses the relationship between the 50-day and 200-day SMAs to determine the overall market trend. Long positions are taken when the price is above the 50-day SMA and the 50-day SMA is above the 200-day SMA, indicating an uptrend. Conversely, short positions are taken when the price is below the 50-day SMA and the 50-day SMA is below the 200-day SMA, indicating a downtrend.
Entry Conditions
Long Position:
-MACD Crossover: The MACD line crosses above the Signal line.
-RSI Confirmation: RSI is below 70, ensuring the asset is not overbought.
-SMA Confirmation: The price is above the 50-day SMA, and the 50-day SMA is above the 200-day SMA, indicating a strong uptrend.
Short Position:
MACD Crossunder: The MACD line crosses below the Signal line.
RSI Confirmation: RSI is above 30, ensuring the asset is not oversold.
SMA Confirmation: The price is below the 50-day SMA, and the 50-day SMA is below the 200-day SMA, indicating a strong downtrend.
Opposite conditions for shorts
Exit Strategy
Stop Loss: Set at 2 times the ATR from the entry price. This dynamically adjusts to market volatility, allowing for wider stops in volatile markets and tighter stops in calmer markets.
Take Profit: Set at 3 times the ATR from the entry price. This ensures a favorable risk-reward ratio of 1:1.5, aiming for higher rewards on successful trades.
Visualization
SMAs: The 50-day and 200-day SMAs are plotted on the chart to visualize the trend direction.
MACD Crossovers: Bullish and bearish MACD crossovers are highlighted on the chart to identify potential entry points.
Summary
This strategy is designed to align multiple indicators to increase the probability of successful trades by confirming trends and momentum before entering a position. It systematically manages risk with ATR-based stop loss and take profit levels, ensuring that trades are exited based on market conditions rather than arbitrary points. The combination of trend indicators (SMAs) with momentum and volatility indicators (MACD, RSI, ATR) creates a robust approach to trading in various market environments.
Improved Volume Based Indicator# Improved Volume Based Indicator
## Overview
The Improved Volume Based Indicator is a technical analysis tool designed to identify potential trading opportunities based on volume patterns, price action, and trend direction. This indicator combines volume analysis with moving averages and the Average True Range (ATR) to generate buy and sell signals.
## Key Components
1. Volume Analysis
- Tracks consecutive volume direction (up or down) for 3 periods
- Calculates volume ratio compared to a short-term moving average
2. Trend Direction
- Uses a 200-period Exponential Moving Average (EMA) to determine overall trend
3. Volatility Measurement
- Incorporates the Average True Range (ATR) for stop-loss and take-profit calculations
## Signal Generation
### Buy Signal Criteria
1. Three consecutive periods of up volume (close > open)
2. Volume ratio > 1.5 (current volume is 50% higher than the short-term average)
3. Current price is above the 200 EMA
### Sell Signal Criteria
1. Three consecutive periods of down volume (close < open)
2. Volume ratio > 1.5 (current volume is 50% higher than the short-term average)
3. Current price is below the 200 EMA
## Risk Management
The indicator calculates stop-loss and take-profit levels based on the ATR:
- Stop Loss: ATR * 1.5 (default)
- Take Profit: ATR * 2.5 (default)
These levels are adjustable through input parameters.
## Usage
1. Add the indicator to your chart
2. Adjust input parameters as needed:
- Volume Period (2-5)
- ATR Period (default 14)
- ATR Multipliers for Stop Loss and Take Profit
- EMA Period (default 200)
3. Monitor for buy and sell signals
4. Use the provided stop-loss and take-profit levels for risk management
## Interpretation
- Buy signals suggest potential upward price movement
- Sell signals suggest potential downward price movement
- Always consider other factors and perform additional analysis before making trading decisions
## Limitations
- This indicator may generate false signals in choppy or ranging markets
- It's best used in conjunction with other technical analysis tools and fundamental analysis
- Past performance does not guarantee future results
Remember to thoroughly test this indicator on historical data and in various market conditions before using it in live trading.
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# 改進的基於交易量的指標
＃＃ 概述
改進的基於成交量的指標是一種技術分析工具，旨在根據成交量模式、價格行為和趨勢方向識別潛在的交易機會。此指標將成交量分析與移動平均線和平均真實波動幅度 (ATR) 結合起來，以產生買入和賣出訊號。
＃＃ 關鍵部件
1. 成交量分析
- 追蹤 3 個週期的連續成交量方向（向上或向下）
- 計算與短期移動平均線相比的成交量比率
2. 趨勢方向
- 使用 200 週期指數移動平均線 (EMA) 來確定整體趨勢
3. 波動率測量
- 納入平均真實波動範圍 (ATR) 以進行停損和停盈計算
## 訊號生成
### 購買訊號標準
1. 連續三個週期的成交量上漲（收盤>開盤）
2.成交量比率>1.5（目前成交量較短期平均高50%）
3. 當前價格高於200 EMA
### 賣出訊號標準
1.連續三個週期的成交量下跌（收盤<開盤）
2.成交量比率>1.5（目前成交量較短期平均高50%）
3. 目前價格低於200 EMA
＃＃ 風險管理
此指標根據 ATR 計算停損和止盈水準：
- 停損：ATR * 1.5（預設）
- 止盈：ATR * 2.5（預設）
這些等級可透過輸入參數進行調整。
＃＃ 用法
1. 將指標加入您的圖表中
2. 根據需要調整輸入參數：
- 卷期 (2-5)
- ATR 週期（預設 14）
- 用於停損和止盈的 ATR 乘數
- EMA 週期（預設 200）
3. 監控買賣訊號
4. 使用提供的停損和停利水準進行風險管理
＃＃ 解釋
- 買進訊號表示價格可能上漲
- 賣出訊號表示價格可能下跌
- 在做出交易決策之前始終考慮其他因素並進行額外分析
## 限制
- 此指標可能會在波動或波動的市場中產生錯誤訊號
- 最好與其他技術分析工具和基本面分析結合使用
- 過去的表現並不能保證未來的結果
請記住，在實際交易中使用該指標之前，請根據歷史數據和各種市場條件徹底測試該指標。
Easy Scalping Lot Calculator for ForexThe calculator was created to make it easier to calculate the lot size on Forex. I planned to use it for the following pairs: AUDCAD, AUDCHF, AUDJPY, AUDUSD, EURAUD, EURCAD, EURCHF, EURGBP, EURJPY, EURNZD, EURUSD, GBPCHF, GBPJPY, GBPUSD, NZDUSD, USDCAD, USDCHF, USDJPY, XAUUSD.
The indicator is a table that shows the calculation of the lot for a predetermined stop loss.
For example, you are planning a trade, have calculated a stop loss of 15 points, and by checking the table you understand approximately what lot you need to use to limit your risk.
In the settings you can change the risk and also determine the stop loss value in points.
The calculator does not take into account the spread in the calculations.
There are websites where you can accurately calculate the lot, but if you trade on small time frames this is not suitable for you.
The calculator uses the formula:
Lot size = maximum risk / stop loss (in pips) / minimum pip value x minimum trading lot.
Scalping System by Machine# Custom Trading System Indicator
This Pine Script indicator is designed to identify potential trading setups based on a specific set of rules. It's intended for use on lower timeframes (M1-M5) in the forex market, particularly during the New York-London overlap period.
## Key Features
1. **EMA Condition**: Uses a 20-period Exponential Moving Average (EMA) to determine trend direction.
2. **Candle Analysis**: Identifies strong bars and candle color changes.
3. **Volume Confirmation**: Checks for increasing volume.
4. **Volatility Filter**: Utilizes the Average True Range (ATR) to gauge market volatility.
5. **Time-based Filter**: Highlights the New York-London overlap period.
6. **Visual Aids**: Plots potential entry points, stop losses, and take profit levels.
## Trading Rules
1. **Buy Signal**:
- Price is above the 20 EMA
- Candle color changes from red to green
- Current candle is a strong bar (closing within 75% of its range)
- Volume is higher than the previous bar
- ATR(14) is above 4 pips OR it's during the NY-London overlap
2. **Sell Signal**:
- Price is below the 20 EMA
- Candle color changes from green to red
- Current candle is a strong bar (closing within 75% of its range)
- Volume is higher than the previous bar
- ATR(14) is above 4 pips OR it's during the NY-London overlap
3. **Stop Loss**: Placed near the low of the setup candle for buys, or near the high for sells.
4. **Take Profit**: Aimed at 1R (one times the range of the setup candle).
## Visual Elements
- **20 EMA**: Plotted as a blue line on the chart.
- **Buy Signals**: Green triangles below the candles.
- **Sell Signals**: Red triangles above the candles.
- **Stop Loss Levels**: Small red dots at the calculated stop loss prices.
- **Take Profit Levels**: Small green dots at the calculated take profit prices.
- **Information Table**: Displays current values for ATR, strong bar condition and volume condition.
## Usage Notes
1. This indicator is designed for manual trading, not automated execution.
2. It works best when combined with analysis of major trend lines, support, and resistance levels.
3. Exercise caution with very large setup candles.
4. Consider additional filters or money management rules for enhanced performance.
5. For higher timeframe bias validation, consider incorporating a 100-period break of structure (BOS) analysis.
## Customization
The indicator includes several input parameters that can be adjusted:
- EMA Length
- ATR Length and Threshold
- Volume Multiplier
- Strong Bar Percentage
Users can also toggle the visibility of stop loss and take profit markers.
Remember, while this indicator can identify potential setups, it should be used in conjunction with other forms of analysis and risk management strategies. Always consider the overall market context and your personal risk tolerance when making trading decisions.
MAC Investor V3.0 [VK]This indicator combines multiple functionalities to assist traders in making informed decisions. It primarily uses Heikin Ashi candles, Moving Averages, and a Price Action Channel (PAC) to provide signals for entering and exiting trades. Here's a detailed breakdown:
Inputs
MAC Length: Sets the length for the PAC calculation.
Use Heikin Ashi Candles: Option to use Heikin Ashi candles for calculations.
Show Coloured Bars around MAC: Option to color bars based on their relation to the PAC.
Show Long/Short Signals: Options to display long and short signals.
Show MAs? : Option to show moving averages on the chart.
Show MAs Trend at the Bottom?: Option to show trend signals at the bottom of the chart.
MA Lengths: Length settings for three different moving averages.
Change MA Color Based on Direction?: Option to change the color of moving averages based on trend direction.
MA Higher TimeFrame: Allows setting a higher timeframe for moving averages.
Show SL-TP Lines: Option to display Stop Loss and Take Profit lines.
SL/TP Percentages: Set the percentages for Stop Loss and three levels of Take Profit.
Calculations and Features
Heikin Ashi Candles: Calculations are based on Heikin Ashi candle data if selected.
Price Action Channel (PAC): Uses Exponential Moving Averages (EMA) of the high, low, and close to create a channel.
Bar Coloring: Colors the bars based on their position relative to the PAC.
Long and Short Signals: Uses crossovers of the close price and PAC upper/lower bands to generate signals.
Moving Averages (MA): Plots three moving averages and colors them based on their trend direction.
Overall Trend Indicators: Uses triangles at the bottom of the chart to show the overall trend of the MAs.
Stop Loss and Take Profit Levels: Calculates and plots these levels based on user-defined percentages from the entry price.
Alerts: Provides alerts for long and short signals.
Use Cases and How to Use
Identifying Trends: The PAC helps to identify the trend direction. If the closing price is above the PAC upper band, it suggests an uptrend; if below the lower band, it suggests a downtrend.
Entering Trades: Use the long and short signals to enter trades. A long signal is generated when the closing price crosses above the PAC upper band, and a short signal is generated when it crosses below the PAC lower band.
Exit Strategies: Utilize the Stop Loss (SL) and Take Profit (TP) levels to manage risk and lock in profits. These levels are automatically calculated based on the entry price and user-defined percentages.
Trend Confirmation with MAs: The moving averages provide additional confirmation of the trend. When all three MAs are trending in the same direction (e.g., all green for an uptrend), it adds confidence to the trade signal.
Overall Trend Indicators: The triangles at the bottom of the chart show the overall trend direction of the MAs:
Green Triangle: All three MAs are trending upwards, indicating a strong uptrend.
Red Triangle: All three MAs are trending downwards, indicating a strong downtrend.
Yellow Triangle: Mixed signals from the MAs, indicating no clear trend.
Bar Coloring for Quick Analysis: The colored bars give a quick visual cue about the market condition, aiding in faster decision-making.
Alerts: Set up alerts to get notified when a long or short signal is generated, allowing you to act promptly without constantly monitoring the chart.
Maximizing Profit
To maximize profit with this indicator:
Follow the Signals: Use the long and short signals to time your entries. Ensure you follow the trend indicated by the PAC and MAs.
Risk Management: Always set your Stop Loss and Take Profit levels to manage risk. This will help you cut losses early and secure profits.
Confirm with MAs: Look for confirmation from the moving averages. When all MAs align with the signal, it indicates a stronger trend.
Overall Trend Indicators: Pay attention to the triangles at the bottom for overall trend confirmation. Only enter trades when the overall trend is in your favor.
Heikin Ashi for Smoothing: Use Heikin Ashi candles for smoother trends and fewer false signals.
Backtesting: Test the indicator on historical data to understand its performance and adjust settings as necessary.
Adapt to Market Conditions: Adjust the lengths of PAC and MAs based on the market's volatility and timeframe you are trading on.
How to Use the Indicator
Add to Chart: Add the indicator to your TradingView chart.
Configure Settings: Customize the input settings to fit your trading strategy and timeframe.
Monitor Signals: Watch for long and short signals and observe the trend direction with the PAC and MAs.
Check Overall Trend: Look at the triangles at the bottom of the chart to see the overall trend direction of the MAs.
Set Alerts: Configure alerts to get notified of new signals.
Manage Trades: Use the SL and TP levels to manage your trades effectively.
First 12 Candles High/Low BreakoutThis indicator identifies potential breakout opportunities based on the high and low points formed within the first 12 candles after the market opens on a 5-minute timeframe. It provides visual cues and labels to help traders make informed decisions.
Features:
Market Open High/Low: Marks the highest and lowest price of the first 12 candles following the market open with horizontal lines for reference.
Breakout Signals: Identifies potential buy or sell signals based on the first 5-minute candle closing above the open high or below the open low.
Target and Stop-Loss: Plots horizontal lines for target prices (100 points by default, adjustable) and stop-loss levels (100 points by default, adjustable) based on the entry price.
Visual Cues: Uses green triangles (up) for buy signals and red triangles (down) for sell signals.
Informative Labels: Displays labels with "Buy" or "Sell" text, target price, and stop-loss price next to the entry signals (optional).
Customization:
You can adjust the target and stop-loss point values using the provided inputs.
How to Use:
Add the script to your TradingView chart.
The indicator will automatically plot the open high, open low, potential entry signals, target levels, and stop-loss levels based on the first 12 candles after the market opens.
Use the signals and price levels in conjunction with your own trading strategy to make informed decisions.
SLOPED Trailing SL with ATR-V1SLOPED Trailing SL with ATR
I thought capital is sometime locked for long periods s when volatility is low, hence:
SLOPED Trailing SL with ATR
This indicator provides a trailing stop loss that dynamically adjusts based on the Average True Range (ATR) and incorporates a user-defined upward slope on flat areas. It is designed to follow the price movement more closely during trends while allowing for a customizable slope to maintain a trailing stop even when the price movement is flat.
Key Features:
ATR-Based Stop Loss:
Utilizes the ATR to calculate a dynamic stop loss level, adjusting to market volatility.
Provides a normal ATR stop loss line that only trails upwards, preventing it from decreasing.
Upward Slope on Flat Areas:
Adds a user-defined upward slope to the trailing stop loss when the price movement is flat.
The slope value is specified in 1/1000 increments (e.g., 0.1% per bar), allowing for fine-tuned control.
Bitcoin Futures vs. Spot Tri-Frame - Strategy [presentTrading]Prove idea with a backtest is always true for trading.
I developed and open-sourced it as an educational material for crypto traders to understand that the futures and spot spread may be effective but not be as effective as they might think. It serves as an indicator of sentiment rather than a reliable predictor of market trends over certain periods. It is better suited for specific trading environments, which require further research.
█ Introduction and How it is Different
The "Bitcoin Futures vs. Spot Tri-Frame Strategy" utilizes three different timeframes to calculate the Z-Score of the spread between BTC futures and spot prices on Binance and OKX exchanges. The strategy executes long or short trades based on composite Z-Score conditions across the three timeframes.
The spread refers to the difference in price between BTC futures and BTC spot prices, calculated by taking a weighted average of futures prices from multiple exchanges (Binance and OKX) and subtracting a weighted average of spot prices from the same exchanges.
BTCUSD 1D L/S Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Spread
The spread is the difference in price between BTC futures and BTC spot prices. The strategy calculates the spread by taking a weighted average of futures prices from multiple exchanges (Binance and OKX) and subtracting a weighted average of spot prices from the same exchanges. This spread serves as the primary metric for identifying trading opportunities.
Spread = Weighted Average Futures Price - Weighted Average Spot Price
🔶 Z-Score Calculation
The Z-Score measures how many standard deviations the current spread is from its historical mean. This is calculated for each timeframe as follows:
Spread Mean_tf = SMA(Spread_tf, longTermSMA)
Spread StdDev_tf = STDEV(Spread_tf, longTermSMA)
Z-Score_tf = (Spread_tf - Spread Mean_tf) / Spread StdDev_tf
Local performance
🔶 Composite Entry Conditions
The strategy triggers long and short entries based on composite Z-Score conditions across all three timeframes:
- Long Condition: All three Z-Scores must be greater than the long entry threshold.
Long Condition = (Z-Score_tf1 > zScoreLongEntryThreshold) and (Z-Score_tf2 > zScoreLongEntryThreshold) and (Z-Score_tf3 > zScoreLongEntryThreshold)
- Short Condition: All three Z-Scores must be less than the short entry threshold.
Short Condition = (Z-Score_tf1 < zScoreShortEntryThreshold) and (Z-Score_tf2 < zScoreShortEntryThreshold) and (Z-Score_tf3 < zScoreShortEntryThreshold)
█ Trade Direction
The strategy allows the user to specify the trading direction:
- Long: Only long trades are executed.
- Short: Only short trades are executed.
- Both: Both long and short trades are executed based on the Z-Score conditions.
█ Usage
The strategy can be applied to BTC or Crypto trading on major exchanges like Binance and OKX. By leveraging discrepancies between futures and spot prices, traders can exploit market inefficiencies. This strategy is suitable for traders who prefer a statistical approach and want to diversify their timeframes to validate signals.
█ Default Settings
- Input TF 1 (60 minutes): Sets the first timeframe for Z-Score calculation.
- Input TF 2 (120 minutes): Sets the second timeframe for Z-Score calculation.
- Input TF 3 (180 minutes): Sets the third timeframe for Z-Score calculation.
- Long Entry Z-Score Threshold (3): Defines the threshold above which a long trade is triggered.
- Short Entry Z-Score Threshold (-3): Defines the threshold below which a short trade is triggered.
- Long-Term SMA Period (100): The period used to calculate the simple moving average for the spread.
- Use Hold Days (true): Enables holding trades for a specified number of days.
- Hold Days (5): Number of days to hold the trade before exiting.
- TPSL Condition (None): Defines the conditions for taking profit and stop loss.
- Take Profit (%) (30.0): The percentage at which the trade will take profit.
- Stop Loss (%) (20.0): The percentage at which the trade will stop loss.
By fine-tuning these settings, traders can optimize the strategy to suit their risk tolerance and trading style, enhancing overall performance.
Double Vegas SuperTrend Enhanced - Strategy [presentTrading]
█ Introduction and How It Is Different
The "Double Vegas SuperTrend Enhanced" strategy is a sophisticated trading system that combines two Vegas SuperTrend Enhanced. Very Powerful!
Let's celebrate the joy of Children's Day on June 1st! Enjoyyy!
BTCUSD LS performance
The strategy aims to pinpoint market trends with greater accuracy and generate trades that align with the overall market direction.
This approach differentiates itself by integrating volatility adjustments and leveraging the Vegas Channel's width to refine the SuperTrend calculations, resulting in a dynamic and responsive trading system.
Additionally, the strategy incorporates customizable take-profit and stop-loss levels, providing traders with a robust framework for risk management.
-> check Vegas SuperTrend Enhanced - Strategy
█ Strategy, How It Works: Detailed Explanation
🔶 Vegas Channel and SuperTrend Calculations
The strategy initiates by calculating the Vegas Channel, which is derived from a simple moving average (SMA) and the standard deviation (STD) of the closing prices over a specified window length. This channel helps in measuring market volatility and forms the basis for adjusting the SuperTrend indicator.
Vegas Channel Calculation:
- vegasMovingAverage = SMA(close, vegasWindow)
- vegasChannelStdDev = STD(close, vegasWindow)
- vegasChannelUpper = vegasMovingAverage + vegasChannelStdDev
- vegasChannelLower = vegasMovingAverage - vegasChannelStdDev
SuperTrend Multiplier Adjustment:
- channelVolatilityWidth = vegasChannelUpper - vegasChannelLower
- adjustedMultiplier = superTrendMultiplierBase + volatilityAdjustmentFactor * (channelVolatilityWidth / vegasMovingAverage)
The adjusted multiplier enhances the SuperTrend's sensitivity to market volatility, making it more adaptable to changing market conditions.
BTCUSD Local picture.
🔶 Average True Range (ATR) and SuperTrend Values
The ATR is computed over a specified period to measure market volatility. Using the ATR and the adjusted multiplier, the SuperTrend upper and lower levels are determined.
ATR Calculation:
- averageTrueRange = ATR(atrPeriod)
**SuperTrend Calculation:**
- superTrendUpper = hlc3 - (adjustedMultiplier * averageTrueRange)
- superTrendLower = hlc3 + (adjustedMultiplier * averageTrueRange)
The SuperTrend levels are continuously updated based on the previous values and the current market trend direction. The market trend is determined by comparing the closing prices with the SuperTrend levels.
Trend Direction:
- If close > superTrendLowerPrev, then marketTrend = 1 (bullish)
- If close < superTrendUpperPrev, then marketTrend = -1 (bearish)
🔶 Trade Entry and Exit Conditions
The strategy generates trade signals based on the alignment of both SuperTrends. Trades are executed only when both SuperTrends indicate the same market direction.
Entry Conditions:
- Long Position: Both SuperTrends must signal a bullish trend.
- Short Position: Both SuperTrends must signal a bearish trend.
Exit Conditions:
- Positions are exited if either SuperTrend reverses its trend direction.
- Additional conditions include holding periods and configurable take-profit and stop-loss levels.
█ Trade Direction
The strategy allows traders to specify the desired trade direction through a customizable input setting. Options include:
- Long: Only enter long positions.
- Short: Only enter short positions.
- Both: Enter both long and short positions based on the market conditions.
█ Usage
To utilize the "Double Vegas SuperTrend Enhanced" strategy, traders need to configure the input settings according to their trading preferences and market conditions. The strategy includes parameters for ATR periods, Vegas Channel window lengths, SuperTrend multipliers, volatility adjustment factors, and risk management settings such as hold days, take-profit, and stop-loss percentages.
█ Default Settings
The strategy comes with default settings that can be adjusted to fit individual trading styles:
- trade Direction: Both (allows trading in both long and short directions for maximum flexibility).
- ATR Periods: 10 for SuperTrend 1 and 5 for SuperTrend 2 (shorter ATR period results in more sensitivity to recent price movements).
- Vegas Window Lengths: 100 for SuperTrend 1 and 200 for SuperTrend 2 (longer window length results in smoother moving averages and less sensitivity to short-term volatility).
- SuperTrend Multipliers: 5 for SuperTrend 1 and 7 for SuperTrend 2 (higher multipliers lead to wider SuperTrend channels, reducing the frequency of trades).
- Volatility Adjustment Factors: 5 for SuperTrend 1 and 7 for SuperTrend 2 (higher adjustment factors increase the responsiveness to changes in market volatility).
- Hold Days: 5 (defines the minimum duration a position is held, ensuring trades are not exited prematurely).
- Take Profit: 30% (sets the target profit level to lock in gains).
- Stop Loss: 20% (sets the maximum acceptable loss level to mitigate risk).
market slayerInput Parameters:
Various input parameters allow customization of the strategy, including options to show trend confirmation, specify trend timeframes and values, set SMA lengths, enable take profit and stop loss, and define their respective values.
Calculations:
Simple Moving Averages (SMAs) are calculated based on the specified lengths.
Buy and sell signals are generated based on the crossover and crossunder of the short and long SMAs.
Confirmation Bars:
Functions are defined to determine bullish or bearish confirmation bars based on certain conditions.
These confirmation bars are used to confirm trend direction and generate additional signals.
Plotting:
SMAs are plotted on the chart.
Trend labels and signal markers are plotted based on the calculated conditions.
Trade Signals:
Buy and sell conditions are defined based on the crossover/crossunder of SMAs and confirmation of trend direction.
Strategy entries and exits are executed accordingly.
Take Profit and Stop Loss:
Optional take profit and stop loss functionality is included.
Trades are automatically closed when profit or loss thresholds are reached.
Closing Trades:
Trades are also closed based on changes in trend confirmation bars to ensure alignment with the overall market direction.
Alerts:
Alert conditions are defined for opening and closing trades, providing notifications when certain conditions are met.
Overall, this script aims to provide a systematic approach to trading by combining moving average crossovers with trend confirmation bars, along with options for risk management through take profit and stop loss orders. Users can customize various parameters to adapt the strategy to different market conditions and trading preferences.
The script uses the request.security() function with the lookahead parameter set to barmerge.lookahead_on to access data from a higher timeframe within the Pine Script on TradingView. Let's break down why it's used:
Higher Timeframe Analysis:
By default, Pine Script operates on the timeframe of the chart it's applied to. However, in trading strategies, it's common to incorporate signals or data from higher timeframes to confirm or validate signals generated on lower timeframes. This helps traders to align their trades with the broader market trend.
Trend Confirmation:
In this script, the confirmationTrendTimeframe parameter allows users to specify a higher timeframe for trend confirmation. The request.security() function fetches the data from this higher timeframe and applies the defined conditions to confirm the trend direction.
Lookahead Behavior:
The lookahead parameter set to barmerge.lookahead_on ensures that the script considers the most up-to-date information available on the higher timeframe when making trading decisions on the lower timeframe. This prevents the script from lagging behind or using outdated data, enhancing the accuracy of trend confirmation.
Usage in confirmationTrendBullish and confirmationTrendBearish:
These variables are assigned the values returned by the request.security() function, which represents the bullish or bearish trend confirmation based on the conditions applied to the data from the higher timeframe.
Tetuan SniperThe TEMA and EMA Crossover Alert with SL, TP, and Order Signal strategy combines the power of Triple Exponential Moving Average (TEMA) and Exponential Moving Average (EMA) to generate high-quality trading signals. This strategy is designed to provide clear entry and exit points, manage risk through dynamic Stop Loss (SL) and Take Profit (TP) levels, and optimize trade sizes based on account balance and risk tolerance.
Key Features:
EMA and TEMA Crossover:
The strategy identifies potential buy and sell signals based on the crossover of EMA and TEMA. A buy signal is generated when TEMA crosses above EMA, and a sell signal is generated when TEMA crosses below EMA.
Dynamic Stop Loss (SL) and Take Profit (TP):
Stop Loss levels are dynamically set based on a user-defined number of pips below (for buy orders) or above (for sell orders) the lowest or highest point since the crossover.
Take Profit levels are dynamically adjusted using another TEMA, providing a flexible exit strategy that adapts to market conditions.
Lot Size Calculation:
The strategy calculates the optimal lot size based on the account balance, risk percentage per trade, and the number of maximum open orders. For JPY pairs, the lot size is adjusted by dividing by 100 to account for the different pip value.
The lot size is rounded to two decimal places for better readability and precision.
Visual Alerts and Labels:
Clear visual alerts and labels are provided for each buy and sell signal, including the recommended SL, TP, and lot size. The labels are placed in a way to avoid overlapping important chart elements.
Trend Visualization:
The area between the TEMA and EMA is colored to indicate the trend, with green for bullish trends and red for bearish trends, making it easy to visualize the market direction.
Inputs:
SL Points: Number of pips for the Stop Loss.
EMA Period: Period for the Exponential Moving Average.
TEMA Period: Period for the Triple Exponential Moving Average.
Account Balance: The total account balance for calculating the lot size.
Risk Percentage: The percentage of the account balance to risk per trade.
Take Profit TEMA Period: Period for the TEMA used to set Take Profit levels.
Lot per Pip Value: The value of 1 pip per lot.
Maximum Open Orders: The maximum number of open orders to split the balance among.
Example Usage
This strategy is suitable for traders who want to automate their trading signals and manage risk effectively. By combining TEMA and EMA crossovers with dynamic SL and TP levels and precise lot size calculation, traders can achieve a disciplined and methodical approach to trading.
Multi-Timeframe Trend Following with 200 EMA Filter - Longs OnlyOverview
This strategy is designed to trade long positions based on multiple timeframe Exponential Moving Averages (EMAs) and a 200 EMA filter. The strategy ensures that trades are only entered in strong uptrends and aims to capitalize on sustained upward movements while minimizing risk with a defined stop-loss and take-profit mechanism.
Key Components
Initial Capital and Position Sizing
Initial Capital: $1000.
Lot Size: 1 unit per trade.
Inputs
Fast EMA Length (fast_length): The period for the fast EMA.
Slow EMA Length (slow_length): The period for the slow EMA.
200 EMA Length (filter_length_200): Set to 200 periods for the primary trend filter.
Stop Loss Percentage (stop_loss_perc): Set to 1% of the entry price.
Take Profit Percentage (take_profit_perc): Set to 3% of the entry price.
Timeframes and EMAs
EMAs are calculated for the following timeframes using the request.security function:
5-minute: Short-term trend detection.
15-minute: Intermediate-term trend detection.
30-minute: Long-term trend detection.
The strategy also calculates a 200-period EMA on the 5-minute timeframe to serve as a primary trend filter.
Trend Calculation
The strategy determines the trend for each timeframe by comparing the fast and slow EMAs:
If the fast EMA is above the slow EMA, the trend is considered positive (1).
If the fast EMA is below the slow EMA, the trend is considered negative (-1).
Combined Trend Signal
The combined trend signal is derived by summing the individual trends from the 5-minute, 15-minute, and 30-minute timeframes.
A combined trend value of 3 indicates a strong uptrend across all timeframes.
Any combined trend value less than 3 indicates a weakening or negative trend.
Entry and Exit Conditions
Entry Condition:
A long position is entered if:
The combined trend signal is 3 (indicating a strong uptrend across all timeframes).
The current close price is above the 200 EMA on the 5-minute timeframe.
Exit Condition:
The long position is exited if:
The combined trend signal is less than 3 (indicating a weakening trend).
The current close price falls below the 200 EMA on the 5-minute timeframe.
Stop Loss and Take Profit
Stop Loss: Set at 1% below the entry price.
Take Profit: Set at 3% above the entry price.
These levels are automatically set when entering a trade using the strategy.entry function with stop and limit parameters.
Plotting
The strategy plots the fast and slow EMAs for the 5-minute timeframe and the 200 EMA for visual reference on the chart:
Fast EMA (5-min): Plotted in blue.
Slow EMA (5-min): Plotted in red.
200 EMA (5-min): Plotted in green.
[MAD] Entrytool / Bybit-LinearThis indicator, "Entry Tool," was coded at request for Sandmann .
It is designed to provide traders with real-time feedback for strategizing entries, exits, and liquidation levels for trades initiated at that given moment.
The tool visualizes average entry prices, stop-loss levels, multiple take-profit targets, and potential liquidation prices, offering a comprehensive overview of possible trade outcomes. It aids traders in pre-planning their trades by visually simulating the impact of different trading decisions directly on the live chart. Each setting and parameter can be customized to align with individual trading strategies and risk tolerances, making this tool versatile for various trading styles, including day trading, swing trading, and position trading.
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Steps to Use the Indicator:
1. Basic Setup:
Setup Type: Choose between "Long" or "Short" to set the direction of the trade.
Leverage: Adjust the leverage to understand its impact on your potential returns and liquidation price.
Tracking follows the close price, alternative you can enter a specific price.
2. Position Setup:
Initial Entry Amount: Set the starting amount for the trade.
Distance: First Increment Percentage from Entry price
Amount: Define the increase for the first incremental addition to the position and specify the amount to be added.
Distance: Second Increment Percentage from Entry
Amount: Set the increase for the second incremental addition and the corresponding amount.
3. Risk Management:
Stop-Loss (SL) Percentage: Set the percentage below or above the average entry price at which the position should be closed to minimize losses.
Take-Profit (TP) Percentages: Define up to four different profit target levels by specifying the percentage above or below the average entry price.
4. Visual Settings:
Box Colors: Customize the colors of the boxes that represent long and short positions to differentiate easily on the chart.
Box Extension: Determine the length by which the box extends beyond the current bar, which helps in visualizing the potential price movement.
Line Colors and Extensions: Select colors for various lines such as the Average Entry Line, Stop-Loss Line, Take-Profit Lines, and Liquidations Line. Adjust the length of these lines for better visibility.
Label Settings: Configure the distance of labels from their corresponding lines and set the font size for better readability.
5. Additional Features:
Liquidation Price Visualization: This new feature calculates and displays the liquidation price based on the current leverage and margin settings, giving traders a critical insight into their risk exposure.
Interactive Drag Point: Adjust the start price manually by dragging the point on the chart, which dynamically updates entry and exit levels as well as risk metrics.
Detailed Leverage Data Array: Input different scenarios with specific leverage, initial margin, and maintenance rates to see how these factors impact potential liquidation points.
6. Informations about leverage calculation
The data used are fetched from Bybit for Linear pairs to calculate the liquidations like in their documentation.
Keep in mind that other exchanges may calulate based on another formular.
EngineerBuySellHighRiskThis TradingView indicator script is designed to identify various trading signals based on price action and the 5-period Exponential Moving Average (EMA), providing traders with insights into potential buy and sell opportunities. The script generates signals under the following categories:
Buy Signals
Regular Buy Signal: Identified when the entire previous candle (Candle 1) is below the 5 EMA, and the following candle (Candle 2) has a higher high compared to Candle 1 and closes higher than its opening price (indicating a green candle). This signal suggests a potential upward momentum as the price moves above the recent lows and the 5 EMA, indicating a buying opportunity.
High-Risk Buy Signal: Similar to the regular buy signal, but it specifically targets scenarios where Candle 1's high is exactly on the 5 EMA. Candle 2 must either have a higher high than Candle 1 or touch the 5 EMA, and it must close higher than its opening price. This signal indicates a potential for an upward trend continuation but is considered higher risk due to the price's proximity to the 5 EMA.
High Buy Risk Signal: This signal is generated under the same conditions as the regular buy signal regarding the position of Candle 1 relative to the 5 EMA and the requirement for Candle 2 to have a higher high. However, it allows for Candle 2 to close lower than its opening price (indicating a red candle), broadening the criteria for a buy signal. This modification acknowledges the potential for buying opportunities even in cases where Candle 2 closes down, assuming the price still shows upward momentum compared to Candle 1.
Sell Signals
Sell Signal: Generated when Candle 1 is entirely above the 5 EMA, and the following candle (Candle 2) has a lower low compared to Candle 1 and closes lower than its opening price (indicating a red candle). This setup suggests a potential downward trend, signaling a selling or shorting opportunity.
High Risk Sell Signal: This signal is for scenarios where Candle 1 is above the 5 EMA, and Candle 2's low is lower than Candle 1's low, but unlike the standard sell signal, it allows Candle 2 to close higher than its opening price (indicating a green candle). It signifies a potential downward price movement but with increased risk due to the mixed signal from Candle 2's close.
Stop-Loss Levels
Buy Stop-Loss Level: For buy signals, the stop-loss is set at the low of Candle 1, providing a risk management level to minimize potential losses if the market moves against the trade.
Sell Stop-Loss Level: For sell signals, the stop-loss is set at the high of Candle 1, serving as a risk management tool to protect against unfavorable price movements after entering a short position.
Visualization
The script uses different colors and labels to distinguish between the types of signals, making it easier for traders to identify and act upon these trading opportunities. It plots the 5 EMA for reference, providing context for the price action relative to this moving average. This script aims to offer a comprehensive toolkit for traders looking for nuanced entry and exit points based on short-term price movements and momentum relative to the 5 EMA.
Bitcoin Momentum StrategyThis is a very simple long-only strategy I've used since December 2022 to manage my Bitcoin position.
I'm sharing it as an open-source script for other traders to learn from the code and adapt it to their liking if they find the system concept interesting.
General Overview
Always do your own research and backtesting - this script is not intended to be traded blindly (no script should be) and I've done limited testing on other markets beyond Ethereum and BTC, it's just a template to tweak and play with and make into one's own.
The results shown in the strategy tester are from Bitcoin's inception so as to get a large sample size of trades, and potential returns have diminished significantly as BTC has grown to become a mega cap asset, but the script includes a date filter for backtesting and it has still performed solidly in recent years (speaking from personal experience using it myself - DYOR with the date filter).
The main advantage of this system in my opinion is in limiting the max drawdown significantly versus buy & hodl. Theoretically much better returns can be made by just holding, but that's also a good way to lose 70%+ of your capital in the inevitable bear markets (also speaking from experience).
In saying all of that, the future is fundamentally unknowable and past results in no way guarantee future performance.
System Concept:
Capture as much Bitcoin upside volatility as possible while side-stepping downside volatility as quickly as possible.
The system uses a simple but clever momentum-style trailing stop technique I learned from one of my trading mentors who uses this approach on momentum/trend-following stock market systems.
Basically, the system "ratchets" up the stop-loss to be much tighter during high bearish volatility to protect open profits from downside moves, but loosens the stop loss during sustained bullish momentum to let the position ride.
It is invested most of the time, unless BTC is trading below its 20-week EMA in which case it stays in cash/USDT to avoid holding through bear markets. It only trades one position (no pyramiding) and does not trade short, but can easily be tweaked to do whatever you like if you know what you're doing in Pine.
Default parameters:
HTF: Weekly Chart
EMA: 20-Period
ATR: 5-period
Bar Lookback: 7
Entry Rule #1:
Bitcoin's current price must be trading above its higher-timeframe EMA (Weekly 20 EMA).
Entry Rule #2:
Bitcoin must not be in 'caution' condition (no large bearish volatility swings recently).
Enter at next bar's open if conditions are met and we are not already involved in a trade.
"Caution" Condition:
Defined as true if BTC's recent 7-bar swing high minus current bar's low is > 1.5x ATR, or Daily close < Daily 20-EMA.
Trailing Stop:
Stop is trailed 1 ATR from recent swing high, or 20% of ATR if in caution condition (ie. 0.2 ATR).
Exit on next bar open upon a close below stop loss.
I typically use a limit order to open & exit trades as close to the open price as possible to reduce slippage, but the strategy script uses market orders.
I've never had any issues getting filled on limit orders close to the market price with BTC on the Daily timeframe, but if the exchange has relatively low slippage I've found market orders work fine too without much impact on the results particularly since BTC has consistently remained above $20k and highly liquid.
Cost of Trading:
The script uses no leverage and a default total round-trip commission of 0.3% which is what I pay on my exchange based on their tier structure, but this can vary widely from exchange to exchange and higher commission fees will have a significantly negative impact on realized gains so make sure to always input the correct theoretical commission cost when backtesting any script.
Static slippage is difficult to estimate in the strategy tester given the wide range of prices & liquidity BTC has experienced over the years and it largely depends on position size, I set it to 150 points per buy or sell as BTC is currently very liquid on the exchange I trade and I use limit orders where possible to enter/exit positions as close as possible to the market's open price as it significantly limits my slippage.
But again, this can vary a lot from exchange to exchange (for better or worse) and if BTC volatility is high at the time of execution this can have a negative impact on slippage and therefore real performance, so make sure to adjust it according to your exchange's tendencies.
Tax considerations should also be made based on short-term trade frequency if crypto profits are treated as a CGT event in your region.
Summary:
A simple, but effective and fairly robust system that achieves the goals I set for it.
From my preliminary testing it appears it may also work on altcoins but it might need a bit of tweaking/loosening with the trailing stop distance as the default parameters are designed to work with Bitcoin which obviously behaves very differently to smaller cap assets.
Good luck out there!
Liquidity Finder🔵 Introduction
The concept of "liquidity pool" or simply "liquidity" in technical analysis price action refers to areas on the price chart where stop losses accumulate, and the market, by reaching those areas and collecting liquidity (Stop Hunt), provides the necessary energy to move the price. This concept is prominent in the "ICT" and "Smart Money" styles. Imagine, as depicted below, the price is at a support level. The general trader mentality is that there is "demand" for the asset at this price level, and this demand will outweigh "supply" as before. So, it is likely that the price will increase. As a result, they start buying and place their stop loss below the support area.
Stop Hunt areas are essentially traders' "stop loss" levels. These are the liquidity that institutional and large traders need to fill their orders. Consequently, they penetrate the price below support areas or above resistance areas to touch their stop loss and fill their orders, and then the price trend reverses.
Cash zones are generally located under "Swings Low" and above "Swings High." More specifically, they can be categorized as support levels or resistance levels, above Double Top and Triple Top patterns, below Double Bottom and Triple Bottom patterns, above Bearish Trend lines, and below Bullish Trend lines.
Double Top and Triple Top :
Double Bottom and Triple Bottom :
Bullish Trend line and Bearish Trend line :
🔵 How to Use
To optimally use this indicator, you can adjust the settings according to the symbol, time frame, and your needs. These settings include the "sensitivity" of the "liquidity finder" function and the swing periods related to static and dynamic liquidity lines.
"Statics Liquidity Line Sensitivity" is a number between 0 and 0.4. Increasing this number decreases the sensitivity of the "Statics Liquidity Line Detection" function and increases the number of lines identified. The default value is 0.3.
"Dynamics Liquidity Line Sensitivity" is a number between 0.4 and 1.95. Increasing this number increases the sensitivity of the "Dynamics Liquidity Line Detection" function and decreases the number of lines identified. The default value is 1.
"Statics Period Pivot" is set to 8 by default. By changing this number, you can specify the period for the static liquidity line pivots.
"Dynamics Period Pivot" is set to 3 by default. By changing this number, you can specify the period for the dynamic liquidity line pivots.
🔵 Settings
Access to adjust the inputs of Static Dynamic Liquidity Line Sensitivity, Dynamics Liquidity Line Sensitivity, Statics Period Pivot, and Dynamics Period Pivot is possible from this section.
Additionally, you can enable or disable liquidity lines as needed using the buttons for "Show Statics High Liquidity Line," "Show Statics Low Liquidity Line," "Show Dynamics High Liquidity Line," and "Show Dynamics Low Liquidity Line."
arpit bollinger bandStrategy Overview:
This strategy utilizes Bollinger Bands based on a 20-period Exponential Moving Average (EMA) with a standard deviation multiplier of 1.5. It is designed to generate early trading signals based on the relationship between the price action and the Bollinger Bands.
Bollinger Bands Calculation:
The upper Bollinger Band is calculated as the 20-period EMA of the closing prices plus 1.5 times the standard deviation of the same period.
The lower Bollinger Band is calculated as the 20-period EMA of the closing prices minus 1.5 times the standard deviation.
Entry Criteria:
Buy Signal: A buy signal is generated when the current candle's high exceeds the high of the candle two periods ago, which had closed below the lower Bollinger Band. This condition implies an anticipation of a bullish reversal.
Sell Signal: A sell signal is generated when the current candle's low falls below the low of the candle two periods ago, which had closed above the upper Bollinger Band. This condition suggests an anticipated bearish reversal.
Stop Loss and Take Profit:
The stop loss for a buy order is set slightly below the low of the current candle, and for a sell order, it is set slightly above the high of the current candle.
The take profit level is determined based on a predefined risk-reward ratio of 1:3. This means the take profit target is set at a distance three times greater than the distance between the entry price and the stop loss.
Risk Management:
The strategy includes an input option to adjust the risk-reward ratio, allowing for flexibility in managing the trade's potential risk versus reward.
Trade Execution:
The strategy automatically plots the buy and sell signals on the chart and executes the trades according to the defined conditions. It also visually indicates the stop loss levels for each trade.
Usage Notes:
This strategy is designed for use in the TradingView platform using Pine Script version 5.
It is important to backtest and paper trade the strategy before using it in live trading to understand its performance characteristics and risk profile.
The strategy should be used as part of a comprehensive trading plan, considering market conditions, trader risk tolerance, and personal trading goals.
Long EMA Strategy with Advanced Exit OptionsThis strategy is designed for traders seeking a trend-following system with a focus on precision and adaptability.
**Core Strategy Concept**
The essence of this strategy lies in use of Exponential Moving Averages (EMAs) to identify potential long (buy) positions based on the relative positions of short-term, medium-term, and long-term EMAs. The use of EMAs is a classic yet powerful approach to trend detection, as these indicators smooth out price data over time, emphasizing the direction of recent price movements and potentially signaling the beginning of new trends.
**Customizable Parameters**
- **EMA Periods**: Users can define the periods for three EMAs - long-term, medium-term, and short-term - allowing for a tailored approach to capture trends based on individual trading styles and market conditions.
- **Volatility Filter**: An optional Average True Range (ATR)-based volatility filter can be toggled on or off. When activated, it ensures that trades are only entered when market volatility exceeds a user-defined threshold, aiming to filter out entries during low-volatility periods which are often characterized by indecisive market movements.
- **Trailing Stop Loss**: A trailing stop loss mechanism, expressed as a percentage of the highest price achieved since entry, provides a dynamic way to manage risk by allowing profits to run while cutting losses.
- **EMA Exit Condition**: This advanced exit option enables closing positions when the short-term EMA crosses below the medium-term EMA, serving as a signal that the immediate trend may be reversing.
- **Close Below EMA Exit**: An additional exit condition, which is disabled by default, allows positions to be closed if the price closes below a user-selected EMA. This provides an extra layer of flexibility and risk management, catering to traders who prefer to exit positions based on specific EMA thresholds.
**Operational Mechanics**
Upon activation, the strategy evaluates the current price in relation to the set EMAs. A long position is considered when the current price is above the long-term EMA, and the short-term EMA is above the medium-term EMA. This setup aims to identify moments where the price momentum is strong and likely to continue.
The strategy's versatility is further enhanced by its optional settings:
- The **Volatility Filter** adjusts the sensitivity of the strategy to market movements, potentially improving the quality of the entries during volatile market conditions.
The Average True Range (ATR) is a key component of this filter, providing a measure of market volatility by calculating the average range between the high and low prices over a specified number of periods. Here's how you can adjust the volatility filter settings for various market conditions, focusing on filtering out low-volatility markets:
Setting Examples for Volatility Filter
1. High Volatility Markets (e.g., Cryptocurrencies, Certain Forex Pairs):
ATR Periods: 14 (default)
ATR Multiplier: Setting the multiplier to a lower value, such as 1.0 or 1.2, can be beneficial in high-volatility markets. This sensitivity allows the strategy to react to volatility changes more quickly, ensuring that you're entering trades during periods of significant movement.
2. Medium Volatility Markets (e.g., Major Equity Indices, Medium-Volatility Forex Pairs):
ATR Periods: 14 (default)
ATR Multiplier: A multiplier of 1.5 (default) is often suitable for medium volatility markets. It provides a balanced approach, ensuring that the strategy filters out low-volatility conditions without being overly restrictive.
3. Low Volatility Markets (e.g., Some Commodities, Low-Volatility Forex Pairs):
ATR Periods: Increasing the ATR period to 20 or 25 can smooth out the volatility measure, making it less sensitive to short-term fluctuations. This adjustment helps in focusing on more significant trends in inherently stable markets.
ATR Multiplier: Raising the multiplier to 2.0 or even 2.5 increases the threshold for volatility, effectively filtering out low-volatility conditions. This setting ensures that the strategy only triggers trades during periods of relatively higher volatility, which are more likely to result in significant price movements.
How to Use the Volatility Filter for Low-Volatility Markets
For traders specifically interested in filtering out low-volatility markets, the key is to adjust the ATR Multiplier to a higher level. This adjustment increases the threshold required for the market to be considered sufficiently volatile for trade entries. Here's a step-by-step guide:
Adjust the ATR Multiplier: Increase the ATR Multiplier to create a higher volatility threshold. A multiplier of 2.0 to 2.5 is a good starting point for very low-volatility markets.
Fine-Tune the ATR Periods: Consider lengthening the ATR calculation period if you find that the strategy is still entering trades in undesirable low-volatility conditions. A longer period provides a more averaged-out measure of volatility, which might better suit your needs.
Monitor and Adjust: Volatility is not static, and market conditions can change. Regularly review the performance of your strategy in the context of current market volatility and adjust the settings as necessary.
Backtest in Different Conditions: Before applying the strategy live, backtest it across different market conditions with your adjusted settings. This process helps ensure that your approach to filtering low-volatility conditions aligns with your trading objectives and risk tolerance.
By fine-tuning the volatility filter settings according to the specific characteristics of the market you're trading in, you can enhance the performance of this strategy
- The **Trailing Stop Loss** and **EMA Exit Conditions** provide two layers of exit strategies, focusing on capital preservation and profit maximization.
**Visualizations**
For clarity and ease of use, the strategy plots the three EMAs and, if enabled, the ATR threshold on the chart. These visual cues not only aid in decision-making but also help in understanding the market's current trend and volatility state.
**How to Use**
Traders can customize the EMA periods to fit their trading horizon, be it short, medium, or long-term trading. The volatility filter and exit options allow for further customization, making the strategy adaptable to different market conditions and personal risk tolerance levels.
By offering a blend of trend-following principles with advanced risk management features, this strategy aims to cater to a wide range of trading styles, from cautious to aggressive. Its strength lies in its flexibility, allowing traders to fine-tune settings to their specific needs, making it a potentially valuable tool in the arsenal of any trader looking for a disciplined approach to navigating the markets.
Octopus Nest Strategy Hello Fellas,
Hereby, I come up with a popular strategy from YouTube called Octopus Nest Strategy. It is a no repaint, lower timeframe scalping strategy utilizing PSAR, EMA and TTM Squeeze.
The strategy considers these market factors:
PSAR -> Trend
EMA -> Trend
TTM Squeeze -> Momentum and Volatility by incorporating Bollinger Bands and Keltner Channels
Note: As you can see there is a potential improvement by incorporating volume.
What's Different Compared To The Original Strategy?
I added an option which allows users to use the Adaptive PSAR of @loxx, which will hopefully improve results sometimes.
Signals
Enter Long -> source above EMA 100, source crosses above PSAR and TTM Squeeze crosses above 0
Enter Short -> source below EMA 100, source crosses below PSAR and TTM Squeeze crosses below 0
Exit Long and Exit Short are triggered from the risk management. Thus, it will just exit on SL or TP.
Risk Management
"High Low Stop Loss" and "Automatic High Low Take Profit" are used here.
High Low Stop Loss: Utilizes the last high for short and the last low for long to calculate the stop loss level. The last high or low gets multiplied by the user-defined multiplicator and if no recent high or low was found it uses the backup multiplier.
Automatic High Low Take Profit: Utilizes the current stop loss level of "High Low Stop Loss" and gets calculated by the user-defined risk ratio.
Now, follows the bunch of knowledge for the more inexperienced readers.
PSAR: Parabolic Stop And Reverse; Developed by J. Welles Wilders and a classic trend reversal indicator.
The indicator works most effectively in trending markets where large price moves allow traders to capture significant gains. When a security’s price is range-bound, the indicator will constantly be reversing, resulting in multiple low-profit or losing trades.
TTM Squeeze: TTM Squeeze is a volatility and momentum indicator introduced by John Carter of Trade the Markets (now Simpler Trading), which capitalizes on the tendency for price to break out strongly after consolidating in a tight trading range.
The volatility component of the TTM Squeeze indicator measures price compression using Bollinger Bands and Keltner Channels. If the Bollinger Bands are completely enclosed within the Keltner Channels, that indicates a period of very low volatility. This state is known as the squeeze. When the Bollinger Bands expand and move back outside of the Keltner Channel, the squeeze is said to have “fired”: volatility increases and prices are likely to break out of that tight trading range in one direction or the other. The on/off state of the squeeze is shown with small dots on the zero line of the indicator: red dots indicate the squeeze is on, and green dots indicate the squeeze is off.
EMA: Exponential Moving Average; Like a simple moving average, but with exponential weighting of the input data.
Don't forget to check out the settings and keep it up.
Best regards,
simwai
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Credits to:
@loxx
@Bjorgum
@Greeny
Four WMA Strategy with TP and SLBasically I read a research paper on how they used different moving averages for long entries and short entries, and it kind of dawned on me that I always used the same one for long entry or exit, or even swing trading. So I smashed this together to see what would happen.
The strategy combines the use of four different WMAs for identifying trade entry points, along with a predefined take profit (TP) and stop loss (SL) for risk management. Here's a detailed description of its features and how it operates:
Main Features
1. **WMAs as the Core Indicator**:
- The strategy uses four WMAs with different lengths. Two WMAs (`longM1` and `longM2`) are used for long entry signals, and the other two (`shortM1` and `shortM2`) for short entry signals.
- The lengths of these WMAs are adjustable through input parameters.
2. **Trade Entry Conditions**:
- A long entry is signaled when the shorter WMA crosses under the longer WMA .
- Conversely, a short entry is signaled when the shorter WMA crosses under the longer WMA.
3. **Take Profit and Stop Loss**:
- The strategy includes a take profit and stop loss mechanism.
- The TP and SL levels are set as a percentage of the entry price, with the percentage values being adjustable through input parameters.
4. **Visual Representation**:
- The WMAs are plotted on the chart for visual aid, each with a distinct color for easy identification.
How It Works
- The strategy continuously monitors the crossing of WMAs to detect potential entry points for long and short positions.
- Upon detecting a long or short condition, it automatically enters a trade and sets the corresponding TP and SL levels based on the current price and the specified percentages.
- The strategy then actively manages the trade, exiting the position when either the TP or SL level is reached.
Drawbacks
- **Overreliance on WMAs**: The strategy heavily relies on WMAs for trade signals. While WMAs are useful for identifying trends, they might not always provide timely entry and exit signals.
- **Market Conditions**: It may not perform well in highly volatile or sideways markets where WMA crossovers could lead to false signals.
- **Risk Management**: The fixed percentage for TP and SL might not be suitable for all market conditions. Traders might need to adjust these values frequently based on market volatility and their risk tolerance.
Apparently I need to emphasize to use brains when using indicators and setting them up to achieve the results you can or want. Also risk of 12% is considered very high so I lowered the numbers to 5%, which tanked the profits, try adjusting them on your own. Check the properties settings for more info on comission and slippage.
Conclusion
The "Four WMA Strategy with TP and SL" is suitable for traders who prefer a moving average-based approach to trading, combined with a straightforward mechanism for risk management through take profit and stop loss. However, like all strategies, it should be used with an understanding of its limitations and ideally tested thoroughly in various market conditions before applying it to live trading.
