Ultimate Stochastics Strategy by NHBprod Use to Day Trade BTCHey All!
Here's a new script I worked on that's super simple but at the same time useful. Check out the backtest results. The backtest results include slippage and fees/commission, and is still quite profitable. Obviously the profitability magnitude depends on how much capital you begin with, and how much the user utilizes per order, but in any event it seems to be profitable according to backtests.
This is different because it allows you full functionality over the stochastics calculations which is designed for random datasets. This script allows you to:
Designate ANY period of time to analyze and study
Choose between Long trading, short trading, and Long & Short trading
It allows you to enter trades based on the stochastics calculations
It allows you to EXIT trades using the stochastics calculations or take profit, or stop loss, Or any combination of those, which is nice because then the user can see how one variable effects the overall performance.
As for the actual stochastics formula, you get control, and get to SEE the plot lines for slow K, slow D, and fast K, which is usually not considered.
You also get the chance to modify the smoothing method, which has not been done with regular stochastics indicators. You get to choose the standard simple moving average (SMA) method, but I also allow you to choose other MA's such as the HMA and WMA.
Lastly, the user gets the option of using a custom trade extender, which essentially allows a buy or sell signal to exist for X amount of candles after the initial signal. For example, you can use "max bars since signal" to 1, and this will allow the indicator to produce an extra sequential buy signal when a buy signal is generated. This can be useful because it is possible that you use a small take profit (TP) and quickly exit a profitable trade. With the max bars since signal variable, you're able to reenter on the next candle and allow for another opportunity.
Let me know if you have any questions! Please take a look at the performance report and let me know your thoughts! :)
ETH
Adapted RSI w/ Multi-Asset Regime Detection v1.1The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of an asset's recent price changes to detect overbought or oversold conditions in the price of said asset.
In addition to identifying overbought and oversold assets, the RSI can also indicate whether your desired asset may be primed for a trend reversal or a corrective pullback in price. It can signal when to buy and sell.
The RSI will oscillate between 0 and 100. Traditionally, an RSI reading of 70 or above indicates an overbought condition. A reading of 30 or below indicates an oversold condition.
The RSI is one of the most popular technical indicators. I intend to offer a fresh spin.
Adapted RSI w/ Multi-Asset Regime Detection
Our Adapted RSI makes necessary improvements to the original Relative Strength Index (RSI) by combining multi-timeframe analysis with multi-asset monitoring and providing traders with an efficient way to analyse market-wide conditions across different timeframes and assets simultaneously. The indicator automatically detects market regimes and generates clear signals based on RSI levels, presenting this data in an organised, easy-to-read format through two dynamic tables. Simplicity is key, and having access to more RSI data at any given time, allows traders to prepare more effectively, especially when trading markets that "move" together.
How we calculate the RSI
First, the RSI identifies price changes between periods, calculating gains and losses from one look-back period to the next. This look-back period averages gains and losses over 14 periods, which in this case would be 14 days, and those gains/losses are calculated based on the daily closing price. For example:
Average Gain = Sum of Gains over the past 14 days / 14
Average Loss = Sum of Losses over the past 14 days / 14
Then we calculate the Relative Strength (RS):
RS = Average Gain / Average Loss
Finally, this is converted to the RSI value:
RSI = 100 - (100 / (1 + RS))
Key Features
Our multi-timeframe RSI indicator enhances traditional technical analysis by offering synchronised Daily, Weekly, and Monthly RSI readings with automatic regime detection. The multi-asset monitoring system allows tracking of up to 10 different assets simultaneously, with pre-configured major pairs that can be customised to any asset selection. The signal generation system provides clear market guidance through automatic regime detection and a five-level signal system, all presented through a sophisticated visual interface with dynamic RSI line colouring and customisable display options.
Quick Guide to Use it
Begin by adding the indicator to your chart and configuring your preferred assets in the "Asset Comparison" settings.
Position the two information tables according to your preference.
The main table displays RSI analysis across three timeframes for your current asset, while the asset table shows a comparative analysis of all monitored assets.
Signals are colour-coded for instant recognition, with green indicating bullish conditions and red for bearish conditions. Pay special attention to regime changes and signal transitions, using multi-timeframe confluence to identify stronger signals.
How it Works (Regime Detection & Signals)
When we say 'Regime', a regime is determined by a persistent trend or in this case momentum and by leveraging this for RSI, which is a momentum oscillator, our indicator employs a relatively simple regime detection system that classifies market conditions as either Bullish (RSI > 50) or Bearish (RSI < 50). Our benchmark between a trending bullish or bearish market is equal to 50. By leveraging a simple classification system helps determine the probability of trend continuation and the weight given to various signals. Whilst we could determine a Neutral regime for consolidating markets, we have employed a 'neutral' signal generation which will be further discussed below...
Signal generation occurs across five distinct levels:
Strong Buy (RSI < 15)
Buy (RSI < 30)
Neutral (RSI 30-70)
Sell (RSI > 70)
Strong Sell (RSI > 85)
Each level represents different market conditions and probability scenarios. For instance, extreme readings (Strong Buy/Sell) indicate the highest probability of mean reversion, while neutral readings suggest equilibrium conditions where traders should focus on the overall regime bias (Bullish/Bearish momentum).
This approach offers traders a new and fresh spin on a popular and well-known tool in technical analysis, allowing traders to make better and more informed decisions from the well presented information across multiple assets and timeframes. Experienced and beginner traders alike, I hope you enjoy this adaptation.
Crypto Volatility Bitcoin Correlation Strategy Description:
The Crypto Volatility Bitcoin Correlation Strategy is designed to leverage market volatility specifically in Bitcoin (BTC) using a combination of volatility indicators and trend-following techniques. This strategy utilizes the VIXFix (a volatility indicator adapted for crypto markets) and the BVOL7D (Bitcoin 7-Day Volatility Index from BitMEX) to identify periods of high volatility, while confirming trends with the Exponential Moving Average (EMA). These components work together to offer a comprehensive system that traders can use to enter positions when volatility and trends are aligned in their favor.
Key Features:
VIXFix (Volatility Index for Crypto Markets): This indicator measures the highest price of Bitcoin over a set period and compares it with the current low price to gauge market volatility. A rise in VIXFix indicates increasing market volatility, signaling that large price movements could occur.
BVOL7D (Bitcoin 7-Day Volatility Index): This volatility index, provided by BitMEX, measures the volatility of Bitcoin over the past 7 days. It helps traders monitor the recent volatility trend in the market, particularly useful when making short-term trading decisions.
Exponential Moving Average (EMA): The 50-period EMA acts as a trend indicator. When the price is above the EMA, it suggests the market is in an uptrend, and when the price is below the EMA, it suggests a downtrend.
How It Works:
Long Entry: A long position is triggered when both the VIXFix and BVOL7D indicators are rising, signaling increased volatility, and the price is above the 50-period EMA, confirming that the market is trending upward.
Exit: The strategy exits the position when the price crosses below the 50-period EMA, which signals a potential weakening of the uptrend and a decrease in volatility.
This strategy ensures that traders only enter positions when the volatility aligns with a clear trend, minimizing the risk of entering trades during periods of market uncertainty.
Testing and Timeframe:
This strategy has been tested on Bitcoin using the daily timeframe, which provides a longer-term perspective on market trends and volatility. However, users can adjust the timeframe according to their trading preferences. It is crucial to note that this strategy does not include comprehensive risk management, aside from the exit condition when the price crosses below the EMA. Users are strongly advised to implement their own risk management techniques, such as setting appropriate stop-loss levels, to safeguard their positions during high volatility periods.
Utility:
The Crypto Volatility Bitcoin Correlation Strategy is particularly well-suited for traders who aim to capitalize on the high volatility often seen in the Bitcoin market. By combining volatility measurements (VIXFix and BVOL7D) with a trend-following mechanism (EMA), this strategy helps identify optimal moments for entering and exiting trades. This approach ensures that traders participate in potentially profitable market moves while minimizing exposure during times of uncertainty.
Use Cases:
Volatility-Based Entries: Traders looking to take advantage of market volatility spikes will find this strategy useful for timing entry points during market swings.
Trend Confirmation: By using the EMA as a confirmation tool, traders can avoid entering trades that go against the trend, which can result in significant losses during volatile market conditions.
Risk Management: While the strategy exits when price falls below the EMA, it is important to recognize that this is not a full risk management system. Traders should use caution and integrate additional risk measures, such as stop-losses and position sizing, to better manage potential losses.
How to Use:
Step 1: Monitor the VIXFix and BVOL7D indicators. When both are rising and the Bitcoin price is above the EMA, the strategy will trigger a long entry, indicating that the market is experiencing increased volatility with a confirmed uptrend.
Step 2: Exit the position when the price drops below the 50-period EMA, signaling that the trend may be reversing or weakening, reducing the likelihood of continued upward price movement.
This strategy is open-source and is intended to help traders navigate volatile market conditions, particularly in Bitcoin, using proven indicators for volatility and trend confirmation.
Risk Disclaimer:
This strategy has been tested on the daily timeframe of Bitcoin, but users should be aware that it does not include built-in risk management except for the below-EMA exit condition. Users should be extremely cautious when using this strategy and are encouraged to implement their own risk management, such as using stop-losses, position sizing, and setting appropriate limits. Trading involves significant risk, and this strategy does not guarantee profits or prevent losses. Past performance is not indicative of future results. Always test any strategy in a demo environment before applying it to live markets.
Quatro SMA Strategy [4h]Hello, I would like to present to you The "Quatro SMA" strategy
Strategy is based on four simple moving averages of different lengths and monitoring trading volume. The key idea is to identify strong market trends by comparing short-term moving averages with the long-term SMA. The strategy generates buy signals when all short-term SMAs are above the SMA(200) and the volume confirms the strength of the move. Similarly, sell signals are generated when all short-term SMAs are below the SMA(200), and the volume is sufficiently high.
The strategy manages risk by applying a stop loss and three different Take Profit levels (TP1, TP2, TP3), with varying percentages of the position closed at each level.
Each Take Profit level is triggered at a specific percentage gain, with the position being closed gradually depending on the achieved targets. The percentage of the position closed at each TP level is also defined by the user.
Indicators and Parameters:
Simple Moving Averages (SMA):
The script utilizes four simple moving averages with different lengths (4, 16, 32, 200). The first three SMAs (SMA1, SMA2, SMA3) are used to determine the trend direction, while the fourth SMA (with a length of 200) serves as a support/resistance line.
Volume:
The script monitors trading volume and checks if the current volume exceeds 2.5 times the average volume of the last 40 candles. High volume is considered as confirmation of trend strength.
Entry Conditions:
- Long Position: Triggered when SMA1 > SMA2 > SMA3, the closing price is above SMA(200), and the volume condition is met.
- Short Position: Triggered when SMA1 < SMA2 < SMA3, the closing price is below SMA(200), and the volume condition is met.
Exit Conditions:
- Long Position: Closed when SMA1 < SMA2 < SMA3 and the closing price is above SMA(200).
- Short Position: Closed when SMA1 > SMA2 > SMA3 and the closing price is below SMA(200).
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
1000SATS and ORDI Market Cap RatioSure! Here is a detailed description and usage guide for your TradingView indicator:
### Indicator Description
**Title**: 1000SATS/ORDI Market Cap Ratio
**Description**: The "1000SATS/ORDI Market Cap Ratio" indicator calculates and visualizes the market capitalization ratio between 1000SATS and ORDI. This indicator allows traders and investors to analyze the relative market strength and valuation trends of 1000SATS compared to ORDI over time. By tracking this ratio, users can gain insights into market dynamics and potential trading opportunities between these two assets.
### Indicator Usage
**Purpose**:
- To compare the market capitalizations of 1000SATS and ORDI.
- To identify potential undervaluation or overvaluation of 1000SATS relative to ORDI.
- To assist in making informed trading and investment decisions based on market cap trends.
**How to Use**:
1. **Add the Indicator to Your Chart**:
- Open TradingView and navigate to your chart.
- Click on the "Indicators" button at the top of the chart.
- Select "Pine Editor" and paste the provided script.
- Click "Add to Chart" to apply the indicator.
2. **Interpret the Ratio**:
- The indicator will plot a line representing the ratio of the market capitalization of 1000SATS to ORDI.
- A rising ratio indicates that the market cap of 1000SATS is increasing relative to ORDI, suggesting stronger market performance or higher valuation of 1000SATS.
- A falling ratio indicates that the market cap of 1000SATS is decreasing relative to ORDI, suggesting weaker market performance or lower valuation of 1000SATS.
3. **Analyze Trends**:
- Use the indicator to spot trends and potential reversal points in the market cap ratio.
- Combine the ratio analysis with other technical indicators and chart patterns to enhance your trading strategy.
4. **Set Alerts**:
- Set custom alerts on the ratio to notify you of significant changes or specific thresholds being reached, enabling timely decision-making.
**Example**:
- If the ratio is consistently rising, it may indicate a good opportunity to consider 1000SATS as a stronger investment relative to ORDI.
- Conversely, if the ratio is falling, it may be a signal to reevaluate the strength of 1000SATS compared to ORDI.
**Note**: Always conduct thorough analysis and consider other market factors before making trading decisions based on this indicator.
### Script
```pinescript
//@version=4
study("1000SATS and ORDI Market Cap Ratio", shorttitle="1000SATS/ORDI Ratio", overlay=true)
// Define the circulating supply for ORDI and 1000SATS
ORDI_supply = 21000000 // Circulating supply of ORDI
SATS_1000_supply = 2100000000000 // Circulating supply of 1000SATS
// Fetch the price data for ORDI
ordi_price = security("BINANCE:ORDIUSDT", timeframe.period, close)
// Fetch the price data for 1000SATS
sats_1000_price = security("BINANCE:1000SATSUSDT", timeframe.period, close)
// Calculate the market capitalizations
ordi_market_cap = ordi_price * ORDI_supply
sats_1000_market_cap = sats_1000_price * SATS_1000_supply
// Calculate the market cap ratio
ratio = sats_1000_market_cap / ordi_market_cap
// Plot the ratio
plot(ratio, title="1000SATS/ORDI Market Cap Ratio", color=color.blue, linewidth=2)
```
This description and usage guide should help users understand the purpose and functionality of your indicator, as well as how to effectively apply it in their trading activities on TradingView.
ETH Long/Short Ratio BITFINEX - (ALPHRACTAL)Indicator Description: ETH Long/Short Ratio BITFINEX - (ALPHRACTAL)
The ETH Long/Short Ratio BITFINEX - (ALPHRACTAL) indicator provides a detailed analysis of Ethereum (ETH) long and short positions in USD and USDT on the Bitfinex exchange. This indicator is ideal for traders who want to monitor market behavior and better understand the relationship between long and short positions.
Features:
USD and USDT Long/Short Ratio:
Calculates and displays the ratio between long and short ETH positions in USD and USDT.
Helps identify market trends and the relative strength between buyers and sellers.
Color Configuration:
Allows customization of chart colors for clear and distinct visualization of USD and USDT ratios.
Uses colors with adjustable transparency to enhance chart visibility.
Label Display:
Option to show or hide labels indicating the type of ratio (USD or USDT) at the latest chart value.
Labels are useful for quickly identifying the visualized ratio.
Display Control:
Option to enable or disable the display of individual USD and USDT ratio charts.
Flexibility to view only the relevant data for your analysis.
How to Use:
Add the indicator to your chart to visualize the long/short ratios of ETH in USD and USDT.
Adjust colors and transparency as per your preference for better visual distinction.
Use the option to show or hide labels for quick identification of the data.
Analyze the relationship between long and short positions to make informed trading decisions, observing market buying and selling trends.
Example Use Cases:
Market Sentiment Analysis: An increase in the Long/Short ratio may indicate bullish sentiment among traders, while a decrease may indicate bearish sentiment.
Identifying Opportunities: Significant discrepancies between USD and USDT ratios may signal arbitrage opportunities or alert to significant market movements.
This indicator is a powerful tool for Ethereum traders who want a deeper understanding of market behavior and the dynamics of long and short positions on Bitfinex. Add the ETH Long/Short Ratio BITFINEX - (ALPHRACTAL) to your technical analysis toolkit and gain an edge in your trading strategy.
Pre-market Highs & Lows on regular trading hours (RTH) chartShows pre-market highs and lows on RTH or ETH chart
-Pre-market duration user input (default is 16 'bar hours'; covering the time from S&P RTH close at 4pm >> 9:30am RTH open next day
-Displays on both RTH and ETH charts
-Written for ES (ES1! or e.g ESM2023), but tested and working on SPY, SPX
-Works across timeframes
Example usage on Electronic trading hours (ETH) chart; showing the 'bar hours' user input lookback duration visually
Regular vs Electronic Trading hours Gap (RTH vs ETH); 4pm-9:30am-Shows the gap between 4pm close and 9:30am open; the Regular trading hours Vs Electronic trading hours Gap (RTH vs ETH).
-Displays this as a box starting at 9:30am, whose bottom is the 9:30am open; top is previous day's 4pm close.
-Displays when chart is toggled to either of ETH or RTH.
-Useful reminder of area above/below opening bell price that price often has a tendency to want to fill in, partially or fully
--(all times here refer to America/New_York timezone)
//Options:
~Number of past boxes to show
~Extend boxes fully to the right
~Box background color, border color, and opacities
//Limitations:
-works only on timeframes 30mins or lower (works on 1,2,5,10,15,30minutes)
-will not work on non-typical low timeframes (like 4min or 7min) since they are not divisible into 30
Altcoin Dominance (without ETH) Excluding Stablecoins UnsymetricAltcoin Dominance (without ETH) Excluding Stablecoins Unsymetric
The purpose of the script is to show Altcoin's strength without Ethereum once we exclude stablecoins.
So we look into all altcoins besides eth and besides stablecoins divided by a value of eth+btc
ETH Dominance Excluding StablecoinsETH Dominance Excluding Stablecoins.
The purpose of the script is to show Ethereum's strength relative to other cryptocurrencies.
Pretty much shows ETH Dominance in comparison to Market Cap once we exclude the 5 largest stablecoins.
VWMA/SMA 3Commas BotThis strategy utilizes two pairs of different Moving Averages, two Volume-Weighted Moving Averages (VWMA) and two Simple Moving Averages (SMA).
There is a FAST and SLOW version of each VWMA and SMA.
The concept behind this strategy is that volume is not taken into account when calculating a Simple Moving Average.
Simple Moving Averages are often used to determine the dominant direction of price movement and to help a trader look past any short-term volatility or 'noise' from price movement, and instead determine the OVERALL direction of price movement so that one can trade in that direction (trend-following) or look for opportunities to trade AGAINST that direction (fading).
By comparing the different movements of a Volume-Weighted Moving Average against a Simple Moving Average of the same length, a trader can get a better picture of what price movements are actually significant, helping to reduce false signals that might occur from only using Simple Moving Averages.
The practical applications of this strategy are identifying dominant directional trends. These can be found when the Volume Weighted Moving Average is moving in the same direction as the Simple Moving Average, and ideally, tracking above it.
This would indicate that there is sufficient volume supporting an uptrend or downtrend, and thus gives traders additional confirmation to potentially look for a trade in that direction.
One can initially look for the Fast VWMA to track above the Fast SMA as your initial sign of bullish confirmation (reversed for downtrending markets). Then, when the Fast VWMA crosses over the Slow SMA, one can determine additional trend strength. Finally, when the Slow VWMA crosses over the Slow SMA, one can determine that the trend is truly strong.
Traders can choose to look for trade entries at either of those triggers, depending on risk tolerance and risk appetite.
Furthermore, this strategy can be used to identify divergence or weakness in trending movements. This is very helpful for identifying potential areas to exit one's trade or even look for counter-trend trades (reversals).
These moments occur when the Volume-Weighted Moving Average, either fast or slow, begins to trade in the opposite direction as their Simple Moving Average counterpart.
For instance, if price has been trending upwards for awhile, and the Fast VWMA begins to trade underneath the Fast SMA, this is an indication that volume is beginning to falter. Uptrends need appropriate volume to continue moving with momentum, so when we see volume begin to falter, it can be a potential sign of an upcoming reversal in trend.
Depending on how quickly one wants to enter into a movement, one could look for crosses of the Fast VWMA under/over the Fast SMA, crosses of the Fast VWMA over/under the Slow SMA, or crosses over/under of the Slow VWMA and the Slow SMA.
This concept was originally published here on TradingView by ProfitProgrammers.
Here is a link to his original indicator script:
I have added onto this concept by:
converting the original indicator into a strategy tester for backtesting
adding the ability to conveniently test long or short strategies, or both
adding the ability to calculate dynamic position sizes
adding the ability to calculate dynamic stop losses and take profit levels using the Average True Range
adding the ability to exit trades based on overbought/oversold crosses of the Stochastic RSI
conveniently switch between different thresholds or speeds of the Moving Average crosses to test different strategies on different asset classes
easily hook this strategy up to 3Commas for automation via their DCA bot feature
Full credit to ProfitProgrammers for the original concept and idea.
Any feedback or suggestions are greatly appreciated.
Time Based Crypto DayTrade StrategyThis is a time based strategy, designed to enter and exit within the same day of the week, using different hours for entry and exit.
The script is long only direction, and it has no risk management inside, so use it with caution.
At the same time you can also calculate each individual hour return within a certain day, and make your own idea about the best moments to be enter.
In order to filter a bit from the bad trades, I have applied an ATR filter, to check if that volatility is rising in order to help eliminate some of the bad trades when there is no volatility around.
For this example, on BTC, it seems that for the last years, on tuesday and thursday, enterring at the beginning of the daily candle, 01:00hours and exit at 00:00 hours, seems to give positive results giving the idea that can be converted in some sort of edge into our favor.
However dont take this entirelly for granted and conduct your own searches
Trend Following based on Trend ConfidenceThis is a Trend Following strategy based on the Trend Confidence indicator.
The goal of this strategy is to be a simple Trend Following strategy, but also to be as precise as possible when it comes to the question 'how confident are we that a linear trend is ongoing?'. For this we calculate the 'confidence' of a linear trend in the past number of closing prices. The idea of this strategy is that past a certain confidence, the ongoing linear trend is more likely to continue than not.
Trend Confidence:
The Trend Confidence shows us how strong of a linear trend the price has made in the past number (given by Length parameter) of closing prices. The steepness of the price change makes the Trend Confidence more extreme (more positive for an uptrend or more negative for a downtrend), and the deviation from a straight line makes the Trend Confidence less extreme (brings the confidence closer to 0). This way we can filter out signals by wild/sudden price moves that don't follow a clear linear trend.
Math behind the Trend Confidence:
A linear fit is made on the past number of closing prices, using Ordinary Linear Regression. We have the steepness of the linear fit: b in y=a+bx . And we have the standard deviation of the distances from the closing prices to the linear fit: sd . The Trend Confidence is the ratio b/sd .
Entries and Exits:
For entry and exit points we look at how extreme the Trend Confidence is. The strategy is based on the assumption that past a certain confidence level, the ongoing linear trend is more likely to continue than not.
So when the Trend Confidence passes above the 'Long entry" threshold, we go Long. After that when the Trend Confidence passes under the 'Long exit' threshold, we exit. The Long entry should be a positive value so that we go Long once a linear uptrend with enough confidence has been detected.
When the Trend Confidence passes below the 'Short entry' threshold, we go Short. After that when the Trend Confidence passes above the 'Short exit' threshold, we exit. The Short entry should be a negative value so that we go Short once a linear downtrend with enough confidence has been detected.
Default Parameters:
The strategy is intended for BTC-USD market, 4 hour timeframe. The strategy also works on ETH-USD with similar parameters.
The Length is arbitrarily set at 30, this means we look at the past 30 closing prices to determine a linear trend. Note that changing the length will change the range of Trend Confidence values encountered.
The default entry and exit thresholds for Longs and Shorts do not mirror each other. This is because the BTC-USD market goes up more heavily and more often than it goes down. So the ideal parameters for Longs and Shorts are not the same.
The positive results of the strategy remain when the parameters are slightly changed (robustness check).
The strategy uses 100% equity per trade, but has a 10% stop loss so that a maximum of 10% is risked per trade.
Commission is set at 0.1% as is the highest commission for most crypto exchanges.
Slippage is set at 5 ticks, source for this is theblock.co.
Ichimoku Cloud with MACD and Trailing Stop Loss (by Coinrule)The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on a chart. It also uses these figures to compute a “cloud” that attempts to forecast where the price may find support or resistance in the future.
The Ichimoku Cloud was developed by Goichi Hosoda, a Japanese journalist, and published in the late 1960s. It provides more data points than the standard candlestick chart. While it seems complicated at first glance, those familiar with how to read the charts often find it easy to understand with well-defined trading signals.
The Ichimoku Cloud is composed of five lines or calculations, two of which comprise a cloud where the difference between the two lines is shaded in.
The lines include a nine-period average, a 26-period average, an average of those two averages, a 52-period average, and a lagging closing price line.
The cloud is a key part of the indicator. When the price is below the cloud, the trend is down. When the price is above the cloud, the trend is up.
The above trend signals are strengthened if the cloud is moving in the same direction as the price. For example, during an uptrend, the top of the cloud is moving up, or during a downtrend, the bottom of the cloud is moving down.
The MACD is a trend following momentum indicator and provides identification of short-term trend direction. In this variation it utilises the 12-period as the fast and 26-period as the slow length EMAs, with signal smoothing set at 9.
This strategy combines the Ichimoku Cloud with the MACD indicator to better enter trades.
Long/Exit orders are placed when three basic signals are triggered.
Long Position:
Tenkan-Sen is above the Kijun-Sen
Chikou-Span is above the close of 26 bars ago
Close is above the Kumo Cloud
MACD line crosses over the signal line
Exit Position:
Price increases 3% trailing
Price decreases 3% trailing
The script is backtested from 1 June 2022 and provides good returns.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Linear EDCA v1.2Strategy Description:
Linear EDCA (Linear Enhanced Dollar Cost Averaging) is an enhanced version of the DCA fixed investment strategy. It has the following features:
1. Take the 1100-day SMA as a reference indicator, enter the buy range below the moving average, and enter the sell range above the moving average
2. The order to buy and sell is carried out at different "speed", which are set with two linear functions, and you can change the slope of the linear function to achieve different trading position control purposes
3. This fixed investment is a low-frequency strategy and only works on a daily level cycle
----------------
Strategy backtest performance:
BTCUSD (September 2014~September 2022): Net profit margin 26378%, maximum floating loss 47.12% (2015-01-14)
ETHUSD (August 2018~September 2022): Net profit margin 1669%, maximum floating loss 49.63% (2018-12-14)
----------------
How the strategy works:
Buying Conditions:
The closing price of the day is below the 1100 SMA, and the ratio of buying positions is determined by the deviation of the closing price from the moving average and the buySlope parameter
Selling Conditions:
The closing price of the day is above the 1100 SMA, and the ratio of the selling position is determined by the deviation of the closing price and the moving average and the sellSlope parameter
special case:
When the sellOffset parameter>0, it will maintain a small buy within a certain range above the 1100 SMA to avoid prematurely starting to sell
The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
----------------
Version Information:
Current version v1.2 (the first officially released version)
v1.2 version setting parameter description:
defInvestRatio: The default fixed investment ratio, the strategy will calculate the position ratio of a single fixed investment based on this ratio and a linear function. The default 0.025 represents 2.5% of the position
buySlope: the slope of the linear function of the order to buy, used to control the position ratio of a single buy
sellSlope: the slope of the linear function of the order to sell, used to control the position ratio of a single sell
sellOffset: The offset of the order to sell. If it is greater than 0, it will keep a small buy within a certain range to avoid starting to sell too early
maxSellRate: Controls the maximum sell multiple. The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
maxBuyRate: Controls the maximum buy multiple. The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
maPeriod: the length of the moving average, 1100-day MA is used by default
smoothing: moving average smoothing algorithm, SMA is used by default
useDateFilter: Whether to specify a date range when backtesting
settleOnEnd: If useDateFilter==true, whether to close the position after the end date
startDate: If useDateFilter==true, specify the backtest start date
endDate: If useDateFilter==true, specify the end date of the backtest
investDayofweek: Invest on the day of the week, the default is to close on Monday
intervalDays: The minimum number of days between each invest. Since it is calculated on a weekly basis, this number must be 7 or a multiple of 7
The v1.2 version data window indicator description (only important indicators are listed):
MA: 1100-day SMA
RoR%: floating profit and loss of the current position
maxLoss%: The maximum floating loss of the position. Note that this floating loss represents the floating loss of the position, and does not represent the floating loss of the overall account. For example, the current position is 1%, the floating loss is 50%, the overall account floating loss is 0.5%, but the position floating loss is 50%
maxGain%: The maximum floating profit of the position. Note that this floating profit represents the floating profit of the position, and does not represent the floating profit of the overall account.
positionPercent%: position percentage
positionAvgPrice: position average holding cost
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策略说明：
Linear EDCA（Linear Enhanced Dollar Cost Averaging）是一个DCA定投策略的增强版本，它具有如下特性：
1. 以1100日SMA均线作为参考指标，在均线以下进入定买区间，在均线以上进入定卖区间
2. 定买和定卖以不同的“速率”进行，它们用两条线性函数设定，并且你可以通过改变线性函数的斜率，以达到不同的买卖仓位控制的目的
3. 本定投作为低频策略，只在日级别周期工作
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策略回测表现：
BTCUSD（2014年09月~2022年09月）：净利润率26378%，最大浮亏47.12%（2015-01-14）
ETHUSD（2018年08~2022年09月）：净利润率1669%，最大浮亏49.63%（2018-12-14）
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策略工作原理：
买入条件：
当日收盘价在 1100 SMA 之下，由收盘价和均线的偏离度，以及buySlope参数决定买入仓位比例
卖出条件：
当日收盘价在 1100 SMA之上，由收盘价和均线的偏离度，以及sellSlope参数决定卖出仓位比例
特例：
当sellOffset参数>0，则在 1100 SMA以上一定范围内还会保持小幅买入，避免过早开始卖出
单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
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版本信息：
当前版本v1.2（第一个正式发布的版本）
v1.2版本设置参数说明：
defInvestRatio: 默认定投比例，策略会根据此比例和线性函数计算得出单次定投的仓位比例。默认0.025代表2.5%仓位
buySlope: 定买的线性函数斜率，用来控制单次买入的仓位倍率
sellSlope: 定卖的线性函数斜率，用来控制单次卖出的仓位倍率
sellOffset: 定卖的偏移度，如果大于0，则在一定范围内还会保持小幅买入，避免过早开始卖出
maxSellRate: 控制最大卖出倍率。单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
maxBuyRate: 控制最大买入倍率。单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
maPeriod: 均线长度，默认使用1100日MA
smoothing: 均线平滑算法，默认使用SMA
useDateFilter: 回测时是否要指定日期范围
settleOnEnd: 如果useDateFilter==true，在结束日之后是否平仓所持有的仓位平仓
startDate: 如果useDateFilter==true，指定回测开始日期
endDate: 如果useDateFilter==true，指定回测结束日期
investDayofweek: 每次在周几定投，默认在每周一收盘
intervalDays: 每次定投之间的最小间隔天数，由于是按周计算，所以此数字必须是7或7的倍数
v1.2版本数据窗口指标说明（只列出重要指标）：
MA：1100日SMA
RoR%: 当前仓位的浮动盈亏
maxLoss%: 仓位曾经的最大浮动亏损，注意此浮亏代表持仓仓位的浮亏情况，并不代表整体账户浮亏情况。例如当前仓位是1%，浮亏50%，整体账户浮亏是0.5%，但仓位浮亏是50%
maxGain%: 仓位曾经的最大浮动盈利，注意此浮盈代表持仓仓位的浮盈情况，并不代表整体账户浮盈情况。
positionPercent%: 仓位持仓占比
positionAvgPrice: 仓位平均持仓成本
Simple RSI and SMA Long and Short (by Coinrule)The relative strength index ( RSI ) is a momentum indicator used in technical analysis . RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
A simple moving average ( SMA ) calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range.
The Strategy enters and closes the trade when the following conditions are met:
LONG
SMA100 is greater than SMA150
RSI is greater than 50
SHORT
SMA100 is less than SMA150
RSI is less than 50
When a long position is opened, it remains open until the conditions for a short are met at which point the long position is closed and the short position is opened. Then, when the conditions for the long position are met, the short will be closed and a long will be opened.
This strategy is back tested from 1 January 2022 to simulate how the strategy would work in a bear market. The strategy provides good returns.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
QQE Student's T-Distribution Bollinger Bands ScreenerThis script scans 20 custom symbols and displays the QQE Students T-Distribution Bollinger Bandwidth as a percentage, the quarter segment percentage, a score that tells you what segment of the band the price is in, and what direction the market is going in. This is useful because it can tell you how volatile a market is and how much reward is in the market. It also tells you what direction the market is going in so you can pick a symbol that has the best looking reward. I really hope that this script complements the group of indicators I have made so far. Here is a list of the other two indicators related to this script.
Please enjoy!
Crypto Map Dashboard v1.0🔰Overview
Charts are an essential part of working with data, as they are a way to condense large amounts of data into an easy to understand format. Visualizations of data can bring out insights to someone looking at the data for the first time, as well as convey findings to others who won’t see the raw data. There are countless chart types out there, each with different use cases. Often, the most difficult part of creating a data visualization is figuring out which chart type is best for the task at hand.
What are the types of metrics, features, or other variables that you plan on plotting? Although it depended on some multiple factors!
But my choices of the chart type for this Crypto datas was Pie chart or Donut char for crypto dominances ,and Colum (Bar) chart for Total MarketCaps .
The audiences that I plan on presenting this for them could be all tradingviewrs , especially crypto lovers ,or those who just aim to have an initial exploration for themselves ,like me!
so this indicator mostly could be an educational indicator script for pine coders !
We can use the " Crypto Map Dashboard " indicator to Get an quick overview of the crypto market and monitor where the smart money Flow changing by comparing the dominances and totals Caps .
In general, it consists of 4 parts:
✅1 =>> Table1 : If you like to see and compare and monitor the changes of dominances of (Bitcoin, Ethereum, Usdt , Usdc , etc.) and their market cap in different times you can see the table on The upper-right corner.
✅2 =>> Table2: Also, in the table lower-right corner, you can see the changes of the totals(Total, Total2 , Total3 and TotalDefi) in the same time periods.
✅3 =>> pie chart or donut chart: By viewing this , you understand better about Table1 Datas, that it depicts exactly how Dominance is distributed and specialized.
✅4 =>> column chart (bar chart) : And in the last you can clearly compare the total marketcaps and see how far they are from their ATHs.
You also can even notice the entry and exit of liquidity from the crypto market!
I must also mention that I am definitely still a beginner compared to more experienced pine coders, and there may be some bugs in my codes and calculations, but I am an open person and I welcome your comments ,Also Let me know if you have any questions.
Lots of Love to all tradingviewers and pineCoder ,Cheers!💚❤️💙
ETH Dominance Excluding BTCThe indicator shows when ETH is undervalued or overvalued with regard to other alts. BTC capitalization is not taken into account.
Coral Trend Pullback Strategy (TradeIQ)Description:
Strategy is taken from the TradeIQ YouTube video called "I Finally Found 80% Win Rate Trading Strategy For Crypto".
Check out the full video for further details/clarification on strategy entry/exit conditions.
The default settings are exactly as TradeIQ described in his video.
However I found some better results by some tweaking settings, increasing R:R ratio and by turning off confirmation indicators.
This would suggest that perhaps the current confirmation indicators are not the best options. I'm happy to try add some other optional confirmation indicators if they look to be more effective.
Recommended timeframe: 1H
Strategy incorporates the following features:
Risk management:
Configurable X% loss per stop loss
Configurable R:R ratio
Trade entry:
Based on strategy conditions below
Trade exit:
Based on strategy conditions below
Backtesting:
Configurable backtesting range by date
Trade drawings:
Each entry condition indicator can be turned on and off
TP/SL boxes drawn for all trades. Can be turned on and off
Trade exit information labels. Can be turned on and off
NOTE: Trade drawings will only be applicable when using overlay strategies
Alerting:
Alerts on LONG and SHORT trade entries
Debugging:
Includes section with useful debugging techniques
Strategy conditions
Trade entry:
LONG
C1: Coral Trend is bullish
C2: At least 1 candle where low is above Coral Trend since last cross above Coral Trend
C3: Pullback happens and price closes below Coral Trend
C4: Coral Trend colour remains bullish for duration of pullback
C5: After valid pullback, price then closes above Coral Trend
C6: Optional confirmation indicators (choose either C6.1 or C6.2 or NONE):
C6.1: ADX and DI (Single indicator)
C6.1.1: Green line is above red line
C6.1.2: Blue line > 20
C6.1.3: Blue trending up over last 1 candle
C6.2: Absolute Strengeh Histogram + HawkEye Volume Indicator (Two indicators combined)
C6.2.1: Absolute Strengeh Histogram colour is blue
C6.2.2: HawkEye Volume Indicator colour is green
SHORT
C1: Coral Trend is bearish
C2: At least 1 candle where high is below Coral Trend since last cross below Coral Trend
C3: Pullback happens and price closes above Coral Trend
C4: Coral Trend colour remains bearish for duration of pullback
C5: After valid pullback, price then closes below Coral Trend
C6: Optional confirmation indicators (choose either C6.1 or C6.2 or NONE):
C6.1: ADX and DI (Single indicator)
C6.1.1: Red line is above green line
C6.1.2: Blue line > 20
C6.1.3: Blue trending up over last 1 candle
C6.2: Absolute Strengeh Histogram + HawkEye Volume Indicator (Two indicators combined)
C6.2.1: Absolute Strengeh Histogram colour is red
C6.2.2: HawkEye Volume Indicator colour is red
NOTE: All the optional confirmation indicators cannot be overlayed with Coral Trend so feel free to add each separately to the chart for visual purposes
Trade exit:
Stop Loss: Calculated by recent swing low over previous X candles (configurable with "Local High/Low Lookback")
Take Profit: Calculated from R:R multiplier * Stop Loss size
Credits
Strategy origin: TradeIQ's YouTube video called "I Finally Found 80% Win Rate Trading Strategy For Crypto"
It combines the following indicators for trade entry conditions:
Coral Trend Indicator by @LazyBear (Main indicator)
Absolute Strength Histogram | jh by @jiehonglim (Optional confirmation indicator)
Indicator: HawkEye Volume Indicator by @LazyBear (Optional confirmation indicator)
ADX and DI by @BeikabuOyaji (Optional confirmation indicator)
RSI with Slow and Fast MA Crossing Strategy (by Coinrule)This strategy utilises 3 different conditions that have to be met to buy and 1 condition to sell. This strategy works best on the ETH/USDT pair on the 4-hour timescale.
In order for the strategy to enter the trade, it must meet all of the conditions listed below:
ENTRY
RSI increases by 5
RSI is lower than 70
MA9 crosses above MA50
To exit a trade, the below condition must be met:
EXIT
MA50 crosses above MA9
This strategy works well on LINK/USDT on the 1-day timeframe, MIOTA/USDT on the 2-hour timeframe, BTC/USDT on the 4-hour timeframe, and BEST/USDT on the 1-day timeframe (and 4h).
Back-tested from 1 January 2020.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
ETH spot volumeIndicator with aggregated volume for all the most actively traded ethereum spot markets.
Can be denominated in either US dollars or the number of coins traded.
Can be displayed as stacked volume or an index that shows the percentage market share each market has.
In the settings you can exclude any market so that it only shows the individual and total volume of the markets you're interested in.
The currency it's traded against is always specified (e.g. USDT, BUSD, ...).
It's public and free for anyone to use.
ETH perpetual swaps volumeIndicator with aggregated volume for all the most actively traded ethereum perpetual swaps.
Can be denominated in either US dollars or the number of coins traded.
Can be displayed as stacked volume or an index that shows the percentage market share each contract has.
In the settings you can exclude any contract so that it only shows the individual and total volume of the markets you're interested in.
"Linear" or "inverse" refers to the type of perpetual swap contract it is.
Inverse contracts use coin margin, so in this case ETH.
Linear contracts use some type of dollar equivalent margin like USDT for example.
The margin is always specified for the linear contracts.
It's public and free for anyone to use.
