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Heikin Ashi RSI + OTT [Erebor]Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a popular momentum oscillator used in technical analysis to measure the speed and change of price movements. Developed by J. Welles Wilder, the RSI is calculated using the average gains and losses over a specified period, typically 14 days. Here's how it works:
Description and Calculation:
1. Average Gain and Average Loss Calculation:
- Calculate the average gain and average loss over the chosen period (e.g., 14 days).
- The average gain is the sum of gains divided by the period, and the average loss is the sum of losses divided by the period.
2. Relative Strength (RS) Calculation:
- The relative strength is the ratio of average gain to average loss.
The RSI oscillates between 0 and 100. Traditionally, an RSI above 70 indicates overbought conditions, suggesting a potential sell signal, while an RSI below 30 suggests oversold conditions, indicating a potential buy signal.
Pros of RSI:
- Identifying Overbought and Oversold Conditions: RSI helps traders identify potential reversal points in the market due to overbought or oversold conditions.
- Confirmation Tool: RSI can be used in conjunction with other technical indicators or chart patterns to confirm signals, enhancing the reliability of trading decisions.
- Versatility: RSI can be applied to various timeframes, from intraday to long-term charts, making it adaptable to different trading styles.
Cons of RSI:
- Whipsaws: In ranging markets, RSI can generate false signals, leading to whipsaws (rapid price movements followed by a reversal).
- Not Always Accurate: RSI may give false signals, especially in strongly trending markets where overbought or oversold conditions persist for extended periods.
- Subjectivity: Interpretation of RSI levels (e.g., 70 for overbought, 30 for oversold) is somewhat subjective and can vary depending on market conditions and individual preferences.
Checking RSIs in Different Periods:
Traders often use multiple timeframes to analyze RSI for a more comprehensive view:
- Fast RSI (e.g., 8-period): Provides more sensitive signals, suitable for short-term trading and quick decision-making.
- Slow RSI (e.g., 32-period): Offers a smoother representation of price movements, useful for identifying longer-term trends and reducing noise.
By comparing RSI readings across different periods, traders can gain insights into the momentum and strength of price movements over various timeframes, helping them make more informed trading decisions. Additionally, divergence between fast and slow RSI readings may signal potential trend reversals or continuation patterns.
Heikin Ashi Candles
Let's consider a modification to the traditional “Heikin Ashi Candles” where we introduce a new parameter: the period of calculation. The traditional HA candles are derived from the open 01, high 00 low 00, and close 00 prices of the underlying asset.
Now, let's introduce a new parameter, period, which will determine how many periods are considered in the calculation of the HA candles. This period parameter will affect the smoothing and responsiveness of the resulting candles.
In this modification, instead of considering just the current period, we're averaging or aggregating the prices over a specified number of periods . This will result in candles that reflect a longer-term trend or sentiment, depending on the chosen period value.
For example, if period is set to 1, it would essentially be the same as traditional Heikin Ashi candles. However, if period is set to a higher value, say 5, each candle will represent the average price movement over the last 5 periods, providing a smoother representation of the trend but potentially with delayed signals compared to lower period values.
Traders can adjust the period parameter based on their trading style, the timeframe they're analyzing, and the level of smoothing or responsiveness they prefer in their candlestick patterns.
Optimized Trend Tracker
The "Optimized Trend Tracker" is a proprietary trading indicator developed by PulseWire user ANIL ÖZEKŞİ. It is designed to identify and track trends in financial markets efficiently. The indicator attempts to smooth out price fluctuations and provide clear signals for trend direction.
The Optimized Trend Tracker uses a combination of moving averages and adaptive filters to detect trends. It aims to reduce lag and noise typically associated with traditional moving averages, thereby providing more timely and accurate signals.
Some of the key features and applications of the OTT include:
• Trend Identification: The indicator helps traders identify the direction of the prevailing trend in a market. It distinguishes between uptrends, downtrends, and sideways consolidations.
• Entry and Exit Signals: The OTT generates buy and sell signals based on crossovers and direction changes of the trend. Traders can use these signals to time their entries and exits in the market.
• Trend Strength: It also provides insights into the strength of the trend by analyzing the slope and momentum of price movements. This information can help traders assess the conviction behind the trend and adjust their trading strategies accordingly.
• Filter Noise: By employing adaptive filters, the indicator aims to filter out market noise and false signals, thereby enhancing the reliability of trend identification.
• Customization: Traders can customize the parameters of the OTT to suit their specific trading preferences and market conditions. This flexibility allows for adaptation to different timeframes and asset classes.
Overall, the OTT can be a valuable tool for traders seeking to capitalize on trending market conditions while minimizing false signals and noise. However, like any trading indicator, it is essential to combine its signals with other forms of analysis and risk management strategies for optimal results. Additionally, traders should thoroughly back-test the indicator and practice using it in a demo environment before applying it to live trading.
The following types of moving average have been included: "SMA", "EMA", "SMMA (RMA)", "WMA", "VWMA", "HMA", "KAMA", "LSMA", "TRAMA", "VAR", "DEMA", "ZLEMA", "TSF", "WWMA". Thanks to the authors.
Thank you for your indicator “Optimized Trend Tracker”. © kivancozbilgic
Thank you for your programming language, indicators and strategies. © PulseWire
Kind regards.
© Erebor_GIT
Indicator
Aroon and ASH strategy - ETHERIUM [IkkeOmar]Intro:
This post introduces a Pine Script strategy, as an example if anyone needs a push to get started. This example is a strategy on ETH, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay. This strategy combines two technical indicators: Aroon and Absolute Strength Histogram (ASH).
Overview:
The strategy employs the Aroon indicator alongside the Absolute Strength Histogram (ASH) to determine market trends and potential trade setups. Aroon helps identify the strength and direction of a trend, while ASH provides insights into the strength of momentum. By combining these indicators, the strategy aims to capture profitable trading opportunities in Ethereum markets. Normally when developing strats using indicators, you want to find some good indicators, but you NEED to understand their strengths and weaknesses, other indicators can be incorporated to minimize the downs of another indicator. Try to look for synergy in your indicators!
Indicator settings:
Aroon Indicator:
- Two sets of parameters are used for the Aroon indicator:
- For Long Positions: Aroon periods are set to 56 (upper) and 20 (lower).
- For Short Positions: Aroon periods are set to 17 (upper) and 55 (lower).
Absolute Strength Histogram (ASH):
ASH is calculated with a length of 9 bars using the closing price as the data source.
Trading Conditions:
The strategy incorporates specific conditions to initiate and exit trades:
Start Date:
Traders can specify the start date for backtesting purposes.
Trade Direction:
Traders can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
1. Long Position Entry: A long position is initiated when the Aroon indicator crosses over (crossover) the lower Aroon threshold, indicating a potential uptrend.
2. Long Position Exit: A long position is closed when the Aroon indicator crosses under (crossunder) the lower Aroon threshold.
3. Short Position Entry: A short position is initiated when the Aroon indicator crosses under (crossunder) the upper Aroon threshold, signaling a potential downtrend.
4. Short Position Exit: A short position is closed when the Aroon indicator crosses over (crossover) the upper Aroon threshold.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it! Strategy
Indicator
Crypto Trend IndicatorThe Crypto Trend Indicator is a trend-following indicator specifically designed to identify bullish and bearish trends in the price of Bitcoin, and other cryptocurrencies. This indicator doesn't provide explicit instructions on when to buy or sell, but rather offers an understanding of whether the trend is bullish or bearish. It's important to note that this indicator is only useful for trend trading.
The band is a visual representation of the 30-day and 60-day Exponential Moving Average (EMA). When the 30-day EMA is above the 60-day EMA, the trend is bullish and the band is green. When the 30-day EMA is below the 60-day EMA, the trend is bearish and the band is red. When the 30-day EMA starts to converge with the 60-day EMA, the trend is neutral and the band is grey.
The line is a visual representation of the 20-week Simple Moving Average (SMA) in the daily timeframe. "Bull" and "Bear" signals are generated when the 20-day EMA is either above or below the 20-week SMA, in conjunction with a bullish or bearish trend. When the band is green and the 20-day EMA is above the 20-week SMA, a “Bull” signal emerges. When the band is red and the 20-day EMA is below the 20-week SMA, a “Bear” signal emerges. The 20-week SMA can potentially also function as a leading indicator, as substantial price deviations from the SMA typically indicate an overextended market.
While this indicator has traditionally identified bullish and bearish trends in various cryptocurrency assets, past performance does not guarantee future results. Therefore, it is advisable to supplement this indicator with other technical tools. For instance, range-bound indicators can greatly improve the decision-making process when planning for entries and exits points. Indicator
Cryptocurrency Market Sentiment v1.0Introduction:
Capable of observing the market sentiment of the cryptocurrency market
The relative status of BTC and altcoins
How it works:
1. The general uptrend process of the cryptocurrency market is BTC → ETH → high-cap altcoins → low-cap altcoins. When funds cannot push up BTC's market cap, funds gradually flow into smaller-cap altcoins until the upward trend ends.
2. Select ETH as the representative of altcoins, and understand the sentiment and current stage
3. Mathematical principle : divide the price of ETH by the price of BTC, and then apply it to the RSI formula .
How to use it:
1. Similar to the RSI indicator , when CMS enters the overbought zone, it represents an active altcoin market, a passionate market sentiment , and the end of the uptrend.
2. When CMS enters the oversold zone, it indicates the leading stage of BTC in the rising trend or the capital flow back to BTC in the declining process .
3. If CMS is at a low level, long positions should focus on altcoins, and short positions should focus on BTC, and vice versa.
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简单介绍：
能够观察加密市场市场情绪
BTC和寨币的相对状态
如何工作：
1、加密市场一般的上涨过程为 BTC → ETH → 大市值山寨 → 小市值山寨，当资金无法推动大市值的BTC上涨时，资金就会逐渐流向市值较小的山寨，直到一轮上涨结束。
2、选取ETH作为altcoins的代表，通过ETH与BTC的关系来了解加密市场的情绪和目前上涨的阶段。
3、数学原理：将ETH的价格/BTC的价格，随后将其带入RSI公式
如何使用：
1、与RSI指标类似，当cms进入超买时，代表寨币市场的活跃，市场情绪热烈，上涨进入尾声。
2、当cms进入超卖时，为上涨中BTC领涨的阶段或下降过程中资金回流BTC。
3、如果cms在低位，做多应关注altcoins，做空应关注btc，反之亦然。
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Price Distance RatioThis study plots the ratio between current price and the price N days ago.
With N input that is configurable, users can find optimal long/short entries when price is in an established trend and price has diverge far from a given local peak or all time high.
With many years of stock trading the analysis indicates a connection between the distance of price and subsequent returns.
Portfolios of stocks with lower price to local highes ratios generally underperformed portfolios of stocks with higher prices to peaks reached similar N days ago.
The highest returns to previous peak are recorded when buying at the biggest dip.
For example, the purchase at 20% drawdown could generate 25% when price returns to the peak. The purchase at 50% drawdown could generate bigger, i.e. 100% return, when price returns to the peak. And the purchase at 90% drawdown could generate much bigger, i.e. 900% return, in a case the price returns to the peak.
However, buying very far below local peaks on almost all holding periods produces lower CAGR returns because of "timing adjustment". In simple words, typically the drawdown takes less time vs. further recovery.
For example:
👉 The largest BTC drawdown in 2013-2015 took 410 days (Peak-to-Valley) . And the recovery of BTC to new highs took 771 days (Valley-to-Peak) after that.
👉 The 3rd longest drawdown in BTC took 363 days (observed from December 17, 2017 to December 15, 2018). And further recovery in BTC to its new high took almost two years - 716 days .
👉The 4th longest drawdown in BTC took 162 days (observed from June 08, 2011 to November 17, 2011). And further recovery in BTC to its new high took more than a year - 469 days .
The concept of this study could recognizes at least 4 different modes of action.
👉 In a clearly established upward trend traders should be buying (following the trend) when Ratio is above 100% and reducing the size when Ratio turns below 100%.
👉 Conversely, in a clearly established downward trend traders should be shorted when Ratio is below 100% and covering when the Ratio turns back to 100%.
👉 In a sideways movement traders are advised to wait carefully if the Ratio near 100% for a long time, and take a position the trend is clear.
👉 Chartists can analyze the dynamic of the indicator - both in terms of trends and overall level. For example as it shown at the chart.
The understading of the study and rules of "timing adjustments" could genarate the awesome opportunities for stock options traders also, with strategies of selling uncovered call options and vertical call spreads.
// Many thanks to @HPotter and @Wheeelman wizards for their continious support and assistance.
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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.
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EMA and MACD with Trailing Stop Loss (by Coinrule)An exponential moving average ( EMA ) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average. An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average ( SMA ), which applies an equal weight to all observations in the period.
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA.
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence ( MACD ) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
The Strategy enters and closes the trade when the following conditions are met:
LONG
The MACD histogram turns bearish
EMA7 is greater than EMA14
EXIT
Price increases 3% trailing
Price decreases 1% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include XRPUSDT on the 1-minute timeframe. This short timeframe means that this strategy opens and closes trades regularly
In order to further improve the strategy, the EMA can be changed from 7 and 14 to, say, EMA20 and EMA50. Furthermore, the trailing stop loss can also be changed to ideally suit the user to match their needs.
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. Strategy
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