Stochastic Moving AverageHi all,
This Strategy script combines the power of EMAs along with the Stochastic Oscillator in a trend following / continuation manner, along with some cool functionalities.
I designed this script especially for trading altcoins, but it works just as good on Bitcoin itself and on some Forex pairs.
______ SIGNALS ______
The script has 4 mandatory conditions to unlock a trading signal. Find these conditions for a long trade below (works the exact other way round for shorts)
- Fast EMA must be higher than Slow EMA
- Stochastic K% line must be in oversold territory
- Stochastic K% line must cross over Stochastic D% line
- Price as to close between slow EMA and fast EMA
Once all the conditions are true, a trade will start at the opening of the next
______ SETTINGS ______
- Trade Setup:
Here you can choose to trade only longs or shorts and change your Risk:Reward.
You can also decide to adjust your volume per position according to your risk tolerance. With “% of Equity” your stop loss will always be equal to a fixed percentage of your initial capital (will “compound” overtime) and with “$ Amount” your stop loss will always be 'x' amount of the base currency (ex: USD, will not compound)
Stop Loss:
The ATR is used to create a stop loss that matches current volatility. The multiplier corresponds to how many times the ATR stop losses and take profits will be away from closing price.
- Stochastic:
Here you can find the usual K% & D% length and overbought (OB) and oversold (OS) levels.
The “Stochastic OB/OS lookback” increase the tolerance towards OB/OS territories. It allows to look 'x' bars back for a value of the Stochastic K line to be overbought or oversold when detecting an entry signal.
The “All must be OB/OS” refers to the previous “Stochastic OB/OS lookback” parameter. If this option is ticked, instead of needing only 1 OB/OS value within the lookback period to get a valid signal, now, all bars looked back must be OB/OS.
The color gradient drawn between the fast and slow EMAs is a representation of the Stochastic K% line position. With default setting colors, when fast EMA > slow EMA, gradient will become solid blue when Stochastic is oversold and when slow EMA > fast EMA, gradient will become solid blue when Stochastic is overbought
- EMAs:
Just pick your favorite ones
- Reference Market:
An additional filter to be certain to stay aligned with the current a market index trend (in our case: Bitcoin). If selected reference market (and timeframe) is trading above selected EMA, this strategy will only take long trades (vice-versa for shorts) Because, let’s face it… even if this filter isn’t bulletproof, you know for sure that when Bitcoin tanks, there won’t be many Alts going north simultaneously. Once again, this is a trend following strategy.
A few tips for increased performance: fast EMA and D% Line can be real fast… 😉
As always, my scripts evolve greatly with your ideas and suggestions, keep them coming! I will gladly incorporate more functionalities as I go.
All my script are tradable when published but remain work in progress, looking for further improvements.
Hope you like it!
在腳本中搜尋"bitcoin"
Chanu Delta RSI StrategyThis strategy is built on the Chanu Delta RSI , which indicates the strength of the Bitcoin market. The problem with the previous Chanu Delta Strategy was that it was simply based on the price difference between the two Bitcoin markets, so there was no universality. However, this new Chanu Delta RSI strategy solves the problem by introducing an RSI that compares the price difference trend.
When the Chanu Delta RSI hits “Bull Level” and “Bear Level” and closes the candle, long and short signals are triggered respectively. The example shown on the screen is a default setting optimized for a 4-hour candlestick strategy based on the Bybit BTCUSDT futures market. You can use it by adjusting the setting value and modifying it to suit you.
This strategy is selectable from both reference and large amplitude BTCUSD markets in order to enable fine backtesting. I recommend using BYBIT:BTCUSDT for the reference market and COINBASE:BTCUSD for the large amplitude market.
(Note) Using the "Chanu Delta RSI" to know the current indicator value in real time, it is convenient to predict the signal of the strategy.
(Note) Because the Chanu Delta RSI represents the price difference based on the Bybit BTCUSDT futures market, backtesting is possible from March 2020.
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이 전략은 비트코인 시장의 강점을 나타내는 Chanu Delta RSI를 기반으로 합니다. 기존 Chanu Delta 전략의 문제점은 단순히 두 비트코인 시장의 가격차를 기준으로 하여 보편성이 없었다는 점이다. 하지만 이번 새로운 Chanu Delta RSI 전략은 가격차이 추세를 비교하는 RSI를 도입해 문제를 해결했습니다.
Chanu Delta RSI가 "Bull Level"과 "Bear Level"에 도달하고 봉마감하면 롱, 숏 신호가 각각 트리거됩니다. 화면에 보이는 예시는 Bybit BTCUSDT 선물 시장을 기반으로 한 4시간 캔들스틱 전략에 최적화된 기본 설정입니다. 설정값을 조정하여 자신에게 맞게 수정하여 사용하시면 됩니다.
이 전략은 정밀한 백테스팅을 가능하게 하기 위해 참조 및 큰 진폭 BTCUSD 시장에서 모두 선택할 수 있습니다. 참조 시장에는 BYBIT:BTCUSDT를 사용하고 큰 진폭 시장에는 COINBASE:BTCUSD를 사용하는 것이 좋습니다.
(주) "Chanu Delta RSI"를 이용하여 현재 지표 값을 실시간으로 알 수 있어 전략의 시그널을 예측하는데 편리합니다.
(주) Chanu Delta RSI는 바이비트 BTCUSDT 선물시장을 기준으로 가격차이를 나타내므로 2020년 3월부터 백테스팅이 가능합니다.
BTC Cap Dominance RSI StrategyThis strategy is based on the BTC Cap Dominance RSI indicator, which is a combination of the RSI of Bitcoin Market Cap and the RSI of Bitcoin Dominance. The concept of this strategy is to get a good grasp of the bitcoin market flow by combining bitcoin dominance as well as bitcoin market cap.
BTC Cap Dominance (BCD) RSI is defined as:
BCD RSI = (BTC Cap RSI + BTC Dominance RSI) / 2
Case 1 (Bull market):
Both Cap RSI and Dominance RSI values are high
Case 2 (Neutral market):
Cap RSI is high but Dominance RSI is low
Cap RSI is low but Dominance RSI is high
Case 3 (Bear market):
Both Cap RSI and Dominance RSI values are low
When the BCD RSI value closes the candle above the Bull level, it triggers a long signal and when the value closes below the Bear level, it triggers a short signal.
(Note) Please note that TradingView's market cap symbols (CRYPTOCAP:TOTAL and CRYPTOCAP:TOTAL2) started in January 2020, so strategy backtesting is possible from this point on.
(Note) Since the real-time BCD RSI value does not come out with this strategy, it is recommended to use it together because the current value can be known and the long-short signal can be predicted in advance by using a separate BCD RSI Index together.
If "Use Combination of dominance RSI ?" is not checked in addition to the recommended default value of the strategy, the recommended values are Length (14), Bull level (74), Bear level (25).
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이 전략은 비트코인 시가총액의 RSI와 비트코인 도미넌스 RSI를 조합하여 만든 BTC Cap Dominance RSI 지표를 기반으로 만들어졌습니다. 이 전략의 컨셉은 비트코인 시가총액뿐만 아니라 비트코인 도미넌스를 조합함으로써 비트코인 시장 흐름을 잘 파악할 수 있도록 하는 것입니다.
BTC Cap Dominance (BCD) RSI는 다음과 같이 정의하였습니다.
BCD RSI = (BTC Cap RSI + BTC Dominance RSI) / 2
Case 1 (강세 장):
Cap RSI와 Dominance RSI 값 모두 높은 경우
Case 2 (횡보 장):
Cap RSI는 높지만 Dominance RSI는 낮은 경우
Cap RSI는 낮지만 Dominance RSI는 높은 경우
Case 3 (약세 장):
Cap RSI와 Dominance RSI 값 모두 낮은 경우
BCD RSI 값이 Bull level 위에서 캔들 마감할 경우 long 신호를 트리거하고 Bear level 아래에서 캔들 마감할 경우 short 신호를 트리거합니다.
(주의) 트레이딩뷰의 시가총액 심볼들 (CRYPTOCAP:TOTAL과 CRYPTOCAP:TOTAL2)이 2020년 1월부터 시작하였으므로 이 시점부터 전략 백테스팅이 가능한 점을 유의하십시오.
(주의) 이 전략은 실시간 BCD RSI 값이 나오지 않기 때문에 별도의 BCD RSI Index를 함께 사용하면 현재 값을 알 수 있어 롱숏 신호를 사전에 예측할 수 있으므로 함께 사용하기를 권장합니다.
전략의 추천 기본값 외에 "Use Combination of dominance RSI ?"를 체크하지 않는 경우 권장하는 값은 Length (14), Bull level (74), Bear level (25) 입니다.
STRATEGY R18-F-BTCHi, I'm @SenatorVonShaft
Just finished the strategy "STRATEGY R18-F-BTC" for trading on #bitcoin and other cryptocurrencies.
As any strategy on TradingView, R18 opens Long/Short positions (with no leverage) on certain price points for assets in the chart. But I intentionally make this strategy for Bitcoin . Strategy is effective with 1h chart and it has %36 winning trade ratio for #bitcoin trade. As strategy uses approximately 1/3 ratio of SL/TP levels, gross profit for 1 year backtest is above %200 (I mean above 3x for only BTC )
Strategy is built on combination of:
- MACD
- RSI
- FIBONACCI levels
- BTCUSDT price itself as indicator (for different crypto assets and BTCUSDTPERP trading. You can select different assets you like for indicator (it's BTCUSDT:Binance by default))
I fine-tuned all levels of indicators above accordingly (it has more than 10 variables that effects strategy itself).
You can find out your own strategy levels by adjusting long/short tp&sl variables as well as initial capital ratio variable.
Reverse option open reverse positions of the strategy
Optimized Keltner Channels SL/TP Strategy for BTCThis strategy is optimized for Bitcoin with the Keltner Channel Strategy, which is TradingView's built-in strategy. In the original Keltner Channel Strategy, it was difficult to predict the timing of entry because the Buy and Sell signals floated in the middle of the candle in real time. This strategy is convenient because if the bitcoin price hits the top or bottom of the Keltner Channel and closes the closing price, you can enter Buy or Sell at the next candle start price. In addition, this strategy provides Stop Loss and Take Profit functions to maximize profit.
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Recommended settings are below.
- length: 9
- multiplier: 1
- source: close
- (v) Use EMA
- Bands Style: Average True Range
- ATR Length: 19
- Stop Loss (%): 20
- Take Profit (%) : 20
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- length: 9
- multiplier: 1
- source: close
- (v) Use EMA
- Bands Style: Average True Range
- ATR Length: 18
- Stop Loss (%): 20
- Take Profit (%) : 5
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▶ Usefulness and Originality
- Stop Loss and Take Profit functions are available
- Convenient Buy and Sell entry compared to the original Keltner Channel Strategy
- Optimized for BTCUSD market (maximizing profits)
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이 전략은 TradingView의 Built-in 전략인 Keltner Channel Strategy를 비트코인에 맞게 최적화되었습니다. 기존의 Keltner Channel Strategy는 Buy, Sell 신호가 캔들 중간에 실시간으로 떠서 진입 시점을 예측하기 어려운 불편함이 있었지만 이 전략은 비트코인 가격이 Keltner Channel 상단 혹은 하단을 찍고 종가를 마감하면 그 다음 캔들 시작가에서 Buy 혹은 Sell 진입이 가능하여 편리합니다. 또한, 이 전략은 Keltner Channel을 만나서 캔들을 마감한 가격 (bprice, sprice)을 시각적으로 plot을 제공하여 타점 및 차트를 보기에 편리하며 손절가 및 목표가를 지정한 백테스팅이 가능합니다.
Flawless Victory Strategy - 15min BTC Machine Learning StrategyHello everyone, I am a heavy Python programmer bringing machine learning to TradingView. This 15 minute Bitcoin Long strategy was created using a machine learning library and 1 year of historical data in Python. Every parameter is hyper optimized to bring you the most profitable buy and sell signals for Bitcoin on the 15min chart. The historical Bitcoin data was gathered from Binance API, in case you want to know the best exchange to use this long strategy. It is a simple Bollinger Band and RSI strategy with two versions included in the tradingview settings. The first version has a Sharpe Ratio of 7.5 which is amazing, and the second version includes the best stop loss and take profit positions with a Sharpe Ratio of 2.5 . Let me talk a little bit more about how the strategy works. The buy signal is triggered when close price is less than lower Bollinger Band at Std Dev 1, and the RSI is greater than a certain value. The sell signal is triggered when close price is greater than upper Bollinger Band at Std Dev 1, and the RSI is greater than a certain value. What makes this strategy interesting is the parameters the Machine Learning library found when backtesting for the best Sharpe Ratio. I left my computer on for about 28 hours to fully backtest 5000 EPOCHS and get the results. I was able to create a great strategy that might be one of TradingView's best strategies out on the website today. I will continue to apply machine learning to all my strategies from here on forward. Please Let me know if you have any questions or certain strategies you would like me to hyper optimize for you. I'm always willing to create profitable strategies!
P.S. You can always pyramid this strategy for more gains! I just don't add pyramiding when creating my strategies because I want to show you the true win/loss ratio based buying one time and one selling one time. I feel like when creating a strategy that includes pyramiding right off the bat falsifies the win rate. This is my way of being transparent with you all. Have fun trading!
BTC and ETH Long strategy - version 1I will start with a small introduction about myself. I'm now trading cryto currencies manually for almost 2 years. I decided to start after watching a documentary on the TV showing people who made big money during the Bitcoin pump which happened at the end of 2017.
The next day, I asked myself "Why should I not give it a try and learn how to trade".
This was in February 2018 and the price of Bitcoin was around 11500USD.
I didn't know how to trade. In fact, I didn't know the trading industry at all.
So, my first step into trading was to open an account with a broken. Then I directly bought 200$ worst of BTC . At that time, I saw the graph and thought "This can only go back in the upward direction!" :)
I didn't know anything about Stop loss, Take profit and Risk management.
Today, almost 2 years after, I think that I know how to trade and can also confirm that I still hold this bag of 200$ of bitcoin from 2018 :)
I did spend the 2 last years to learn technical analysis , risk management and leverage trading.
Today (14/05/2020), I know what I'm doing and I'm happy to see that the 2 last years have been positive in terms of gains. Of course, I did not make crazy money with my saving but at least I made more than if I would have kept it in my bank account.
Even if I like trading, I have a full time job which requires my full energy and lots of focus, so, the biggest problem I had is that I didn't have enough time to look at the charts.
Also, I realized that sometimes, neither technical analysis , nor fundamentals worked with crypto currency (at least for short time trading). So, as I have a developer background I decided to try to have a look at algo trading.
The goal for me was neither to make complex algos nor to beat the market but just to automate my trading with simple bot catching the big waves.
I then started to take a look at TV pine script and played with it.
I did my first LONG script in February 2020 to Long the BTC Market. It has some limitations but works well enough for me for the time being. Even if the real trades will bring me half of what the back testing shows, this will still be a lot more than what I was used to win during the last 2 years with my manual trading.
So, here we are! Below you will find some details about my first LONG script. I'm happy to share it with you.
Feel free to play with it, give your comments and bring improvements to it.
But please note that it only works fine with the candle size and crypto pair that I have mentioned below. If you use other settings this algo might loose money!
- Crypto pairs : XBTUSD and ETHXBT
- Candle size: 2 Hours
- Indicator used: Volatility , MACD (12, 26, 7), SMA (100), SMA (200), EMA (20)
- Default StopLoss: -1.5%
- Entry in position if: Volatility < 2%
AND MACD moving up
AND AME (20) moving up
AND SMA (100) moving up
AND SMA (200) moving up
AND EMA (20) > SAM (100)
AND SMA (100) > SMA (200)
- Exit the postion if: Stoploss is reached
OR EMA (20) crossUnder SMA (100)
Here is a summary of the results for this script:
XBTUSD : 01/01/2019 --> 14/05/2020 = +107%
ETHXBT : 01/01/2019 --> 14/05/2020 = +39%
ETHUSD : 01/01/2019 --> 14/05/2020 = +112%
It is far away from being perfect. There are still plenty of things which can be done to improve it but I just wanted to share it :) .
Enjoy playing with it....
Hash Ribbons Backtest - Bitcoin Beats YT
Hello Hello Hello and welcome back to Bitcoin Beats!
This is a script written by capriole_charles
Go check out the original!
I have added leverage and stoploss % but also made it a strategy so we can look back at past trades to see patterns and profit.
Personally I feel this is not enough data to trade off as BTC is such a young asset. However I have seen other models similar to this for other assets that hold strong.
Trade safe!
Good bye from bitcoin beats!
Not Meant For The 1H! My Bad! higher timeframes are better!
The "Spring" is the confirmed Miner capitulation period:
The 1st "gray" circle is the start of Capitulation (1 month Hash Rate crosses UNDER 2 month Hash Rate)
Last "green" circle is the end of Capitulation (1 month Hash Rate crosses OVER 2 month Hash Rate)
The "greener" the spring gets (up until blue) represents Hash Rate recovery (it is increasing)
The "blue" circle is the first instance of positive momentum following recovery of Hash Rate (1m HR > 2m HR). This is historically a rewarding place to buy with limited downside.
REAL STRATEGY : Dow_Factor_MFI/RSI_DVOG_StrategyI'm actually one of those who think it's more important to extract clues from indicators than strategy, but I wanted to test the data about the probability and dow factor I've shared for a long time.
Usually, Bitcoin is used as an eye stain for strategy success, since the graph has increased significantly from the beginning.
To prevent this, I used a commission and in the last lines of document I shared Bitmex's Bitcoin and Ethereum 1W test results.
I don't think there's a factor to repaint. ( Warn me if u see or observe )
I considered Bitcoin because I found working with liquid parities much more realistic.
Ethereum and Bitmex have been featured as a spot and may soon find a place at the CME , so I've evaluated the Ethereum .
But since the Ethereum Bitmex was also spot new, I deleted results that were less than 10 closed trades.
Since the Dow Theory also looks at the harmony in the indices, just try it in the Cryptocurrency market.
Use as indicator in other markets. Support with channels, trend lines with big periods and other supportive indicators.
And my personal suggestion : Use this script and indicator TF : 4H and above.
Specifications :
Commission. ( % 0.125 )
Switchable Methods ( Relative Strength Index / Money Flow Index )
Alarms. (Buy / Sell )
Position closure when horizontal market rates weighs.
Progressive gradual buy/sell alarms.
Clean code layout that will not cause repaint. (Caution : source = close )
Switchable barcolor option (I / 0 )
*****Test results :*****
drive.google.com
Summary:
It was a realistic test.
It has achieved great success in some markets, but as I mentioned earlier, use it only to gain insight into the price movements of cryptos.
Use as indicator in other markets.
This code is open source under the MIT license. If you have any improvements or corrections to suggest, please send me a pull request via the github repository : github.com
Stay tuned ! Noldo.
Strategy for The Bitcoin Buy/Sell IndicatorThis is the strategy for
Starting with a capital of $3,000 XBT , one might have $15,975 dollar worth of XBT plus whatever the bitcoin has appreciated over the years.
The Sharpe Ratio: 0.586, Net Profit is 532%, 57 closed trades from 2017 till today, Profit factor of 3.745 (aka for every dollar loss, there is 3.745 dollar profit) with 14% drawdown .
Let that sink in.
ADX for BTC [PineIndicators]The ADX Strategy for BTC is a trend-following system that uses the Average Directional Index (ADX) to determine market strength and momentum shifts. Designed for Bitcoin trading, this strategy applies a customizable ADX threshold to confirm trend signals and optionally filters entries using a Simple Moving Average (SMA). The system features automated entry and exit conditions, dynamic trade visualization, and built-in trade tracking for historical performance analysis.
⚙️ Core Strategy Components
1️⃣ Average Directional Index (ADX) Calculation
The ADX indicator measures trend strength without indicating direction. It is derived from the Positive Directional Movement (+DI) and Negative Directional Movement (-DI):
+DI (Positive Directional Index): Measures upward price movement.
-DI (Negative Directional Index): Measures downward price movement.
ADX Value: Higher values indicate stronger trends, regardless of direction.
This strategy uses a default ADX length of 14 to smooth out short-term fluctuations while detecting sustainable trends.
2️⃣ SMA Filter (Optional Trend Confirmation)
The strategy includes a 200-period SMA filter to validate trend direction before entering trades. If enabled:
✅ Long Entry is only allowed when price is above a long-term SMA multiplier (5x the standard SMA length).
✅ If disabled, the strategy only considers the ADX crossover threshold for trade entries.
This filter helps reduce entries in sideways or weak-trend conditions, improving signal reliability.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when:
✅ ADX crosses above the threshold (default = 14), indicating a strengthening trend.
✅ (If SMA filter is enabled) Price is above the long-term SMA multiplier.
🔻 Exit Conditions
A position is closed when:
✅ ADX crosses below the stop threshold (default = 45), signaling trend weakening.
By adjusting the entry and exit ADX levels, traders can fine-tune sensitivity to trend changes.
📏 Trade Visualization & Tracking
Trade Markers
"Buy" label (▲) appears when a long position is opened.
"Close" label (▼) appears when a position is exited.
Trade History Boxes
Green if a trade is profitable.
Red if a trade closes at a loss.
Trend Tracking Lines
Horizontal lines mark entry and exit prices.
A filled trade box visually represents trade duration and profitability.
These elements provide clear visual insights into trade execution and performance.
⚡ How to Use This Strategy
1️⃣ Apply the script to a BTC chart in TradingView.
2️⃣ Adjust ADX entry/exit levels based on trend sensitivity.
3️⃣ Enable or disable the SMA filter for trend confirmation.
4️⃣ Backtest performance to analyze historical trade execution.
5️⃣ Monitor trade markers and history boxes for real-time trend insights.
This strategy is designed for trend traders looking to capture high-momentum market conditions while filtering out weak trends.
Ultimate T3 Fibonacci for BTC Scalping. Look at backtest report!Hey Everyone!
I created another script to add to my growing library of strategies and indicators that I use for automated crypto trading! This strategy is for BITCOIN on the 30 minute chart since I designed it to be a scalping strategy. I calculated for trading fees, and use a small amount of capital in the backtest report. But feel free to modify the capital and how much per order to see how it changes the results:)
It is called the "Ultimate T3 Fibonacci Indicator by NHBprod" that computes and displays two T3-based moving averages derived from price data. The t3_function calculates the Tilson T3 indicator by applying a series of exponential moving averages to a combined price metric and then blending these results with specific coefficients derived from an input factor.
The script accepts several user inputs that toggle the use of the T3 filter, select the buy signal method, and set parameters like lengths and volume factors for two variations of the T3 calculation. Two T3 lines, T3 and T32, are computed with different parameters, and their colors change dynamically (green/red for T3 and blue/purple for T32) based on whether the lines are trending upward or downward. Depending on the selected signal method, the script generates buy signals either when T32 crosses over T3 or when the closing price is above T3, and similarly, sell signals are generated on the respective conditions for crossing under or closing below. Finally, the indicator plots the T3 lines on the chart, adds visual buy/sell markers, and sets alert conditions to notify users when the respective trading signals occur.
The user has the ability to tune the parameters using TP/SL, date timerames for analyses, and the actual parameters of the T3 function including the buy/sell signal! Lastly, the user has the option of trading this long, short, or both!
Let me know your thoughts and check out the backtest report!
Momentum Alligator 4h Bitcoin StrategyOverview
The Momentum Alligator 4h Bitcoin Strategy is a trend-following trading system that operates on dual time frames. It utilizes the 1D Williams Alligator indicator to identify the prevailing major price trend and seeks trading opportunities on the 4-hour (4h) time frame when the momentum is turning up. The strategy is designed to close trades if the trend fails to develop or holding position if price continues increasing without any significant correction. Note that this strategy is specifically tailored for the 4-hour time frame.
Unique Features
2-layers market noise filtering system: Trades are only initiated in the direction of the 1D trend, determined by the Williams Alligator indicator. This higher time frame confirmation filters out minor trade signals, focusing on more substantial opportunities. At the same time, strategy has additional filter on 4h time frame with Awesome Oscillator which is showing the current price momentum.
Flexible Risk Management: The strategy exclusively opens long positions, resulting in fewer trades during bear markets. It incorporates a dynamic stop-loss mechanism, which can either follow the jaw line of the 4h Alligator or a user-defined fixed stop-loss. This flexibility helps manage risk and avoid non-trending markets.
Methodology
The strategy initiates a long position when the d-line of Stochastic RSI crosses up it's k-line. It means that there is a high probability that price momentum reversed from down to up. To avoid overtrading in potentially choppy markets, it skips the next two trades following a winning trade, anticipating sideways movement after a significant price surge.
This strategy has two layers trades filtering system: 4h and 1D time frames. The first one is awesome oscillator. It shall be increasing and value has to be higher than it's 5-period SMA. This is an additional confirmation that long trade is opened in the direction of the current momentum. As it was mentioned above, all entry signals are validated against the 1D Williams Alligator indicator. A trade is only opened if the price is above all three lines of the 1D Alligator, ensuring alignment with the major trend.
A trade is closed if the price hits the 4h jaw line of the Alligator or reaches the user-defined stop-loss level.
Risk Management
The strategy employs a combined approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined stop-loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 2% drop from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Stochastic RSI on 4h time frame to open long trade when momentum started reversing to the upside. On the one hand, Stochastic RSI is one of the most sensitive indicator, which allows to react fast on the potential trend reversal. On the other hand, this indicator can be too sensitive and provide a lot of false trend changing signals. To eliminate this weakness we use two-layers trades filtering system.
The first layer is the 4h Awesome oscillator. This is less sensitive momentum indicator. Usually it starts increasing when price has already passed significant distance from the actual reversal point. The strategy opens long trade only is Awesome oscillator is increasing and above it's 5-period SMA. This approach increases the probability to filter the false signals during the choppy market or if the reversal is false.
The second layer filter is the Williams Alligator indicator on 1D time frame. The 1D Alligator serves as a filter for identifying the primary trend and increases probability to avoid the trades with low potential because trading against major trend usually is more risky. It's much better to catch the trend continuation than local bounce.
Last but not least feature of this strategy is close trades condition. It uses the flexible approach. First of all, user can set up the fixed stop-loss according to his own risk-tolerance, by default this value is 2% of price movement. It restricts the potential loss at the moment when trade has just been opened. Moreover strategy utilizes the 4h Williams Alligator's jaw line to exit the trade. If price fell below it trade is closed. This approach helps to not keep open trade if trend is not developing and hold it if price continues going up.
Backtest Results:
Operating window: Date range of backtests is 2021.01.01 - 2024.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -3.04%
Maximum Single Profit: +29.67%
Net Profit: +6228.01 USDT (+62.28%)
Total Trades: 118 (24.58% win rate)
Profit Factor: 1.71
Maximum Accumulated Loss: 1527.69 USDT (-11.52%)
Average Profit per Trade: 52.78 USDT (+0.89%)
Average Trade Duration: 60 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use:
Add the script to favorites for easy access.
Apply to the 4h timeframe desired chart (optimal performance observed on the BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Big Whale Purchases and SalesBig Whale Purchases and Sales - plots big whale transactions on your chart!
People that hold more than 1% of a crypto currencies circulating supply are considered whales and have a huge influence on price, not just because they can move the market with their huge transactions, but also because other traders often track their wallets and follow their example. Taking a look at whale holdings, one can see why whale worship is so common in crypto: While Bitcoin has a relatively low whale concentration, many of the Top 100 Cryptocurrencies have whales control 60% or more of their circulating supply.
Integrating IntoTheBlock data, this script plots the transactions of these whales and, in strategy mode, copy trades them.
Features:
Strategy Mode: Switches the script between an indicator and a strategy.
Standard Deviations: The number of Standard Deviations that a transaction needs to surpass to be considered worth plotting. Setting this to 0 will show all whale transactions, higher settings will only show the biggest transactions.
Blockchain: The Chain on which Whale activity is tracked.
Mayer Multiple StrategyCreated by Trace Mayer, the Mayer Multiple is calculated dividing the current price of Bitcoin by its 200-day moving average. This simple script allows to backtest strategies based on Mayer Multiple levels, which can be easily adjusted. It can be tested on any chart and any timeframe.
Chanu Delta StrategyThis strategy is built on the Chanu Delta Indicator, which indicates the strength of the Bitcoin market. When the Chanu Delta Indicator hits “Delta_bull” and “Delta_bear” and closes the candle, long and short signals are triggered respectively. The example shown on the screen is a default setting optimized for a 4-hour candlestick strategy based on the Bybit BTCUSDT futures market. For the 15-minute candle, "Delta_bull=32", "Delta_bear=-31", "Source=hlc3" are best. You can use it by adjusting the setting value and modifying it to suit you.
If you use this strategy in conjunction with the Chanu Delta Indicator, it is convenient to anticipate alert signals in advance. Since the Chanu Delta Indicator represents the price difference based on the Bybit BTCUSDT futures market, backtesting is possible from March 2020.
Extremely Overfit Bitcoin Long/ShortThis is a highly overfit (in my opinion) script to long/short BTC on the 15m time frame. May be usable for other cryptocurrencies or timeframes with some parameter adjustments. I backtested it on a few exchanges with ETH.
The simplest way to increase the number of trades is to decrease the "FastChannelLength" parameter or increase the "SlowChannelLength" parameter, or both. Decreasing the margins of the channels also increases the number of trades. In GENERAL, you should expect that adding more trades will hurt profitability, because, as the title says, this script is extraordinarily overfit.
It does include a commission fee from the start, which I find is essential to not providing an overly rosy view of how a strategy would work.
Scalping using RSI 2 indicator with TSLThis strategy implements a simply scalping using the RSI (calculated on two periods), the slopes of two MAs ( EMA or SMA ) having different lengths (by default, I use 50 and 200).
A trailing stop loss (%) is used.
Entry conditions:
.) Fast MA > Slow MA and Price > Slow MA and RSI < Oversold Threshold ------> go Long
.) Fast MA < Slow MA and Price < Slow MA and RSI > Overbought Threshold ------> go Short
Exit conditions:
.) Long entry condition is true and (close >= TP or close <= TSL ) ----> close short position
.) Short entry condition is true and (close <= TP or close >= TSL ) ----> close long position
The strategy performed best on Bitcoin and the most liquid and capitalized Altcoins but works excellent on volatile assets, mainly if they often go trending.
Works best on 3h - 4h time frame.
There's also an optional Volatility filter, which opens the position only if the difference between the two slopes is more than a specific value, which can be set in the study inputs. The purpose is not opening positions if the price goes sideways and the noise is way > than the signal.
Note:
.) the RSI length is 2;
.) the oversold Threshold is 90%;
.) the overbought Threshold is 10%;
.) by default, the trailing stop loss per cent is 1%;
.) by default, the fast MA length is 50;
.) by default, the slow MA length is 200;
.) by default, the MA used is EMA.
Cheers.
RSI Classic Strategy (by Coinrule)One of the questions hobbyist traders more often ask is: what is the perfect trading indicator?
Every indicator is just a tool, so its efficiency is proportional to your ability to read its signals and translate them into an actionable trading strategy. The RSI is likely the most flexible and easy to use among the technical indicators.
This trading strategy tries to catch short-term swings on the coins of your choice with a simple yet profitable setup.
Buy when the RSI is lower than 30 (you can adjust it to 35 in times of steep uptrend).
Sell when the RSI is greater than 65 (the target may range between 60 and 75 depending on the volatility of the coin).
Note that the buy signal comes when the indicator crosses below 30 and not when it crosses above 30 as it happens on the built-in RSI strategy on Tradingview.
The present script overperforms the built-in strategy, even adding trading fees and using a lower amount of capital for each trade (30%). That means that the system can deliver higher net-profits with lower risk levels.
A typical example of market conditions where this strategy works perfectly is as follows.
The first initial breakout indicates that a new leg up in the trend may start. Bitcoin starts to trade within a range which you can identify when it reaches the point 3. That is the perfect time to start the rule because
- trading within a channel anticipates possible swings up and down
- the trend is on the upside, providing low downside risk in buying the dips.
This strategy works well with selected coins of your choice, and it's a great fit on leverage exchanges like Binance Futures.
If you prefer to run it across all available coins on the market, instead, you may choose an optimized version.
EMA Slope Cross Trend Follower StrategyThis strategy uses the cross of the slopes of two EMAs having different lengths to generate trend follower signals. By default, I use 130 and 400, which behave very well.
The conditions which make the strat enter the market are:
- Fast Slope > Slow Slope and price > EMA 200 : go Long
- Fast Slope < Slow Slope and price < EMA200 : go Short
The simple slopes cross in the opposite direction, closes the position.
The strategy performs best on Bitcoin and the most liquid and capitalized Altcoins, but works greatly on volatile assets as well, in particular if they often go trending.
Works best on 4h time frame.
There's also an optional Volatility filter, which opens the position only if the difference between the two slopes is more than a specific value, which can be set in the strategy inputs. The purpose is not opening positions if price is going sideways and the noise is way > than the signal.
Enjoy it!
ATR and T3 strategyT3 Moving Average indicator was originally developed by Tim Tillson in 1998/99.
T3 Moving Average is considered as improved and better to traditional moving averages as it is smoother and performs better in trending market conditions.
It offers multiple opportunities when the price is in the state of retracement and therefore allows to minimize your exposed risk and allowing your profits run.
This strategy is for trend followers who are patient enough to have 6-10 trades per year.
What's included in strategy?
Two ATR (Code was taken from J.Dow and modified)
Tillson Moving average
Enter long signal:
When both ATR (Long and Short) are in uptrend and the bar closes above Upper Tillson's moving average band: Enter Long
Exit Long signal:
When hl2 is lower than Lower Tillson Moving Average band
Enter short signal:
When both ATR (Long and Short) are in downtrend and the bar closes below Lower Tillson's moving average band: Enter Short
Exit Shortsignal:
When hl2 is higher than Upper Tillson's Moving Average band
Best to use with Bitcoin on 12H TF
Can be used for different time frames as well but the settings must be adjusted accordingly
Remember, overtrading can be harmful to your trading account.
If this is helpful for you, consider a tip
BTC: 3FiBnveHo3YW6DSiPEmoCFCyCnsrWS3JBR
ETH: 0xac290B4A721f5ef75b0971F1102e01E1942A4578
Created by CryptoJoncis
Bitcoin 1H-15M Breakout StrategyKey Features
1H and 15M Timeframes:
The script uses the 1-hour timeframe for the range and 15-minute timeframe for breakout conditions.
request.security is used to fetch the higher timeframe data.
Risk Management:
Variables entry_price, sl_price, and tp_price are declared explicitly as float with na initialization to handle dynamic assignment.
Stop-loss and take-profit levels are calculated based on the specified Risk-Reward Ratio (RRR) and buffer (in pips).
Trade Logic:
Long trade triggered when the 15-minute candle closes above the 1-hour high.
Short trade triggered when the 15-minute candle closes below the 1-hour low.
Visualization:
The range_high and range_low (previous 1-hour high and low) are plotted on the chart using dashed lines.
Debugging:
Enabling the show_debug input displays labels showing stop-loss and take-profit values for easier troubleshooting.
