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!
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Logarithmic Regression (Weekly)This script is a combination of different logarithmic regression fits on weekly BTC data. It is meant to be used only on the weekly timeframe and on the BLX chart for bitcoin. The "fair value" line is still subjective, as it is only a regression and does not take into account other metrics.
[5F] Aggregated Volume Spot BTC 10 Exchanges-══════════════════════════════-
10 exchanges aggregated spot volume of Bitcoin.
You can choose which exchanges to display.
Each color characterizes an exchange.
Sorry for my bad english
Note : The list of exchanges in the infopanel is always the same, even if you disable exchanges. If I have the time, I will try to fix this.
Here are the listed exchanges :
- Okex
- Huobi
- Binance
- Bitfinex
- Bitstamp
- Coinbase
- FTX
- Kraken
- Gemini
- Phemex
Thanks to all Pinecoders who share their work with the community.
-══════════════════════════════-
Pi-cycle top for Bitcoin bull-runUsage
Whenever the Pi-Cycle top conditions are met, the red circle appears at the bottom of the chart. Theoretically, this marks the top of the bull-run in Bitcoin within 3 days.
Credit and overview
Indicator Overview
The Pi Cycle Top Indicator has historically been effective in picking out the timing of market cycle highs to within 3 days.
It uses the 111 day moving average (111DMA) and a newly created multiple of the 350 day moving average, the 350DMA x 2.
Note: The multiple is of the price values of the 350DMA not the number of days.
For the past three market cycles, when the 111DMA moves up and crosses the 350DMA x 2 we see that it coincides with the price of Bitcoin peaking.
It is also interesting to note that 350 / 111 is 3.153, which is very close to Pi = 3.142. In fact, it is the closest we can get to Pi when dividing 350 by another whole number.
It once again demonstrates the cyclical nature of Bitcoin price action over long time frames. Though in this instance it does so with a high degree of accuracy over the past 7 years.
How It Can Be Used
Pi Cycle Top is useful to indicate when the market is very overheated. So overheated that the shorter term moving average, which is the 111 day moving average, has reached a x2 multiple of the 350 day moving average. Historically it has proved advantageous to sell Bitcoin at this time in Bitcoin’s price cycles.
Created By Philip Swift
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....
2-Year MA MultiplierIndicator built by lookintobitcoin specifically for identifying ideal Bitcoin buy and sell regions.
lookintobitcoin describes this indicator as:
"The 2-Year MA Multiplier is intended to be used as a long term investment tool.
It highlights periods where buying or selling Bitcoin during those times would have produced outsized returns.
To do this, it uses a moving average (MA) line, the 2yr MA, and also a multiplication of that moving average line, 2yr MA x5.
Note: the x5 multiplication is of the price values of the 2yr moving average, not of its time period.
Buying Bitcoin when price drops below the 2yr MA (green line) has historically generated outsized returns. Selling Bitcoin when price goes above the 2yr MA x 5 (red line) has been historically effective for taking profit."
BEST Mayer MultipleHello traders
I'm not a HODLer by any means. I know when to sell (or I think I know....) when an asset starts going against me too much.
Even if it's a "long-term" investment.
My mentor used to telling me this: "If a short-term trade becomes a long-term investment, then you're in for a hell of a ride".
I have no clue if Bitcoin/BTC will go back up or not - I don't even care because I'm an intraday trader.
What if BTC was actually a way to accumulate more fiat? Satoshi fooled us
I coded this Mayer Multiple according to the specifications below. By the way, I'm a big fan of Willy Woo. I've been monitoring all his work since I learned about crypto (10 minutes ago.... it's a joke come on)
charts.woobull.com
Scaling
To respect the Mayer's multiple model, I recommend to select the Logarithmic scaling as shown below
imgur.com
What Mayer's model says
Using the reference below, the model says we're in the oversold zone. But, we can be in that zone for months/years...
When a model says an asset could bounce in a 1000-7000 USD range... well... I don't know how I would be able to perform optimally with that insight. This is very subjective and not a recommendation.
Mayer's Multiple model reference
All the BEST
Dave
Blockchain Artificial Neural NetworksI found a very high correlation in a research-based Artificial Neural Networks.(ANN)
Trained only on daily bars with blockchain data and Bitcoin closing price.
NOTE: It does not repaint strictly during the weekly time frame. (TF = 1W)
Use only for Bitcoin .
Blockchain data can be repainted in the daily time zone according to the description time.
Alarms are available.
And you can also paint bar colors from the menu by region.
After making reminders, let's share the details of this interesting research:
INPUTS :
1. Average Block Size
2. Api Blockchain Size
3. Miners Revenue
4. Hash Rate
5. Bitcoin Cost Per Transaction
6. Bitcoin USD Exchange Trade Volume
7. Bitcoin Total Number of Transactions
OUTPUTS :
1. One day next price close (Historical)
TRAINING DETAILS :
Learning cycles: 1096436
AutoSave cycles: 100
Grid :
Input columns: 7
Output columns: 1
Excluded columns: 0
Training example rows: 446
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0
Network :
Input nodes connected: 7
Hidden layer 1 nodes: 5
Hidden layer 2 nodes: 0
Hidden layer 3 nodes: 0
Output nodes: 1
Controls :
Learning rate: 0.1000
Momentum: 0.8000
Target error: 0.0100
Training error: 0.010571
The average training error is really low, almost worth the target.
Without using technical analysis data, we established Artificial Neural Networks with blockchain data.
Interesting!
Yope BTC PL channelThis is a new version of the old "Yope BTC tops channel", but modified to reflect a power-law curve fitted, similar to the model proposed by Harold Christopher Burger in his medium article "Bitcoin’s natural long-term power-law corridor of growth".
My original tops channel fitting is still there for comparison. In fact, it looks like the old tops channel was a bit too pessimistic.
Note that these channels are still pure naive curve-fitting, and do not represent an underlying model that explains it, like is the case for PlanB's "Modeling Bitcoin's Value with Scarcity" which uses Stock-to-Flow.
The motivation for this exercise is to observe how long this empirical extrapolation is valid. Will the price of bitcoin stay in either of both channels?
Note on usage: This script _only_ works with the BLX "BraveNewCoin Liquid Index for Bitcoin" in the 1D, 3D and 1W time-frames!
It may be necessary to zoom in and out a few times to overcome drawing glitches caused by the extreme time-shifting of plots in order to draw the extrapolated part.
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.
The Golden Ratio MultiplierBy Philip Swift
As Bitcoin continues to progress on its adoption journey, we learn more about its growth trajectory.
Rather than Bitcoin price action behaving like a traditional stock market share price, we see it act more like a technology being adopted at an exponential rate.
This is because Bitcoin is a network being adopted by society, and because it is decentralised money with limited supply, its price is a direct representation of that adoption process.
There are a number of regression analysis tools and stock to flow ratio studies that are helping us to understand the direction of Bitcoin’s adoption curve.
The new tool outlined in this paper brings an alternative degree of precision to understanding Bitcoin’s price action over time. It will demonstrate that Bitcoin’s adoption is not only following a broad growth curve but appears to be following established mathematical structures.
In doing so, it also:
Accurately and consistently highlights intracycle highs and lows for Bitcoin’s price.
Picks out every market cycle top in Bitcoin’s history.
Forecasts when Bitcoin will top out in the coming market cycle.
To begin, we will use the 350 day moving average of Bitcoin’s price. It has historically been an important moving average because once price moves above it, a new bull run begins.
more ...
medium.com
All rights reserved to Philip Swift (@PositiveCrypto)
NVT Signal with RMA and thresholds [alertable]NVT Signal, or NVTS, is an indicator that compares the market cap of Bitcoin to the aggregate USD value of daily transactions on the Bitcoin blockchain. It is a value indicator that shows a multiple of Bitcoin price against the actual usage of its blockchain. When the NVTS is low, it suggests Bitcoin price is low relative to the amount of utility the network provides, and vice versa.
For more information on NVTS, visit medium.com
This indicator aims to provide the following:
1. An open-source implementation of NVTS on Tradingview, as the most popular one currently is closed-source.
2. To provide two simple ways to define and visualize "overbought" or "oversold" conditions using the NVTS. Here, we have absolute value of NVTS & deviation from a long-term moving average.
3. Crude integration into Tradingview's alert system.
What this indicator CANNOT do:
1. Timeframes below 1d.
2. Signals based on statistical analyses, such as seen in Bollinger Bands et al. (However, with the appropriate type of account, you can add BBands on top of this indicator.)
I would like to express my gratitude to Willy Woo, Chris Burniske and Dimitry Kalichkin for their work on NVT Ratio and NVT Signal, without which my indicator would not have been created.
Feel free to fork & improve, or experiment with settings. I hope this indicator will be useful to someone.
Alpha-Sutte ModelThe Alpha-Sutte model is an ongoing project run by Ansari Saleh Ahmar, a lecturer and researcher at Universitas Negeri Makassar in Indonesia, that attempts to make forecasts for time series like how Arima and Holt-Winters models do. Currently Ahmar and his team have conducted research and published papers comparing the efficacy of the Alpha-Sutte and other models, such as Arima and Holt-Winters, on topics ranging from forecasting Turkey's CPI data, Bitcoin prices, Apple's stock prices, primary energy supply of Indonesia, to infant mortality rates in China.
The Alpha-Sutte model in comparison to the other two models listed above shows promise in providing a more accurate forecast, and the project has been able to receive some of its funding from organizations such as the US Agency for International Development, which is a part of the US Federal Government, so maybe the project has some actual merit.
How it works:
In this model there are four values presented at the top of the window.
1) The first value in blue is the value of the Alpha-Sutte model whose purpose is to forecast the price of the current bar.
2) The second value in yellow is an adaptive version of the Alpha-Sutte model that I made. The purpose of the adaptive Alpha-Sutte model is to expand upon the Alpha-Sutte by allowing new information to be introduced, causing the value to change during the current period, hence the adaptiveness of it.
3) The third value in aqua is the moving average of the low% Sutte line which is a predictive line that is based off of the close and low of the current and previous periods.
4) The fourth value in red is the moving average of the high% Sutte line which is a predictive line that is based off of the close and high of the current and previous periods.
Trend signals:
If low% Sutte (aqua value/line) is greater than high% Sutte (red value/line) then this is a buy signal.
If high% Sutte (red value/line) is greater than low% Sutte (aqua value/line) then this is a sell signal.
Caveat:
Even though this model's purpose is to forecast the future, will it be able to predict periods of large movements? No, of course not, but it will adjust quickly to try to make more accurate forecasts for the next period. This was also a reason why I made an adaptive version of this model to try to reduce some of the discrepancies between the Alpha Sutte and price when there is a large unexpected move.
*WARNING before using this I would highly recommend that you look up "Sutte Indicator" online and read some of the papers about this model before you use this , even though this model has shown merit when compared to Arima and Holt-Winter models this is still an ongoing project.*
Hopefully this project will actually come to something in the near future as the calculation for this time series predictive model is much easier to calculate and program in pine editor than something like an Arima model.
*Also, if you know how to use R language there is a package for the "Alpha-Sutte model".*
CryptoM173's Gimme MoneyLatest version. Nobody gave me feedback and managing requests to add people became a PITA. Enjoy.
I like money, you like money, this set up has the potential to make a LOT of it. That being said, I do NOTmake any warranties of this making you money, nor do I guarantee you will NOT lose money. In the end, you're the one configuring it and interpreting the results. Providing that you DO set it up correctly and it makes you obscene amounts of money, donations are always welcome (addresses below).
Before you start, it's probably you read EVERYTHING below.
You'll have to do some tweaking of the MA's to find a strat that best suits your needs. It is an indicator you're welcome to use to assist in your trading decisions. I made this script for renko charts and trading bitcoin -1.64% because the standard strat wasn't working out. if you find you're getting a lot of consecutive colored bars or crosses on Renko, you may need to switch from ATR 14 to something like Traditional 50. You will need to adjust the "box value" for traditional renko to fit the asset you're working with, on the time frame you're trading on. Smaller values (i.e. on bitcoin -1.64% I use a box value of 50 on 4hr and 1D with absurd success) but you need to make sure they're not too small, otherwise small moves may appear larger than they are, resulting in a bunch of break-even trades. If you're going to be trading cryptocurrency, it's easiest to switch back to ATR14 to get an idea of the Average Trading range to have a reference point to start from trading btc -1.64% (i.e .000034 rather than 50).
It's a great tool if you're looking to carry both swap and futs positions and keep an eye on the short term swap opportunities while monitoring the status of your futs position and help decide whether or not to close a long at a correction or not and while this strategy has been most effective for me with Renko bars, it's been very useful for monitoring futs positions on traditional charts.
For access, feel free to DM -0.34% me on twitter, @CryptoM173
If you're the generous type, feel free to donate Bitcoin to: 3BMEXWz6Es7iLdi9zAyMWWHHZPNbMKPqrV
BTC Price Spread - Coinbase & Futs - Premiums & DiscountsThis indicator takes the price of Bitcoin on Coinbase and the futures price on Mex, and compares it the average price of Bitcoin across other major exchanges.
This essentials give us a spread at which Bitcoin is going for.
In turn, this could be a possible tool to help determine market sentiment.
This indicator was created for experimental purposes.
Use at your own digression.
Stealthy7 Bayes Conditional RSI Trader StrategyWhat does it do?
This script checks whether RSI movement affects future price.
Trades when probability increases or decreases.
Developed for daily(D) bars and Bitcoin. This script is just a toy and for educational use.
Please rent my bots at cryptotrader.org/?r=51
CM_DayOfWeek All Instruments V2Updated Code That Highlights Bars Based On Days Of The Week.
Works On Daily and Intra-Day Bars.
Works on All Instruments. Stocks, Forex, Futures, Bitcoin.
Shows Correct Trading Sessions!!!
Ability to Turn On/Off Each Day Of The Week via Inputs Panel.
[Outperforms Bitcoin Since 2011] Professional MA StrategyThis Strategy OUTPEFORMS Bitcoin since 2011.
Timeframe: Daily
MA used (Fast and Slow): WMA (Weighted Moving Average)
Fast MA Length: 30 days (Reflects the Monthly Trend - Short Term Perspective)
Slow MA Length: 360 days (Reflects the Annual Trend - Long Term Perspective)
Position Size: 100% of equity
Margin for Long = 10% of equity
Margin for Short = 10% of equity
Open Long = Typical Price Crosses Above its Fast MA and Price is above its Slow MA
Open Short = Typical Price Crosses Below its Fast MA and Price is below its Slow MA
Close Long = Typical Price Crosses Below its Fast MA
Close Short = Typical Price Crosses Below its Fast MA
note: Typical Price = (high + low + close) / 3
Justin's Bitcoin Power Law PredictorJustin's MSTR Powerlaw Price Predictor is a Pine Script v6 indicator for TradingView that adapts Giovanni Santostasi’s Bitcoin power law model to forecast MicroStrategy (MSTR) stock prices. Using the formula Price = A * (daysSinceGenesis)^B, it calculates fair, upper, and floor prices with constants A_fair = 1.16e-17, A_floor = 0.42e-17, and B = 5.82, starting from Bitcoin’s genesis (January 3, 2009). The script plots these prices, displays values in a table.
Source: www.ccn.com
Mutanabby_AI | ATR+ | Trend-Following StrategyThis document presents the Mutanabby_AI | ATR+ Pine Script strategy, a systematic approach designed for trend identification and risk-managed position entry in financial markets. The strategy is engineered for long-only positions and integrates volatility-adjusted components to enhance signal robustness and trade management.
Strategic Design and Methodological Basis
The Mutanabby_AI | ATR+ strategy is constructed upon a foundation of established technical analysis principles, with a focus on objective signal generation and realistic trade execution.
Heikin Ashi for Trend Filtering: The core price data is processed via Heikin Ashi (HA) methodology to mitigate transient market noise and accentuate underlying trend direction. The script offers three distinct HA calculation modes, allowing for comparative analysis and validation:
Manual Calculation: Provides a transparent and deterministic computation of HA values.
ticker.heikinashi(): Utilizes TradingView's built-in function, employing confirmed historical bars to prevent repainting artifacts.
Regular Candles: Allows for direct comparison with standard OHLC price action.
This multi-methodological approach to trend smoothing is critical for robust signal generation.
Adaptive ATR Trailing Stop: A key component is the Average True Range (ATR)-based trailing stop. ATR serves as a dynamic measure of market volatility. The strategy incorporates user-defined parameters (
Key Value and ATR Period) to calibrate the sensitivity of this trailing stop, enabling adaptation to varying market volatility regimes. This mechanism is designed to provide a dynamic exit point, preserving capital and locking in gains as a trend progresses.
EMA Crossover for Signal Generation: Entry and exit signals are derived from the interaction between the Heikin Ashi derived price source and an Exponential Moving Average (EMA). A crossover event between these two components is utilized to objectively identify shifts in momentum, signaling potential long entry or exit points.
Rigorous Stop Loss Implementation: A critical feature for risk mitigation, the strategy includes an optional stop loss. This stop loss can be configured as a percentage or fixed point deviation from the entry price. Importantly, stop loss execution is based on real market prices, not the synthetic Heikin Ashi values. This design choice ensures that risk management is grounded in actual market liquidity and price levels, providing a more accurate representation of potential drawdowns during backtesting and live operation.
Backtesting Protocol: The strategy is configured for realistic backtesting, employing fill_orders_on_standard_ohlc=true to simulate order execution at standard OHLC prices. A configurable Date Filter is included to define specific historical periods for performance evaluation.
Data Visualization and Metrics: The script provides on-chart visual overlays for buy/sell signals, the ATR trailing stop, and the stop loss level. An integrated information table displays real-time strategy parameters, current position status, trend direction, and key price levels, facilitating immediate quantitative assessment.
Applicability
The Mutanabby_AI | ATR+ strategy is particularly suited for:
Cryptocurrency Markets: The inherent volatility of assets such as #Bitcoin and #Ethereum makes the ATR-based trailing stop a relevant tool for dynamic risk management.
Systematic Trend Following: Individuals employing systematic methodologies for trend capture will find the objective signal generation and rule-based execution aligned with their approach.
Pine Script Developers and Quants: The transparent code structure and emphasis on realistic backtesting provide a valuable framework for further analysis, modification, and integration into broader quantitative models.
Automated Trading Systems: The clear, deterministic entry and exit conditions facilitate integration into automated trading environments.
Implementation and Evaluation
To evaluate the Mutanabby_AI | ATR+ strategy, apply the script to your chosen chart on TradingView. Adjust the input parameters (Key Value, ATR Period, Heikin Ashi Method, Stop Loss Settings) to observe performance across various asset classes and timeframes. Comprehensive backtesting is recommended to assess the strategy's historical performance characteristics, including profitability, drawdown, and risk-adjusted returns.
I'd love to hear your thoughts, feedback, and any optimizations you discover! Drop a comment below, give it a like if you find it useful, and share your results.
Pi Cycle Top Indicator - mychaelgoPlots the original Pi Cycle Top moving averages and marks bars where the 111DMA is rising and crosses above the 350DMA×2, often coinciding with Bitcoin cycle peaks. Includes a label with the signal price.
Sat Stacking Strategies Simulation (SSSS)Sat Stacking Strategies Simulation (SSSS)
This indicator simulates and compares different Bitcoin stacking strategies over time, allowing you to visualize performance, cost basis, and stacking behavior directly on your chart.
Core Features:
Three Stacking Strategies
• Trend-Based – Stack only when price is above/below a long-term SMA.
• Stack the Dip – Buy during sharp pullbacks or oversold conditions.
• Price Zone – Stack only in “cheap”, “fair”, or “expensive” zones based on a simulated Short-Term Holder (STH) cost basis.
Always Stack Benchmark
Compare your chosen strategy against a simple “Always Stack” approach for a real-world DCA reference.
Performance Metrics Table
Track:
• Total Fiat Added
• Total BTC Accumulated
• Current Value
• Average Cost per BTC
• PnL %
• CAGR
• Sharpe Ratio & Stdev
• Stack Events & Time Underwater
Advanced Options
• Simulate cash-secured puts on unused fiat.
• Simulate covered calls on BTC holdings.
• Roll over unused stacking amounts for future buys.
This tool is designed for Bitcoiners, stackers, and DCA enthusiasts who want to backtest and visualize their stacking plan—whether you keep it simple or go full quant.
Sometimes the best alpha is just showing up every week with your wallet open… and occasionally wearing a helmet. 🪖💰
