Kioseff Trading - AI-Optimized RSIAI-Optimized RSI
Introducing AI-Optimized RSI: a streamlined solution for traders of any skill level seeking to rapidly test and optimize RSI. Capable of analyzing thousands of strategies, this tool cuts through the complexity to identify the most profitable, reliable, or efficient approaches.
Paired with TradingView's native backtesting capabilities, the AI-Optimized RSI learns from historical performance data. Set up is easy for all skill levels, and it makes fine-tuning trading alerts and RSI straightforward.
Features
Purpose : Uncover optimal RSI settings and entry levels with precision. Say goodbye to random guesses and arbitrary indicator use—this tool provides clear direction based on data.
Target Performance : You set the goal, and AI-RSI seeks it out, whether it's maximizing profits, efficient trading, or achieving the highest win rate.
AI-Powered : With intelligent AI recommendations, the tool dynamically fine-tunes your RSI approach, steering you towards ideal strategy performance.
Rapid Testing : Evaluate thousands of RSI strategies.
Dual Direction : Perfect both long and short RSI strategies with equal finesse.
Deep Insights : Access detailed metrics including profit factor, PnL, win rate, trade counts, and more, all within a comprehensive strategy script.
Instant Alerts : Set alerts and trade.
Full Customization : Test and optimize all RSI settings, including cross levels, profit targets and stop losses.
Simulated Execution : Explore the impact of limit orders and other trade types through simulation.
Integrative Capability : Combine your own custom indicators or others from the TradingView community for a personalized optimization experience.
Flexible Timeframes : Set your optimization and backtesting to any date range.
Key Settings
The image above shows explanations for a list of key settings for the optimizer.
Direction : This setting controls trade direction: Long or Short.
Entry Condition : Define RSI entry: Select whether to trigger trades on RSI crossunders or crossovers.
RSI Lengths Range : Choose the range of RSI periods to test and find the best one.The AI will find the best RSI period for you.
RSI Cross Range : Set the range for RSI levels where crosses trigger trade signals. The AI will find the best level for you.
Combinations : Select how many RSI strategies to compare.
Optimization Type : Choose the goal for optimization and the AI: profit, win rate, or efficiency.
Profit Target : Set your profit target with this setting.
Stop Loss : Decide your maximum allowable loss (stop loss) per trade.
Limit Order : Specify whether to include limit orders in the strategy.
Stop Type : Choose your stop strategy: a fixed stop loss or a trailing stop.
How to: Find the best RSI for trading
It's important to remember that merely having the AI-Optimized RSI on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal RSI settings and strategy.
1.Starting Your Strategy Setup
Begin by deciding your goals for each trade: your profit target and stop loss. You'll also choose how to manage your stops – whether they stay put (fixed) or move with the price (trailing), and whether you want to exit trades at a specific price (limit orders). Keep the initial settings for RSI lengths and cross ranges at their default to give the tool a broad testing field. The AI's guidance will refine these settings to pinpoint the most effective ones through a process of comprehensive testing.
The image above shows our chart prior to any optimization efforts.
Note: the settings shown above in the key settings section will be used to start our demonstration.
2. Follow AI’s suggestions
Optimization Prompt: After loading your strategy, the indicator will prompt you to change the RSI length range and RSI level range to a better performing range.
Continue changing the RSI length range and RSI level range to match the indicator's suggestions until "Best Found" is displayed!
The image above shows results after we applied the tool’s suggestions. New suggestions have appeared, and we will continue to apply them.
Continue to adjust settings as recommended by the optimizer. If no better options are found, the optimizer will suggest increasing the number of combinations. Repeat this process until the optimizer indicates that the optimal setting has been identified.
Success! With the "Best Found" notification, an optimized RSI is now active. The AI will keep refining the strategy based on ongoing performance, ensuring continuous optimization.
AI Mode
AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components:
Heuristic-Based Decision Making: The algorithm evaluates multiple RSI-based trading strategies using specific metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable strategies for trade execution.
Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions.
Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization.
Settings
AI Mode Aggressiveness:
Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from “Low” to “High”, with “High” indicating a more assertive trading approach.
Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies.
Adaptive Learning Aggressiveness:
Description: When Adaptive Learning is enabled, the "Adaptive Learning Aggressiveness" setting controls how dynamically the AI adapts to market conditions using selected performance metrics.
Functionality: This setting impacts the AI's responsiveness to shifts in strategy performance. By adjusting this setting, you can control how quickly the AI moves away from strategies that may have been historically successful but are currently underperforming, towards strategies that are showing current promise.
Optimization
Trading system optimization is immensely advantageous when executed with prudence.
Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail.
Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
Learning
Kioseff Trading - AI-Optimized Supertrend
AI-Optimized Supertrend
Introducing AI-Optimized Supertrend: a streamlined solution for traders of any skill level seeking to rapidly test and optimize Supertrend. Capable of analyzing thousands of strategies, this tool cuts through the complexity to identify the most profitable, reliable, or efficient approaches.
Paired with TradingView's native backtesting capabilities, the AI-Optimized Supertrend learns from historical performance data. Set up is easy for all skill levels, and it makes fine-tuning trading alerts and Supertrend straightforward.
Features
Rapid Supertrend Strategy Testing : Quickly evaluate thousands of Supertrend strategies to find the most effective ones.
AI-Assisted Optimization : Leverage AI recommendations to fine-tune strategies for superior results.
Multi-Objective Optimization : Prioritize Supertrend based on your preference for the highest win rate, maximum profit, or efficiency.
Comprehensive Analytics : The strategy script provides an array of statistics such as profit factor, PnL, win rate, trade counts, max drawdown, and an equity curve to gauge performance accurately.
Alerts Setup : Conveniently set up alerts to be notified about critical trade signals or changes in performance metrics.
Versatile Stop Strategies : Experiment with profit targets, trailing stops, and fixed stop losses.
Binary Supertrend Exploration : Test binary Supertrend strategies.
Limit Orders : Analyze the impact of limit orders on your trading strategy.
Integration with External Indicators : Enhance strategy refinement by incorporating custom or publicly available indicators from TradingView into the optimization process.
Key Settings
The image above shows explanations for a list of key settings for the optimizer.
Set the Factor Range Limits : The AI suggests optimal upper and lower limits for the Factor range, defining the sensitivity of the Supertrend to price fluctuations. A wider range tests a greater variety, while a narrower range focuses on fine-tuning.
Adjust the ATR Range : Use the AI's recommendations to establish the upper and lower bounds for the Average True Range (ATR), which influences the Supertrend's volatility threshold.
ATR Flip : This option lets you interchange the order of ATR and Factor values to quicky test different sequences, giving you the flexibility to explore various combinations and their impact on the Supertrend indicator's performance.
Strategies Evaluated : Adjust this setting to determine how many Supertrend strategies you want to assess and compare.
Enable AI Mode : Turn this feature on to allow the AI to determine and employ the optimal Supertrend strategy with the desired performance metric, such as the highest win rate or maximum profitability.
Target Metric : Adjust this to direct the AI towards optimizing for maximum profit, top win rates, or the most efficient profits.
AI Mode Aggressiveness : Set how assertively the AI pursues the chosen performance goal, such as highest profit or win rate.
Strategy Direction : Choose to focus the AI's testing and optimization on either long or short Supertrend strategies.
Stop Loss Type : Specify the stop loss approach for optimization—fixed value, a trailing stop, or Supertrend direction changes.
Limit Order : Decide if you want to execute trades using limit orders for setting your profit targets, stop losses, or apply them to both.
Profit Target : Define your desired profit level when using either a fixed stop loss or a trailing stop.
Stop Loss : Define your desired stop loss when using either a fixed stop loss or a trailing stop.
How to: Find the best Supertrend for trading
It's important to remember that merely having the AI-Optimized Supertrend on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal Supertrend settings and strategy.
Optimizing Supertrend involves adjusting two key parameters: the Factor and the Average True Range (ATR). These parameters significantly influence the Supertrend indicator's sensitivity and responsiveness to price movements.
Factor : This parameter multiplies the ATR to determine the distance of the Supertrend line from the price. Higher values will create a wider band, potentially leading to fewer trade signals, while lower values create a narrower band, which may result in more signals but also more noise.
ATR (Average True Range) : ATR measures market volatility. By using the ATR, the Supertrend adapts to changing market volatility; a higher ATR value means a more volatile market, so the Supertrend adjusts accordingly.
During the optimization process, these parameters are systematically varied to determine the combination that yields the best performance based on predefined criteria such as profitability, win rate, or risk management efficiency. The optimization aims to find the optimal Factor and ATR settings.
1.Starting Your Strategy Setup
Begin by deciding your goals for each trade: your profit target and stop loss, or if all trades exit when Supertrend changes direction. You'll also choose how to manage your stops – whether they stay put (fixed) or move with the price (trailing), and whether you want to exit trades at a specific price (limit orders). Keep the initial settings for Supertrend Factor Range and Supertrend ATR Range at their default to give the tool a broad testing field. The AI's guidance will refine these settings to pinpoint the most effective ones through a process of comprehensive testing.
Demonstration Start: We'll begin with the settings outlined in the key settings section, using Supertrend's direction change to the downside as our exit signal for all trades.
2. Continue applying the AI’s suggestions
Keep updating your optimization settings based on the AI's recommendations. Proceed with this iterative optimization until the "Best Found" message is displayed, signaling that the most effective strategy has been identified.
While following the AI's suggestions, we've been prompted with a new suggestion: increase the
number of strategies evaluated. Keep following the AI's new suggestions to evaluate more strategies. Do this until the "Best Found" message shows up.
Success! We continued to follow the AI’s suggestions until “Best Found” was indicated!
AI Mode
AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components:
Heuristic-Based Decision Making: The algorithm evaluates multiple Supertrend-based trading strategies using metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable strategies for trade execution.
Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions.
Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization.
AI Mode Settings
AI Mode Aggressiveness:
Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from “Low” to “High”, with “High” indicating a more assertive trading approach.
Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies.
Optimization
Trading system optimization is immensely advantageous when executed with prudence.
Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail.
Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
Level 1 - Learn to code simply - PineScriptThe goal of this script is honestly to help everyone learn about trading with bots and algos.
At least, to get started.
Level 1:
10 lines of code.
learn to plot 2 moving averages on your chart.
learn to create a signal from a crossover.
learn the very basics of Pine Script algo.
Learning Built-in VarsI'm currently working on v5 of my Pine Script Programming Course.
As a part of it, I'm building a few tools/widgets to help students get the content easier.
Here is one of the tools. It's quite basic with it you can select a bar and see all the build-in variables for this bar (Except strategy variables)
I hope it will help you in learning Pine Script!
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
Cava Signals Backtesting/VisualizerPLEASE READ THE DESCRIPTION CAREFULLY
Trying this again, as it seems I keep violating the rules unintentionally. Moderator, please forgive me as I try to make this right.
This backtesting/visualizer script was created for me to get a visual idea of the Cava Signals indicator throughout its development time and continuous optimization.
This script is to be used on the 30-minute timeframe on supported markets, and whether I can only publish strategies on regular candles, the indicator is meant to trigger on heikin ashi candles.I understand backtesting on non-regular candles produces unrealistic results, but I emphasize that this script is more for visualization purposes rather than accurate $ amounts from the trades. The signals are used along with a dedicated bot configuration, so part of the strategy is not managed by the script, but by the bot's config.
Some behind the scenes on what we are looking at:
a combination of ema and sma crosses on different time frames (5m, 15m, 30m, 60m and 90m) - we call this the wave trend
a combination of stochastic rsi on different time frames (10m, 30m)
a combination of schaff trend cycles on different time frames (5m, 20m and 30m)
a combination of money flow index on different time frames (10m and 30m)
volume information for each supported market/pair
and a couple of other info particular to each pair
With the above combination of data points, we try to optimize our strategy for an entry, for dca'ing down in case the coin goes down as well as dca'ing up to maximize profit when a coin is going up, take profit levels when we recognize a good time to do so, and of course, a closing level. I would like to emphasize the *visualization* purpose of this script in recognizing lows, highs, and market structure to identify the important levels to signal - this script is NOT to be used for accurate backtesting, but for an idea of the overall performance of when signals are triggered.
Let me try to explain the workflow and icons you see on the chart:
The colored circles on the bottom of the chart are all buy signals; each color corresponds to a particular buy signal, we have a combination of 9 possible situations that would trigger a buy signal. Some would trigger a buy signal only in combination with other buy signals or other indicators within the script. we also display a green upwards arrow below bars when a buy signal is triggered.
The colored arrows pointing down on the top of the chart are close signals. We have a combination of 5 closing criteria each color corresponds to one, just like the buy signals do. We only close a trade in profit. If not in profit, we will look to DCA down.
DCA signals are shown by the green flag above bars. they are signals to DCA up or down depending on the trade being negative or positive. DCA'ing up or down is also managed by the bot's configuration for limits on when to accept the signal.
Take Profit levels are shown by the green diamond above bars and work in conjunction with the bot's config on when to take the signal if at all and other take profit levels. Usually, when we hit the first take profit level we move our stop loss to entry via the bot's take profit safety feature. You can see this call with the close entry named TPS .
The black bars you may see on the chart is to illustrate when the market is extended based on a particular strategy. During this period we will not trigger a buy signal unless there is a huge spike in positive volume .
The green number below the bars is the total positive delta volume on the buy candles.
On the table on the right upper corner, we show some information on the market and performance of the backtesting - for visualization purposes only!
Currently, the script is tailored to work with the following markets/pairs:
Binance Spot: ADA, ALGO, ATOM, AVAX, BNB, BTC , DOT, ETH, LINK, LUNA, MATIC, SOL, VET, XRP, XTZ
Binance Futures: BTC , ETH, ADA, ALGO, ATOM, BNB, COMP, DOT, ENJ , LINK, OCEAN, OMG, SOL, VET, XMR, XRP, XTZ, AVAX, AAVE, DOGE, LTC, LUNA, MKR , NEAR, ONT, RUNE, SUSHI, LTC, XLM , COMP, ONT, THETA, FTM , EGLD , WAVES, ONE, HTN , CHZ , HOT, MANA, CRV , RVN, BAT, ANKR, 1INCH, ALICE, ATA , AXS , CHR , COTI, NKN , RAY, REN, SRM , SXP , TLM
ByBit Inverse Perpetual: BTCUSD , ETHUSD
ByBit Futures: AAVE, ADA, ALGO, AVAX, AXS , BNB, BTC , DOT, ETH, LINK, LTC, MATIC, SOL, SUSHI, UNI , XEM, XRP, XTZ
The chosen pairs are subject to change based on the best-performing assets we are constantly analyzing.
I hope this helps to understand the script, its purpose and ideas. I hope this satisfies the community rules - it was not my intention to break them - if there's anything on the above or the script that still violates the guidelines, please let me know and accept my apologies in advance.
If anyone would like to know more, let me know in the comment section.
Thank you!
DMI + HMA - No Risk ManagementDMI (Directional Movement Index) and HMA (Hull Moving Average)
The DMI and HMA make a great combination, The DMI will gauge the market direction, while the HMA will add confirmation to the trend strength.
What is the DMI?
The DMI is an indicator that was developed by J. Welles Wilder in 1978. The Indicator was designed to identify in which direction the price is moving. This is done by comparing previous highs and lows and drawing 2 lines.
1. A Positive movement line
2. A Negative movement line
A third line can be added, which would be known as the ADX line or Average Directional Index. This can also be used to gauge the strength in which direction the market is moving.
When the Positive movement line (DI+) is above the Negative movement line (DI-) there is more upward pressure. Ofcourse visa versa, when the DI- is above the DI+ that would indicate more downwards pressure.
Want to know more about HMA? Check out one of our other published scripts
What is this strategy doing?
We are first waiting for the DMI to cross in our favoured direction, after that, we wait for the HMA to signal the entry. Without both conditions being true, no trade will be made.
Long Entries
1. DI+ crosses above DI-
2. HMA line 1 is above HMA line 2
Short Entries
1. DI- Crosses above DI+
2. HMA line 1 is below HMA lilne 2
Its as simple as that.
Conclusion
While this strategy does have its downsides, that can be reduced by adding some risk manegment into the script. In general the trade profitability is above average, And the max drawdown is at a minimum.
The settings have been optimised to suite BTCUSDT PERP markets. Though with small adjustments it can be used on many assets!
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!
Surf's Up Alerts 1.0Optimal Markets - USDT/ BTC -USD/ BTC all major exchanges
Optimal Chart - 4H
Average trades - 1-2/week
YTD Profit (0 leverage) = 62%
This script was designed to give new traders confidence and some guidance when entering into the crypto trading industry.
When added to the USD/ BTC 4H (optimal) charts of any high volume exchange, three new alert conditions will appear under the Surf's Up indicator alerts. Turn on the "Buy Signal" and "Sell Signal" to be alerted of potential large price increases. This script analyzes multiple data pieces to determine points in which the price has the highest probability of moving up, along with a sell alert that will alert the user of either: the point at which the trend is dying and to take profit OR that the trend is not happening, and to cut your losses. "Secure Profit" can be set to alert you of given profit target, at which time you can set a stop loss just above break even, essentially making a risk-free trade! This is OPTIONAL as it could cause you to a leave a large winning trade too early as well :)
Buy and Sell conditions have been programmed to know when the user is already in a trade, so multiple alerts will not fire, allowing full integration of auto trading as well.
Surf's Up is a back-tested strategy turned study in order to give high potential trade alerts. This way, anyone can easily add the script to the BTC/USD 4H chart, and simply turn on/off any of the 3 alerts: Buy, Sell, or Secure Profit.
You can get more information along with access to this script/alert system by clicking the link in the signature, or sending us a PM here on Tradingview.
Happy Trading!
Rsi, Ema , Ma and Bollinger Bands for 1 min BtcusdtThis is for 1 min Btcusdt pair.
I am tring to find a way to catch %1 ups and downs.
Basicly it buys when rsi low and minute candle closes under ema,ma and lower bollinger band,
it sells when candle goes over upper bb,low ma, when rsi high.
It sells when rsi high ,candle closes over upper bb,over low ma and does the opposite when buying.
I know it's crowded but still tring to learn what to do ^^
I welcome any suggestions to improve.
It works better with shorts for now.
Don't buy with this !! You might lose big !
Simple Price Momentum - How To Create A Simple Trading StrategyThis script was built using a logical approach to trading systems. All the details can be found in a step by step guide below. I hope you enjoy it. I am really glad to be part of this community. Thank you all. I hope you not only succeed on your trading career but also enjoy it.
docs.google.com
PtahX 3 EMA IndicatorA Basic 3 EMA Study / Indicator built in version 4 of Pinescript.
Individual color changing lines based on the position of the price (close) relative to each specific EMA
Alerts can be set for either
- All Signals Bullish
- All Signals Bearish
I try to keep my code clean and readable with comments and always enjoy seeing what others do with it. Please give me a thumbs up if you find it usefull & as always I hope you have very good luck with your trades!! :)
Cheers
PtahX
Cash in/Cash out Report (CICO) - Quiets market noiseThe cash in/cash out report (CICO for short) was built with the intent to quiet the market noise. The blunt way to say it, this indicator quiets the market manipulators voice and helps the retail investor make more money. I believe money is better of in the 99% hands versus the greedy hoarding that is currently going on. There are dozens of companies in the SP500 that have the same tax rate as unborn babies, nada. These hoarders also have machine learning high frequency trading bots that purposely create fear and anxiety in the markets. When all of the major markets move at the exact same time of day on frequent occasions, I see red flags. I recommend looking into Authorized participants in the ETF market to understand how the markets can be manipulated, specifically Creation and Redemption.
Enough of my rant. This indicator is open source. Directions on how to use the indicator can be found within the code. The basic summary is, clear your charts to bare minimums. Make the colors gray on all candles. Then apply this indicator. The indicator will color the "buy" and "sell" signals on the chart. Keep in mind, markets are manipulated to create fear in the retail investors little heart and can change drastically at any second. This indicator will show real time changes in running sum into and out of the market, it is estimated by average prices and not exact.
Once the chart is all greyed out and the indicator is applied you will see an area colored red and green. What this indicator does is takes a running sum of the new money into and out of the market. It takes the average of the high and low price times the volume. If the price is going up the value is positive, going down will be negative. Then the running sum is displayed. The area section is the running sum and the column bars are each value. When a market is steadily increasing in value you will see the large green area grow. When markets shift, values and display will change in color and vector. Full descriptions are available within the script in the comment sections.
I hope this help you make more money. If this helps you grow profits, give it a like!
Happy investing 99%er!
Volume Weighted DistanceThis script holds several useful functions from statistics and machine learning (ML) and takes measurement of a volume weighted distance in order to identify local trends. It attempts at applying ML techniques to time series processing, shows how different distance measures behave and gives you an arsenal of tools for your endeavors. Tested with BTCUSD.
REM: oddly enough, many people forget that the scripts in PS are generally just STUDIES, i.e. exercises, experiments, trials, and do not embody a final solution. Please treat them as intended ;))
Channel Break Out Binary StrategyI am learning pine script at the moment and this is my first attempt at creating an expire time based strategy for binary options based on a simple example like the built-in Channel Break Out Strategy.
