Markov Chain Trend IndicatorOverview
The Markov Chain Trend Indicator utilizes the principles of Markov Chain processes to analyze stock price movements and predict future trends. By calculating the probabilities of transitioning between different market states (Uptrend, Downtrend, and Sideways), this indicator provides traders with valuable insights into market dynamics.
Key Features
State Identification: Differentiates between Uptrend, Downtrend, and Sideways states based on price movements.
Transition Probability Calculation: Calculates the probability of transitioning from one state to another using historical data.
Real-time Dashboard: Displays the probabilities of each state on the chart, helping traders make informed decisions.
Background Color Coding: Visually represents the current market state with background colors for easy interpretation.
Concepts Underlying the Calculations
Markov Chains: A stochastic process where the probability of moving to the next state depends only on the current state, not on the sequence of events that preceded it.
Logarithmic Returns: Used to normalize price changes and identify states based on significant movements.
Transition Matrices: Utilized to store and calculate the probabilities of moving from one state to another.
How It Works
The indicator first calculates the logarithmic returns of the stock price to identify significant movements. Based on these returns, it determines the current state (Uptrend, Downtrend, or Sideways). It then updates the transition matrices to keep track of how often the price moves from one state to another. Using these matrices, the indicator calculates the probabilities of transitioning to each state and displays this information on the chart.
How Traders Can Use It
Traders can use the Markov Chain Trend Indicator to:
Identify Market Trends: Quickly determine if the market is in an uptrend, downtrend, or sideways state.
Predict Future Movements: Use the transition probabilities to forecast potential market movements and make informed trading decisions.
Enhance Trading Strategies: Combine with other technical indicators to refine entry and exit points based on predicted trends.
Example Usage Instructions
Add the Markov Chain Trend Indicator to your TradingView chart.
Observe the background color to quickly identify the current market state:
Green for Uptrend, Red for Downtrend, Gray for Sideways
Check the dashboard label to see the probabilities of transitioning to each state.
Use these probabilities to anticipate market movements and adjust your trading strategy accordingly.
Combine the indicator with other technical analysis tools for more robust decision-making.
Algorithmictrading
Hulk Grid Algorithm V2 - The Quant ScienceIt's the latest proprietary grid algorithm developed by our team. This software represents a clearer and more comprehensive modernization of the deprecated Hulk Grid Algorithm. In this new release, we have optimized the source code architecture and investment logic, which we will describe in detail below.
Overview
Hulk Grid Algorithm V2 is designed to optimize returns in sideways market conditions. In this scenario, the algorithm divides purchases with long orders at each level of the grid. Unlike a typical grid algorithm, this version applies an anti-martingale model to mitigate volatility and optimize the average entry price. Starting from the lower level, the purchase quantity is increased at each new subsequent level until reaching the upper level. The initial quantity of the first order is fixed at 0.50% of the initial capital. With each new order, the initial quantity is multiplied by a value equal to the current grid level (where 1 is the lower level and 10 is the upper level).
Example: Let's say we have an initial capital of $10,000. The initial capital for the first order would be $50 * 1 = $50, for the second order $50 * 2 = $100, for the third order $50 * 3 = $150, and so on until reaching the upper level.
All previously opened orders are closed using a percentage-based stop-loss and take-profit, calculated based on the extremes of the grid.
Set Up
As mentioned earlier, the user's goal is to analyze this strategy in markets with a lack of trend, also known as sideways markets. After identifying a price range within which the asset tends to move, the user can choose to create the grid by placing the starting price at the center of the range. This way, they can consider trading the asset, if the backtesting generates a return greater than the Buy & Hold return.
Grid Configuration
To create the grid, it's sufficient to choose the starting price during the launch phase. This level will be the center of the grid from which the upper and lower levels will be calculated. The grid levels are computed using an arithmetic method, adding and subtracting a configurable fixed amount from the user interface (Grid Step $).
Example: Let's imagine choosing 1000 as the starting price and 50 as the Grid Step ($). The upper levels will be 1000, 1050, 1100, 1150, 1200. The lower levels will be 950, 900, 850, 800, and 750.
Markets
This software can be used in all markets: stocks, indices, commodities, cryptocurrencies, ETFs, Forex, etc.
Application
With this backtesting software, is possible to analyze the strategy and search for markets where it can generate better performance than Buy & Hold returns. There are no alerts or automatic investment mechanisms, and currently, the strategy can only be executed manually.
Design
Is possible to modify the grid style and customize colors by accessing the Properties section of the user interface.
Hybrid EMA AlgoLearner⭕️Innovative trading indicator that utilizes a k-NN-inspired algorithmic approach alongside traditional Exponential Moving Averages (EMAs) for more nuanced analysis. While the algorithm doesn't actually employ machine learning techniques, it mimics the logic of the k-Nearest Neighbors (k-NN) methodology. The script takes into account the closest 'k' distances between a short-term and long-term EMA to create a weighted short-term EMA. This combination of rule-based logic and EMA technicals offers traders a more sophisticated tool for market analysis.
⭕️Foundational EMAs: The script kicks off by generating a 50-period short-term EMA and a 200-period long-term EMA. These EMAs serve a dual purpose: they provide the basic trend-following capability familiar to most traders, akin to the classic EMA 50 and EMA 200, and set the stage for more intricate calculations to follow.
⭕️k-NN Integration: The indicator distinguishes itself by introducing k-NN (k-Nearest Neighbors) logic into the mix. This machine learning technique scans prior market data to find the closest 'neighbors' or distances between the two EMAs. The 'k' closest distances are then picked for further analysis, thus imbuing the indicator with an added layer of data-driven context.
⭕️Algorithmic Weighting: After the k closest distances are identified, they are utilized to compute a weighted EMA. Each of the k closest short-term EMA values is weighted by its associated distance. These weighted values are summed up and normalized by the sum of all chosen distances. The result is a weighted short-term EMA that packs more nuanced information than a simple EMA would.
Hobbiecode - Five Day Low RSI StrategyThis is a simple strategy that is working well on SPY but also well performing on Mini Futures SP500. The strategy is composed by the followin rules:
1. If today’s close is below yesterday’s five-day low, go long at the close.
2. Sell at the close when the two-day RSI closes above 50.
3. There is a time stop of five days if the sell criterium is not triggered.
If you backtest it on Mini Futures SP500 you will be able to track data from 1993. It is important to select D1 as timeframe.
Please share any comment or idea below.
Have a good trading,
Ramón.
Risk Reward Calculator [lovealgotrading]
OVERVIEW:
This Risk Reward Calculator strategy can help you maximize your RR value with help of algorithmic trading.
INDICATOR:
I wanted to setup my trades more easier with this indicator, I didn't want to calculate everytime before orders, with help this indicator we can calculate R:R value, avarage price, stoploss price, take-profit price, order prices, all position cost and more ...
Our strategy is a risk revard calculation indicator that is made easy to use by using visualized lines and panels, and also has algorithmic trading support.
With the help of this indicator, we can quickly and easily calculate our risk reward values and enter the positions.
If we want to ensure that our balance grows regularly while trading in the stock market, we need to manage the risks and rewards otherwise we may fall below our initial balance at the end of the day, even if we seem to be winning.
What is the Risk-Reward value ?
This value is a value that shows how many times the amount of risk we take when entering the position is successful, we will earn.
- For example, you risked $100 while entering the trade, so if your trade stops, you will lose 100 $.
Your Risk-Reward(RR) value is 2 means that if your position is successful, you will have 200 $ in your pocket.
A trader's success is determined by the amount of R he earns monthly or yearly, not how much money he makes.
What is different in this indicator ?
I want to say thank you to © EvoCrypto. His Calculator (weighted) – evo indicator helped me when I was developed my indicator.
I want to explain what I have improved:
1-In this strategy, we can determine the time period in which we want to open our positions.
2-We can open a maximum of 4 positions in the same direction and close our positions at a single level. StopLoss or TakeProfit
3-This indicator, which works in the form of a strategy, shows where our positions have been opened or closed. With the help of this, it helps us to determine our strategy in our future positions more accurately.
4-The most important improvement is that we do not miss our positions with the help of alarms (WEB HOOK). if we want, we receive by quickly connecting all these positions to our robot, the software can enter and exit the position while we are busy.
IMPLEMENTATION DETAILS – SETTINGS:
1 - We can set the start and end dates of the positions we will take.
2- We can set our take profit, stoploss levels.
3- If your trade is stopped, we can determine the amount of the trade that we will lose.
4- We can adjust our entry levels to positions and our position sizes at entry levels.
(Sum of positions weight must be 100%)
5- We can receive our positions even if we are busy with the help of algorithmic trading. For this, we must paste our Jshon codes into the fields specified in the settings panel.
6- Finally, we can change the settings we want and don't want to have in our visual elements.
Let's make a LONG side example together
We have determined our positions to enter stoploss, take profit and long positions. We did not forget to set the start time of our strategy
Our strategy appear on the graph as follows.
Our strategy has calculated the total position size, our R-R value, the distance of the current price to the stop and take profit levels, in short, a lot of things we could look visually.
Notes:
If you're going to connect this bot to an automatic Long or Short direction,
Don’t forget! you need to Webhook URL,
Don’t miss paste this code to your message window {{strategy.order.alert_message}}
ALSO:
If you have any ideas what to add to my work to add more sources or make calculations cooler, feel free to write me.
AUTOMATIC GRID BOT STRATEGY [ilovealgotrading]
OVERVIEW:
This Grid trading strategy can help you maximize your profit in a ranging sideways market with no clear direction.
INDICATOR:
We can get some money by taking advantage of the movement of the price between the range we have determined.
Short positions are opened while the price is rising, long positions are opened while the price is falling.
Therefore, there is no need to predict the trend direction.
What is different in this indicator:
I want to say thank you to © thequantscience. His GRID SPOT TRADING ALGORITHM - GRID BOT TRADING strategy helped me when I was writing my indicator.
I want to explain what I have improved:
1- Grid strategy is a type of strategy that can be traded in very short time frames and users can trade this strategy algorithmically by connecting this strategy to their own accounts with the help of API systems. For this reason, I have developed a software that can give us signals by dynamically changing the long and short messages when users are trading.
2- We can change the start and end dates of our grid bot as we want. It is necessary to use this setting when setting up automatic bots, so that previously opened transactions are not taken into account.
3 - Lot or quantity size should not be excessively small when users are taking automatic trades because exchanges have limitations, to avoid this problem, I have prevented this error by automatically rounding up to the nearest quantity size inside the software.
4 - Users can avoid excessive losses by using stop loss on this grid bot if they wish.
5 - When our price is over the range high or below the range low, our open positions are closed, if the stop button is active. We can also change which close price time frame we take as a basis from the settings.
6 -Users can set how many dollars they can enter per transaction while performing their transactions automatically.
IMPLEMENTATION DETAILS – SETTINGS:
This script allows the user to choose the highs and lows leves of our range. Our bot trades in the specified range.
1. This strategy allows us to set start and end backtest dates.
2. We can change range high and range low leves of our bot
3. IF people want to trade algorithmically with the help of this bot, there are 6 different input systems that will receive the Json codes as an alarm
4. IF the price closes above the upper line or below the lower line, all transactions will be closed. We can determine in which time frame our transactions will be stopped if the price closes outside these levels.We can adjust how our bot works by activating or turning off the Stop Loss button.
5. In this strategy, you can determine your dollar cost for per position.
6. The user can also divide the interval we have determined into 10 parts or 20 equal parts.
7. The grid is divided and colored at the interval we set. At the same time, if we don't want we can turn off colored channels.
Notes:
If you're going to connect this bot to an automatic Long and Short direction,
Don’t forget! you need to Webhook URL,
Don’t miss paste this code to your message window {{strategy.order.alert_message}}
ALSO:
Set your range below the support zones and above the resistance zones.
Don't be afraid to take a wide range, it doesn't matter if you make a little money, the important thing is that you don't lose money.
If you have any ideas what to add to my work to add more sources or make calculations cooler, suggest in DM .
Reinforced RSI - The Quant Science This strategy was designed and written with the goal of showing and motivating the community how to integrate our 'Probabilities' module with their own script.
We have recreated one of the simplest strategies used by many traders. The strategy only trades long and uses the overbought and oversold levels on the RSI indicator.
We added stop losses and take profits to offer more dynamism to the strategy. Then the 'Probabilities' module was integrated to create a probabilistic reinforcement on each trade.
Specifically, each trade is executed, only if the past probabilities of making a profitable trade is greater than or equal to 51%. This greatly increased the performance of the strategy by avoiding possible bad trades.
The backtesting was calculated on the NASDAQ:TSLA , on 15 minutes timeframe.
The strategy works on Tesla using the following parameters:
1. Lenght: 13
2. Oversold: 40
3. Overbought: 70
4. Lookback: 50
5. Take profit: 3%
6. Stop loss: 3%
Time period: January 2021 to date.
Our Probabilities Module, used in the strategy example:
Hulk Grid Algorithm - The Quant ScienceGrid-based intraday algorithm that works 50% in trend following and 50% in swing trading. Orders are executed on a grid of 10 levels. The grid levels are dynamic and calculated on the difference between the previous day's open and close. The algorithm makes only long trades based on the following logic:
1. The daily close of the previous day is analyzed, the first condition is met if the previous day was bullish, closing higher than the 'opening.
2. Must pass 'x' number of bars before placing market orders.
3. The range, as the difference between close and open of the previous day must be greater than 'x'.
If these three conditions are met then the algorithm will proceed to place long orders. On a total of 10 grid levels, up to five trades are executed per day.
If the current close is above level 1 of the grid (previous day's close) then trend following trading will take place, working on the upper 5 levels. In this case each order is placed starting at level 1 and closed at each level above.
If the current close is below level 1 of the grid (previous day's open) then swing trading will be carried out, working on the lower 5 levels. In this case each order is placed starting at level 2 and closed at the upper level.
If at the time of order execution the price is above or below the stop loss and take profit levels, the algorithm will cancel the orders and prevent trading.
All orders are closed exclusively for two reasons:
1. If the stop loss or take profit level is confirmed.
2. If the daily session is ended.
UI Interface
You can adjust:
1. Backtesting period
2. 'x' number of bars before placing orders at the market (remember to always add 2 to the number you enter in the user interface if you enter 2 then execution will occur at the market opening after the fourth bar).
3. Intercepted price range between close and open of the previous day, avoiding trading on days when the range is too low.
4. Stop loss, level calculated from the 'last lower grid, if the market breaks this level the grid is destroyed and closes all open positions.
5. Take profit, the level calculated from the last upper grid, if the market breaks this level the grid is destroyed and closes all open positions.
The backtesting you see in the example was generated on:
BINANCE:BTCUSDT
Timeframe 15 min
Stop loss 2%
Take profit 2%
Minimum bars 3
Size grid range 500
This algorithm can be used only on intraday timeframe.
iMoku (Ichimoku Complete Tool) - The Quant Science iMoku™ is a professional all-in-one solution for the famous Ichimoku Kinko Hyo indicator.
The algorithm includes:
1. Backtesting spot
2. Visual tool
3. Auto-trading functions
With iMoku you can test four different strategies.
Strategy 1: Cross Tenkan Sen - Kijun Sen
A long position is opened with 100% of the invested capital ($1000) when "Tenkan Sen" crossover "Kijun Sen".
Closing the long position on the opposite condition.
There are 3 different strength signals for this strategy: weak, normal, strong.
Weak : the signal is weak when the condition is true and the price is above the 'Kumo'
Normal : the signal is normal when the condition is true and the price is within the 'Kumo'
Strong : the signal is strong when the condition is true and the price is below the 'Kumo'
Strategy 2: Cross Price - Kijun Sen
A long position is opened with 100% of the invested capital ($1000) when the price crossover the 'Kijun Sen'.
Closing the long position on the opposite condition.
There are 3 different strength signals for this strategy: weak, normal, strong.
Weak : the signal is weak when the condition is true and the price is above the 'Kumo'
Normal : the signal is normal when the condition is true and the price is inside the 'Kumo'
Strong : the signal is strong when the condition is true and the price is below the 'Kumo'
Strategy 3: Kumo Breakout
A long position is opened with 100% of the invested capital ($1000) when the price breakup the 'Kumo'.
Closing the long position with a percentage stop loss and take profit on the invested capital.
Strategy 4: Kumo Twist
A long position is opened with 100% of the invested capital ($1000) when the 'Kumo' goes from negative to positive (called "Twist").
Closing the long position on the opposite condition.
There are 2 different strength signals for this strategy: weak, and strong.
Weak : the signal is weak when the condition is true and the price is above the 'Kumo'
Strong : the signal is strong when the condition is true and the price is below the 'Kumo'
This script is compliant with algorithmic trading.
You can use this script with trading terminals such as 3Commas or CryptoHopper. Connecting this script is very easy.
1. Enter the user interface
2. Select and activate a strategy
3. Copy your bot's links into the dedicated fields
4. Create and activate alert
Disclaimer: algorithmic trading involves risk, the user should consider aspects such as slippage, liquidity and costs when evaluating an asset. The Quant Science is not responsible for any kind of damage resulting from use of this script. By using this script you take all the responsibilities and risks.
Customizable Non-Repainting HTF MACD MFI Scalper Bot StrategyThis script was originally shared by Wunderbit as a free open source script for the community to work with.
WHAT THIS SCRIPT DOES:
It is intended for use on an algorithmic bot trading platform but can be used for scalping and manual trading.
This strategy is based on the trend-following momentum indicator . It includes the Money Flow index as an additional point for entry.
HOW IT DOES IT:
It uses a combination of MACD and MFI indicators to create entry signals. Parameters for each indicator have been surfaced for user configurability.
Take profits are fixed, but stop loss uses ATR configuration to minimize losses and close profitably.
HOW IS MY VERSION ORIGINAL:
I started trying to deploy this script myself in my algorithmic trading but ran into some issues which I have tried to address in this version.
Delayed Signals : The script has been refactored to use a time frame drop down. The higher time frame can be run on a faster chart (recommended on one minute chart for fastest signal confirmation and relay to algotrading platform.)
Repainting Issues : All indicators have been recoded to use the security function that checks to see if the current calculation is in realtime, if it is, then it uses the previous bar for calculation. If you are still experiencing repainting issues based on intended (or non intended use), please provide a report with screenshot and explanation so I can try to address.
Filtering : I have added to additional filters an ABOVE EMA Filter and a BELOW RSI Filter (both can be turned on and off)
Customizable Long and Close Messages : This allows someone to use the script for algorithmic trading without having to alter code. It also means you can use one indicator for all of your different alterts required for your bots.
HOW TO USE IT:
It is intended to be used in the 5-30 minute time frames, but you might be able to get a good configuration for higher time frames. I welcome feedback from other users on what they have found.
Find a pair with high volatility (example KUCOIN:ETH3LUSDT ) - I have found it works particularly well with 3L and 3S tokens for crypto. although it the limitation is that confrigurations I have found to work typically have low R/R ratio, but very high win rate and profit factor.
Ideally set one minute chart for bots, but you can use other charts for manual trading. The signal will be delayed by one bar but I have found configurations that still test well.
Select a time frame in configuration for your indicator calculations.
Select the strategy config for time frame. I like to use 5 and 15 minutes for scalping scenarios, but I am interested in hearing back from other community memebers.
Optimize your indicator without filters (trendFilter and RSI Filter)
Use the TrendFilter and RSI Filter to further refine your signals for entry. You will get less entries but you can increase your win ratio.
I will add screenshots and possibly a video provided that it passes community standards.
Limitations: this works rather well for short term, and does some good forward testing but back testing large data sets is a problem when switching from very small time frame to large time frame. For instance, finding a configuration that works on a one minute chart but then changing to a 1 hour chart means you lose some of your intra bar calclulations. There are some new features in pine script which might be able to address, this, but I have not had a chance to work on that issue.
SIMPLE CANDLESTICK PATTERN ALGO BACKTESTING - TESLA 4HMany traders spend a lot of time to create algorithms full of unrealistic and far from reality indicators and market conditions. With this script I want to help traders understand the advantage of the Pine language. Using indicators with no statistical foundation and creating algorithms with technical indicators and thousands of conditions is not always the right way to create an efficient tool.
With this script that we have called "SimpleBarPattern_LongOnly" we analyse the market through a simple condition, using bars or candles.
How it works
The condition is constructed as follows. You go long with 100% of the established capital and 0.03% commission. The first condition is that the minimum of the period under analysis falls below the opening level. The second condition is that the low of the period is below the low of the previous period. The third condition is that the close of the period is above the opening level. The final condition wants the current close to be higher than the previous open and higher than the previous close. We used a statistical approach in the creation of this script, some candlestick patterns that reflect these conditions are: Bullish Engulfing, Bullish Hammer and Morning Star .
This strategy aims to help traders make more accurate decisions while using candlesticks for their trading and scientifically demonstrates that candlesticks are valid statistical tools for financial analysis.
"SimpleBarPattern_LongOnly" is a very lightweight script created with Pine v5. We developed a user interface that can adjust the analysis period from a few days to several years.
The initial capital set is €1,000 (You can change this from the "Properties" section of the user interface).
Each individual trade uses 100% of the set capital, in this case €1,000.
The default commission per trade is 0.03% (You can change this in the "Properties" section of the user interface).
User Interface
1) General backtest time settings: Set the history period to be analysed
StartDate: backtest start date
StartMonth: backtest start month
StartYear: backtest start year
EndDate: backtest end day
EndMonth: backtest end month
EndYear: backtest end year
3) Stop Loss
4) Take Profit
Please do not hesitate to contact us for any questions or information.
Disclaimer
Be careful, the past is not a guarantee of future performance, so remember to use the script as a pure analysis tool. The developer takes no responsibility for any use other than research and analysis and can in no way be held liable for damages resulting from wrong use of this code.
Coinbase_3-MIN_HFT-StrategyThis conceptual strategy trades against the short-term trend. The first position can be either long or short.
In the short-term, prices fluctuate up and down on wide spread exchanges.
And if the price moves to one side, the price tends to return to its original position momentarily.
This strategy set stop order. Stop price is calculated with upper and lower shadows.
