Gann's square of 9 overextended indicatorThis indicator is inspired by the book “The Definitive Guide to Forecasting Using W.D. Gann’s Square of Nine”. It’s designed to identify overextended price levels in the market.
The indicator uses the concept of Gann’s Square of 9, which is a method for forecasting price movements by observing geometric relationships between price and time. It calculates the square root of the price, then subtracts the square root of a simple moving average of the price. The difference is then converted to degrees to create the indicator values.
The indicator plots four horizontal lines, representing two upper and two lower thresholds. When the indicator crosses these lines, it suggests that the price may be overextended and a reversal could be imminent.
Please note that the Price Multiplier parameter needs to be adjusted for each timeframe and security to ensure accurate results. This is because different securities and timeframes can have different price scales, and the multiplier helps to normalize the price data for the calculation.
The indicator also includes a Moving Average Size parameter, which determines the length of the simple moving average used in the calculation.
This indicator can be a useful tool for traders looking to identify potential reversal points in the market. However, like all indicators, it should be used in conjunction with other forms of analysis and it’s not recommended to rely solely on this indicator for trading decisions.
Forecasting
Auto Fibo on IndicatorsThis drawing tool aims to draw auto Fibonacci Retracement Levels on desired indicators.
Users can define the target indicator to draw Auto Fibo Lines, from the "settings tab":
There are six commonly used indicators below the charts that can be selected to draw Fibonacci Retracement lines on:
RSI : Relative Strength Index
CCI : Commodity Channel Index
MFI : Money Flow Index
STOCHASTIC : Stochastic Oscillator
CMF : Chaikin Money Flow
CMO : Chande Momentum Oscillator
Fibonacci Retracement Levels will appear automatically after applying the indicator.
The "Auto Fibo on Indicators" tool looks back. It checks the indicator levels for a desired number of bars and then draws the Fibonacci Levels automatically in the right way, considering the final movements of the indicator.
There are five commonly used Fibonacci Levels added between the Highest and Lowest values such as:
%23.6
%38.2
%50 (Not precisely a Fibonacci Level, indeed)
%61.8 (Golden Ratio)
%78.6
Four extra levels can be added from the settings tab by checking their boxes:
%127.2 (adjustable level)
%161.8
%261.8
%361.8
Default lookback bars of Auto Fibo Levels: 144 (which is also a Fibonacci number)
Default Indicator: RSI
Default Indicator length: 14
Default data source: CLOSE
Users can also define and show overbought and oversold levels by unchecking the "Do not Show Indicator Overbought / Oversold Levels?" button from the settings menu.
In technical analysis, Fibonacci Levels on price can guide valuable trading signals for investors.
Levels can be significant support and resistance levels for breakouts and turning points.
This drawing tool aims to follow those necessary levels on indicators to observe critical levels and breakouts.
Monte Carlo Simulation - Your Strategy [Kioseff Trading]Hello!
This script “Monte Carlo Simulation - Your Strategy” uses Monte Carlo simulations for your inputted strategy returns or the asset on your chart!
Features
Monte Carlo Simulation: Performs Monte Carlo simulation to generate multiple future paths.
Asset Price or Strategy: Can simulate either future asset prices based on historical log returns or a specific trading strategy's future performance.
User-Defined Input: Allows you to input your own historical returns for simulation.
Statistical Methods: Offers two simulation methods—Gaussian (Normal) distribution and Bootstrapping.
Graphical Display: Provides options for graphical representation, including line plots and histograms.
Cumulative Probability Target: Enables setting a user-defined cumulative probability target to quantify simulation results.
Adjustable Parameters: Offers numerous user-adjustable settings like number of simulations, forecast length, and more.
Historical Data Points: Option to specify the amount of historical data to be used in the simulation (price).
Custom Binning: Allows you to select the binning method for histograms, with options like Sturges, Rice, and Square Root.
Best/Worst Case: Allows you to show only the best case / worst case outcome (range) for all simulations!
Scatterplot: allows you to show up to 1000 potential outcomes for a specified trade number (or bars forward price endpoint) using a scatter plot.
The image above shows the primary components of the indicator!
The image above shows the best/worst case outcome feature in action!
The image above shows a "fun feature" where 1000 simulated end points for a 15-bar price trajectory are shown as a scatter plot!
How To Perform a Monte Carlo Simulation On Your Strategy
Really, you can input any data into the indicator it will perform a Monte Carlo Simulation on it :D
The following instructions show how to export your strategy results from TradingView to an Excel File, copy the data, and input it into the indicator.
However , you are not limited to following this method!
Wherever your strategy results are stored, simply copy and paste them into the indicator text area in the settings and simulations will begin.
Returns Should Follow This Format
1
3
-3
2
-5
The numbers are presented as a single column. No commas or separators used.
The numbers above are in sequential order. A return of "1" for the first trade and a return of "-5" for the last trade. Your strategy returns will likely be in sequential order already so don't worry too much about this (:
How To Perform a Monte Carlo Simulation On Your TradingView Strategy With Excel Data
Export your strategy returns to an excel file using TradingView
Navigate to your downloads folder to column G "Profit"
Click the column and press CTRL + SPACE to highlight the entire column
Press CTRL + C to copy the entire column
Open this indicator's settings and paste the returns into the text area
The image above illustrates the process!
Notes on Inputting Returns
*Must input your returns without a separate as a vertical list
*The initial text area can only hold so many return values. If your list of trades is large you can input additional returns into two additional text areas at the bottom of the indicator settings.
That should be it; thank you for checking this out!
Weighted Momentum Forecast
The Weighted Momentum Forecast (EWMF) is a predictive indicator designed to forecast the potential direction and magnitude of the next candle's close. It combines the principles of momentum, trend confirmation, and volatility adjustment to make its predictions.
**Components:**
1. **Rate of Change (ROC)**: Measures the momentum of the market.
2. **Average True Range (ATR)**: Represents the market's recent volatility.
3. **Moving Average Convergence Divergence (MACD)**: Used to confirm the momentum's direction.
4. **Trend Moving Average**: A longer-term moving average to confirm the general trend.
5. **Bollinger Bands**: Adjusts the forecast to account for extreme predictions.
**Logic:**
1. **Momentum Bias**: The crossover and crossunder of the MACD line and its signal line are used to determine the momentum's bias. A crossover indicates a bullish bias, while a crossunder indicates a bearish bias.
2. **Trend Confirmation**: If the current close is above the trend moving average, the indicator has a bullish bias, and vice versa.
3. **Forecast Calculation**: The forecast for the next candle's close is calculated based on the current close, the rate of change, the momentum's bias, and the trend's bias. This value is then adjusted for volatility using the ATR.
4. **Volatility Adjustment**: If the forecasted value is beyond the Bollinger Bands, it's adjusted to be within the bands to account for extreme predictions.
**Usage:**
The EWMF plots a purple line representing the forecasted value of the next candle's close. This forecasted value provides traders with a visual representation of where the price might head in the next period, based on recent momentum, trend, and volatility.
**Note**: This is a heuristic approach and is not guaranteed to be accurate. It's essential to use this indicator in conjunction with other tools, backtest on historical data, and use proper risk management techniques. Always be aware of the inherent risks involved in trading and never risk more than you're willing to lose.
Kaschko's Seasonal TrendThis script calculates the average price moves (using each bar's close minus the previous bar's close) for the trading days, weeks or months (depending on the timeframe it is applied to) of a number of past calendar years (up to 30) to construct a seasonal trend which is then drawn as a seasonal chart (overlay) onto the price chart. Supported are the 1D,1W,1M timeframes.
The seasonal chart is adjusted to the price chart (so that both occupy the same height on the overall chart) and it is also de-trended, which means that the seasonal chart's starting value is the same in each year and the progression during the year is adjusted so that no abrupt gap occurs between years and the highs and lows of consecutive years of the seasonal chart (if projected over more than one year) are also at the same level. Of course, this also means that the absolute value of the seasonal chart has no meaning at all.
You can configure the number of bars the seasonal chart is drawn into the future. This projection shows how price could move in the future if the market shows the same seasonal tendencies like in the past. On the daily chart, the trading week of year (TWOY), trading day of month (TDOM) and trading day of year (TDOY) are shown in the status line.
Caution is advised as seasonality is based on the past. It is not a reliable prediction of the future. But it can still be used as an additional confirmation or contradiction of an otherwise recognized possible impending trend.
I have used a virtually identical indicator for a long time in a commercial software package popular among futures traders, but have not found anything comparable here. Therefore I implemented it myself. I hope you find it useful.
Abz US Real ratesThis indicator shows Fed Funds Rate vs US inflation. It also shows the US 10 year bond yield and provides a color indication that aims to indicate if this is a period where owning TLT is a good idea or not. It is not investment advice and it is only aiming to indicate whether the trend is supportive or not for long dated US bonds in comparison with short dated treasury bills and versus inflation.
Recessions: Recessions are indicated by a grey background.
Yield inversion: Periods where the Fed Funds Rate is above the US 10 year bond yield are shown as a maroon background and frequently are macro indicators of an upcoming recession. Like other macro signals, this can't be relied upon as a timing tool.
This is intended to be used as an indictor on a long term chart. Minimum would be weekly but could be even more valid to focus on a chart with monthly candles.
K's Reversal Indicator IIIK's Reversal Indicator III is based on the concept of autocorrelation of returns. The main theory is that extreme autocorrelation (trending) that coincide with a technical signals such as one from the RSI, may result in a powerful short-term signal that can be exploited.
The indicator is calculated as follows:
1. Calculate the price differential (returns) as the current price minus the previous price.
2. the correlation between the current return and the return from 14 periods ago using a lookback of 14 periods.
3. Calculate a 14-period RSI on the close prices.
To generate the signals, use the following rules:
* A bullish signal is generated whenever the correlation is above 0.60 while the RSI is below 40.
* A bearish signal is generated whenever the correlation is above 0.60 while the RSI is above 60.
YinYang Bar ForecastOverview:
YinYang Bar Forecast is a prediction indicator. It predicts the movement for High, Low, Open and Close for up to 13 bars into the future. We created this Indicator as we felt the TradingView community could benefit from a bar forecast as there wasn’t any currently available.
Our YinYang Bar Forecast is something we plan on continuously working on to better improve it, but at its current state it is still very useful and decently accurate. It features many calculations to derive what it thinks the future bars will hold. Let’s discuss some of the logic behind it:
Each bar has its High, Low, Open and Close calculated individually for highest accuracy. Within these calculations we first check which bar it is we are calculating and base our span back length that we are getting our data from based on the bar index we are generating. This helps us get a Moving Average for this bar index.
We take this MA and we apply our Custom Volume Filter calculation on it, which is essentially us dividing the current bars volume over the average volume in the last ‘Filtered Length’ (Setting) length. We take this decimal and multiply it on our MA and smooth it out with a VWMA.
We take the new Volume Filtered MA and apply a RSI Filter calculation on it. RSI Filter is where we take the difference between the high and low of this bar and we multiply it with an RSI calculation using our Volume Filtered MA. We take the result of that multiplication and either add or subtract it from the Volume Filtered MA based on if close > open. This makes our RSI Filtered MA.
Next, we do an EMA Strength Calculation which is where we check if close > ema(close, ‘EMA Averaged Length’) (Setting). Based on this condition we assign a multiplier that is applied to our RSI Filtered MA. We divide by how many bars we are predicting and add a bit to each predictive bar so that the further we go into the future the stronger the strength is.
Next we check RSI and RSI MA levels and apply multiplications based on its RSI levels and if it is greater than or less than the MA. Also it is affected by if the RSI is <= 30 and >= 70.
Finally we check the MFI and MFI MA levels and like RSI we apply multiplications based on its MFI levels and if it is greater than or less than the MA. It is also affected by if the MFI is <= 30 and >= 70.
Please note the way we calculate this may change in the future, this is just currently what we deemed works best for forecasting the future bars. Also note this script uses MA calculations out of scope for efficiency but there is potential for inconsistencies.
Innately it’s main use is the projection it provides. It only draws the bars for realtime bars and not historical ones, so the best way to backtest it is with TradingView’s Replay Tool.
Well, enough of the logic behind it, let's get to understanding how to use it:
Tutorial:
So unfortunately we aren’t able to plot legit bars/candles into the future so we’ve had to do a bit of a work around using lines and fills. As you can see here we have 4 Lines and 3 Zones:
Lines:
Green: Represents the High
Orange: Represents the Open
Teal: Represents the Close
Red: Represents the Low
Zones:
High Zone: This zone is from either Open or Close to the High and is ALWAYS filled with Green.
Open/Close Zone: This zone is from the Open to the Close and is filled with either Green or Red based on if it's greater than the previous bar (real or forecasted).
Low Zone: This zone is from either Open or Close to the Low and is ALWAYS filled with Red.
As you can see generally the Forecasted bars are generally within strong pivot locations and are a good estimation of what will likely go on. Please note, the WHOLE structure of the prediction can change based on the current bars movements and the way it affects the calculations.
Let's look 1 bar back from the current bar just so we can see what it used to Forecast:
As you can see it has changed quite a bit from the previous bar, but if you look close, we drew horizontal lines around where its projecting the next bar to be (our current realtime bar), if we go back to the live chart:
Its projections were pretty close for the high and low. Generally, right now at least, it does a much better job at predicting the high and low than it does the open and close, however we will do our best to fine tune that in future updates.
Remember, this indicator is not meant to base your trades on, but rather give you a Forecast towards the general direction of the next few bars. Somewhat like weather, the farther the bar (or day for weather), the harder it is to predict. For this reason we recommend you focusing on the first few bars as they are more accurate, but review the further ones as they may help show the trend and the way that pair will move.
We will conclude this tutorial here, hopefully this Predictive Indicator can be of some help and use to you. If you have any questions, comments, ideas or concerns please let us know.
Settings:
Forecast Length: How many bars should we predict into the Future? Max 13
Each Bar Length Multiplier: For each new Forecast bar, how many more bars are averaged? Min 2
VWMA Averaged Length: All Forecast bars are put into a VWMA, what length should we use?
EMA Averaged Length: All Forecast bars are put into a EMA, what length should we use?
Filtered Length: What length should we use for Filtered Volume and RSI?
EMA Strength Length: What length should we use for the EMA Strength
HAPPY TRADING!
Buy/Sell BoxThis indicator tries to identify the points where the price exceeds or falls below a rectangle based on the opening and closing prices of the previous period, the creation of the boxes occurs when a doji is detected therefore it will calculate the coordinates of the rectangle that will be drawn around it, therefore the indicator offers buy or sell signals based on this logic. Specifically, the buy signal is generated if the closing price is above the top of the rectangle and satisfies some previous price conditions while the sell signal is generated if the closing price is below the bottom of the rectangle and satisfies some conditions of previous prices within a further threshold based on the Ema 150.
Lines are then drawn on the graph to visually display the extreme price levels, which can be useful for any confirmation of buy and sell signals, Stop Loss and Take Profit, Trend Filter (to visually understand if the trend is bullish or bearish)
A potentially effective trading strategy could involve identifying buy and sell signals near the extreme price level lines drawn by the indicator. This approach can be used to try to improve the accuracy of your trading signals and make more informed decisions. For example:
When you receive a buy or sell signal based on the dojis and rectangles generated by the indicator, check whether the price is also near one of the extreme price level lines. If you are receiving a buy signal and notice that the current price is near a low of the lower level line, this may further confirm the buying opportunity, as the price is near a significant resistance level. On the contrary, if the sell signal was close to a maximum price level it could confirm an excellent short entry.
It is also possible to use the boxes as reference points to set the stop loss and take profit levels. If you are entering a buy position, you might consider setting your stop loss just below an upper line of the last box. Additionally, you may want to set your take profit near a higher price level if you are looking to maximize profits. This will help manage risks and protect your capital.
Ruth Buy/Sell Signal for Day Trade and Swing TradeRuth is based on the most known technical indicators and designed for intraday traders. Ruth's aim is to find the best Buy/Sell points and decide to stop loss point with minimum Loss also Ruth tries to find multiple Profit points as TP1/TP2/TP3/TP4/TP5. Ruth was designed based on the heat map colors to be user-friendly and easy to read. While cold color preferred for Short positions, warm colors preferred for Long positions. The most important feature of Ruth is that after the signal is generated, the candles in which the profitable levels are painted one by one with their own special color codes, so that even the most inexperienced users can understand where they should close their positions.
There are two types of signal Ruth can produce for fast trade.
Short Signal: These signals means market tends to be move to down.
Short Stop Loss Point: This is the maximum risk for the position. Shown with single red line inside of the signal.
Short Entry Point: This is the best entry price for short side position. Shown with single baby blue line inside of the signal.
Short Take Profit (TP1): This level represents the profit level the signal is most likely to reach. Shown with single blue line inside of the signal.
Short Take Profit (TP2): This level represents the profit level with a high probability of the signal occurring. Shown with single light purple line inside of the signal.
Short Take Profit (TP3): This level represents the profit level with an intermediate probability of the signal occurring. Shown with single dark purple line inside of the signal.
Short Take Profit (TP4): This level represents the profit level with a low probability of the signal occurring. Shown with single light lilac line inside of the signal.
Short Take Profit (TP5): This level represents the profit level with a tight probability of the signal occurring. Shown with single dark lilac line inside of the signal.
Long Signal: These signals means market tends to be move to up.
Long Stop Loss Point: This is the maximum risk for the position. Shown with single red line inside of the signal.
Long Entry Point: This is the best entry price for short side position. Shown with single baby blue line inside of the signal.
Long Take Profit (TP1): This level represents the profit level the signal is most likely to reach. Shown with single greenish yellow line inside of the signal.
Long Take Profit (TP2): This level represents the profit level with a high probability of the signal occurring. Shown with yellow purple line inside of the signal.
Long Take Profit (TP3): This level represents the profit level with an intermediate probability of the signal occurring. Shown with single dark yellow line inside of the signal.
Long Take Profit (TP4): This level represents the profit level with a low probability of the signal occurring. Shown with single orange line inside of the signal.
Long Take Profit (TP5): This level represents the profit level with a tight probability of the signal occurring. Shown with single dark orange line inside of the signal.
Timeframe: In general best and fastest results occurred in shorter timeframes like 1 min / 5 mins / 15 mins but feel free to try higher timeframes.
Tips & Tricks:
1) Gray line drawn ot the graph represents Dema, we suggests you to go on Short Singals under gray line and go on Long Signals upper gray line.
2) Mostly, Signals easily reach their TP2 / TP3 levels and then generally there is reaction or take profit desire so commodity price turns the opposite direction. If in short time price won't turn to Signal direction close position.
3) Don't forget, every positions has own risks and profits but trade in main trend is crucial.
GP - Long Short ScannerThis script is made to predict the point at which price-time charts will rise or fall. The script was inspired by the RSI and TSI formulas. The formula is simply; Calculates the RSI and TSI values of open, high, low and close. Calculated values are converted to an array. The maximum and minimum values in the array are taken for the candles included in the calculation. These values calculate the time when the "Long" label will be seen on the chart of the candle that will increase the price. At the same time, it calculates the time when the "Short" label will appear on the chart of the candle that will decrease the price. Although these calculations are not precise; Seeing the “Long” label means that the price will rise at that candle, and seeing the “Short” label means that the price will decrease at that candle. The “Long”, “Short” tags from this script alone should not be used to determine the direction of the price. It can be used on all price-time charts.
Bursa Malaysia Index SeriesBursa Malaysia Index Series. The index computation is as follows:-
Current aggregate Market Capitalisation/Base Aggregate Market Capitalisation x 100.
The Bursa Malaysia Index Series is calculated and disseminated on a real-time basis at 60-second intervals during Bursa’s trading hours.
Buy/Sell EMA CrossoverThe indicator identifies potential trading opportunities within the market. It is entirely based on the combination of exponential moving averages by drawing triangles on the chart that identify buy or sell signals combined with vertical bars that create areas of interest.
Specifically, when a buy signal occurs, the indicator draws a vertical bar with an azure background, indicating a possible buy area. Similarly, a sell signal is represented by a vertical bar with a fuchsia background, indicating a possible sell area.
These areas represent the main point of the indicator which uses exponential moving averages which, based on the direction of prices, identify the trend and color the background of the graph in order to visually highlight the predominant trend.
The green triangles above the bars of the chart suggest possible upside opportunities (good bullish entry points) when the 21 ema crosses the 200 ema.
While on the contrary the red triangles, 21 ema lower than the 200 ema, can indicate possible bearish trends (good bearish entry points).
While the white and purple triangles reveal moments of potential indecision or market change.
We can think of them as situations of uncertain trend in which it is possible to place a long or short order near some conditions that we are going to see.
The white triangles below, which are created when the 13 ema is higher than the 21 ema, indicate a possible bullish zone while the purple triangles above (13 ema lower than the 21) could suggest a bearish reflex
Colored lines represent moving averages blue = 200, 21= fuchsia and 13 = white. If the price is above the 200 period line then it could be a bullish opportunity, otherwise it could be a bearish one.
An interesting strategy to adopt is to evaluate, for example, the inputs near the vertical bars (azure - long) (fuchsia - short) when a white or purple triangle appears.
The more prominent green triangle indicates that the trend is going in a long direction.
On the contrary, the red (short) triangles are the opposite of the green ones and have the same importance as input logic.
The white triangle instead present more often inside the indicator identifies interesting buying areas of short duration, it is important to consider that the closer the triangles are to the vertical blue bars the stronger the entry signal.
Finally, the purple triangles are the short-term bearish trends whose entry near the fuchsia vertical bars defines a short.
HL 930 by JPThe "High and Low of 9:30 Candle" strategy is a simple trading strategy commonly used in the stock market and other financial markets. It involves using the price range (high and low) of the first candlestick that forms at the opening of a trading session, typically at 9:30 AM, as a basis for making trading decisions. Here's a description of this strategy:
1. Timeframe: This strategy is often applied to intraday trading, where traders focus on short-term price movements within a single trading day.
2. 9:30 AM Candle: The strategy begins by observing the first candlestick that forms at 9:30 AM, which is the opening time for many stock markets, including the New York Stock Exchange (NYSE). This candle represents the price action during the first few minutes of trading.
3. High and Low: Identify the highest price (the candle's high) and the lowest price (the candle's low) during the 9:30 AM candle's time period. These price levels are critical for the strategy.
4. Trading Decisions:
Long (Buy) Signal: If the current market price breaks above the high of the 9:30 AM candle, it may trigger a bullish signal. Traders may consider entering a long (buy) position, anticipating further upward momentum.
Short (Sell) Signal: Conversely, if the market price breaks below the low of the 9:30 AM candle, it may trigger a bearish signal. Traders may consider entering a short (sell) position, anticipating further downward movement.
5. Stop-Loss and Take-Profit: To manage risk, traders often set stop-loss orders just below the low (for long positions) or just above the high (for short positions) of the 9:30 AM candle. They may also establish take-profit levels based on their risk-reward preferences.
6. Time Frame: This strategy is typically used for short-term trading and may be effective in capturing quick price movements that often occur at the market open. Traders often close their positions before the end of the trading day.
7. Caution: While the "High and Low of 9:30 Candle" strategy can be straightforward, it should not be used in isolation. Traders should consider other technical and fundamental factors, such as volume, market sentiment, news events, and overall market trends, when making trading decisions.
Remember that trading strategies always carry risks, and it's essential to have a well-thought-out risk management plan in place. Additionally, backtesting and practice are crucial before implementing any trading strategy in a live market to evaluate its historical performance and suitability for your trading style.
Cross Correlation [Kioseff Trading]Hello!
This script "Cross Correlation" calculates up to ~10,000 lag-symbol pair cross correlation values simultaneously!
Cross correlation calculation for 20 symbols simultaneously
+/- Lag Range is theoretically infinite (configurable min/max)
Practically, calculate up to 10000 lag-symbol pairs
Results can be sorted by greatest absolute difference or greatest sum
Ability to "isolate" the symbol on your chart and check for cross correlation against a list of symbols
Script defaults to stock pairs when on a stock, Forex pairs when on a Forex pair, crypto when on a crypto coin, futures when on a futures contract.
A custom symbol list can be used for cross correlation checking
Can check any number of available historical data points for cross correlation
Practical Assessment
Ideally, we can calculate cross correlation to determine if, in a list of assets, any of the assets frequently lead or lag one another.
Example
Say we are comparing the log returns for the previous 10 days for SPY and XLU.
*A single time-interval corresponds to the timeframe of your chart i.e. 1-minute chart = 1-minute time interval. We're using days for this example.
(Example Results)
A lag value (k) +/-3 is used.
The cross correlation (normalized) for k = +3 is -0.787
The cross correlation (normalized) for k = -3 is 0.216
A positive "k" value indicates the correlation when Asset A (SPY) leads Asset B (XLU)
A negative "k" value indicates the correlation when Asset B (XLU) leads Asset A (SPY)
A normalized cross correlation of -0.787 for k = +3 indicates an "adequately strong" negative relationship when SPY leads XLU by 3 days.
When SPY increases or decreases - XLU frequently moves in the opposite direction 3 days later.
A cross correlation value of 0.216 at k = −3 indicates a "weak" positive correlation when XLU leads SPY by 3 days.
There's a slight tendency for SPY to move in the same direction as XLU 3 days later.
After the cross-correlation score is normalized it will fall between -1 and 1.
A cross-correlation score of 1 indicates a perfect directional relationship between asset A and asset B at the corresponding lag (k).
A cross correlation of -1 indicates a perfect inverse relationship between asset A and asset B at the corresponding lag (k).
A cross correlation of 0 indicates no correlation at the corresponding lag (k).
The image above shows the primary usage for the script!
The image above further explains the data points located in the table!
The image above shows the script "isolating" the symbol on my chart and checking the cross correlation between the symbol and a list of symbols!
Wrapping Up
With this information, hopefully you can find some meaningful lead-lag relationships amongst assets!
Thank you for checking this out (:
Bitcoin Market Cap wave model weeklyThis Bitcoin Market Cap wave model indicator is rooted in the foundation of my previously developed tool, the : Bitcoin wave model
To derive the Total Market Cap from the Bitcoin wave price model, I employed a straightforward estimation for the Total Market Supply (TMS). This estimation relies on the formula:
TMS <= (1 - 2^(-h)) for any h.This equation holds true for any value of h, which will be elaborated upon shortly. It is important to note that this inequality becomes the equality at the dates of halvings, diverging only slightly during other periods.
Bitcoin wave model is based on the logarithmic regression model and the sinusoidal waves, induced by the halving events.
This chart presents the outcome of an in-depth analysis of the complete set of Bitcoin price data available from October 2009 to August 2023.
The central concept is that the logarithm of the Bitcoin price closely adheres to the logarithmic regression model. If we plot the logarithm of the price against the logarithm of time, it forms a nearly straight line.
The parameters of this model are provided in the script as follows: log(BTCUSD) = 1.48 + 5.44log(h).
The secondary concept involves employing the inherent time unit of Bitcoin instead of days:
'h' denotes a slightly adjusted time measurement intrinsic to the Bitcoin blockchain. It can be approximated as (days since the genesis block) * 0.0007. Precisely, 'h' is defined as follows: h = 0 at the genesis block, h = 1 at the first halving block, and so forth. In general, h = block height / 210,000.
Adjustments are made to account for variations in block creation time.
The third concept revolves around investigating halving waves triggered by supply shock events resulting from the halvings. These halvings occur at regular intervals in Bitcoin's native time 'h'. All halvings transpire when 'h' is an integer. These events induce waves with intervals denoted as h = 1.
Consequently, we can model these waves using a sin(2pih - a) function. The parameter determining the time shift is assessed as 'a = 0.4', aligning with earlier expectations for halving events and their subsequent outcomes.
The fourth concept introduces the notion that the waves gradually diminish in amplitude over the progression of "time h," diminishing at a rate of 0.7^h.
Lastly, we can create bands around the modeled sinusoidal waves. The upper band is derived by multiplying the sine wave by a factor of 3.1*(1-0.16)^h, while the lower band is obtained by dividing the sine wave by the same factor, 3.1*(1-0.16)^h.
The current bandwidth is 2.5x. That means that the upper band is 2.5 times the lower band. These bands are forming an exceptionally narrow predictive channel for Bitcoin. Consequently, a highly accurate estimation of the peak of the next cycle can be derived.
The prediction indicates that the zenith past the fourth halving, expected around the summer of 2025, could result in Total Bitcoin Market Cap ranging between 4B and 5B USD.
The projections to the future works well only for weekly timeframe.
Enjoy the mathematical insights!
Bitcoin wave modelBitcoin wave model is based on the logarithmic regression model and the sinusoidal waves, induced by the halving events.
This chart presents the outcome of an in-depth analysis of the complete set of Bitcoin price data available from October 2009 to August 2023.
The central concept is that the logarithm of the Bitcoin price closely adheres to the logarithmic regression model. If we plot the logarithm of the price against the logarithm of time, it forms a nearly straight line.
The parameters of this model are provided in the script as follows: log (BTCUSD) = 1.48 + 5.44log(h).
The secondary concept involves employing the inherent time unit of Bitcoin instead of days:
'h' denotes a slightly adjusted time measurement intrinsic to the Bitcoin blockchain. It can be approximated as (days since the genesis block) * 0.0007. Precisely, 'h' is defined as follows: h = 0 at the genesis block, h = 1 at the first halving block, and so forth. In general, h = block height / 210,000.
Adjustments are made to account for variations in block creation time.
The third concept revolves around investigating halving waves triggered by supply shock events resulting from the halvings. These halvings occur at regular intervals in Bitcoin's native time 'h'. All halvings transpire when 'h' is an integer. These events induce waves with intervals denoted as h = 1.
Consequently, we can model these waves using a sin(2pih - a) function. The parameter determining the time shift is assessed as 'a = 0.4', aligning with earlier expectations for halving events and their subsequent outcomes.
The fourth concept introduces the notion that the waves gradually diminish in amplitude over the progression of "time h," diminishing at a rate of 0.7^h.
Lastly, we can create bands around the modeled sinusoidal waves. The upper band is derived by multiplying the sine wave by a factor of 3.1*(1-0.16)^h, while the lower band is obtained by dividing the sine wave by the same factor, 3.1*(1-0.16)^h.
The current bandwidth is 2.5x. That means that the upper band is 2.5 times the lower band. These bands are forming an exceptionally narrow predictive channel for Bitcoin. Consequently, a highly accurate estimation of the peak of the next cycle can be derived.
The prediction indicates that the zenith past the fourth halving, expected around the summer of 2025, could result in prices ranging between 200,000 and 240,000 USD.
Enjoy the mathematical insights!
Pro Bollinger Bands CalculatorThe "Pro Bollinger Bands Calculator" indicator joins our suite of custom trading tools, which includes the "Pro Supertrend Calculator", the "Pro RSI Calculator" and the "Pro Momentum Calculator."
Expanding on this series, the "Pro Bollinger Bands Calculator" is tailored to offer traders deeper insights into market dynamics by harnessing the power of the Bollinger Bands indicator.
Its core mission remains unchanged: to scrutinize historical price data and provide informed predictions about future price movements, with a specific focus on detecting potential bullish (green) or bearish (red) candlestick patterns.
1. Bollinger Bands Calculation:
The indicator kicks off by computing the Bollinger Bands, a well-known volatility indicator. It calculates two pivotal Bollinger Bands parameters:
- Bollinger Bands Length: This parameter sets the lookback period for Bollinger Bands calculations.
- Bollinger Bands Deviation: It determines the deviation multiplier for the upper and lower bands, typically set at 2.0.
2. Visualizing Bollinger Bands:
The Bollinger Bands derived from the calculations are skillfully plotted on the price chart:
- Red Line: Represents the upper Bollinger Band during bearish trends, suggesting potential price declines.
- Teal Line: Represents the lower Bollinger Band in bullish market conditions, signaling the possibility of price increases.
3.Analyzing Consecutive Candlesticks:
The indicator's core functionality revolves around tracking consecutive candlestick patterns based on their relationship with the Bollinger Bands lines. To be considered for analysis, a candlestick must consistently close either above (green candles) or below (red candles) the Bollinger Bands lines for multiple consecutive periods.
4. Labeling and Enumeration:
To convey the count of consecutive candles displaying consistent trend behavior, the indicator meticulously assigns labels to the price chart. The position of these labels varies depending on the direction of the trend, appearing either below (for bullish patterns) or above (for bearish patterns) the candlesticks. The label colors match the candle colors: green labels for bullish candles and red labels for bearish ones.
5. Tabular Data Presentation:
The indicator complements its graphical analysis with a customizable table that prominently displays comprehensive statistical insights. Key data points within the table encompass:
- Consecutive Candles: The count of consecutive candles displaying consistent trend characteristics.
- Candles Above Upper BB: The number of candles closing above the upper Bollinger Band during the consecutive period.
- Candles Below Lower BB: The number of candles closing below the lower Bollinger Band during the consecutive period.
- Upcoming Green Candle: An estimated probability of the next candlestick being bullish, derived from historical data.
- Upcoming Red Candle: An estimated probability of the next candlestick being bearish, also based on historical data.
6. Custom Configuration:
To cater to diverse trading strategies and preferences, the indicator offers extensive customization options. Traders can fine-tune parameters such as Bollinger Bands length, upper and lower band deviations, label and table placement, and table size to align with their unique trading approaches.
Pro RSI CalculatorThe "Pro RSI Calculator" indicator is the latest addition to a series of custom trading tools that includes the "Pro Supertrend Calculator" and the "Pro Momentum Calculator."
Building upon this series, the "Pro RSI Calculator" is designed to provide traders with further insights into market trends by leveraging the Relative Strength Index (RSI) indicator.
Its primary objective remains consistent: to analyze historical price data and make informed predictions about future price movements, with a specific focus on identifying potential bullish (green) or bearish (red) candlestick patterns.
1. RSI Calculation:
The indicator begins by computing the RSI, a widely used momentum oscillator. It calculates two crucial RSI parameters:
RSI Length: This parameter determines the lookback period for RSI calculations.
RSI Upper and Lower Bands: These thresholds define overbought and oversold conditions, typically set at 70 and 30, respectively.
2. RSI Bands Visualization:
The RSI values obtained from the calculation are skillfully plotted on the price chart, appearing as two distinct lines:
Red Line: Represents the RSI when indicating a bearish trend, anticipating potential price declines.
Teal Line: Represents the RSI in bullish market conditions, signaling the possibility of price increases.
3. Consecutive Candlestick Analysis:
The indicator's core functionality revolves around tracking consecutive candlestick patterns based on their relationship with the RSI lines.
To be included in the analysis, a candlestick must consistently close either above (green candles) or below (red candles) the RSI lines for multiple consecutive periods.
4. Labeling and Enumeration:
To communicate the count of consecutive candles displaying consistent trend behavior, the indicator meticulously assigns labels to the price chart.
Label positioning varies depending on the trend's direction, appearing either below (for bullish patterns) or above (for bearish patterns) the candlesticks.
The color scheme aligns with the candle colors: green labels for bullish candles and red labels for bearish ones.
5. Tabular Data Presentation:
The indicator enhances its graphical analysis with a customizable table that prominently displays comprehensive statistical insights.
Key data points in the table include:
- Consecutive Candles: The count of consecutive candles displaying consistent trend characteristics.
- Candles Above Upper RSI: The number of candles closing above the upper RSI threshold during the consecutive period.
- Candles Below Lower RSI: The number of candles closing below the lower RSI threshold during the consecutive period.
- Upcoming Green Candle: An estimated probability of the next candlestick being bullish, derived from historical data.
- Upcoming Red Candle: An estimated probability of the next candlestick being bearish, also based on historical data.
6. Custom Configuration:
To cater to various trading strategies and preferences, the indicator offers extensive customization options.
Traders can fine-tune parameters like RSI length, upper, and lower bands, label and table placement, and table size to align with their unique trading approaches.
The Next Pivot [Kioseff Trading]Hello!
This script "The Next Pivot" uses various similarity measures to compare historical price sequences to the current price sequence!
Features
Find the most similar price sequence up to 100 bars from the current bar
Forecast price path up to 250 bars
Forecast ZigZag up to 250 bars
Spearmen
Pearson
Absolute Difference
Cosine Similarity
Mean Squared Error
Kendall
Forecasted linear regression channel
The image above shows/explains some of the indicator's capabilities!
The image above highlights the projected zig zag (pivots) pattern!
Colors are customizable (:
Additionally, you can plot a forecasted LinReg channel.
Should load times permit it, the script can search all bar history for a correlating sequence. This won't always be possible, contingent on the forecast length, correlation length, and the number of bars on the chart.
Reasonable Assessment
The script uses various similarity measures to find the "most similar" price sequence to what's currently happening. Once found, the subsequent price move (to the most similar sequence) is recorded and projected forward.
So,
1: Script finds most similar price sequence
2: Script takes what happened after and projects forward
While this may be useful, the projection is simply the reaction to a possible one-off "similarity" to what's currently happening. Random fluctuations are likely and, if occurring, similarities between the current price sequence and the "most similar" sequence are plausibly coincidental.
That said, if you have any ideas on cool features to add please let me know!
Thank you (:
Machine Learning: Trend Pulse⚠️❗ Important Limitations: Due to the way this script is designed, it operates specifically under certain conditions:
Stocks & Forex : Only compatible with timeframes of 8 hours and above ⏰
Crypto : Only works with timeframes starting from 4 hours and higher ⏰
❗Please note that the script will not work on lower timeframes.❗
Feature Extraction : It begins by identifying a window of past price changes. Think of this as capturing the "mood" of the market over a certain period.
Distance Calculation : For each historical data point, it computes a distance to the current window. This distance measures how similar past and present market conditions are. The smaller the distance, the more similar they are.
Neighbor Selection : From these, it selects 'k' closest neighbors. The variable 'k' is a user-defined parameter indicating how many of the closest historical points to consider.
Price Estimation : It then takes the average price of these 'k' neighbors to generate a forecast for the next stock price.
Z-Score Scaling: Lastly, this forecast is normalized using the Z-score to make it more robust and comparable over time.
Inputs:
histCap (Historical Cap) : histCap limits the number of past bars the script will consider. Think of it as setting the "memory" of model—how far back in time it should look.
sampleSpeed (Sampling Rate) : sampleSpeed is like a time-saving shortcut, allowing the script to skip bars and only sample data points at certain intervals. This makes the process faster but could potentially miss some nuances in the data.
winSpan (Window Size) : This is the size of the "snapshot" of market data the script will look at each time. The window size sets how many bars the algorithm will include when it's measuring how "similar" the current market conditions are to past conditions.
All these variables help to simplify and streamline the k-NN model, making it workable within limitations. You could see them as tuning knobs, letting you balance between computational efficiency and predictive accuracy.
Price Variation and Projection IndicatorThis indicator calculates and visualizes various aspects of price variation and projection based on certain parameters such as rate of change, time interval, constant value, and more. It helps traders understand potential price movements and provides insights into potential support and resistance levels.
The indicator displays the following information:
Resistance and support levels based on the highest and lowest prices over a specified period.
∆P (Price Variation) calculated between two high oscillations.
∆t (Time Variation) calculated between two high oscillations.
Price variation rate.
Price projections based on rate of change and the most occurred variation.
Additionally, parallel lines are drawn to illustrate projected price ranges, and the most frequent ∆P value is shown for reference.
in short the indicator does it projects possible support and resistance for you to add a mark for example you see that it gave a projection you mark it on the chart with horizontal line or horizontal ray you can configure it by Period or by ∆t calculation limit au increase the period it will increase the projection of all targets interesting periods to use 20 50 80 120 200 since the ∆t calculation limit au decrease increases the projection in the Price projection that is showing the information in blue color when increasing it decreases the projection target ∆t calculation interesting limit to use 3 4 6 7 8 9
it works for all timeframes can be used for Swing trade or day trade
use I like to use it with a closed market that helps me to trace possible support and resistance can be used with open market as well
Choose your preferred language to display the information
Please note that this indicator is designed for educational and informational purposes. Always conduct your own analysis and consider risk management strategies before making trading decisions.
Crypto/DXY ScoringHi!
This indicator "Crypto/DXY Scoring", a multi-purpose script, consists of various comparison statistics (including an alternative RS/RSMOM model) to show the strength of a currency against the DXY.
Features
"Contrived" RS/RSMOM alternative model
Compare the strength of the crypto currency on your chart to any asset (DXY default)
Glass's ∆
Z-comparison
Hedges' g
Cliff's Delta
Z-score for log returns
RRG graph (with adjusted dimensions) Traditional RRG graph coming soon (:
Let's go over some simplified interpretations of what's shown on the chart!
The image above provides generalized interpretations for the three of the data series plotted by the indicator.
The image above further explains the other plots for the indicator!
The image above shows the final result!
Underlying Theory
"When the dollar is strong as indicated by the DXY, it usually means that investors are seeking safety in traditional assets. Bitcoin (crypto) is often considered a "risk-on" asset, meaning investors might sell BTC in favor of holding dollars, thus driving BTC prices down."
Given the complexities associated with this relationship, including its contentious implications and a variable correlation between crypto and the DXY, this theory is one within a plethora.
That said, regardless of accuracy, this indicator adheres to the theory outlined above (:
The image above shows the purpose of the red/lime columns and the corresponding red/green lines.
Should the crypto on your chart and the DXY (or comparison symbol) exhibit negative correlation, and should the performance of DXY (or comparison symbol) hold any predictive utility for the subsequent performance of the crypto on your chart, the red columns violating the red line might indicate an upcoming "dump" for the crypto on your chart.
Lime green columns violating the green line may indicator an inverse response.
Alternative Relative Rotation Graph
In its current state, the alternated dimensions for the Relative Rotation Graph cause it to function more as a "Relative Performance Graph".
Fear not; a traditional RRG graph is coming soon!
The image above shows our alternative RRG!
Interpretation
With this model, you can quickly/intuitively assess the relative performance of the display cryptos against an index of their performance.
The image above shows generalized interpretations of the model!
That's it for this indicator! Thank you for checking it out; more to come (:
