Bắt đầu

Hồi quy tuyến tính

Linear Regression - Auto Adjust To Ideal Pearson's R (Min & Max)This is meant as a partner to my linear regression strategy script. This one however is just the indicator only so you can overlay the technique over other strategies. To use this script you need to understand what Pearson's R is; which is how correlated a set of data is to a line within a given deviation (+ or -). If the Pearson's R is negative (-) then the trend is going upwards. If the value is positive (+) then the trend is going downwards. There is a lot of debate as to what the ideal negative and positive values are for the Pearson's R, so you can change these in the settings. What the script will do is attempt to automatically find (and draw the trend lines) based on a given minimum period and a maximum period (both set in the settings) that match the ideal Pearson's R settings selected. Ideally the data is MOST correlated the closest it is to -1 or 1. This means the pattern is very reliable. This script was designed and works very well with the bar replay mode. You may need a more professional version of TradingView to use this correctly. This mode allows you to see the script in action as it mutates and changes according to the new data being introduced. I've pre-set the Pearson's R (+) and (-) ranges to what I think is ideal.
Chỉ báo
của Gentleman-Goat
21
Linear Regression Pearson's R - Trend Channel StrategyThis script takes advantage of the Pearson's R attribute of the data set you provide. Pearson's R attempts to find how correlated data is with a potential pattern. If the number is negative the correlation is upwards . If it's positive the correlation is downwards . Pearson's R can only be a number between -1 and 1. It should be impossible to ever reach -1 or 1 as that would be a perfect correlation. This particular strategy involves using linear regression and Pearson's R to keep recalculating steps back from the current position until the Pearson's R reaches the desired amount. For example, in my experience I have found that 0.85 for as a buy point is very good as it means the trend is very reliable and solid. When the market tends to be bullish it tends to do so longer then when it's bearish. Likewise when a downtrend is more real, I found that 0.71 for the negative Pearson's R value is ideal and gives the best results. These can all be changed in the settings section (with the gear icon) next to when you set your results. This strategy is really fun/useful to watch if you have the replay bar mode enabled for TradingView. This script supports this and all you have to do is go into the settings and enable realtime mode . Doing this you can actually see the trend lines change in realtime and comes in very handy for seeing long term reversals as you will see the Pearson's R value start to go down or up indicating the path it's going on. WARNING: This script is very intensive on the processing power of your machine. If you find that it's to slow you may have to go into the settings of the script and adjust the 'step by' parameter so that it calculates a little faster. It won't be as accurate but it will be good enough. I feel I've optimized it with it's current setting as an example of what you want to aim for. If there are any questions do no hesitate to message or ask me. I love feedback on the community for new features and ideas! This works best with with XBTUSD on the 4 hourly chart . It does not seem to work well if you go below hourly or go above daily.
Chiến lược
của Gentleman-Goat
14
Leavitt Convolution & Acceleration by CryptorhythmsLeavitt Projection, Convolution, & Acceleration by Cryptorhythms Intro Bringing you another open source Gem this time from the January 2020 Issue of TASC. Description In the article in the Oct 2019 TASC issue titled "An interplanetary marriage" author Jay Leavitt describes the evolution process required in strategy design by introducing his Mars strategy. This grew out of concepts presented in his earlier TASC articles such as the stratosphere, moon rocket, and tech emini strategies. This dual indicator uses a linear regression of price data to help derive slope and acceleration information, in turn helping him to identify trends and trend turning points. Additions As usual a few useful extras are included such as a rudimentary signaling system, bar coloration by trade state, overbought/oversold areas to assist in algorithmic setups, and more! 👍 We hope you enjoyed this indicator and find it useful! We post free crypto analysis, strategies and indicators regularly. This is our 71st script on Tradingview! 💬Check my Signature for other information
Chỉ báo
của theheirophant
3
Leavitt Convolutions Multicator - Jay Leavitt, Ph.D.Hot off the press, I present this next generation "Leavitt Convolutions Multicator" employing PSv4.0, originally formulated by Jay Leavitt, Ph.D. for TASC - January 2020 Traders Tips. Basically it's an all-in-one combination of three Leavitt indicators. This triplet indicator, being less than a 60 line implementation at initial release, is a heavily modified version of the original indicator using novel techniques, surpassing Leavitt's original intended design. Utilizing the "Power of Pine", I included the maximum amount of features I could surmise in an ultra small yet powerful package. Configurations are displayed above in multiple scenarios that should be suitable for most traders. Features List Includes: Dark Background - Easily disabled in indicator Settings->Style for "Light" charts or with Pine commenting AND much, much more... You have the source! For those of you who are new to Pine Script, this script may also help you understand advanced programming techniques in Pine and how they may be utilized in a most effective manner. Most notably, the script shows how to potentially combine three indicators in one with Pine. This is commonly what my dense intricate code looks like behind the veil, and if you are wondering why there is no notes, that's because the notation is in the variable naming. The comments section below is solely just for commenting and other remarks, ideas, compliments, etc... regarding only this indicator, not others. When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members, I may implement more ideas when they present themselves as worthy additions. As always, "Like" it if you simply just like it with a proper thumbs up, and also return to my scripts list occasionally for additional postings. Have a profitable future everyone!
Chỉ báo
của ImmortalFreedom
16
NAND PerceptronExperimental NAND Perceptron based upon Python template that aims to predict NAND Gate Outputs. A Perceptron is one of the foundational building blocks of nearly all advanced Neural Network layers and models for Algo trading and Machine Learning. The goal behind this script was threefold: To prove and demonstrate that an ACTUAL working neural net can be implemented in Pine, even if incomplete. To pave the way for other traders and coders to iterate on this script and push the boundaries of Tradingview strategies and indicators. To see if a self-contained neural network component for parameter optimization within Pinescript was hypothetically possible. NOTE: This is a highly experimental proof of concept - this is NOT a ready-made template to include or integrate into existing strategies and indicators, yet (emphasis YET - neural networks have a lot of potential utility and potential when utilized and implemented properly). Hardcoded NAND Gate outputs with Bias column (X0): // NAND Gate + X0 Bias and Y-true // X0 // X1 // X2 // Y // 1 // 0 // 0 // 1 // 1 // 0 // 1 // 1 // 1 // 1 // 0 // 1 // 1 // 1 // 1 // 0 Column X0 is bias feature/input Column X1 and X2 are the NAND Gate Column Y is the y-true values for the NAND gate yhat is the prediction at that timestep F0,F1,F2,F3 are the Dot products of the Weights (W0,W1,W2) and the input features (X0,X1,X2) Learning rate and activation function threshold are enabled by default as input parameters Uncomment sections for more training iterations/epochs: Loop optimizations would be amazing to have for a selectable length for training iterations/epochs but I'm not sure if it's possible in Pine with how this script is structured. Error metrics and loss have not been implemented due to difficulty with script length and iterations vs epochs - I haven't been able to configure the input parameters to successfully predict the right values for all four y-true values for the NAND gate (only been able to get 3/4; If you're able to get all four predictions to be correct, let me know, please). // //---- REFERENCE for final output // A3 := 1, y0 true // B3 := 1, y1 true // C3 := 1, y2 true // D3 := 0, y3 true PLEASE READ: Source article/template and main code reference: towardsdatascience.com towardsdatascience.com towardsdatascience.com
Chỉ báo
của UnknownUnicorn2796841
14
Function Decimal To Binary/Binary To DecimalNOTE: Experimental. Pinescript implementation of Decimal to Binary and Binary to Decimal that is intended for use in the development of a neural network proof of concept. Intended for use in as subcomponent in the development of a more complex/highly experimental prototype. Protection/logic for edge cases above 11111111/255 (8bits) is NOT implemented. Do NOT use this in any trading system or component without edge case testing/unit tests. // Decimal to Binary, Binary to Decimal Reference: // diwasfamily.com // www.wikihow.com // // www.khanacademy.org
Chỉ báo
của UnknownUnicorn2796841
Bitcoin Logarithmic Growth CurvesThis plots logarithmic curves fitted to major Bitcoin bear market tops & bottoms. Top line is fitted to bull tops, bottom line is fitted to lower areas of the logarithmic price trend (which is not always the same as bear market bottoms). Middle line is the median of the top & bottom, and the faded solid lines are fibonacci levels in between. Inspired by & based on a Medium post by Harold Christopher Burger, which shows how linear Bitcoin's long-term price growth is when plotted on a double-log chart (log scaling on the price AND time axis). These curves will only make sense for tickers representing Bitcoin vs. USD (such as BITSTAMP:BTCUSD, BITMEX:XBTUSD, BLX index). Plotting on other assets will probably end up with lines that shoot off into space without any relationship to the underlying price action. The upper, middle & lower curves can be projected into the future, which can be turned on or off in the indicator settings. The fibonacci levels can also be switched on/off. And the upper & lower curve intercepts & slopes can be tweaked. I'm releasing this open-source, if you end up making something cool based off of this code, I don't need attribution but please hit me up on here or on twitter (same username) so I can check out what ya made. Thanks, hope y'all enjoy it.
Chỉ báo
của quantadelic
49
Center of Gravity BF 🚀Thanks to HPotter for the code I based this strategy on. Center of Gravity calculation is based here on a linear regression function using the least squares method. We use this to calculate a channel consisting of 2 lines, green and red on the chart This strategy employs a dynamic stop loss function that measures stop loss placement based on recent ATR. How signals are generated: Price closes above green line = Go Long Price closes below red line = Go Short Yellow dotted line = stop loss based on long entry Orange dotted line = stop loss based on short entry INSTRUCTIONS Green background = Go Long, put your stop loss at the yellow dotted line Red background = Go Short, put your stop loss at the orange dotted line NB: The stop losses printed on the chart are calculated from the point of entry on a trade, if you make a different entry to what is indicated, the corresponding stop loss will be different to what the indicator displays.
Chiến lược
của bennef
2
Regression Channel [DW]This is an experimental study which calculates a linear regression channel over a specified period or interval using custom moving average types for its calculations. Linear regression is a linear approach to modeling the relationship between a dependent variable and one or more independent variables. In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. The regression channel in this study is modeled using the least squares approach with four base average types to choose from: -> Arnaud Legoux Moving Average (ALMA) -> Exponential Moving Average (EMA) -> Simple Moving Average (SMA) -> Volume Weighted Moving Average (VWMA) When using VWMA, if no volume is present, the calculation will automatically switch to tick volume, making it compatible with any cryptocurrency, stock, currency pair, or index you want to analyze. There are two window types for calculation in this script as well: -> Continuous, which generates a regression model over a fixed number of bars continuously. -> Interval, which generates a regression model that only moves its starting point when a new interval starts. The number of bars for calculation cumulatively increases until the end of the interval. The channel is generated by calculating standard deviation multiplied by the channel width coefficient, adding it to and subtracting it from the regression line, then dividing it into quartiles. To observe the path of the regression, I've included a tracer line, which follows the current point of the regression line. This is also referred to as a Least Squares Moving Average (LSMA). For added predictive capability, there is an option to extend the channel lines into the future. A custom bar color scheme based on channel direction and price proximity to the current regression value is included. I don't necessarily recommend using this tool as a standalone, but rather as a supplement to your analysis systems. Regression analysis is far from an exact science. However, with the right combination of tools and strategies in place, it can greatly enhance your analysis and trading.
Chỉ báo
của DonovanWall
20
Linear Regression Trend ChannelThis is my first public release of indicator code and my PSv4.0 version of "Linear Regression Channel", as it is more commonly known. It replicates TV's built-in "Linear Regression" without the distraction of heavy red/blue fill bleeding into other indicators. We can't fill() line.new() at this time in Pine Script anyways. I entitled it Linear Regression Trend Channel, simply because it seems more accurate as a proper description. I nicely packaged this to the size of an ordinary napkin within 20 lines of compact code, simplifying the math to the most efficient script I could devise that fits in your pocket. This is commonly what my dense intricate code looks like behind the veil, and if you are wondering why there is no notes, that's because the notation is in the variable naming. I excluded Pearson correlation because it doesn't seem very useful to me, and it would comprise of additional lines of code I would rather avoid in this public release. Pearson correlation is included in my invite-only advanced version of "Enhanced Linear Regression Trend Channel", where I have taken Linear Regression Channeling to another level of fully featured novel attainability using this original source code. Features List Includes: "Period" adjustment "Deviation(s)" adjustment "Extend Method" option to extend or not extend the upper, medial, and lower channeling Showcased in the chart below is my free to use "Enhanced Schaff Trend Cycle Indicator", having a common appeal to TV users frequently. If you do have any questions or comments regarding this indicator, I will consider your inquiries, thoughts, and ideas presented below in the comments section, when time provides it. As always, "Like" it if you simply just like it with a proper thumbs up, and also return to my scripts list occasionally for additional postings. Have a profitable future everyone!
Chỉ báo
của ImmortalFreedom
22
Time Series ForecastIntroduction Forecasting is a blurry science that deal with lot of uncertainty. Most of the time forecasting is made with the assumption that past values can be used to forecast a time series, the accuracy of the forecast depend on the type of time series, the pre-processing applied to it, the forecast model and the parameters of the model. In tradingview we don't have much forecasting models appart from the linear regression which is definitely not adapted to forecast financial markets, instead we mainly use it as support/resistance indicator. So i wanted to try making a forecasting tool based on the lsma that might provide something at least interesting, i hope you find an use to it. The Method Remember that the regression model and the lsma are closely related, both share the same equation ax + b but the lsma will use running parameters while a and b are constants in a linear regression, the last point of the lsma of period p is the last point of the linear regression that fit a line to the price at time p to 1, try to add a linear regression with count = 100 and an lsma of length = 100 and you will see, this is why the lsma is also called "end point moving average". The forecast of the linear regression is the linear extrapolation of the fitted line, however the proposed indicator forecast is the linear extrapolation between the value of the lsma at time length and the last value of the lsma when short term extrapolation is false, when short term extrapolation is checked the forecast is the linear extrapolation between the lsma value prior to the last point and the last lsma value. long term extrapolation, length = 1000 short term extrapolation, length = 1000 How To Use Intervals are create from the running mean absolute error between the price and the lsma. Those intervals can be interpreted as possible support and resistance levels when using long term extrapolation, make sure that the intervals have been priorly tested, this mean the intervals are more significants. The short term extrapolation is made with the assumption that the price will follow the last two lsma points direction, the forecast tend to become inaccurate during a trend change or when noise affect heavily the lsma. You can test both method accuracy with the replay mode. Comparison With The Linear Regression Both methods share similitudes, but they have different results, lets compare them. In blue the indicator and in red a linear regression of both period 200, the linear regression is always extremely conservative since she fit a line using the least squares method, at the contrary the indicator is less conservative which can be an advantage as well as a problem. Conclusion Linear models are good when what we want to forecast is approximately linear, thats not the case with market price and this is why other methods are used. But the use of the lsma to provide a forecast is still an interesting method that might require further studies. Thanks for reading !
Chỉ báo
của alexgrover
24
[RD] LCS - line channels (basic) v3 - [republish]================================================================== July 18 2019 - LCS - line channels (basic) by RootDuk Version : v3 - read the notes ================================================================== Easy script to draw channels based on ie. GANN using the following input params - ibback : barsback to search for high and low - ffactor : factor to up/downscale the lines - oextend : extend lines, left, right, both, none - bshowline : show horizontal lines yes/no - bsshowdown : show diag down lines yes/no - bsshowup : show diag up lines yes/no - bshowindm : show index marker, where is you current ibback =================================================================== Notes =================================================================== When you use this code, pls let me know where and how you used it as iam always curious what some can do with it. Thanks! =================================================================== Updates =================================================================== v1 v2 - July 17 2019 - Removed support wallets from source code. I think the source - has been deleted because of this, find no other clue. v3 - July 18 2019 - Republish
Chỉ báo
của RootDuk
9