Non-repainting — Indicators and Strategies

HKM - Renko Emulator with EMA Trend This is a Renko based Emulator to plot on any chart type which prints the box as printed on a Renko charts and is a Non-Repaint version. You can use either Traditional or ATR Method on current chart Timeframe. Option to plot an EMA Line is provided with Trend indication.

Smoothing R-Squared Comparison Introduction Heyo guys, here I made a comparison between my favorised smoothing algorithms. I chose the R-Squared value as rating factor to accomplish the comparison. The indicator is non-repainting. Description In technical analysis, traders often use moving averages to smooth out the noise in price data and identify trends. While moving averages are a useful tool, they can also obscure important information about the underlying relationship between the price and the smoothed price. One way to evaluate this relationship is by calculating the R-squared value, which represents the proportion of the variance in the price that can be explained by the smoothed price in a linear regression model. This PineScript code implements a smoothing R-squared comparison indicator. It provides a comparison of different smoothing techniques such as Kalman filter, T3, JMA, EMA, SMA, Super Smoother and some special combinations of them. The Kalman filter is a mathematical algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement. The input parameters for the Kalman filter include the process noise covariance and the measurement noise covariance, which help to adjust the sensitivity of the filter to changes in the input data. The T3 smoothing technique is a popular method used in technical analysis to remove noise from a signal. The input parameters for the T3 smoothing method include the length of the window used for smoothing, the type of smoothing used (Normal or New), and the smoothing factor used to adjust the sensitivity to changes in the input data. The JMA smoothing technique is another popular method used in technical analysis to remove noise from a signal. The input parameters for the JMA smoothing method include the length of the window used for smoothing, the phase used to shift the input data before applying the smoothing algorithm, and the power used to adjust the sensitivity of the JMA to changes in the input data. The EMA and SMA techniques are also popular methods used in technical analysis to remove noise from a signal. The input parameters for the EMA and SMA techniques include the length of the window used for smoothing. The indicator displays a comparison of the R-squared values for each smoothing technique, which provides an indication of how well the technique is fitting the data. Higher R-squared values indicate a better fit. By adjusting the input parameters for each smoothing technique, the user can compare the effectiveness of different techniques in removing noise from the input data. Usage You can use it to find the best fitting smoothing method for the timeframe you usually use. Just apply it on your preferred timeframe and look for the highlighted table cell. Conclusion It seems like the T3 works best on timeframes under 4H. There's where I am active, so I will use this one more in the future. Thank you for checking this out. Enjoy your day and leave me a like or comment. 🧙‍♂️ --- Credits to: ▪@loxx – T3 ▪@balipour – Super Smoother ▪ChatGPT – Wrote 80 % of this article and helped with the research

VHF Adaptive Linear Regression KAMA Introduction Heyo, in this indicator I decided to add VHF adaptivness, linear regression and smoothing to a KAMA in order to squeeze all out of it. KAMA: Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low. KAMA will adjust when the price swings widen and follow prices from a greater distance. This trend-following indicator can be used to identify the overall trend, time turning points and filter price movements. VHF: Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length. Linear Regression Curve: A line that best fits the prices specified over a user-defined time period. This is very good to eliminate bad crosses of KAMA and the pric. Usage You can use this indicator on every timeframe I think. I mostly tested it on 1 min, 5 min and 15 min. Signals Enter Long -> crossover(close, kama) and crossover(kama, kama ) Enter Short -> crossunder(close, kama) and crossunder(kama, kama ) Thanks for checking this out! -- Credits to ▪️@cheatcountry – Hann Window Smoohing ▪️@loxx – VHF and T3 ▪️@LucF – Gradient

Chandelier Exit ZLSMA Strategy Introduction Heyo guys, I recently checked out some eye-catching trading strategy videos on YT and found one to test. This indicator is based on the video. Usage The recommended timeframe is 5 min. Signals Long Entry => L Label Price crosses above ZLSMA and Chandelier Exit shows Buy Long Exit => green circle Price crosses below ZLSMA Short Entry => S Label Price crosses below ZLSMA and Chandelier Exit shows Sell Short Exit => orange circle Prices crosses above ZLSMA Ty for checking this out. Enjoy! -- Credits to @netweaver2011 - ZLSMA @everget – Chandelier Exit

Adaptive Fisherized KST Introduction Heyo guys, here is a new adaptive fisherized indicator of me. I applied Inverse Fisher Transform, Ehlers dominant cycle analysis, smoothing and divergence analysis on the Know Sure Thing (KST) indicator. Moreover, the indicator doesn't repaint. Usage I didn't backtest the indicator, but I recommend the 5–15 min timeframe. It can be also used on other timeframs, but I have no experience with that. The indicator has no special filter system, so you need to find an own combo in order to build a trading system. A trend filter like KAMA or my Adaptive Fisherized Trend Intensity Index could fit well. If you find a good combo, let me know it in the comments pls. Signals Zero Line KST crossover 0 => Enter Long KST crossunder 0 => Enter Short Cross KST crossover KST MA => Enter Long KST crossunder KST MA => Enter Short Cross Filtered KST crossover KST MA and KST above 0 => Enter Long KST crossunder KST MA and KST under 0 => Enter Short KST crossunder 0 => Exit Long KST crossover 0 => Exit Short More to read: KST Explanation Enjoy and let me know your opinion! -- Credits to - @tista - @blackcat1402 - @DasanC - @cheatcountry

Adaptive Fisherized Stochastic Center of Gravity Introduction I modified the script "Fisher Stochastic Center of Gravity" of @DasanC for this indicator. I added inverse Fisher transform, cycle period adaptiveness mode (Ehlers) and smoothing to it. Moreover, I added buy and sell and beautified some stuff. Lastly, it is also non-repainting! Usage This indicator can be used like a normal stochastic, but I don't recommend divergence analysis on it. That fisherization stuff seems to make the graphs unuseable for that because it tries. It works well on every timeframe I would say, but lower timeframes are recommended, because of the fast nature of stochastic. Usually it does a good job on entry confirmation for reversals and trend continuation trades. Recommended indicator to combine with this indicator is RSI cyclic smoothed v2 . This is the best RSI version I know. In trending market it is recommended to look more on the inner bands and in flat market it is recommended to look more on the outer bands. When RSI shows oversold and this indicator shows a crossover of the Center of Gravity plot through the bottom line -> Long entry is confirmed When RSI shows overbought and this indicator shows a crossunder of the Center of Gravity plot through the top line -> Short entry is confirmed Settings The adaptive mode is enabled by default to give you straight the whole indicator experience. The default settings are optimized, but should be changed depending on the market. An example: Market has a low volatility and a high momentum -> I want a slower/higher length to catch the slower new highs and lows. Market has higher volatility and a low momentum, -> I want a faster/lower length to catch the faster new highs and lows Signals Crossover Buy -> cog crossover signalLine Sell -> cog crossunder signalLine Overbought/Oversold Crossover Buy -> cog crossover lowerBand Sell -> cog crossunder lowerBand I use this indicator a lot, because I don't know a better stochastic on this community here. @DasanC did an awesome work with his version I used as base for this script. Enjoy this indicator and let the profit roll! 🔥

Candlestick OB Finder Introduction Hello, this here is a non-repainting candlestick indicator which is able to detect OB looking candlestick formations. Usage It can be used to confirm entries, but be aware that it produces a lot of false signals. Somehow the swings tend to reverse at these points. I recommend the 10–15 minutes timeframe. I hope you enjoy this small indicator. :)