AI-Bank-Nifty Tech Analysis

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This code is a TradingView indicator that analyzes the Bank Nifty index of the Indian stock market. It uses various inputs to customize the indicator's appearance and analysis, such as enabling analysis based on the chart's timeframe, detecting bullish and bearish engulfing candles, and setting the table position and style.

The code imports an external script called BankNifty_CSM, which likely contains functions that calculate technical indicators such as the RSI, MACD, VWAP, and more. The code then defines several table cell colors and other styling parameters.

Next, the code defines a table to display the technical analysis of eight bank stocks in the Bank Nifty index. It then defines a function called get_BankComponent_Details that takes a stock symbol as input, requests the stock's OHLCV data, and calculates several technical indicators using the imported CSM_BankNifty functions.

The code also defines two functions called get_EngulfingBullish_Detection and get_EngulfingBearish_Detection to detect bullish and bearish engulfing candles.

Finally, the code calculates the technical analysis for each bank stock using the get_BankComponent_Details function and displays the results in the table. If the engulfing input is enabled, the code also checks for bullish and bearish engulfing candles and displays buy/sell signals accordingly.

The FRAMA stands for "Fractal Adaptive Moving Average," which is a type of moving average that adjusts its smoothing factor based on the fractal dimension of the price data. The fractal dimension reflects self-similarity at different scales. The FRAMA uses this property to adapt to the scale of price movements, capturing short-term and long-term trends while minimizing lag. The FRAMA was developed by John F. Ehlers and is commonly used by traders and analysts in technical analysis to identify trends and generate buy and sell signals. I tried to create this indicator in Pine.

In this context, "RS" stands for "Relative Strength," which is a technical indicator that compares the performance of a particular stock or market sector against a benchmark index.

The "Alligator" is a technical analysis tool that consists of three smoothed moving averages. Introduced by Bill Williams in his book "Trading Chaos," the three lines are called the Jaw, Teeth, and Lips of the Alligator. The Alligator indicator helps traders identify the trend direction and its strength, as well as potential entry and exit points. When the three lines are intertwined or close to each other, it indicates a range-bound market, while a divergence between them indicates a trending market. The position of the price in relation to the Alligator lines can also provide signals, such as a buy signal when the price crosses above the Alligator lines and a sell signal when the price crosses below them.

In addition to these, we have several other commonly used technical indicators, such as MACD, RSI, MFI (Money Flow Index), VWAP, EMA, and Supertrend. I used all the built-in functions for these indicators from TradingView. Thanks to the developer of this TradingView Indicator.

I also created a BankNifty Components Table and checked it on the dashboard.
Informacje o Wersji:
This passage is describing a recent update to a piece of code that now includes a new feature called CPMA (Conceptive Moving Average), which has been developed specifically for analyzing trends. With this script, users have the ability to analyze one or multiple stocks, including BankNifty and Nifty. Additionally, the script has a new tool that uses CPMA to detect bullish and bearish trends, which are then displayed in a table that can be customized with different colors and sizes. The table can also be hidden or positioned in different locations on the chart. To further enhance the analysis and display, the script also provides various inputs that can be customized according to the user's preferences.

This passage acknowledges the use of an inbuilt script for candlestick pattern detection by Tradingview and expresses gratitude towards the developers. I do some modification in the script to suit trend needs and improve its accuracy.
Informacje o Wersji:
I have incorporated some significant updates into the existing code. Now, in addition to the previous functionalities, the code includes the following:

SGX Nifty: The code now tracks the Nifty gap and gap down by utilising SGX Nifty. SGX Nifty is a derivative of the Indian Nifty index that trades on the Singapore Exchange. It allows traders to anticipate the opening direction of the Nifty index before the Indian markets open.

DOW Jones: To consider the global impact on BankNifty, the code now takes into account the movements of the DOW Jones index. DOW Jones is a widely followed stock market index in the United States that reflects the performance of 30 major American companies. Analysing its trends can provide insights into the potential effect on BankNifty.

India VIX: The code now incorporates the India VIX (Volatility Index) for market trend analysis. India VIX measures the expected volatility in the Indian stock markets over the next 30 days. By considering the VIX, the code aims to gauge the sentiment and volatility in the market, which can be valuable for decision-making.

Additionally, inspired by an idea from LUX ALGO, I have implemented a visually appealing feature using gradient colors. This visual gradient display adds an intuitive element to the output, making it easier to interpret the results.

I would like to express my gratitude to LUX ALGO for their insightful idea regarding the visual gradient display. Their contribution has enhanced the overall functionality of the code. With these updates, the code now offers a comprehensive analysis of the market by incorporating SGX Nifty, DOW Jones, India VIX, and a visually appealing representation of the data. Thank you!"
Skrypt open-source

Zgodnie z prawdziwym duchem TradingView, autor tego skryptu opublikował go jako open-source, aby traderzy mogli go zrozumieć i zweryfikować. Brawo dla autora! Możesz używać go za darmo, ale ponowne wykorzystanie tego kodu w publikacji jest regulowane przez Dobre Praktyki. Możesz go oznaczyć jako ulubione, aby użyć go na wykresie.

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