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TradingView Pine Code for False Breakout Strategy
Explanation: 1. Parameters: – `window`: The rolling window period for calculating the highest high and lowest low. – `reversal_period`: The period over which to check for reversals to identify false breakouts. 2. Rolling High and Low Calculation: – `high_rolling` and `low_rolling` calculate the highest high and lowest low over the specified rolling…
Excel VBA Code For False Breakout Strategy
Explanation: 1. Rolling High/Low Calculation: Columns H (`High_Rolling`) and I (`Low_Rolling`) store the rolling high and low values over a 14-day window. 2. Breakout Detection: Columns J (`Breakout_High`) and K (`Breakout_Low`) store 1 if there is a breakout above the rolling high or below the rolling low, respectively. 3. False Breakout Detection: …
Tradingview.com Pine Code For Inside Bar Momentum Strategy
This script identifies buy and sell opportunities based on inside bar patterns and ensures that no consecutive buy or sell signals are generated. The signals are then plotted on the chart along with the support and resistance levels.
Fibonacci Retracement Algorithmic Trading Strategy
The Fibonacci Algorithmic Trading Strategy is a popular method among traders to identify potential support and resistance levels in the market. This strategy leverages Fibonacci retracement levels, which are derived from the Fibonacci sequence, a mathematical series where each number is the sum of the two preceding ones. Key levels, like 38.2%, 50%, and 61.8%,…
Testing for stationarity in time series – Algo Swing Trading
For a Time-Series to be classified as covariance Stationarity (weak stationarity), it must satisfy following 3 conditions It will not be surprising to say that Stationarity is a desired characteristic of time-series as it makes modeling and extrapolating (forcasting) into the future more feasible. It is because the stationarity is easier to predict than the…
Time Series Decomposition – Algo Swing Trading
Lets assume a time-series with a clear trend, can be increasing on decreasing. One of the option that we have is to remove/extract the trend component from the times series before modeling the remaining series. This will make the series stationary, and then we can add it back after the rest of the components have…