Moonhub Cycle Index

2023年4月15日

Moonhub Cycle Index is a composite index derived from three popular technical analysis indicators: Moving Average Convergence Divergence (MACD), Schaff Trend Cycle (STC), and Detrended Price Oscillator (DPO). The indicator is designed to help identify potential trends and market sentiment by combining the unique characteristics of each indicator.

Key components of the indicator include:

Input Parameters:
COEMA Length (len_DIema): The length of the Exponential Moving Average (EMA) applied to the Custom Index. Default is set to 9.
COSMA Length (len_DIsma): The length of the Simple Moving Average (SMA) applied to the Custom Index. Default is set to 30.

Indicators:
MACD: A momentum oscillator that shows the relationship between two moving averages of a security's price. It is calculated using the difference between the 12-period and 26-period EMA, and a 9-period EMA (signal line) of the MACD.
STC: A cyclic indicator that identifies cyclical trends in the market. It is calculated using the Stochastic oscillator formula applied to the close, high, and low prices over a 10-period lookback window.
DPO: A price oscillator that eliminates the trend from price data to focus on underlying cycles. It is calculated using a custom function that shifts the price by half the length and subtracts the SMA from the shifted price.

Custom Index: The composite index is calculated by taking the average of the MACD line, STC, and DPO.

COEMA and COSMA: Exponential and Simple Moving Averages applied to the Custom Index using the lengths specified by the input parameters (len_DIema and len_DIsma).

Plots: The Custom Index, COEMA, and COSMA are plotted with different colors and line widths to visualize their interaction and provide insights into potential market trends.

This Custom Index Indicator can be useful for traders who want to analyze the market using a combination of these indicators to make more informed decisions. It can also help identify potential trends and market sentiment by combining the unique characteristics of each indicator.