Many classic indicators such as MACD, RSI, EMA are basically a combination of "iron triangle" equipped by hand. The more advanced ones may be candle pattern analysis and Elliott wave theory. Today we are going to talk about trading strategies based on volatility and linear regression, as well as correlation coefficients. These indicators are easy to create in Pine, and I will be creating a volatility correlation-based indicator to publish to my public script library in the near future.
Trading strategies you may not have seen! Dry goods to share!
Enough talk, please see the picture
1. In the linear regression in the chart, I draw the Pearson correlation coefficient with a yellow circle, which proves that 93.95% of the price falls within the standard deviation of the standard deviation band of the upper and lower 2 (you can refer to the standard deviation concept of Bollinger Band, //For a normal distribution, within one standard deviation of plus or minus is 68.2%, plus or minus two standard deviations is 95.4%, plus or minus three standard deviations is a 99.6% confidence interval//See statistics)
2. The indicator in the side graph is based on Close to Close's historical volatility percentage (great idea by @Balipour) and its SMA line, please note that the part larger than the SMA line we call "mean reversion", smaller than the SMA line part of it is called "trends",
It can be seen that the price always fluctuates during "reversion to the mean", just like the volatility reading, the volatility is large but will eventually return to its *mean*, the part below the SMA is the "trend", which proves that the current market There is a "trend", which may be left or right trading, (the direction is clearly expressed in the linear regression)
3. The above two points can see whether the current market is "trend" or "mean reversion", then continue to look at the correlation coefficient in the sub-picture indicator. I will not repeat the principle. The source of the correlation coefficient is Close (close). price), the correlation is the historical volatility, 0 is the dividing line of the correlation coefficient, above 0 is a positive correlation, below 0 is a negative correlation, under a significant positive correlation, we describe the current market as a percentage of historical volatility is "mean reversion" It is still the fluctuation of the "trend" to operate. As can be seen in the figure, in the positive correlation fluctuation, we have captured a lot of trading signals.
Finally, thanks to TV for such excellent and powerful chart analysis software
Trading strategies you may not have seen! Dry goods to share!
Enough talk, please see the picture
1. In the linear regression in the chart, I draw the Pearson correlation coefficient with a yellow circle, which proves that 93.95% of the price falls within the standard deviation of the standard deviation band of the upper and lower 2 (you can refer to the standard deviation concept of Bollinger Band, //For a normal distribution, within one standard deviation of plus or minus is 68.2%, plus or minus two standard deviations is 95.4%, plus or minus three standard deviations is a 99.6% confidence interval//See statistics)
2. The indicator in the side graph is based on Close to Close's historical volatility percentage (great idea by @Balipour) and its SMA line, please note that the part larger than the SMA line we call "mean reversion", smaller than the SMA line part of it is called "trends",
It can be seen that the price always fluctuates during "reversion to the mean", just like the volatility reading, the volatility is large but will eventually return to its *mean*, the part below the SMA is the "trend", which proves that the current market There is a "trend", which may be left or right trading, (the direction is clearly expressed in the linear regression)
3. The above two points can see whether the current market is "trend" or "mean reversion", then continue to look at the correlation coefficient in the sub-picture indicator. I will not repeat the principle. The source of the correlation coefficient is Close (close). price), the correlation is the historical volatility, 0 is the dividing line of the correlation coefficient, above 0 is a positive correlation, below 0 is a negative correlation, under a significant positive correlation, we describe the current market as a percentage of historical volatility is "mean reversion" It is still the fluctuation of the "trend" to operate. As can be seen in the figure, in the positive correlation fluctuation, we have captured a lot of trading signals.
Finally, thanks to TV for such excellent and powerful chart analysis software