Discussing the article: "ARIMA Forecasting Indicator in MQL5"

New comment
 

Check out the new article: ARIMA Forecasting Indicator in MQL5.

In this article we are implementing ARIMA forecasting indicator in MQL5. It examines how the ARIMA model generates forecasts, its applicability to the Forex market and the stock market in general. It also explains what AR autoregression is, how autoregressive models are used for forecasting, and how the autoregression mechanism works.

The first part of the model is called autoregression. This beautiful word means a simple thing: today's price depends on yesterday's, the day before yesterday's, and so on. It's as if the market remembers its past and builds the future on its basis.

If EUR/USD has risen for three days in a row, there is a chance that it will rise tomorrow too. Not necessarily, but the trend may continue. The autoregressive part of the model captures these patterns by analyzing how much past values influence the current ones.

Math in simple words: imagine that you have the EUR/USD exchange rate for the last five days: 1.0800, 1.0825, 1.0850, 1.0875, 1.0900. Autoregression says: "Look, every day the exchange rate increased by about 25 points (0.0025), which means that tomorrow it will be around 1.0925." The model finds coefficients — numbers that show how strongly yesterday's price affects today's, the day before yesterday's on today's, and so on.

The formula looks something like this: tomorrow’s_price = 0.7 × today’s_price + 0.2 × yesterday’s_price + 0.1 × the day before yesterday’s_price. These coefficients 0.7, 0.2, 0.1 are selected by the model itself, analyzing the history. The higher the coefficient, the stronger the impact of this day on the forecast.


Author: Yevgeniy Koshtenko

 
The Renko and Arima merger should be more stable
 

Where is the differential part?

 
Hao T # :
Combining Renko and Arima should be more stable.

Yeah, I use it too.

New comment