A script has been developed to calculate autocorrelation and partial autocorrelation functions, displaying results graphically. Key input parameters include:

1. N: Data window for calculation, where a default value of 100 is set. Capable of handling large datasets, it efficiently processes over 100,000 bars.

2. K: Number of lags for analysis, defaulted at 16. Typically, analysis remains effective with lags under 40, though the script supports up to 500.

3. start_pos: Defines data window offset, with zero indicating calculations start from the latest loaded bar.

4. duration: Chart display period, set for 10 seconds.

These settings facilitate comprehensive time series analysis, enabling efficient examination of large datasets for technical insights. Adjust parameters according to specific analysis needs.

👉 Read | Calendar | @mql5dev

#MQL5 #MT5 #script

Recent evaluations have highlighted performance and accuracy issues with the standard API functions ChartXYToTimePrice and ChartTimePriceToXY. ChartXYToTimePrice fails to function correctly when X and Y parameters fall outside the visible chart window, defaulting to zero values. Additionally, ChartTimePriceToXY experiences inaccuracies in certain scenarios. Both functions exhibit slow performance.

To address these issues, a revised script demonstrates improved accuracy across all parameter ranges. It utilizes a method where X and Y coordinates are translated to time and price and then reverted back. Accuracy is validated if input coordinates match the output. A discrepancy indicates functional errors, notating the issue during execution. The script concludes by reporting the final outcome, remaining silent if functionality is assured.

👉 Read | AppStore | @mql5dev

#MQL5 #MT5 #script