2024-04-29 Qatari Rial News
2024-04-28
Summary of Last Week
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Comprehensive Analysis
Based on the provided data, the following is a detailed analysis highlighting the overall trend, seasonality and outliers in the QAR exchange rates over the given time period.
1. Overall Trend
The overall trend of the exchange rate seems more volatile than stable during the period under review. The rate began at 0.37229 on 29th March 2024 and ended at 0.37510 on 26th April 2024, showing a slight increase over the course of about a month. However, there were several fluctuations throughout this period, with the rate rising and falling multiple times. Thus, it doesn't follow a steadily increasing or decreasing trend.
2. Seasonality
The dataset does not immediately show strong trends of seasonality or recurring patterns. Given that the timestamps are in increments of a few hours, regular daily patterns might be obscured. More granular data (with more frequent time intervals) might reveal daily fluctuations related to market opening and closing times. At the same time, due to the volatile nature of the exchange rate observed throughout this period, it's hard to spot a clear-cut seasonal pattern.
3. Outliers
At first glance, a large drop in the exchange rate on April 3rd and 4th from about 0.372 to around 0.370 may be considered an outlier as it signifies a sudden drop when compared to the surrounding data points. There are also significant fluctuations towards the end of this series with the rate rising to 0.37853 on April 12th, dropping to 0.37719 on the 19th, and then rising again to 0.37984 on the 16th. These peaks and troughs could be surprising based on the broad trend analysis and may be considered outliers.
However, the very definition of 'outliers' depends on the characteristics of the time series in question and the context. In the absence of any concrete information about standard deviations of the changes, or other statistical metrics, these supposed outliers are based on descriptive observations rather than stringent statistical definitions.