2024-04-26 Syrian Pound News
2024-04-25
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
1. Overall Trend Analysis
The data provided spans a full day of exchange rates given at 5-minute intervals. Upon observing the dataset, it's noteworthy that the exchange rate remained constant at a value of 0.00054 from the start of the day till around 07:30:04. After that, the exchange rate increased slightly to 0.00055 and remained at that value for a significant portion of the remainder of the day. However, at 11:10:03 it decreased back to 0.00054 where it remained stable till the end of the day. Thus, the overall trend shows that the exchange rates remained remarkably stable throughout the day with minor fluctuation seen in the morning hours.
2. Seasonality and Recurring Patterns
Given the one-day range of the data provided, there doesn't appear to be any clear seasonal trends in this dataset. An analysis of longer-term data would be required to identify potential seasonality or recurring patterns in the exchange rates—for example, over multiple months or years. However, the minor fluctuation in the morning could hint at a possible influence of market opening times or other events early in the day, and further inspection over a longer period might shed light on this.
3. Outliers and Volatility
In the data presented, there are no noticeable outliers—instances where the exchange rate significantly deviates from the established pattern. The rates stayed within the narrow range between 0.00054 and 0.00055 throughout the day. This suggests a very low level of volatility in the exchange rate for this specific day, with a very minor increase observed in the morning before returning to the initial rate.
In conclusion, given the parameters and constraints, the exchange rate displayed high stability with a minute elevation in the morning. However, we need to remember that this analysis is based on a single day's data, and as such, might not fully capture the regularity or stand-alone incidents over a longer timeframe.