2024-05-01 Sudanese Pound News
2024-04-30
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Overview of the Trend
The data provided follows the changes in exchange rates from the 30th of April, 2024. The range of data points allows for the following analysis:
- From the beginning of the dataset to the end, it's seen that there is a minor increase in the exchange rate. The rate starts at 0.00233 at 00:00:02. It experiences a slight increase, hitting a peak value of 0.00235 at 08:50:03, and this value is maintained through the rest of the data points.
Seasonality and Recurring Patterns
As this is time-series data, identifying patterns and trends emerging over specific periods is crucial. However, the data does not indicate strong seasonality given the narrow range. The rate generally appears relatively stable across the recorded timestamps.
Outliers and Schedule Anomalies
In the given data set, no obvious outliers or unexpected variabilities in the exchange rate can be observed, which is unusual for financial data. The rate instead remains quite stable at 0.00235 from 08:50:03 onwards.
This stability could indicate a lack of significant market influences during this period.
Final Thoughts
This analysis provides a basic understanding of the dataset's patterns. The exchange rate appears to be relatively stable with minor fluctuations. However, without considering events such as market closing/opening hours, weekends/holidays, or the release of significant financial news and reports, the results could be deemed incomplete by some financial analysts. Such events typically have direct impacts on exchange rates.
Overall, the rate's stability stands as a notable feature within the given data set. Forecasting future rates would require additional details, including a broader data set and consideration of external factors that could impact the rates to ensure the accuracy of the forecast model.