2024-05-08 Pula News
2024-05-07
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Overall Trend of Exchange Rates
The overall trend of the exchange rate of BWP over the period presented in this dataset exhibits a rather stable pattern, with small incremental increases and decreases. Specifically, the data begins at a rate of 0.10079 and ends at a rate of 0.10088, indicating modest fluctuations over this period.
Seasonality or Recurring Patterns
In terms of seasonality or recurring patterns, there seems to be no clear pattern within every 24-hour window - every day. The values don't exhibit a significant or consistent rise or drop at certain hours of the day. However, given the relatively small range of the exchange rates and limited data points, a more detailed time series analysis with more data over a longer time frame might be required to identify any significant seasonal patterns.
Outliers in the Exchange Rates
- There are a few instances where the exchange rate drops or increases slightly more than the usual rates, such as on 2024-05-07 06:25:02 where it drops to 0.10054 from the previous 0.10079, and on 2024-05-07 20:05:02 where it drops to 0.10078 from the previous 0.10096. However, these instances seem to correct themselves shortly after, moving back towards the average rate, and thus may be viewed as temporary market fluctuations rather than significant outliers.
- Otherwise, the dataset does not seem to include any significant outliers or extreme values that could significantly distort the data analysis. This implies that the exchange rate, despite minor fluctuations, remained relatively stable over the given period.
Overall, this analysis offers a granular view of the exchange rate of BWP at various points in time. It indicates that while there were minimal fluctuations in the exchange rate, the general trend was one of stability with no significant outliers or seasonal patterns evident within the data.