2024-05-03 Naira News
2024-05-02
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 in the Exchange Rate
Considering the data presented, the general trend appears to show minimal variation for quite some time, with a slight increase in the latter part of the time series. For the majority of the period in question, the exchange rate remained at 0.00098, and around the timestamp of 2024-05-02 03:25:02, it started to increase to 0.00099 and then to 0.001. This trend indicates that there has been a gradual appreciation of GPB against NGN over this period.
Seasonality or Recurring Patterns
With regard to seasonality and recurring patterns, the dataset does not appear long enough to draw any conclusions about long-term or annual seasonality, which usually requires several years of data. However, no daily cyclical patterns could be observed either. The data seems to reflect a largely static exchange rate with a sudden rise around the end of the period, reverting to the previous rate at the end.
Notable Outliers in the Dataset
Based on the provided data, there may not be any significant outliers, given that the provided exchange rates remained between 0.00098 and 0.001. There is no instance where the exchange rate differs significantly from what is expected based on the small variations in the data. Considering this, no outliers can be presently identified in the timeseries.
Consideration of External Events
The analysis of the data was done without considering specific external events or factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports, in accordance with the guidelines provided.
In summary, the provided timeseries reflects a relatively invariant exchange rate for the most part with subtle increases near the later timestamps. For a comprehensive understanding of the reasons behind these fluctuations or stagnant nature, a more in-depth, holistic analysis may be required, incorporating larger datasets and potentially considering external factors.