2024-04-30 Rwanda Franc News
2024-04-29
Summary of Last Month
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Analysis of RWF Exchange Rate Time Series Data
This dataset represents a time series data for the exchange rate of the RWF (Rwandan Franc) at different points of time. This analysis aims to give a comprehensive perspective on the trend, variability, and outliers in the data.
Observations on Overall Trend
The overall trend of the RWF exchange rate in the given dataset is remarkably stable. The data remains steady at an exchange rate of 0.00106 for the majority of the timestamps, indicating that there is no significant inflation or deflation during this period. There are only two fluctuations to an exchange rate of 0.00105, but the rate quickly returns to the baseline of 0.00106.
Identification of Seasonality or Recurring Patterns
Given the static nature of the dataset, where the exchange rate remains constant for most of the interval, it is challenging to identify any obvious seasonality or recurring patterns in the data. Seasonality typically involves regular and predictable changes in a time series that recur every calendar year. As there are no noticeable peaks and troughs in this dataset, there's no clear evidence of any seasonal influence or cyclical patterns.
Detection of Outliers
There are no instances in the data where the exchange rate strays far from the consistent figure of 0.00106, therefore, we cannot point out any outliers based on the given data. Only two instances where the rate drops to 0.00105 could be considered as momentary anomalies, but they would not typically be classified as significant outliers, given that they do not deviate drastically from the common value.
Summary
In conclusion, the Rwandan Franc demonstrated remarkable stability during the covered period, with very limited fluctuations. There is no observable seasonality pattern or striking outliers. For a more comprehensive analysis, it would be helpful to have data over a longer period or during a time of more significant economic changes.
