2024-04-19 Moldovan Leu News
2024-04-18
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 Analysis
The currency exchange rates show a pattern of fluctuation with a downward trend overall. The value of the exchange rate at the start of the data series is 0.0772. This rate gradually decreases until it reaches a rate of 0.07671 towards the end of the given time period. It is necessary to note that the decrease is not linear, there are periods of both rise and fall within the interval, however from a comprehensive view, the decrease is more prevalent.
Seasonality and Recurring Patterns
This dataset doesn't exhibit an obvious seasonality or recurring pattern at first glance due to the relatively short time period and small fluctuations in the exchange rate. However, there seem to be some periods of relative stability where the exchange rate remains more or less stable. These periods are often followed by slight drops in the exchange values. More dataset would be required for the identification of recurring patterns across a longer timeline.
Outliers Identification
Barring a few exceptions, the exchange rate does not show extreme fluctuations. The outliers are not significantly different from the rest of the data in order to be classified as strong anomalies. They can be seen at various points like a drop to 0.07675 at time 2024-04-18 20:15:03 and a rise to 0.07698 at time 2024-04-18 12:25:03 but they quickly revert back to the slight fluctuating pattern that is seen throughout this dataset. It's therefore reasonable to infer that such minor fluctuations are common in this dataset and are not significantly divergent from the usual trend.
Conclusion
In conclusion, the MDL exchange rates from the given dataset shows a slight overall decrease within the given timeframe with periods of stability followed by minor dips as a recurring pattern. Extreme fluctuations, or outliers, are rare and quickly revert back to the common trend. Overall, the rates seem to be remarkably stable. It is however recommended to perform a similar analysis on a larger dataset for more accurate pattern recognition and forecasting.