2024-05-06 Belarussian Ruble News
2024-05-05
Summary of Last Week
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Analysis of the Exchange Rate (BYR) Dataset
The provided dataset exhibits a series of exchange rates (BYR) recorded at different timestamps. The data spans from April 5, 2024, to May 3, 2024. However, before proceeding with the analysis, it is essential to note that given dataset exhibits static value of exchange rate (7.0E-5) throughout the period. Despite the time series nature of the dataset, it offers limited inputs for comprehensive analysis because of this constant rate. Therefore, the interpretations provided here are solely based on the available data and do not consider external factors such as market opening/closing hours, weekends/holidays, or the release of key financial news and reports. Additionally, the analysis will not generate any forecast for future rates.
1. Overall Trend of the Exchange Rates
From the given dataset, it is clearly visible that the exchange rate is constant over the entire period. This means that there is no discernible increase or decrease in the exchange rates. The exchange rate remains stable at a value of 7.0E-5 from April 5, 2024, to May 3, 2024. Therefore, the overall trend can be classified as a horizontal trend with no specific decreasing or increasing pattern.
2. Seasonality or Recurring Patterns
Typically, in a variant dataset, seasonal patterns could be identified as regular fluctuations that occur periodically in a similar manner. Still, in the case of this dataset, since the exchange rate does not vary and remains constant throughout the period, no such seasonality or recurring patterns are evident in the data. Thus, there are no identifiable cyclical patterns or fluctuations apparent that could indicate any periodic behavior in the dataset.
3. Noting Any Outliers
An outlier is often understood as a data point that deviates significantly from the overall observations. Considering the given dataset, since all the data points are the same, 7.0E-5, there are no outliers. None of the entries deviate from this consistent figure. Hence, there are no noticeable anomalies or outliers within the provided exchange rate data series.
In conclusion, the dataset, despite its time variant nature, shows a lack of variance in terms of exchange rates. Hence, trend analysis, seasonal pattern identification, or outlier detection are not applicable in this scenario.