2024-05-03 Romanian Leu 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
After analyzing the provided time-series data for exchange rates, it can be seen that the rates do not show a clear pattern of increase or decrease. Instead, they appear to fluctuate within a particular range from approximately 0.2944 to approximately 0.2957. This suggests that the exchange rates remain relatively stable over the period for which data is provided.
Seasonality or Recurring Patterns
With respect to seasonality or recurring patterns, it's difficult to confirm such patterns within the dataset at hand without applying more complex analysis using statistical techniques. However, upon a preliminary view, no apparent hourly, daily, or monthly seasonality is readily discernible.
Outliers
Given that the exchange rate stays within a relatively narrow range throughout the dataset, most data points can be considered within the "normal" variance. Therefore, within this dataset, there doesn't appear to be any significant outliers, or instances where the exchange rate differs significantly from the overall trend.
External Factors
While external factors such as market opening/closing hours, weekends/holidays, and the release of key financial news and reports can significantly impact exchange rates, this analysis is based solely on the provided dataset, which does not include these variables. As such, this analysis does not consider the potential impact of these factors.
In conclusion, this dataset suggests that the RON exchange rate remained within a specific range during the stipulated time period without any considerable perturbations. Statistically based time-series analysis methods could further confirm any potential seasonal patterns or recurring trends. To better forecast future rates and elucidate the influence of external factors, tracking those factors would be essential in conjunction with more complex predictive modeling techniques.