2024-04-24 Libyan Dinar News
2024-04-23
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
Based on the provided dataset, the LYD exchange rate depicts minor fluctuations over the time frame provided. To ascertain the precise trend - whether it's ascending, descending, or steady - calculating the average exchange rate change or visually graphing the rate over time would be beneficial. Nevertheless, no significant long-term incremental or decremental trends jump out from the data set.
Seasonality and Recurring Patterns
In the context of currency exchange rates, seasonality refers to predictable and recurring patterns or cycles that emerge over the course of the year. From the data provided, it's difficult to conclude decisively about the presence of seasonality. That said, no pronounced recurring patterns could be discerned directly from the raw data. For a more robust confirmation, advanced time-series analysis or decomposition methods may be employed to better spot any seasonal or cyclical patterns that aren't immediately apparent.
Outliers or Significant Rate Deviations
Outliers in a dataset are values that are notably different from most other values. For this dataset, the exchange rates don't demonstrate extreme variability: they fall in a relatively stable range. However, a more meticulous outlier detection would necessitate statistical analysis, such as establishing standard deviations or using methods like the IQR (Interquartile Range).
Although the provided dataset does not suggest drastic fluctuations in the exchange rate, it's imperative to remember that external factors significantly influence exchange rates. It includes factors like macroeconomic indicators, geopolitical events, and changes in the global marketplace. This simple data review disregards such external elements and focuses solely on the presented dataset.
