2024-05-22 Libyan Dinar News
2024-05-21
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 of Exchange Rates
The dataset spans through a day's worth of exchange rate data for LYD. Throughout the day, the rates largely fluctuated between 0.2815 and 0.2825. There were instances of slight dips and rises; however, there is no clear increasing or decreasing trend discernible from the data. It can be assumed that the rates mostly remained stable throughout the given period.
Seasonality or Recurring Patterns
Time-series data can often show seasonality where certain patterns recur at regular intervals. However, in the dataset provided, there don't seem to be any noticeable recurring patterns on an hourly basis. Therefore, this data could be considered as non-seasonal.
Identification of Outliers
An outlier in time-series data is a data point that differs significantly from other observations. Generally, these are unexpected spikes or dips. Here, looking at the data, most fluctuations are within a relatively tight range. A few notable exceptions include instances where the rate dipped to its lowest at 0.2815, or when it spiked to its highest at around 0.2826. Depending on the context and threshold set for defining an outlier, these instances may be considered as outliers since they deviate significantly from the average exchange rate.
However, it is essential to note that the presence of these outliers does not necessarily imply that there is an issue with the data or the underlying system, but it could signal an area that might warrant further investigation. In this context, these could have been caused by a variety of factors such as sudden market movement, important financial news releases, among others.
Please be reminded that this is a high-level analysis, and for a comprehensive understanding of the data, we could employ sophisticated statistical models, considering more data and incorporating external market factors.
