2024-04-19 Latvian Lats 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 of the Exchange Rates
Analyzing the dataset provides a clear understanding of the trend in exchange rates. The exchange rate started at a value of 2.27396 and ended at 2.27806, indicating a slight overall increase during this period. However, it is essential to note that the rate fluctuation was not monotonic. There were several periods of both significant increases and drops throughout the observed timestamps. Therefore, even though there's an overall increase, the trend isn't strictly rising but rather wavy, with values rising and falling intermittently.
Seasonality or Recurring Patterns
Considering the dataset provided and without making any contextual assumptions regarding the specific timing of the timestamps, it's challenging to accurately identify any clear seasonality or recurring patterns in the changes of exchange rates. To establish a clear pattern or seasonality, a more extended and comprehensive dataset would be advantageous, perhaps encompassing a whole year or multiple years, and comprising specific days (like weekends and weekdays) or specific times (like market opening and closing hours). Considering these factors can help in establishing any repetitiveness or pattern in the data trends.
Identification of Outliers
In the dataset provided, determining any significant outliers is challenging due to the size and limited scope of data. An outlier analysis would consider values that are disproportionately higher or lower compared to the majority of the dataset. However, in this case, the variations, although present, don't seem too drastic in the context of the entire dataset. The data fluctuates within a relatively narrow range, and it seems there are no extreme jumps or drops in the exchange rate that would qualify as significant outliers. It is worth noting though that such analysis is generally better performed using dedicated statistical tools that can plot and visualize the data for easier recognition of outliers.