2024-05-22 Lithuanian Litas 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
Understanding the overall trend of the exchange rates
Looking at the dataset provided, it appears that the LTL exchange rate initially remains relatively stable, with very slight fluctuations between 0.46182 and 0.46113. However, after the timestamp '2024-05-21 07:35:03', the exchange rate begins to rise, peaking at 0.46295, which indicates an upward trend for a short period of time. Afterwards, the exchange rate decreases slightly, stabilizing around the 0.4623 mark for the latter part of the dataset.
Identifying any seasonality or recurring patterns in the changes of exchange rates
Identifying seasonality or reoccurring patterns in time-series data requires a cyclical pattern to repeat over a specific period. In this dataset, as it covers only a single day's worth of data, it does not provide sufficient information to identify any seasonal pattern or to make conclusions about recurring patterns beyond this particular day. Research over a longer period of time would be necessary to identify if any weekly, monthly, or annual patterns exist.
Noting any outliers, or instances where the exchange rate differs significantly from what would be expected based on the trend or seasonality
An outlier within the dataset is the reading at '2024-05-21 07:35:03', where the LTL exchange rate increased significantly to 0.46216 from the previous 0.46129. After that, the reading at '2024-05-21 08:05:03' further peaked at 0.46295, deviating from the normal slight fluctuations observed in this data. After reaching this peak, the data does not return to the range seen prior, but instead stabilises at a slightly higher level around 0.462. It's worth noting that without further context or information about possible causes for these jumps, these are mere observations, but these points significantly deviate from the overall trend within this dataset.