2024-04-22 Latvian Lats News
2024-04-21
Summary of Last Week
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
1. Understanding Overall Trend
From a high-level observation, the exchange rate data show a somewhat fluctuating pattern with both increasing and decreasing trends within the given period. The value at the earliest date is 2.24222 and it gradually increases over time to reach a peak of 2.28623. However, after reaching this peak, it shows a general downward trend until it stabilizes towards the most recent data points. The overall direction of the trend suggests a modest increase in the long term.
2. Identifying Seasonality
Within the given data, it is challenging to definitively identify any seasonality or recurring patterns just based on the raw numbers. This is because the data is limited and does not cover a sufficient length of time (e.g. multiple years) to establish clear seasonal trends. However, if we partition the data to smaller time frames, some repeated patterns might become apparent. For instance, there might be intra-day patterns that appear when the market is open. Nevertheless, without further information or context, making definitive claims on seasonality is difficult.
3. Noting Outliers
Identifying outliers within this data set can be difficult without applying statistical analysis. One way to identify potential outliers would be by looking for the highest and lowest points and their deviation from the general trend. For example, on 2024-04-10, the exchange rate jumps to 2.2563, which seems to be a significant increase from the previous data point. On another occasion, the exchange rate falls to 2.22909 on 2024-04-04, which also is a significant deviation from its previous value. These could be potential outliers, but further statistical analysis would be required to definitively categorise these instances as outliers.
