2024-05-06 Zloty News
2024-05-05
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
Understanding the overall trend
Based on the data provided, we can observe that the overall trend of the exchange rates is generally stable but tends to fluctuate slightly over the period shown. Initial values start around 0.34273 and see a progressive growth until it reaches its maximum value of 0.34658 on the 9th of April, 2024. However, there is then a gradual decrease until a value of 0.33605 on the 16th of April, 2024. For the remainder of the period, the exchange rate appears to oscillate between 0.339 and 0.338. It should be noted that these observations are not assessing any large-scale trends over extended periods, but rather small oscillations within the given timeframe.
Identifying Seasonality or Recurring Patterns
In terms of seasonality or recurring patterns, it is challenging to discern any distinct pattern within this dataset. This is due to the minute scale of changes and fluctuation in the exchange rates which makes it difficult to draw any definitive conclusions on any pattern or seasonal trends that occur daily, weekly, or monthly. However, one possible pattern that may be observed is the slight tendency for the exchange rate to decrease during the early part of the week (on Mondays and Tuesdays) while rising again towards the end (on Fridays). Again, this observation is tentative and requires additional data for confirmation.
Identifying Outliers
Regarding outliers in this dataset, it appears to be relatively consistent in its values with very few instances of significant deviation. The exchange rate stays within a relatively tight range, with minimal volatility. However, there may be slight outliers like when the exchange rate reaches its maximum value of 0.34658 on 9th April, 2024 and lowest values of 0.33605 and 0.33634 respectively on 16th April, 2024. These points could potentially be considered outliers due to them standing as extreme values relative to the generally stable nature of the rest of the series.