2024-05-06 Bulgarian Lev 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
After analyzing the data provided, it seems that the exchange rates do not exhibit a clear upward or downward trend. The rates start at around 0.7514, showing minor fluctuations initially then experiencing a slight increase to 0.75603, followed by a decline and rise again with some fluctuations, eventually closing at 0.75376. The rates generally fluctuate within a relatively small range, indicating a more or less stable trend. However, to make a stronger conclusion about the overall trend taking into account the volatility, a larger dataset spanning over a longer period may be needed.
Seasonality or Recurring Patterns
As for any seasonality or recurring patterns, such characteristics are typically seen in higher-frequency data, such as hourly data in this case, where similar patterns recur at regular intervals. In this dataset, the data is limited, so it's difficult to conclude definitively on this matter. It does seem like there are minor fluctuations on a regular basis which may indicate there could be some intra-day seasonality. However, observing the data doesn't appear to show patterns that are linked to specific days of the week. To further confirm the existence of seasonality or recurring patterns in the exchange rate, a detailed statistical test such as the autocorrelation function (ACF) should be applied.
Outliers
In terms of outliers, given the relatively stable range in which the rates fluctuate, there doesn't appear to be any drastic spikes or dips in the exchange rate that could be considered an outlier. The highest rate is 0.7577, and the lowest rate is 0.7459, both of which don't stray too far from the range's average. Therefore, no significant outliers can be identified just from the data observation. Although, a more strict statistical test could be utilized for more accurate outlier detection.
