2024-05-01 Danish Krone News
2024-04-30
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
1. Overall trend of the exchange rates
Upon examining the data provided, it can be observed that the exchange rates for DKK slightly fluctuated over the period, offering a blend of increase and decrease, however, with an overall stabilization trend. The range of these rates, encapsulating the lowest (0.19639) and the highest (0.19739) values, hints at a relatively stable environment. This is indicative of the currency market being stable over this timeframe, with no drastic or volatile shifts that could significantly impact the currency exchange rate.
2. Seasonality and recurring patterns
Regarding seasonality or recurring patterns, the data does not show any clear, consistent, periodic exchange rate changes that can be attributed to a particular time of day or specific periods. However, a more detailed analysis over a larger dataset might show different results. It's important to note that the exchange rates of currencies can be influenced by numerous factors and not subjected to seasonality effects to a significant extent.
3. Outliers in the data
While most data values appear to hover around the same mark, offering a sense of uniformity, there are a few instances where a slight, noticeable deviation from the prevailing exchange rate value can be seen. However, such instances are relatively few and far between, and do not represent drastic or dramatic departures from the general trend and range. For instance, the peak value of 0.19739 could be considered an outlier as it surpasses the usual fluctuation range. Likewise, the lowest value of 0.19639 seems to deviate from the standard pattern. These outliers do not drastically alter the overall stable scenario, but rather contribute to the slight fluctuation within the stability.
P.S.: To do a more robust analysis and to determine outliers more accurately, software tools, sophisticated algorithms, or statistical techniques can be employed. These can provide a more detailed and in-depth view of such complex financial data.
