2024-04-18 Euro News
2024-04-17
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Overall Trend Analysis
After analyzing the provided time series financial data, it can be noted that the EUR exchange rate exhibits various changes over the provided dataset. There's no clear trend of consistent increase or decrease. The rates fluctuate within a certain range, indicating a range-bound behavior. Such behavior is quite common in forex markets where the exchange rate of a currency pair often oscillates within a certain price range (support and resistance levels) for a given period.
Seasonality and Recurring Patterns
In terms of seasonality or recurring patterns, analysis of the given dataset doesn't show any distinct or clear-cut seasonal effect or cyclical pattern in the data. This might require more extended data set that includes multiple cycles of a year to identify seasonal effects accurately.
Outliers Identification
Identifying outliers in time-series financial data like exchange rates is important because they can distort the overall picture and result from market anomalies or extreme events. In the analysis of this dataset, there does seem to be some data points that diverge from the general exchange rate range, but more statistical analysis would be required to determine true outliers.
In conclusion, the analysis above is a basic interpretation of the dataset. For more in-depth insights and to identify minute patterns or fluctuations, more advanced statistical tools and models would be required. These could include regression analysis, moving averages, or machine learning algorithms for pattern recognition.