2024-05-10 Pound Sterling News
2024-05-09
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Here is a detailed analysis of exchanged rates as provided in the dataset. My primary focus is on understanding the general trend of exchanged rates, identifying reoccurring patterns, and conducting an appreciation of outliers.
General Trend of Exchanged Rates
Regarding the general trend, the data indicates that the exchanged rates have been fluctuating. At initial point, the exchange rate is 1.71472 which has gradually decreased to approximately 1.7134 in a span of a few hours. Afterwards, we observe a slight increase followed by occasional drops. The lowest exchange rate of 1.70928 was recorded on 2024-05-09 06:10:02. The end of the data series points to a rate of 1.7134, suggesting an overall decline during the given data timeline.
Seasonality and Recurring Patterns
While it's difficult to definitively state that there is a seasonal or regular pattern due to the nature and short span of data, there are slight drops in exchange rate that can be considered as a pattern. These slight drops followed by an increase and subsequent decline shows a certain cyclical behavior. However, to draw a definitive conclusion, a more in-depth or longer time series data would be required.
Outliers and Significant Differences
Observing the data for unexpected spikes or drops (outliers) that don't adhere to the overall pattern, the point at 1.70928 exchange rate stands out being the minimum rate that was registered. Other records of significance exist at exchange rates of 1.71475 and 1.7152, which exhibit a rate much higher in comparison to neighbouring time periods. Similarly, a sharp decline from 1.71435 to 1.71048 also represents an outlier.
In conclusion, the given exchange rate data suggests a fluctuating behavior over the time period with occasional outliers cropping up. Extracting a precise pattern or trend identification demands for a more extensive dataset for analysis.