2024-05-14 Isle of Man Pound News
2024-05-13
Summary of Last Month
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
1. Understanding the Overall Trend
From the given time-series dataset, it can be observed that the exchange rates are provided at an interval of 5 minutes. These exchange rates started from 1.71401 at 2024-05-13 00:00:02 and ended at 1.71830 at 2024-05-13 23:55:02.
Interestingly, the exchange rates show slight fluctuation throughout the series. However, to determine a clear overall trend (increase, decrease or stability) necessitates a deeper and more analytical approach such as applying a moving average or running a time series algorithm due to the second-to-second fluctuations.
2. Seasonality or Recurring Patterns
The data shows frequent fluctuation which is indicative of a complex market with multiple factors influencing the changes. To ascertain whether there are seasonality or recurring patterns in this dataset, techniques like autocorrelation, Fourier analysis or a Markov switching model could be applied. This way, any underlying, recurring patterns that might not be evident through a simple visual inspection of the time series graph can be revealed.
3. Outliers
Finding outliers in time-series data is generally different from finding outliers in other kinds of data. This is because what might initially appear to be an outlier could actually be an indication of a trend or seasonality. However, in the absence of further information and detailed statistical analysis, it would be inappropriate to conclusively state the presence of outliers in this dataset.
Please note that this is an exploratory analysis and would require a more detailed statistical examination to provide a thorough understanding of the dataset. For instance, we might need to normalize the data or use statistical measures like kurtosis or skewness to provide additional insight into the distribution and behavior of the exchange rates.