Summary of Last Week
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
- Standard Deviation:
Based on the time-series data provided, let's analyze the overall trend, possible seasonality, and potential outliers in the GYD exchange rates over the given period.
Understanding the Overall Trend
Upon inspection of the dataset, we can observe some fluctuations in the exchange rate values, but overall, the rates appear largely stable. The exchange rates range between 0.00638 and 0.00649, with some slight fluctuations that don't point to a stable increasing or decreasing trend. The average exchange rate also remains relatively stable at around the same range. Therefore, it seems reasonable to conclude that the data shows a generally stable GYD exchange rate trend over the observed period of time.
Due to the high frequency of the time-series data (around every 2-hours), it's difficult to identify clear seasonality without performing in-depth statistical analysis. However, from a high-level analysis, there does not appear to be any clear recurring patterns or seasonality in the exchange rates. Any minor fluctuations appear to happen randomly rather than at consistent intervals. We need to conduct a more detailed analysis, such as spectral analysis or autocorrelation function, to confirm this observation.
Noting Any Outliers
At a glance, there don't appear to be significant outliers in the dataset. The exchange rates remain within a relatively narrow band and show slight fluctuations. Any potential outliers would need to be identified using more sophisticated statistical techniques, such as the Z-score or the Interquartile Range (IQR) methods. However, for the purpose of this high-level analysis, there are no clearly identifiable outliers within this data.
Please note that this analysis is based purely on the provided dataset and does not take into account any external factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports. A more in-depth analysis that considers such factors would likely provide more insight into the trends, seasonality, and outliers observed.