Summary of Yesterday
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
- Standard Deviation:
The dataset shows that the exchange rate over time oscillates within a quite narrow range with the minimum value being 0.75134 and the maximum value being 0.75537. However, generally, the trend of the data set could be seen as relatively stable as it doesn't witness large fluctuations within the given timeframe.
Seasonality or Recurring Patterns:
Looking into the dataset, it is hard to definitively state the existence of seasonality or recurring patterns just based on the provided dataset. This is due to the fact that fluctuations in exchange rates are influenced by myriad factors including market demand, the global economic situation, and financial news or reports. For a clearer picture, a larger data set with a wider time frame will be required. In addition, time series analysis techniques or decomposition methods may be useful to understand seasonality better.
Given the tight range in which the exchange rates vary and the consistency of the fluctuations, there don't appear to be obvious outliers or instances where the exchange rate differs significantly from the expected values. The exchange rate seems to follow a consistent pattern of change within the observed period.
Although the task does not allow considering external factors such as market opening/closing hours, weekends/holidays, or the release of key financial news and reports, it is important to note, these factors do play a significant role in the movement of exchange rates. Hence, for a thorough analysis or to obtain an accurate forecast, these factors should ideally be considered.
Moreover, an analysis of this kind usually gives more accurate results when accompanied by visualization tools such as line charts or time series plots, which unfortunately could not be incorporated due to the requested text-based(html) format of the result.
Lastly, as financial markets are hugely influenced by global events and unforeseen incidents, the analysis could deviate from the expected trend in the presence of such events.