Summary of Last Month
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
- Standard Deviation:
Understanding the Overall Trend
The dataset provided contains exchange rates data from February 26, 2024. It appears that the exchange rate has fluctuated throughout the given period, seeing minor increases and decreases. There isn't a clear upward or downward trend when considering the entire range of data.
Identifying Seasonality or Recurring Patterns
In examining the data more closely, some subtle patterns begin to emerge. The fluctuations appear to be regular, and there could be some level of seasonality within hours of each day though this is not entirely clear without further statistical analysis. Additionally, some regular small peaks and troughs suggest that there may be certain intraday times where the rate commonly increases or decreases.
Noting any Outliers
There are also a few potential outliers within the data. For instance, on February 26, 2024, at around 1:45 am, the exchange rate peaks at 2.23421 before sharply dropping at 2:10 am to 2.23337, and later at 4:05 am it drops to its lowest for the period at 2.23484. However, these shifts are quite minor and could merely reflect normal market volatility.
It should be noted that without additional contextual data or knowledge of what events might have been occurring during these dates, it is difficult to definitively identify these instances as outliers or as part of the underlying data structure.
Considering External Factors
While the instruction was to not consider external factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports, it's important to note that these factors can have a significant effect on exchange rates. Market hours and the release of financial news can also create unique patterns in financial time series data. However, these are not considered in this analysis due to the instructions given.
From our analysis, the LVL exchange rate over this period at first appears relatively stable, with only minor hourly fluctuations. However, there could be underlying patterns within each trading day’s data or subtle changes between days that require more thorough statistical investigation to detect.
Also note that any conclusions formed from this dataset would only apply to the period of data provided. Future predictions were not performed due to the instructions given.