2024-04-22 Syrian Pound News
2024-04-21
Summary of Last Week
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Understanding the Overall Trend
Upon viewing the data, it appears that we have three distinct periods with different exchange rate ranges. The SYP exchange rates maintain a consistent value of 0.0001 from the period of 2024-03-22 to 2024-04-09. Around 2024-04-10 there was a slight increase in the exchange rates where the rates have changed to around 0.00011 and remained stable at this value until 2024-04-12. However, from 2024-04-15 onwards, there is a significant increase in the exchange rates where the rates have climbed to and maintained at approximately 0.00055. Considering these observations, we can ascertain that the trend of exchange rates generally starts off at a stable point, experiences a small rise, and subsequently a big jump.
Identifying Seasonality or Recurring Patterns
In terms of seasonality or recurring patterns, it is hard to clearly identify any due to the nature of the data provided. There is no discernible weekly or monthly pattern as most of the day's rate remain unchanged. It would suggest that the SYP exchange rates are possibly influenced by certain events or factors that aren't consistent enough to form a pattern. However, we can note an underlying trend, which consists of a relatively stable rate, followed by a slight increase, and ultimately significant spike which characterizes the overall data.
Detecting Outliers
Looking at the values, there does not appear to be any significant outliers within each defined period. Each defined period displays an exchange rate value that is consistent without any drastic deviations that may be defined as outliers. For example, the rates remain stable at 0.0001, 0.00011, and 0.00055 respectively for each period. It is interesting to note that the jump from 0.00011 to 0.00055 could be considered an outlier in the grand scheme of the entire data series as this is a significant leap compared to the previous changes we've observed within their respective periods.