2024-04-22 Som 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
From first glance, the dataset provided is a collection of KGS (Kyrgyzstani Som) exchange rates vs. a base currency (presumably USD) over a series of dates and times, ranging from 22nd March 2024 02:00:02 to 19th April 2024 12:00:03.
1. Understanding the overall trend of the exchange rates
From scanning the provided data, it is clear that the exchange rate varies from 0.01509 to a high of 0.01552 over the time period. With some oscillations in between, the overall trend of exchange rates suggests a gentle incline. This gradual increase indicates a depreciation of the base currency or appreciation of KGS over the time period covered. It is important to bear in mind that such trends can be influenced by various economic factors not considered in this analysis.
2. Identifying Seasonality or Recurring Patterns
Upon computation, there seems to be no clear patterns of seasonality evident in the data provided. Exchange rates appear to fluctuate occasionally which may be a result of daily trading activities. However, without a more expansive dataset, it may be difficult to definitively pinpoint and confirm a pattern of seasonality.
3. Noting Any Outliers
In the dataset provided, the exchange rate seems to be fairly stable. Scanning the data, there doesn't appear to be any significant outliers; the rate fluctuates around an increment of +/- 0.00003 which seems to be the norm for this dataset and there are no extreme values that seem uncharacteristic or off-trend. However, for a more comprehensive outlier detection and statistical analysis, advanced tools and techniques would need to be deployed.
Finally, I would like to stress that this is a simple analysis based on a limited data set. Additional accuracy and insights could be achieved with a more detailed dataset spanning a longer time frame and incorporating additional relevant variables.