2024-05-17 Sri Lanka Rupee News
2024-05-16
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Firstly, the structure of the provided data has been parsed and understood. This dataset depicts a timestamp corresponding to the exchange rates (in LKR), generating a time series data. This analysis will stick closely to the provided data, and will not take into account potential influencing factors such as market opening/closing hours, weekends/holidays, or the release of key financial factors.Overall trend of the exchange rates (LKR)
The LKR exchange rates provided in the data set are remarkably steady across the timeframe, with minor fluctuations observed. The bulk of the data values are hovering around the value of 0.00454. Towards the end of the time series data, starting from 06:25:02, we notice a slight decrease in the rate to 0.00453 which remains unchanged till the end of the time series. This depicts a minor depreciation of currency over the observed time period.
Identifying Seasonality or Recurring Patterns
Given the granularity of the data (every five minutes), and the relatively stable nature of the exchange rate over this period, there don't appear to be any notable recurring patterns or seasonal trends in this exchange rate within the available data. Longer-term data covering multiple months or years might reveal such patterns, especially when aligning data with economic events or trends. In this data set, however, noteworthy patterns or seasonality is quite elusive due to close-knit data points and short span of data.
Noting any Outliers
The dataset does not display any immediate outliers. All data points fall within the very narrow range of 0.00453 to 0.00454. This narrow range allows for asserting that no significant fluctuations or unexpected occurrences have occurred within this data set regarding the exchange rate.
Please note that these observations are purely data-driven considering provided time-series. To make an accurate prediction or to gauge the impacts of specific events on financial trends, a broader data set with more influencing factors would provide a more comprehensive insight.