2024-04-17 Pula News
2024-04-16
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
After carefully reviewing the provided time-series financial data, here are my findings:
1. Understanding the Overall Trend of Exchange Rates
The overall trend seems to be somewhat stable with a slight increase over time. The BWP exchange rate started at 0.09967 and ended at 0.09996. While the increments are marginal, it does indicate a small upward trend over the monitored period. It is important to note that while these changes are relatively small, such slight variations at the level of exchange rates can have significant consequences in large financial transactions.
2. Identifying Seasonality or Recurring Patterns
In the given data set, there's insufficient evidence to identify any clear seasonality or recurring patterns in the exchange rates based purely on the provided dataset for one day. Typically, seasonal patterns require longer periods to observe - usually a few months or more - and tend to be influenced by macroeconomic events, which we've excluded from this analysis as per your request.
3. Outliers Observations
The data does not seem to exhibit any significant outliers or extreme fluctuations. The exchange rates provided are relatively stable and within a close range of values, with the highest recorded rate being 0.10021 and the lowest being 0.09961. No notable spikes or drops beyond this range were detected, suggesting consistent market conditions during this specific period. Please note that a more robust outlier detection would require statistical analysis that wasn't done during this analysis.
In the world of financial time-series data, it's common to see complex trends, seasonal patterns, cyclical changes, and even random 'noise'. While our manual analysis of this specific dataset indicates overall stability and a slight upward trend, please bear in mind that this is an oversimplified analysis and cannot provide a full understanding of the complexities inherent in financial data. More advanced statistical techniques can be employed for a more granular understanding.