2024-05-10 Loti News
2024-05-09
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
1. Overall Trend Analysis
Looking at the dataset, it seems that the change in exchange rates over time is quite minimal, fluctuating between 0.07385 and 0.07394. The general trend in the value appears to be somewhat stable, neither showing a significant increase nor decline.
2. Seasonality and Recurring Pattern Analysis
Identifying seasonality and patterns in time-series data can be a bit challenging due to the minute-by-minute changes represented in this dataset. However, there are no clear or significant persistent patterns in the exchange rates changes over the described timestamp. The data seems to fluctuate randomly within a very narrow range, and no specific cyclical behavior is apparent upon the first analysis.
3. Outliers Detection
As for outliers, because the data's range is quite narrow, any substantial deviation from this range can be regarded as an outlier. Despite this, the provided dataset doesn't exhibit any noticeable outliers, meaning there are no significant swings from the usual rate fluctuation pattern. To make a definitive conclusion about the presence of outliers, we would need to conduct a more robust statistical analysis like Z-score or IQR methods.
Conclusion
In summary, the data presents a relatively stable exchange rate over the given timeframe, with some minor fluctuations. Since the range of these fluctuations is quite tight, no clear seasonality or trend is immediately apparent. Also, there doesn't appear to be any significant outliers present within the dataset. An extensive and deep statistical analysis might reveal more detailed insights about trend, cyclical behavior, and outliers.