2024-05-09 Tenge News
2024-05-08
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Analysis Results
The provided dataset demonstrates the exchange rate value of KZT (Kazakhstani Tenge) captured at different timestamps through the day on May 8, 2024. However, contrary to expectations, the dataset portrays very limited variability in exchange rates in general. The changes in exchange rates occur in a very tight range, indicating high stability.
Overall Trend
Observing the overall trend, it's predominantly stable with little volatility. The majority of the dataset shows an exchange rate of 0.00312. There's a slight increase to 0.00313 observed at around 06:35, which sustained till about 07:40. Post that, the rate dropped back to the prior rate of 0.00312 and remained the same for the rest of the day.
Seasonality and Pattern
With respect to seasonality or recurring patterns, this sole day's data isn't sufficient to conclusively state any daily pattern or seasonality. It will need additional context or a broader dataset spanning multiple days or months for this information to be deduced. The small change that was noticed during the early morning hours might be of interest to investigate for a potential pattern.
Outliers
For this particular dataset, there are no specific outliers. We only see a minimal variation from the dominant exchange rate of 0.00312 which might not be classified as significant as it returns to the dominant value quite quickly.
In anticipation of further analysis
While this analysis is based solely on the data provided and does not consider external factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports, taking these into account could provide a more in-depth understanding of the rate changes. A future analysis might also benefit from data spanning a longer time period for better understanding of trends, patterns and seasonality.