2024-04-22 Tunisian Dinar 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
Overall Trend
Upon preliminary examination of the data, there appears to be a minuscule upward trend in the TND exchange rate from 2024-03-22 to 2024-04-19. The exchange rate starts at 0.43878 and ends at 0.43611, despite some fluctuations in between. However, this modest increase does not conclusively indicate a stable upward trend, and might as well be part of a larger cycle or due to random fluctuations. In order to claim a definitive trend, a more extensive range of data would need to be analyzed.
Seasonality or Recurring Patterns
Determining seasonality or recurring patterns in the exchange rates is a complex task that usually requires a more extensive dataset spanning across multiple years. From the data given here, across a period of around 1 month, no clear signs of seasonality can be detected. There might be some minor recurring patterns during certain hours of the day, possibly due to the opening and closing of markets, but it's difficult to confirm a definitive pattern without a more comprehensive dataset.
Outliers
Outliers in the dataset are values that deviate significantly from the general trend or pattern. Identifying specific outliers in this dataset is quite challenging due to the modest variations and tight range of the exchange rates. However, generally, the value at the timestamp '2024-04-08 12:00:02' with the exchange rate of 0.4357 and at '2024-04-16 16:00:02' with an exchange rate of 0.43721 could be potential outliers. Noticeably, the TND exchange rate mostly ranges from 0.43 to 0.44 and these outliers are off with a meager margin. A sophisticated statistical analysis can provide us a more accurate identification of the outliers.
Note: Please always validate the thorough statistical analysis. An exchange rate is determined by a multitude of factors and can behave unpredictably at times. Therefore, a comprehensive understanding of such data requires not only statistical analysis but also a deep understanding of the financial market.