2024-05-10 Taka 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. Understanding the Overall Trend of the Exchange Rates
The data provided consists of timestamps along with corresponding BDT exchange rates, spanning a period from May 9, 2024, to May 9, 2024. Analyzing this data over the given period, it appears that the exchange rate undergoes minor fluctuations throughout the day but reveals a mostly stable pattern, maintaining a value in the range of 0.01169 to 0.01251. The rates initially show a small uptick, starting at 0.0125 and reaching a peak of 0.01251 in a few instances, then declining to a low of 0.01168 subsequently towards the end of the period in question. This is not to say the value is continuously decreasing. The data suggests that the trend is more flat and stable than sharply upward or downward.
2. Identifying Seasonality or Recurring Patterns in the Exchange Rates
At first glance, the data seems to be lacking obvious seasonality or recurring patterns within the given one-day timeframe. However, it should be noted that further analysis over a more extended period (such as several weeks or months) may be required to establish if there is any such seasonality or recurring pattern. For the data given, there are minor fluctuations in exchange rates, but it remains within a narrow range which limits the identification of noticeable patterns.
3. Noting Any Outliers in the Exchange Rates
The dataset provided shows very mild variation in the exchange rate values, with a minimal range between the maximum and minimum values observed (i.e., 0.01251 and 0.01168, respectively). There are a few dips to the lower end of this range, but such drops are infrequent and quickly return to the average rate value. Additionally, these dips do not seem to be drastic enough to warrant categorization as significant outliers, given the overall stability and minor fluctuations within the dataset.