2024-05-20 Ngultrum News
2024-05-19
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
Analysis of a Provided Time Series Dataset - BTN Exchange Rates
The given dataset is a comprehensive list of BTN exchange rates at different timestamps from 19-Apr-2024 to 17-May-2024. Let's break down the analysis into sections to understand the overall trend, seasonality, and outliers.
1. Overall Trend of Exchange Rates
Observing the data, it seems that the exchange rate has been staying relatively stable over the entire period. Starting from 0.01642 on 19-Apr-2024, it moves up and down slightly, with the highest rate recorded at 0.0165 and the lowest at 0.0163. However, the rate tends to stay within these boundaries, pointing towards a relatively stable exchange rate with minor fluctuations.
2. Seasonality or Recurring Patterns
Seasonality or recurring patterns can often be observed in time series data. This dataset, however, does not exhibit strong seasonality or repeating patterns on first glance. The fluctuations in exchange rates seem random with no discernible repeating pattern within the given timeframe.
3. Outliers in the Exchange Rates
Outliers are data points that stand out from the regular observations in a dataset. In this case, an outlier would be an exchange rate that significantly differs from the overall trend. Given that the BTN exchange rate mostly stayed within the range of 0.0163 to 0.0165, any value outside this range could be considered an outlier. Nevertheless, the range is too narrow to include any critical outliers in the given dataset.
In summary, the dataset shows a stable BTN exchange rate with minor fluctuations. It doesn't show any strong seasonality or recurring patterns, and there don't appear to be significant outliers. This can be a result of stable economic conditions, amongst other factors. However, this analysis is solely based on the data provided and does not take external factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports into consideration.