2024-05-03 Ngultrum News
2024-05-02
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
After conducting a detailed analysis of the provided time-series data, here are the findings derived from understanding the overall trend, observing seasonality, and noting any outliers for the exchange rates (BTN).
1. Overall Trend of Exchange Rates
The provided data shows that the BTN exchange rate remained fairly stable throughout the time period, fluctuating between 0.01638 and 0.01645. The overall trend was neither increasing nor decreasing significantly, suggesting that there was relatively little volatility in this exchange rate during this period. Variations in the exchange rate were minor, showing the standard fluctuations one would expect in any financial market. However, these fluctuations seem to be random rather than forming a consistent up or down trend.
2. Seasonality and Recurring Patterns
Repeated patterns or seasonality in the dataset were not clearly identifiable. The exchange rate data appears to be consistent, with minor fluctuations throughout all timestamps. In fact, the exchange rate fluctuates within a very narrow band, indicating that this rate does not display a specific seasonal pattern. Future analysis might involve a larger dataset or more granular data (minute by minute) to determine more subtle patterns or seasonality.
3. Outliers in the Data
Given the narrow waveband within which the data fluctuates, there are no notable outliers over this period. Every observed change, whether an increase or decrease, in the exchange rate is in-line with the overall behavior of the data. However, I must note that the absence of clear outliers may also be a result of the narrow scope of the given dataset in terms of time and the limited scale we're working with for the exchange rate. The extent to which the data ranges (only 0.00007) would make any potential outlier less significant than in a dataset with a larger range.