2024-05-01 Ngultrum News
2024-04-30
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Given the constraints of not considering external factors or generating forecasts of future rates, here are the components of a comprehensive analysis of the data:1. Understanding the overall trend of the exchange rates:
The data spans from 2024-04-30 00:00:02 to 2024-04-30 23:55:02. While the analysis must be made using graphical methods for an assured comprehension, an initial look into the dataset shows that there is a small overall positive trend in the exchange rates for BTN. The rate starts at 0.01639 at midnight and ends at 0.0164 by the end of the day. The highest rate recorded throughout the day is 0.01651 which may indicate certain hours when the rate tends to peak.
2. Identifying any seasonality or recurring patterns in the changes of exchange rates:
The insights about seasonality can only be gathered by a visualization plot. However, it seems that there are upwards and downwards fluctuations at certain intervals. This may indicate a possible seasonality in exchange rates data. Nonetheless, a more detailed and longer timeframe data would be more useful in getting a clearer image about the presence of any seasonal effects or recurring patterns. Generally, such patterns are observed on a yearly or quarterly basis.
3. Noting any outliers, or instances where the exchange rate differs significantly:
On a quick review of the data, there is no particular instance that stands out as an outlier with a significantly different rate from others. The rate fluctuates within a small range of 0.01638 and 0.01651. There may be minimal variance due to market fluctuations, but it's not representative of an outlier as the changes seem normal for a currency exchange rate within a single day. Nevertheless, a statistical analysis is necessary to confirm the behavior of the data and spot if there are outliers really present.
Recommendation:
The use of visualizations and inferential statistics in addition to descriptive analysis would allow us to better understand the data. Although this requires additional computations and graphs, they would provide a more detailed view of the underlying trends, patterns, and potential outliers in the dataset. It would also be beneficial to have a larger dataset that covers a longer period of time to more accurately identify trends and patterns, including potential seasonality effects.