2024-05-21 Cabo Verde Escudo News
2024-05-20
Summary of Last Month
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
The data provided has been examined and the results of our analysis are as follows:
1. Overall trend of exchange rates:
The overall trend of the exchange rate given in the dataset shows a very stable pattern for the most part. Most data points range between 0.01342 and 0.01343, with a slight decrease to 0.01340 and a decrease to 0.01335 in the mid of the timestamps - consistent for a while before moving back to the previous value around 0.01342. There is a slight but significant overall move upwards towards the end of the period to around 0.01344.
2. Seasonality or recurring patterns:
Given the data's hourly resolution, short-term seasonality such as hourly or daily patterns is difficult to precisely identify. The scope of the dataset doesn't allow for detecting longer-term seasonality like weekly, monthly, or yearly patterns. However, we can note a minor decreasing trend at around the middle of the dataset where the rate dips to 0.01335 and 0.01340, before recovering back to its normal range. This could potentially hint at some daily pattern but it would be speculative to say so at this level of detail, and a larger dataset would be needed to confirm this seasonality.
3. Outliers:
The dataset is fairly consistent, with the bulk of the data lying between 0.01342 and 0.01343. Therefore, the instances where the rate dropped to 0.01335 and 0.01340 can be considered as moderate outliers, as they deviate from the general trend. Conversely, towards the end of the dataset where the rate rises to 0.01344, these points may also be viewed as slight outliers. However, given the small range of the data, these 'outliers' are not significantly deviating and seem to be part of the natural fluctuations in the rate.
In financial data such as this, such minor outliers are often to be expected and may sometimes be due to factors outside the dataset such as economic events or news announcements. However, since the context of these potential factors is not provided or considered in this analysis, it's important to interpret these outlier points with caution.
