2024-05-14 Bolivar News
2024-05-13
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
Comprehensive Analysis of the Provided Dataset
Based on the provided dataset, all the recorded datapoints for vef exchange rates are '0' across varying time-stamps representing different points in a single day (2024-05-13). This results in a flat line time series data with no observable trend, seasonality, or outliers. Here's a detailed look at each aspect:
1. Trend Analysis
Usually, a trend in time series data is observable when there's a consistent increase or decrease in data over time. In this case, given the exchange rate values are consistently '0' for all timestamps, no trend can be determined. Thus, it can be concluded that the exchange rates remained stable over the period shown.
2. Seasonality Check
Seasonality is a characteristic of a time series in which the data experiences regular and predictable changes that recur every calendar year. However, in this dataset, due to the lack of variability in the 'vef' values, any seasonality, or otherwise recurring pattern, couldn't be identified.
3. Outlier Analysis
Outliers in a dataset are extreme values that deviate from other observations in the data. They may indicate a variability in the data, experimental errors, or a novelty. In this case, as all the vef exchange rates are '0' across the given timestamps, we can confirm there are no outliers in the data.
In conclusion, the given data doesn't provide much information for a comprehensive financial analysis due to the lack of variability in the values. Further accurate and variable data may be required to perform an effective trends, seasonality, or outlier analysis.
