2024-04-30 Bolivar News
2024-04-29
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
Based on the data you provided, I am unable to perform any financial analysis as the value for the exchange rate (VEF) is 0 at all times in the provided time-series data. Therefore, I'm unable to assess trends or identify patterns and outliers. In a typical situation, if the data varied, it would be possible to generate analysis based on the three goals you outlined, even without considering specific market events, news or forecasts. 1.Exchange Rate Trend
This would involve plotting the exchange rates over time and visually inspecting the chart to understand if the currency is appreciating, depreciating or maintaining stability.
2.Identifying Seasonality
Observation of recurring patterns on a daily, weekly, monthly, or yearly basis when possible, would be the basis of seasonality identification. This can be achieved by performing a time series decomposition into trend, seasonal, and residual components.
3.Outliers Detection
Outliers or anomalies in the data, where the exchange rate deviates significantly from the trend or seasonality patterns, would be identified using statistical methods for outlier detection. These might include methods like the Z-score or IQR method.
To obtain meaningful insights from this analysis, a dataset with varied exchange rates over a specified timeline is needed.