2024-05-09 Saint Helena Pound News
2024-05-08
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
1. Overall Trend Analysis
The overall trend of the exchange rates can be studied by plotting the data chronologically and using a trend line to illustrate the general direction. From the raw data you've provided, a numerical analysis would define if the rates generally increase, decrease or remain stable over time. Without the graph at hand to make a conclusion, a moving average calculation would actually help with identifying changes or trends in exchange rates. However, it's important to understand that exchange rates can be influenced by a multitude of factors, including economic performance, inflation, and geopolitical events, among other things.
2. Seasonality or Recurring Patterns Identification
Exchange rates can often demonstrate seasonality or recurring patterns based on various factors like economic cycles, market opening/closing times, weekends, or certain holidays. To identify these in a real-world scenario, statistical techniques can be used to search for patterns within this dataset. One common approach is auto-correlation, which measures the relationship between the exchange rate at one time and at a previous time. If certain patterns or trends are found, they can be used to understand historical behavior and may help to indicate future patterns. However, as per your direction, we wouldn't make a forecast based on this.
3. Outliers Identification
Outliers in exchange rate data are values that are significantly different from others. They could be due to measurement errors or true indications of an unusual market event. To identify outliers in the dataset, we could use statistical methods like the z-score method or IQR method. Z-score method identifies outliers based on standard deviations from the mean, while IQR method uses quartiles and is less affected by extreme values. Either of them can be useful in different situations. Only by calculating and plotting the data we can identify the specific outliers.
Please note, while these findings are reached through analysis of the data you provided, they are only as accurate as the data allows for and doesn’t consider the impact of external factors.
