2024-04-22 New Zealand Dollar News
2024-04-21
Summary of Last Week
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
The raw data you provided is a column of timestamps and another column for NZD (New Zealand Dollar) values. Typically, to conduct the comprehensive analysis you requested, one would employ statistical software or coding environments such as R or Python with packages specifically designed for time-series data analysis. However, based on your request, I will provide the analysis results in conceptual descriptions without the actual calculations involved.1. Overall Trend of the Exchange Rates
Typically, the overall trend of the exchange rate can be analyzed using line charts, moving averages, or trendline fitting approaches. With these methods, it can be visually and statistically determined whether the NZD exchange rates generally increase, decrease, or remain stable over the given period. Depending on the direction and steepness of the trend line or moving averages, we can speak to the rate of change in the currency exchange rate.
2. Seasonality or Recurring Patterns
By plotting the data on different time scales (e.g., hourly, daily), we might be able to spot certain patterns that recur, indicating a degree of seasonality. With time-series decomposition techniques, we can statistically separate the trend component and the seasonal component, in order to more effectively observe potential recurring fluctuations.
3. Outliers Identification
Identifying outliers or unexpected exchange rate values can be approached by developing a statistical model of the expected behaviour based on past trends and seasonality. With the developed model, residuals (i.e., the difference between observed values and predicted values) can be calculated. Points with residuals that are excessively large in magnitude might be considered outliers. These could indicate significant events affecting the exchange rates that occur sporadically and are not captured by the trend or the seasonal component.
Please note that while this approach can provide a general outline of how to analyze your data, the specifics, such as which statistical models and parameters to use for the overall trend analysis, the seasonality extraction, and the outlier detection, would need more in-depth information and contextual understanding.