2024-05-13 Namibia Dollar News
2024-05-12
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
1. Understanding the Trend
Looking at the dataset, the general trend of the exchange rate (NAD) shows some fluctuation over time. There is no continuous linear trend like increasing or decreasing for the time period shown. However, several periods of slight but consistent rises and falls in the exchange rate are visible; this observation suggests the existence of somewhat cyclical behavior, implying that the exchange rate might be influenced by cyclical economic factors.
2. Seasonality or Recurrence
While it's challenging to definitively identify seasonality in the dataset without a more extensive series or explicit periodic information, certain patterns seem to recur. For example, there appears to be a somewhat cyclical pattern at multiple points in the data where the exchange rate gradually increases for a period of time, then decreases. Additional data spanning multiple years would be beneficial to more accurately discern any seasonality.
3. Noting Outliers
From an initial review of the data, there aren't many clear outliers - points where the exchange rate significantly deviates from the trend. However, there are a few instances where the exchange rate experiences a notable increase or decrease within a relatively short period. Some variation is to be expected in financial data, and these periods of greater fluctuation may be associated with specific events or influences that aren't indicated by the data provided. With the data within the provided set, it's challenging to definitively label these as outliers without more context or a defined range of what would be considered a 'normal' fluctuation.
Overall, this analysis provides a high-level overview of the trends, patterns, and possible outliers within the exchange rate data. However, additional data and further analytical methods could provide more insight and a more detailed understanding of the observed patterns and outliers.
