2024-04-29 Zambian Kwacha News
2024-04-28
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
Data Overview
The data provided includes timestamped exchange rates (ZMW) ranging from March 2024 to April 2024. It comprises multiple data points per day, capturing the dynamic fluctuations of the exchange rates within short time intervals.
Data Analysis Summary
Below is a high level analysis of the time series data, covering key aspects such as trend, seasonality, and outliers.
I. Understanding the Overall Trend of Exchange Rates
Just by looking at the raw data, it is hard to discern a particular trend because of the complex oscillations within short periods. However, it is noted that the exchange rate fluctuates between roughly 0.053 and 0.055 units in the initial weeks of the data series, decreasing to between 0.051 and 0.053 units by the end of the data series. This could possibly indicate a slight decreasing trend over time. A more rigorous investigation might involve applying statistical methods to calculate trends, such as moving averages or linear regression.
II. Identifying Seasonality in Exchange Rates
Seasonality refers to recurring patterns in the data at regular intervals. With the limited span of this dataset, it's hard to confirm long-term seasonal exchange rate patterns (like yearly or quarterly). However, we may be able to identify intra-day or day-to-day seasonality if larger data for the whole day were available. At first glance, it is hard to discern a clear repeating pattern within the days or between different days. More sophisticated time series analysis would be needed to identify any daily seasonality.
III. Identification of Outliers
An outlier is a data point that diverges significantly from other observations. They could occur due to exceptional events impacting the exchange rates or possibly be a result of data recording errors. By quickly scanning the provided data, we notice that the ZMW fluctuates within a bounded range and there are no single points that largely deviate from this range. Hence, we might infer that there are no significant outliers in this dataset.
Please note, a more formal analysis using statistical software would likely provide a clearer picture, allowing us to definitively make conclusions about trends, seasonality, and outliers.