ZMW Exchange Rate Remains Steady But Points to Slight Downward Trend
2024-05-02
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
To start with, it is clear that this time series financial data is a large dataset representing a continuous sequence of exchange rate changes (ZMW). In this particular case, the data is timestamped at five-minute intervals across the entire day.1. Overall Trend of Exchange Rates:
Checking the changes from the start to the end of the dataset, it is noticeable that exchange rates slightly decreased. The rate started at 0.05145 and ended at 0.05088. Now, this change is not very pronounced, but it indicates a slight downward trend.
2. Seasonality or Recurring Patterns:
Due to the high-resolution (five-minute intervals) of the dataset, it is difficult to directly observe daily or seasonal patterns. However, exchange rates seem to remain relatively stable over the course of a full day. Although small fluctuations can be observed every few minutes, there is no strong recurrent pattern that stands out over the daily cycle.
3. Outliers in the Exchange Rates:
The dataset doesn't seem to feature significant instances of outliers. Larger fluctuations can be observed, but they appear to be within acceptable range considering the nature of exchange rates. However, at the timestamp "2024-05-02 06:20:02", the exchange rate dropped from 0.05146 to 0.05096, which could possibly be considered as a minor outlier.
In conclusion, the overall trend indicates a slight decrease in the exchange rate over time with very minimal seasonal or hourly fluctuations. The data is relatively stable, with a few noticeable changes that can be considered as minor outliers. Please note that this analysis is merely scratching the surface and a deep dive analysis with more sophisticated tools and methods like autocorrelation, Fourier analysis, and wavelet analysis could be used to better understand the time-series dataset at hand if required.