2024-05-01 Riel News
2024-04-30
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Analysis of the Dataset
Upon initial inspection of the provided dataset, it can be observed that the dataset consists of timestamped exchange rates in KHR. This information is a time series, with timestamps recording the fluctuations in exchange rates at various moments throughout the day and across a range of days within the month of April 2024.
Understanding the Overall Trend
Interestingly, the exchange rates provided in the dataset show no changes throughout the observed period. Each timestamped rate is recorded at 0.00034. This indicates an unusual stability in the exchange rates, which generally tend to fluctuate due to a myriad of influencing factors. However, based solely on this dataset, the trend is characterized by a constant exchange rate.
Seasonality or Recurring Patterns
Since the exchange rate remains constant throughout the recorded period, there are no discernible patterns of seasonality or recurring changes. Typical seasonality or patterns in exchange rates might include daily fluctuations correlated with the opening and closing hours of financial markets, or longer-term trends associated with broader economic cycles. These are not evident in the provided data.
Outliers or Noteworthy Instances
As the exchange rate remains unchanged throughout the entire data set, there are no outliers or deviations from the observed trend. All recorded exchange rates of 0.00034 fall exactly on this trend. Typically, in a more varied dataset, instances where the exchange rate differs significantly from the trend or seasonality would be noted as outliers. However, none such instances can be pointed out in this data.
In conclusion, while this dataset provides an accurate record of the exchange rates at specific times, its characteristic of a constant rate throughout the recorded period precludes more in-depth trend analysis, identification of recurring patterns, or the notation of outliers. Given different data with more varied rates, a richer, more insightful analysis could be undertaken.