2024-05-22 Zloty News
2024-05-21
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Data Overview
The dataset provides time series data of exchange rates (in PLN) taken at different timestamps. Based on a preliminary look at this data, it appears all data points appear at fairly regular intervals.
Trend of The Exchange Rates
By quickly parsing through the given data, there doesn't appear to be a distinct overall trend in exchange rates. The values fluctuate marginally, staying confined to a narrow range. Without conducting specific numerical measures of trend such as moving averages, it's challenging to identify if the currency is appreciating, depreciating, or remaining stable. It would be necessary to plot these values or conduct further statistical analysis to get a deeper insight.
Seasonality or Recurring Patterns
The given data is not enough to derive certain conclusions about potential recurring patterns or seasonality. As the data spans across a single day, it is impossible to correctly determine the presence of weekly or monthly patterns. For a robust analysis of seasonality, it would require daily data for several years. However, there might be intraday patterns given that different global financial markets open/close at different times. Observing patterns in smaller intervals (e.g., hourly, every few minutes) may also reveal certain intraday trends or patterns.
Outliers
In terms of outliers, there do not appear to be any significant instances where the exchange rate deviates notably from the overall range of data at least in this specific set. The rate doesn't take on any unexpected values or any sharp peaks or troughs that can imply an outlier. However, a more statistical approach such as box plots or establishing an acceptable deviation from the mean/median may better highlight outliers in the data.
Overall Analysis
The provided dataset offers interesting insights but needs further in-depth analysis to produce valuable conclusions about trends, patterns, and outliers. Important to note is that exchange rates are prone to numerous influencing factors, including macroeconomic indicators, geopolitical events, and market sentiment. Therefore, a holistic view encompassing broader market happenings could help us understand the underlying drivers of change in the exchange rates observed in this dataset.