2024-04-23 Convertible Mark News
2024-04-22
Summary of Last Month
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Data Structure
This dataset seems to be consisting time-series financial data with 1 day of data points, precisely calculated at every 5-minute interval. The data also contains exchange rate values ranging from 0.74505 to 0.74836 for the given day.
Trend Analysis
The financial time series data needs to be plotted graphically to understand the trend. Here, the trend can be analyzed during each interval of the day, on an average. The exchange rate illustrates a minor fluctuation within the range of 0.74505 to 0.74836 without a significant upward or downward trend.
Seasonality
Seasonality refers to regular, predictable changes in a time series that occur within particular intervals. In the context of this data, since we have only one day of data points, we will need more data to determine if there is any seasonality in currency exchange rate change. Traditionally, financial data like this one may exhibit intra-day seasonality, where certain trends can repeatedly show up at specific times within the day. However, identifying such patterns requires detailed intraday data analysis.
Outliers
Outliers in a dataset are values that excessively deviate from the normal range of the data. These could be caused by a myriad of factors, such as market anomalies, major financial news events, errors in data collection, etc. In the given data, without descriptive statistics or a visualization, it's hard to identify any potential outliers just from the raw figures. Proper graphs or statistical analyses can help in identifying any extreme jumps in the exchange rate that stand out from the rest of the data.
Conclusion
In conclusion, the dataset provides a high-resolution snapshot of the changes in exchange rate within a single day. Although the data doesn't seem to demonstrate a clear overall upward or downward trend, there's a slight fluctuation in the exchange rates throughout. Without larger timescales and more data points, it is challenging to identify clear seasonality or outliers. For a more in-depth and accurate analysis, extending the data range, including data visualization, and deep descriptive statistics or advanced analyses such as time series decomposition or Fourier analysis could be considered.
