BTC Exchange Rate Shows Volatility in Bittersweet Day for Investors
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
Understanding the Overall Trend of Exchange Rates
The overall trend of the exchange rates seems to be highly volatile with both upward and downward movements throughout the given period. Since there is no information about the start and end times, it's difficult to summarize the general movement. However, a look at the raw data suggests that the exchange rate of BTC showed distinct periods of both increases and decreases over the given period. The maximum exchange rate recorded is 97403.91299, and the minimum is 94264.73489.
Identifying Seasonality or Recurring Patterns
Without a given time period or more specific date data, identifying seasonal or recurring patterns in this times series data is rather challenging. With the current dataset we have, the data appears random and doesn't display any significant recurring trend or seasonality. Applying a more sophisticated time series analysis or providing more specific date data could potentially reveal such patterns.
Noting Any Outliers
Outliers in time series data are typically sudden, unexplained spikes or drops that do not align with the overall trend. Given the high volatility of BTC exchange rates, such outliers may be common. Looking at the raw data, there are indeed instances where there are significant drops or rises within a small period, but without having a robust statistical model, pinpointing these outliers would be complex.
It's also essential to understand that in financial markets, what may appear as outliers could actually be the results of various market events or news.
Please note that providing more precise timestamps and a larger dataset would allow for a more thorough analysis, and more advanced statistical methods might reveal additional insights like trend decomposition or autocorrelation.