2024-05-06 Tala News
2024-05-05
Summary of Last Week
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
1. Overall Trend of Exchange Rates
The data provided spans from April 5, 2024, to May 3, 2024. Over this period, the WST exchange rate has seen fluctuation with both periods of increase and decrease. There isn't a consistent upwards or downwards trend. The exchange rate began at a 0.49055 on 2024-04-05 02:00:02, and ended at 0.48816 on 2024-05-03 12:00:02. Despite the various ups and downs over the month, the exchange rate at the end of the period is not significantly different from that at the start, indicating a relatively stable rate.
2. Seasonality and Recurring Patterns
Identifying seasonality or recurring patterns in time-series data typically requires a longer dataset that spans multiple cycles of the expected seasonal period (for example, several years of data to determine annual seasonality). Given the limitation of one month's data, it is difficult to rigorously identify any seasonal trends in the exchange rates. That said, regular daily fluctuations are noticeable in the data which might be related to market opening and closing hours, suggesting possible intraday seasonality.
3. Outliers Analysis
There are few instances in this period, where the exchange rate spikes or dips significantly, such as on 2024-04-10 around 08:00:03 where we can see a sudden increase from 0.49018 to 0.49344, but such instances could be explained as normal market volatility. In general, the exchange rates fluctuations appear to stay within a certain range without any extreme outliers visible in the dataset provided, although a rigorous statistical analysis would be necessary to confirm any potential outliers in the dataset.
Note: While you have asked for excluding any external factors like market hours or financial news, these factors can often significantly influence the exchange rates and would typically be considered in a comprehensive analysis on financial data.