Stability Reigns as AMD Exchange Rate Exhibits Minimal Shifts
2024-05-01
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 Exchange Rates (AMD):
Looking at the provided data, specific observations can be made relating to the trend, seasonality, and the presence of outliers in exchange rates. The data is time-stamped and describes the exchange rate fluctuations of the given currency (AMD) over time. It should be noted that all given information derives solely from a thorough analysis of the data as provided, and doesn't factor in any potential effects of external factors such as market opening/closing hours, weekends/holidays, or the release of key financial news and reports. There will also be no forecast for future rates provided in this analysis.
1. Overall Trend:
From the exchange rates data, it can be observed that the values mostly remained stable over the provided timestamps. The rate starts at 0.00353 and maintains at this value until the timestamp 2024-05-01 06:25:02, where it increased to 0.00355. The rate again remains consistent until 2024-05-01 13:25:03, decreases to 0.00354, and changes to 0.00353 briefly at 2024-05-01 13:55:03. Since then, the rate oscillates between 0.00354 and 0.00355 until the end of the given dataset.
2. Seasonality:
There appears to be no clear seasonal pattern observable in the provided data. The exchange rate's slight fluctuations occur seemingly randomly throughout the dataset without any discernible time frames wherein these variations tend to occur. This absence could potentially be due to the relatively small range of data provided, that might not be sufficient to determine longer-term seasonal trends.
3. Outliers:
Based on the provided information, no notable outliers can be identified. The data points hover around the mean exchange rate value of roughly 0.00354 with little deviation, hence no data point can be categorised as significantly distinct or extreme.
Do consider, though, that the absence of extreme outliers in this dataset doesn't necessarily imply the absence of potential anomalies in a larger dataset. It is always recommended to further investigate larger datasets spanning longer periods for a more comprehensive understanding and detection of possible outliers.