2024-04-18 Dong News
2024-04-17
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Overall Analysis
On analyzing the given dataset, an immediate observation is consistent, the VND exchange rate over the provided period. In every case and timestamp, the given rate is '5.0E-5', which indicates there is no fluctuation, increase, or decrease in the exchange rate during this period. The exchange rate appears to remain completely stable over the duration of the timestamps provided, which is an extremely rare scenario in real-world foreign exchange markets, which are typically marked by frequent fluctuations.
Trend Analysis
Usually, trend analysis involves observing whether exchange rates increase, decrease, or stabilize over time. However, in this case, there is no discernible pattern or trend at all since the rate remains persistently constant. Given that our dataset does not depict any variety or variation, we cannot determine a trend in the usual sense of the term.
Seasonality
Just like with the trend analysis, we encounter a similar situation when observing for seasonality, i.e., recurring patterns over specific periods. It's usual to note periods during which the rates typically increase or decrease (daily, weekly, monthly, etc). However, due to the static nature of the data provided where the exchange rate remains stable at a constant value, we could not identify any discernible seasonal patterns.
Outliers
Outliers are usually individual data points that diverge significantly from the rest and thus, can heavily influence the final analytical results. However, in this dataset, since there are no variations or changes in the exchange rate at any point, no outliers can be identified. The data is uniform without any data point bypassing the consistent value of '5.0E-5'.
In conclusion, the provided dataset does not offer much insights in terms of trends, seasonality or outliers due to the constant exchange rate value across all timestamps. For a more accurate and detailed analysis, it's advisable to use a dataset that reflects the dynamic nature of the forex market.