2024-04-23 Tugrik 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
Analysis of Time-series Data: Trending, Seasonality, and Outliers
Firstly, the MNT exchange rate appears to be constant throughout the entire dataset. The value for MNT remains at 0.0004 for all timestamps given, indicating a trend of stability in the exchange rate over the period shown. Generally, exchange rates fluctuate due to aspects such as inflation rates, interest rates, country’s debt levels, terms of trade, political stability and economic performance among others. However, in this dataset, no change is observed in the exchange rate. This could be due to the way the data is sampled, or extraordinary stability in the external factors which typically influence an exchange rate.
Seasonality in the dataset
As there are no fluctuations in the value of MNT exchange rate data provided, no seasonality or recurring patterns are apparent. Usually, seasonality would be manifested as specific patterns occurring at regular intervals over time in the dataset. This might not be the case in this dataset due to the absence of fluctuations and hence the possible absence of certain external influences.
Outliers in the dataset
Similarly, due to the constant exchange rate in the dataset, there are no exceptions or instances that deviate from the trend indicating there are no outliers in this dataset. Outliers would typically appear as extreme values that are noticeable against the trend of the data, but as the data is identical for all timestamps, no such cases exist in this situation.
In conclusion, the dataset shows a stable MNT exchange rate with no observable seasonality or outliers. However, it is rare for financial time-series data to show no change over time, so it might be useful to review the data collection and sampling techniques used to gather this dataset.