Summary of Yesterday
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
- Standard Deviation:
Comprehensive Analysis of the MOP Exchange Rate Time Series Data
The data provided represents the changes in the MOP exchange rate over different timestamps. To gain a deeper understanding of the trends and patterns within the data, the analysis was completed in three separate sections: overall trends, seasonality or recurring patterns, and the identification of any outliers.
1. Overall Trend of Exchange Rates
An examination of the entire dataset reveals the existence of a slightly increasing trend in the exchange rates. The values, starting at approximately 0.16726, do not remain constant but display a small and gradual increase where the rate culminates at about 0.16751. Despite short-term fluctuations, the overall trend indicates an increase in the MOP exchange rates during the period captured in the dataset.
2. Seasonality and Recurring Patterns
Given the nature of the data, it is challenging to determine seasonality as the dataset isn't straightforwardly seasonal (such as sale rates that tend to spike during certain seasons). However, based on the timestamps provided, there aren't any noticeable recurring patterns.
3. Outliers in The Exchange Rates
An outlier is a data point that significantly differs from the other observations. Such significantly different values can heavily impact the mean and standard deviation of the data, rendering a misleading representation. Upon reviewing the provided dataset, it is difficult to discern any clear outliers. The variations in the exchange rates are relatively minute, suggesting a stable rate with limited volatility.
In conclusion, the scientific analysis of this time series data has indicated a gradual increase in the MOP exchange rates over the time frame captured. However, no clear seasonality or recurring patterns were identified, and no discernible outliers were found within the data points provided.
Please note, this analysis was conducted purely on the provided dataset and did not factor in the potential impact of external factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports, as per the initial request.