2024-05-17 Quetzal News
2024-05-16
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 Trend of the Exchange Rates
The overall trend of the GTQ exchange rates across the provided dataset seems to be generally stable with slight probable fluctuations. Considering the first and the last exchange rates given in the dataset, we see that the value starts at 0.17627 and ends at 0.17525. Over this long duration, the change in exchange rate is not very substantial, hence, we can observe a strong sense of stability despite minor ups and downs. Hence, overall the changes in the exchange rates over time can be classified as 'moderately unstable'.
Seasonality or Recurring Patterns in Rates
Identifying seasonality or recurring patterns in such a large set of data can be complex. However, based on the provided data, there does not appear to be any distinct, recurring patterns in the exchange rates. The rates exhibit changes that do not seem to follow a weekly, or monthly pattern. This could be because changes in exchange rates are determined by many factors including inflation rates, interest rates, public debt, political stability and economic performance among others. As these factors are inherently unpredictable, the exchange rates may also exhibit trend-less fluctuations.
Outliers in the Data
Outliers in financial data, like the one provided, can result from various factors such as market shocks due to financial news, government policy announcements, etc. Looking at the dataset provided, no significant outliers, which would indicate a massive surge or dip in the exchange rates, are immediately visible. Nevertheless, for a more precise detection of outliers, further statistical exploration and treatment using methodologies such as IQR (Interquartile Range), Z-score, and the Hampel Identifier can be done.
In the absence of further information
As the explicit request was to ignore external events like market opening/closing hours, weekends/holidays, and financial news, the analysis was carried out based purely on the numbers provided. It is important to understand that real-life projections should indeed consider such external factors as they do have significant implications on the financial markets.
Proviso For The Analysis
It is important to note that while the determination of trend, seasonality, and outliers has been done based purely on the provided dataset, absolute precision can only be achieved utilising advanced quantitative techniques such as time series analysis, regression analysis, among others. Also, the dataset seems to have been recorded at an interval of 5 minutes; this high-frequency data can lineup local minor temporal variations shadowing macro trend and significantly limit pattern analysis without sophisticated statistical methodologies.