2024-05-13 Azerbaijanian Manat News
2024-05-12
Summary of Last Week
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Before we begin, it's important to note the format of the data provided and the variables it contains. The dataset is a time series, with timestamps in the format 'YYYY-MM-dd hh:mm:ss'. The variable 'azn' represents the exchange rate at each corresponding timestamp. The analysis will focus on identifying trends, patterns, and outliers in the exchange rate, without considering external factors like market timing, holidays, or financial news events.
1. Understanding the Overall Trend
The overall trend of the exchange rate can be discerned by looking at the start and end points of the data as well as the general direction of the data in between. Upon visual inspection, the exchange rates show a degree of volatility, indicating up and down swings throughout the period. However, it's worth noting that the rates at the beginning and end of the period are not significantly different, suggesting that, overall, the rates may have remained relatively stable.
2. Identifying Seasonality and Recurring Patterns
At first glance, there doesn't appear to be a clear, predictable pattern or seasonality in the data. The exchange rates fluctuate both up and down throughout the course of the period. However, a more thorough time series analysis may reveal subtle recurring patterns or cycles that aren't immediately obvious. This could involve dividing the data into smaller chunks and comparing the patterns within each chunk.
3. Noting Any Outliers
Outliers in this context would be instances where the exchange rate differed significantly from what might be expected based on the surrounding data points. There are a few potential outliers in this dataset. These include the point at 2024-04-16 14:00:03, with a notably high value of 0.84559, and the points at 2024-05-02 04:00:02 and 2024-04-26 02:00:02, with comparatively low values of 0.79772 and 0.79858, respectively. These outliers suggest instances of significant volatility in the currency market.
This initial analysis provides the basis for a deeper investigation, and further statistical techniques can be applied to extract more complex patterns or to validate the observations made. Please note, however, that currency markets are affected by a multitude of factors, and this simple analysis doesn't take into account many potentially key influences.