2024-04-16 Moroccan Dirham News
2024-04-15
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
Overall Trend Analysis
Following a review of the dataset, it's observable that the exchange rate keeps changing from the start of the historical observations until the end. The trend, however, is not clear just by looking at individual data points. A mathematical approach, such as running a linear regression over the time series, would be necessary to determine if the overall trend is significantly increasing, decreasing, or remaining stable.
Seasonality and Recurring Patterns
In any time series data, seasonality refers to predictable and recurring patterns that occur periodically over time. These could be daily or hourly patterns based on market opening and closing hours, weekly patterns depending on the days of the week, or even monthly and annual patterns. Looking at the dataset provided, it's not immediately clear if there is a certain time of day or day of the week when the exchange rates tend to be higher or lower. Deeper analysis using time series decomposition models can provide more insight into any possible seasonality in this data.
Outliers Analysis
Identifying outliers, or observations that deviate significantly from the other observations, is a key aspect of time series analysis. Outliers could be due to data errors, or they could represent legitimate but rare large changes in the exchange rate. Visual methods such as box plots or standard deviations can be used to detect outliers. In this dataset, without any specific calculations or visuals, it's difficult to pinpoint the exact outliers. However, applying these methods can help to identify and understand them
Please note: To make more precise conclusions on trends, seasonality, and outliers, a more advanced analysis using dedicated statistical software or programming languages with statistical capabilities would be needed. This would allow for use of algorithms and models specifically designed for time series data.