2024-05-01 Azerbaijanian Manat News
2024-04-30
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Analysis of Exchange Rates
In order to analyze the trend, one would visually represent the given data points on a time series graph. This analysis solely focuses on the numerical data provided ignoring any external factors such as holidays, news, and reports.
1. Overall Trend
The overall trend of the exchange rates can be inferred by the inspection of data points over the entire period. Ideally, if the rates increase over time then the trend is positive, if it decreases then the trend is negative, otherwise, if it remains relatively stable the trend is considered flat or stationary.
2. Seasonality and Recurring Patterns
Time series data often exhibits regular patterns over time. This could be the case in our dataset. To ascertain this, we might want to look for periods where there are consistent, regular fluctuations in exchange rates. If such fluctuations are present and recur over a fixed period, then we can say that there is a seasonality or recurrent pattern in the data.
3. Outliers in the Data
Outliers, in the context of time-series data, are point-values that are markedly different from the expected value based on the trend or seasonality. To identify such outliers in the data, we would calculate an expected value for each point, based on the trend and/or seasonality. Any data point that deviates significantly from its expected value could be regarded as an outlier.
To note, fluctuation of exchange rates is a natural occurrence in currency markets due to a variety of factors, including changes in supply and demand, interest rate, inflation, and political stability, and the presence of outliers doesn't necessarily indicate a problem or anomaly needing correction.
Towards analysis of financial time-series data, it's also important to consider the concept of volatility: the degree of variation of a trading price series over time. High volatility often signifies increased uncertainty or risk.
In conclusion, your time-series data of exchange rates requires careful examination and interpretation considering the above principles. It is recommended to visualize the data which will provide a clearer image of the trend, seasonality, and outliers present in the data.
