ANG Exchange Rate Witnesses Intriguing Fluctuations Amid Market Volatility
2024-03-11
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
1. Understanding the overall trend of the exchange rates
Looking at the ANG exchange rates across the time series data provided, a decreasing trend can be observed in general during the specified period. The starting rate was 0.74872, whereas it concludes with a rate of 0.74725. This indicates a subtle decline in the exchange rate, signifying a slight loss in strength of the currency. However, it is to be noted that although the overall trend is decreasing, there are periods of fluctuation and volatility during this timeframe.
2. Identifying any seasonality or recurring patterns in the changes of exchange rates
Upon visual inspection of the data, some cyclic patterns become apparent. These could hint at the presence of intra-day seasonality, which is a common attribute of financial time-series data such as exchange rates. To definitively state whether there is a recurring pattern within the daily data, a deeper analysis involving decomposition or autocorrelation checks would be necessary and recommended for the future. As per the available data patterns, it seems the currency tends to fluctuate within a confined range which keeps adjusting with time, indicating a balance of demand and supply forces at play which could be composed of various factors.
3. Noting any outliers, or instances where the exchange rate differs significantly
The dataset provided contains a few distinct instances where the exchange rate suddenly peaks relative to the adjacent data points. Notable peaks appear in data points associated with the timestamp ‘2024-03-11 03:55:02’ and '2024-03-11 05:20:02', where the exchange rate jumps up to 0.75423 and 0.75386 respectively. It is also noticeable at '2024-03-11 15:35:04' with a peak of 0.75426. These sudden fluctuations can be considered outliers and might be the result of high impact economic events or technical aspects such as drastic variations in demand-supply dynamics amongst others. Such outliers can have significant implications if they are frequent because they can mislead the analysis on the general trend and cyclicality of the data. However, in this specific data set, the number of such isolated peaks is minimal and hence their overall impact on the analysis might be contained.
