2024-04-23 Forint News
2024-04-22
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 of Exchange Rates
The given dataset for the HUF exchange rate shows a generally stable rate for the period shown. The exchange rate seems to oscillate between 0.0037 and 0.00372. There are no significant increases or decreases over this period, and the value stays within a small range. The oscillatory behavior suggests that there might be micro-trends in the data set (likely due to business hours or daily trading patterns), but the overall trend is counterbalanced and results in a stable trend.
Identifying Seasonality or Recurring Patterns
To identify seasonal or cyclical behavior in the time series data, we would need to look at data on a finer granularity. Here, with data only available for a single day, it is challenging to discern any recurring seasonal or hourly patterns. However, the granularity of the data suggests that it was likely collected at a regular interval (every few minutes), indicating the potential for intra-day patterns if more days were included.
Outliers in Exchange Rates
From the given data, there appear to be no significant outliers or unusual variations in the exchange rate. The rate remains relatively constant throughout the dataset, fluctuating mainly between 0.0037 and 0.00372. This close range of variation indicates a lack of irregularities or unexpected changes in the exchange rates.
External Factors Influence on Exchange Rates
The time series data provided for analysis correlates to a relatively short period (24 hours). Within this span, it isn’t feasible to observe long-term effects of external factors such as the opening/closing of different world markets, weekends/holidays, or the release of key financial reports. However, it's worth noting that these factors can greatly influence exchange rates in a more comprehensive and extended dataset.
The analysis of this data is based solely on the time-series information provided, ignoring specific events or external factors. For more accurate and nuanced predictions, it's recommended to consider event-based, macroeconomic, and market data in conjunction with time-series analysis.