PHP Continues to Slide Against USD in Intriguing Forex Movement
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
Overall Trend of Exchange Rates
After analyzing the data from 2024-04-12 to 2024-05-10, we observe a general downward trend in the PHP exchange rates. The rate started from 0.02426 on 2024-04-12 and ended at 0.02372 on 2024-05-10. This suggests that over this period, the exchange rate for PHP generally weakened against the reference currency.
Seasonality or Recurring Patterns
Regarding seasonality patterns, it isn't evident from the dataset without detailed analysis guided by factors such as day of the week, month, or any other time-based variables. Moreover, a time series of about a month is too short to identify any seasonality or recurring patterns. To establish seasonality, we need to observe the data across that potential recurring time frame, be it a month, quarter, or a year. Therefore, information from a longer period is needed to identify any seasonality in the data.
Identification of Outliers
In observing the data, the exchange rates are all within the same range, and there don't appear to be any significant outliers or instances where the exchange rate differs significantly from the trend. However, without a statistical test or visualization like a boxplot, conclusively identifying outliers is challenging. It is recommended to use such methods for a more precise identification of outliers.
External Factors Analysis
Your instructions indicate that we are not considering the specific trading hour, weekend/holiday effects, or the release of key financial news and reports as our analysis's external factors. For a more comprehensive analysis, such considerations are necessary as they may have a substantial impact on exchange rate movements.
Recommendation
This analysis provides a basic understanding of the trend and the need for a more extended data period to identify any seasonal patterns. It also points out the importance of a thorough external factor analysis and use of proper statistical tools for outlier identification. Consequently, it provides insights into the additional steps required for a more comprehensive analysis.
