2024-05-01 Pa Anga 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
This analysis starts from the raw data provided, which includes timestamps and corresponding exchange rates (TOP).Uncovering Overall Trend
The overall trend of exchange rates throughout the dataset can be discerned by plotting the data over time. From the analysis, it's clear that there is a general upward trend in exchange rates from 0.57458 to 0.57867, which indicates a relative depreciation of the base currency. However, it's essential to mention the quite drastic drop in value from 0.57865 to 0.57697 near the end of the dataset, representing an unusual event or possible outlier in the data. The closing rate at the end of the dataset is 0.57697, which is lower than the opening rate of 0.57458.
Identifying Seasonality
Seasonality refers to periodic fluctuations that occur regularly in a data set. Often these can be annual, monthly, weekly, or even daily events. Our data set does not cover a sufficiently extended period (such as multiple years or months) to conduct a comprehensive analysis of long-term seasonality like annual or monthly. However, based on intra-day analysis, there doesn't appear to be a clear pattern illustrating a significant intra-day seasonality in the data.
Analyzing Outliers
Outliers in a data set are values that are significantly higher or lower than most of the other values. In finance, outliers are often caused by specific events that lead to extreme fluctuations in the market. The most evident outlier in our dataset is observed at the end of the dataset, where a sudden drop in the exchange rate occurs from 0.57865 to 0.57697. This drop is significantly worse than the gradual increase that characterized the overall trend.
While we've analyzed the data for trends, seasonality, and outliers, it's vital to interpret these findings in the context of other events and factors. This analysis is limited by the scope of the dataset and does not consider external factors and their possible impacts on the exchange rates.