2024-05-01 Latvian Lats 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
1. Understanding the overall trend of the exchange rates
From the data provided, the exchange rates seem to follow an increasing trend overall. This is indicated by the fact that the closing rate (2.27802) is higher than the opening rate (2.26182). While there are fluctuations throughout the day, and even within segments of the same day, the general movement is upward. However, this alone isn't enough to predict future performance and should be corroborated with other analysis methods for a more reliable conclusion.
2. Identifying any seasonality or recurring patterns in the changes of exchange rates
As for seasonality or recurring patterns, from the data given, it's not immediately clear if there is any specific seasonality that can be observed. The data provided might not cover a full enough time range to establish any consistent seasonal effects or recurring patterns. Financial data tend to need longer term evaluation for seasonality to become evident. To establish any sort of pattern, a more in-depth algorithmic analysis or visualization such as a time series decomposition or autocorrelation function can be applied to search for redundancies or repeating patterns.
3. Noting any outliers or instances where the exchange rate differs significantly from what would be expected based on the trend or seasonality
Notable outliers can be seen around the 07:40:02 timestamp. There is a significant jump in the exchange rate from 2.26091 to 2.2686. Additionally, there's a sharp increase in the rates at the 08:00:04 timestamp (from 2.26893 to 2.27056). These outliers could be the result of market anomalies, unexpected news, or other unforeseen factors affecting the currency exchange. It's always important to remember that time series data, especially financial data, is often prone to random fluctuations and noise, thus, any deviation should be viewed critically and comprehensively.
It's crucial to further investigate these outliers to understand their causes, as they could potentially lead to more precise future trend predictions or identifying systematic errors in recording data.
