Summary of Last Month
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
- Standard Deviation:
Overview Of Dataset
The dataset provided reflects exchange rates (KES) recorded at specific time intervals (5 to 15 minutes apart) for a 24-hour period on February 26, 2024. It appears to be high frequency data often used in intraday trading analysis.
1. General Trend of Exchange Rates
Upon initial visual inspection, the KES exchange rate varied between 0.00922 and 0.00941 throughout the day. After starting at 0.00941, it experienced a downward trend until it stabilized around 0.00929, it decreased slightly and maintained a little volatility around the 0.00929 rate for a significant part of the day. Towards the end of the day, the rate further decreased to 0.00922. On the whole, the general trend for this particular day was a slight decrease, with the rate relatively stable for large parts of the day at 0.00929 and later 0.00922.
2. Seasonality or Recurring Patterns
Due to the nature of the dataset (one day of data), it is challenging to identify any significant seasonality or recurring patterns. Seasonality typically requires multiple points of data spread out over longer periods (e.g., months or years) to recognize repetitive cycles. However, an intraday pattern of relative stability during certain hours can be seen.
3. Notable Outliers
Throughout the given day, there appear to be no significant outliers in the dataset, with the exchange rate largely maintaining a range between 0.00922 and 0.00941. Any minor fluctuations within this range seem consistent with regular trading volatility rather than exceptional outliers.
Keep in mind that any analysis conducted based on one day of data may not present a comprehensive understanding of long-term trends, recurring patterns, or potential outliers. A larger dataset covering a more extended period would give more robust, dependable results, accounting for external factors like market opening/closing hours, weekends/holidays, and possible reactions to financial news or economic developments.
As specified, we didn't forecast future rates or consider specific events such as market news or holidays in this analysis and stuck strictly to the data and information provided.