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

1. Understanding the overall trend of the exchange rates

Looking at the data, it appears that there is a general trend of slight increase in the exchange rate from April 2024 until the end of the data in late April 2024. The eyeballing method might not give us the most accurate results but nevertheless, it is indicative of a larger trend. The rate appears to start at approximately 0.01022 and slowly increases to reach 0.01012 over the course of the period. While these changes are relatively small, they indicate a slight appreciation of the KES currency against whatever currency is being compared against over this period.

2. Identifying any seasonality or recurring patterns in the change of exchange rates

It's relatively difficult to discern any clear seasonality or recurring patterns in this dataset. This is mostly due to the short timeframe (just over a month), as exchange rate changes are often driven by longer-term economic and financial factors. While there's slight volatility evident in the data, it doesn't seem to follow a predictable or recurring pattern within the timeframe. Please note that larger datasets (typically including several years of data) would be needed to identify meaningful seasonal patterns in exchange rates, particularly as these rates can be influenced by a variety of cyclical economic factors.

3. Noting any outliers in the exchange rates

While there is some variation in the exchange rates over the period, there are no true outliers or instances where the exchange rate demonstrates a dramatic shift from the existing trend. The rates generally vary between 0.01010 and 0.01028, which suggests moderate volatility but no extreme shocks or unexpected shifts in rates. However, it's important to keep in mind that even small movements in exchange rates can have significant implications in financial markets, particularly for investors and companies engaged in international trade.

Note that while some fluctuations might seem larger relative to the immediate previous data points - such as the jump from 0.01045 to 0.01068 observed at one point - these don't represent true outliers relative to the overall range of exchange rates in the dataset.

It's also noteworthy that identifying outliers in exchange rate data can be tricky, because what appears to be an unusual swing might be due to a variety of external factors such as abrupt economic news or policy changes, geopolitical events, or even trading errors.

For a more nuanced analysis of the data, we might need to incorporate a wider range of statistical measures such as the standard deviation or other measures of volatility, or applying more advanced analytical methods such as time series decomposition or machine learning algorithms.