2024-04-22 Cayman Islands Dollar News
2024-04-21
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
Data Analysis Overview
The given dataset is a time-series data that explains the fluctuation in exchange rates (KYD) at different timestamps. Herein, initial observations indicate that the data does reflect changes in rates over a specific period. In this analysis, I shall investigate the overall trend of the exchange rates over the given period, identify potential seasonality or recurring patterns, and spotlight any potential outliers in the data.
1. Overall Trend Analysis
The overall trend of the exchange rates generally seems to fluctuate quite a bit. The data indicates a series of ups and downs but with no precise constant trend. The fluctuations could imply market volatility during the recorded period. It is not accurate to claim that the trend generally increases, decreases, or remains stable over the period shown as it varies considerably throughout the dataset.
2. Seasonality and Recurring Patterns
As for seasonality or recurring patterns, the data over the defined period doesn't suggest any apparent seasonality. The rates seem to fluctuate irrespective of the time of day or specific timelines. This lack of seasonality might be due to the dataset's narrow timespan, which may not encapsulate seasonal aspects. Therefore, it would be inappropriate to speculate or conclude any seasonality patterns based on the presented dataset.
3. Outliers Identification
The fluctuations in the exchange rates seem to be significant at times. Some high jumps and drops can be viewed as outliers, particularly where rates differ meaningfully from recent values. Remember, these fluctuations may be influenced by various contributing factors, including reaction to change in policies, global events, and economy indicators which, at this point, we are not considering.
In conclusion, a more detailed, specific approach using econometric modeling, for instance, ARIMA models, or machine learning algorithm would be required to derive a more quantitative analysis and predictive insights from the provided time-series data. Another recommended approach would be to consider external factors such as market news, economic indicators, and fiscal policies while analyzing the data.