2024-04-29 Denar News
2024-04-28
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
Given that we have a time-series dataset, depicting the change in MKD exchange rates over time, let's start by identifying the overall trends, finding recurring patterns (seasonality), and noting any outliers.
Overall Trend Analysis
The MKD exchange rate begins with a value of 0.0237 on 2024-03-29 02:00:02 and ends with a value of 0.02375 on 2024-04-26 14:00:01. Though there are fluctuations within this time frame, the rate seems to have a fairly consistent value with very minimal changes overall. There is a slight uptick in the rate around the 2024-04-04 mark, reaching a month's high of 0.02403 at 2024-04-09 10:00:03, however, it doesn't seem to indicate a significant upward or downward trend over the given period. Therefore, the trend can be said to be essentially flat.
Seasonality Analysis
As the data spans around a month, unlike other data such as yearly sales data, it does not provide a clear opportunity for demonstrating seasonality like quarterly or yearly fluctuations. However, the intra-day fluctuations might be examined for patterns. At a cursory glance, there doesn't appear to be a clear recurring pattern on a daily or weekly basis but it would require a more detailed investigation to confirm.
Outliers Analysis
If we consider an outlier to be a rate that deviates significantly from the rates immediately preceding and following it, there are few instances that may qualify. For instance, on 2024-04-10 08:00:03, the exchange rate spiked to 0.02409, making it the highest rate in the month and a significant jump from the previous rate of 0.02393. But it immediately receded back to 0.02389 about 2 hours later. This might be influenced by a number of factors and would require further analysis to comprehend fully. However, the general rate change throughout the period does not show a lot of outliers.
Further in-depth analysis using appropriate statistical methods and models can help obtain a better understanding of the dataset.