2024-04-16 Moldovan Leu News
2024-04-15
Summary of Last Month
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Overall Trend Analysis
From the data provided, it seems that there is a ranging trend with slight fluctuations in the MDL exchange rates over the time period of the data set. The rates do not show any significant rise or fall. However, some minor fluctuations can be observed. Initially, the rates start at 0.07795 and remain around this value with little deviation until around the 06:25:02 timestamp at which point there's a noticeable increase in the exchange rate to around 0.07798. The rate also peaks at around the 09:15:03 timestamp with a rate of 0.07809. It is observed to slowly climb its way to a maximum of 0.07829 noted at the 19:55:02 timestamp before it starts to decrease again and stabilizes at around 0.078 by the end of the dataset.
Seasonality and Recurring Patterns
In terms of seasonality or recurring patterns, due to the granularity of the data (every 5 minutes), it is difficult to observe clear daily or weekly trends without further statistical analysis. However, on a minute-by-minute basis, it does not seem to indicate a clear pattern or cycle at this level of detail. If a wider timeframe were available, such as few months or years, clear patterns might be more discernible.
Outliers Analysis
In the provided time series data, there don’t appear to be explicit notable outliers. The data seems to oscillate around a mean without any unexpected spikes or troughs. Any noticeable fluctuation in the exchange rates seems to be a part of the overall trend and does not stand out as a significant deviation or outlier. Given more data or a wider variety of measures (such as trading volume or other related forex pairs), outliers might be easier to notice.
Given the nature of the provided dataset, it is critical to note that specific external factors might influence the fluctuation in rates, such as market opening/closing hours, weekends/holidays, or the release of key financial news and reports. While these have not been explicitly considered in this analysis, they can play key roles in the accurate interpretation of time series financial data.