2024-04-29 Naira 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
Data Analysis
First and foremost, the given dataset is a time series data representing the fluctuation of NGN (Nigerian Naira) exchange rate over specified timestamps stretching from March 29, 2024, to April 26, 2024.
Trend Analysis:
Based on the data provided, it can be seen that there's a general increase in the exchange rate during this period. It started from a low of 0.00097 on March 29, 2024, and climbed to a high point of 0.0012 on April 16, 2024. This uptrend is marked by slight fluctuations along the way, but the overall trajectory remains upwards.
Seasonality and Recurring Patterns:
During the period of analysis, the dataset does not show discernible seasonality or recurring patterns, which could be because the data covers only one month. For seasonality to become evident, a more extended period may be required. However, there appear to be slight recurring patterns within daily trades, with some minor variations in the exchange rate occurring around similar timeframes daily.
Outliers Analysis:
With respect to the defined range, the data does not appear to have significant outliers. The values remain within a relatively narrow range, and there are no major spikes or dips that could be classified as outliers. Any slight variations that occur are consistent with the normal dynamics of currency exchange rates, which are influenced by a myriad of factors.
However, there are a couple of significant increases in the NGN rate, reaching the highest point at 0.0012 - first on April 15, 2024, and maintaining the same till April 16, 2024. This peak falls within the dataset's overall trend but represents a noticeable rise compared to prior and subsequent rates.
Note: This analysis concentrates solely on the numerical trends within the dataset and does not consider potential external influences such as market news, political events, economic indicators, etc.