2024-05-22 Norwegian Krone News
2024-05-21
Summary of Yesterday
- Opening:
- Closing:
- Difference of Opening & Closing:
- Daily High:
- Daily Low:
- Difference of Daily High & Low:
Statistical Measures
- Mean:
- Standard Deviation:
Trend
Analysis of Time-Series Financial Data
The given dataset presents a timestamp and exchange rate values of NOK. To provide an overall understanding, let's start by analyzing the NOK exchange rate evolution, looking at its trend, seasonality, and potential outliers. Remember, the interpretation will be purely data-driven and won't take external events or future forecasts into consideration.
1. Overall Trend
Starting from around 0.12725, the exchange rates display a gradual oscillating increase, reaching a peak of 0.12822. After that, rates exhibit a downward trend, dipping to a low point of about 0.12753, before climbing back up towards the end of the dataset. This suggests that there is some volatility in exchange rates, with small peaks and troughs reflecting the market's continual adjustments.
2. Seasonality
Regarding seasonality, it seems that the data doesn't show a clear daily pattern. There's no clear indication of specific times where the rate consistently increases or decreases. The absence of a noticeable pattern may be due to several factors, including market opening and closing hours or the release of key financial news and reports. However, as stated initially, our analysis doesn't take into account these external factors.
3. Outliers
An outlier in a dataset is an observation that lies an abnormal distance from other values in a random sample from a population. The dataset showed a certain degree of consistency with only minor discrepancies, which suggests the lack of significant outliers in the exchange rate data. However, at approximately 2024-05-21 16:55:02 where the rate dropped to 0.12753, this could potentially be considered an outlier considering the overall dataset.
In conclusion, exchange rates fluctuate and can be influenced by a myriad of factors. They tend not to have strict daily patterns, making their movements hard to predict solely based on historical data.