Aruban Florin Forecast

Not for Invesment, Informational Purposes Only

Summary of Yesterday

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  • Closing:
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  • Daily High:
  • Daily Low:
  • Difference of Daily High & Low:

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Overall Trend:

    The dataset shows that the exchange rate over time oscillates within a quite narrow range with the minimum value being 0.75134 and the maximum value being 0.75537. However, generally, the trend of the data set could be seen as relatively stable as it doesn't witness large fluctuations within the given timeframe.

    Seasonality or Recurring Patterns:

    Looking into the dataset, it is hard to definitively state the existence of seasonality or recurring patterns just based on the provided dataset. This is due to the fact that fluctuations in exchange rates are influenced by myriad factors including market demand, the global economic situation, and financial news or reports. For a clearer picture, a larger data set with a wider time frame will be required. In addition, time series analysis techniques or decomposition methods may be useful to understand seasonality better.

    Outliers:

    Given the tight range in which the exchange rates vary and the consistency of the fluctuations, there don't appear to be obvious outliers or instances where the exchange rate differs significantly from the expected values. The exchange rate seems to follow a consistent pattern of change within the observed period.

    External Factors:

    Although the task does not allow considering external factors such as market opening/closing hours, weekends/holidays, or the release of key financial news and reports, it is important to note, these factors do play a significant role in the movement of exchange rates. Hence, for a thorough analysis or to obtain an accurate forecast, these factors should ideally be considered.

    Moreover, an analysis of this kind usually gives more accurate results when accompanied by visualization tools such as line charts or time series plots, which unfortunately could not be incorporated due to the requested text-based(html) format of the result.

    Lastly, as financial markets are hugely influenced by global events and unforeseen incidents, the analysis could deviate from the expected trend in the presence of such events.

Summary of Yesterday

  • Opening:
  • Closing:
  • Difference of Opening & Closing:
  • Daily High:
  • Daily Low:
  • Difference of Daily High & Low:

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Overall Trend Analysis

    By observing the data, we can see that the exchange rate has a slightly increasing trend from an initial value of 0.75267 to a closing value of 0.75399. It implies that the exchange rate moderately appreciated over the provided time duration. However, the increment was not linear – containing various fluctuations in-between.

    Seasonality and Recurring Patterns

    In terms of seasonality or recurring patterns, given the limited dataset and scope of data (only one day), it's difficult to comment on a larger scale about the seasonality. However, an hourly pattern can be noticed where certain times the exchange rate has shown a tendency to rise or fall, but this needs in-depth hourly analysis.

    Outlier Identification

    Outliers in a dataset are extreme values that deviate significantly from other observations. Observing the dataset, there seem to be no outliers as all the values provided remain in a small range, close to each other. However, this does not mean outliers don't exist. Further statistical analysis is required with robust techniques such as Z-Score or the IQR method to identify any possible outliers.

    Note

    For more precise and accurate analysis, multiple days of data with specific events like market opening/closing, weekends/holidays, release of key financial news would be beneficial as it could impact the exchange rates drastically. The provided data is within too short a range to fully understand the broader picture of exchange rate behavior.

Summary of Yesterday

  • Opening:
  • Closing:
  • Difference of Opening & Closing:
  • Daily High:
  • Daily Low:
  • Difference of Daily High & Low:

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

Summary of Last Month

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Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Overall Trend

    The overall trend of the exchange rates seems to be relatively stable with minor fluctuations. The data begins at a rate of 0.75057 and ends at 0.74910. Although there are slight increases and decreases throughout the dataset, there is no continuous increase or decrease that would signify a definitive upward or downward trend over the observed period.

    Seasonality and Recurring Patterns

    When it comes to time-series data, seasonality refers to predictable and recurring patterns that occur periodically. In this dataset, it's difficult to identify a clear pattern of seasonality within this particular time frame. The rates neither appear to show repetitive highs or lows nor seem to rise or fall during consistent periods. Therefore, it is safe to conclude that no strong seasonality or recurring patterns are detected from this dataset.

    Outliers

    An outlier in a dataset is a value that is significantly higher or lower than most of the other values. From the given dataset, there are no such instances where the exchange rate differs significantly from the remaining data. All values fall within a relatively close range of each other, with no rates diverting significantly. Hence, no obvious outliers could be identified in this dataset.

Summary of Last Week

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Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Before carrying out the analysis, it is important to note that the data presented is in timestamp format and AWG exchange rate. The data will be evaluated in the light of three specific objectives: Understanding the overall trend of the exchange rates, identifying any recurring patterns in the changes of exchange rates, and noting any outliers. This analysis does not consider any specific event or external factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports. Plus, it does not generate any forecast for future rates.

    1. Understanding the Overall Trend of the Exchange Rates

    The data shows the fluctuations in the AWG exchange rate over an unspecified period. A close look at the values indicates a mix of increases and decreases without a clear, consistent trend of either a general increase or decrease. However, the exchange rate does not appear to remain entirely stable, but instead, it shows moderate fluctuations.

    2. Identifying Seasonality or Recurring Patterns

    Identifying any seasonality or recurring patterns in the exchange rates involves examining the data for any repeated cycles of increase or decrease. At a glance, this data appears to be random without a clear cyclical pattern. However, a deeper statistical analysis might reveal subtle underlying patterns or cycles not immediately perceptible through a cursory examination.

    3. Noting Any Outliers

    Outliers in this context would be instances where the exchange rate differs significantly from the general trend. Considering the mixed nature of the trend, determining an outlier might require more specific parameters. However, a significant drop or spike could potentially be considered an outlier. A more detailed analysis involving statistical techniques such as standard deviation or Z-score could help in outlining such instances distinctly.

    In conclusion, the AWG exchange rates presented here exhibit a somewhat erratic pattern with fluctuations but without a clear trend, seasonality, or obvious outliers based on a cursory examination. To gather more detailed and accurate insights, a rigorous statistical analysis would be recommended.

Summary of Yesterday

  • Opening:
  • Closing:
  • Difference of Opening & Closing:
  • Daily High:
  • Daily Low:
  • Difference of Daily High & Low:

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    1. Understanding the overall trend of the exchange rates

    Given the timestamps and corresponding AWG (Aruban Florin) exchange rates, it appears that the overall trend of this currency is incrementally increasing over time. The AWG begins at 0.74851 and ends at 0.75004 between 2024-02-19 01:00:02 to 2024-02-23 14:00:01, usually fluctuating around the starting value. This indicates a small tendency towards an increase.

    2. Identifying any seasonality or recurring patterns in the changes of exchange rates

    Initial observation does not indicate any noticeable seasonality or recurring patterns within this dataset. The data points show minor up and down fluctuations but without a clear repeating cycle. However, confirmation would require further statistical analysis such as decomposition or spectral analysis. At this level of granularity, the changes seem to be driven more by inherent financial market volatility rather than by seasonality effects.

    3. Noting any outliers, or instances where the exchange rate differs significantly from what would be expected based on the trend or seasonality

    Given the relatively stable behavior of the AWG throughout the timestamps provided, there don't seem to be any significant outliers in this data set. However, it's noteworthy that the exchange rate did encounter a dip to 0.74719 on 2024-02-22 03:00:02, before recovering to the previous levels. This could be indicative of market volatility during that specific time. These dips and rises though notable, do not represent outliers as such and can be considered as part of the overall complex movement of the financial market.

    To conclude, understanding financial time-series data, such as exchange rates, requires nuanced analysis and a thorough understanding of the financial milieu. Overall, the AWG appears to be slightly appreciating over time, with no clear patterns of seasonality observed. Some dips and jumps are observed, but they are most likely a reflection of common market volatility.

Summary of Yesterday

  • Opening:
  • Closing:
  • Difference of Opening & Closing:
  • Daily High:
  • Daily Low:
  • Difference of Daily High & Low:

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    1. Understanding the overall trend of the exchange rates

    The first part of the analysis focuses on the overall trend of the exchange rates. By examining the data, we can see that the exchange rates fluctuate over time. However, there is a general trend of increase from the beginning of the data set towards the end. The exchange rate begins at around 0.74791 and concludes at 0.75013. Although the rate occasionally declines at certain points, the overall pattern suggests an upward trend.

    2. Identifying any seasonality or recurring patterns in the changes of exchange rates

    Upon close inspection, it doesn't appear that the data shows any clear seasonality or recurring patterns. The trend is generally upwards, but this does not seem to be closely tied to any particular timing or cycle in the data. The data seems to indicate that there are variations in the rates throughout the day, but no clear pattern can be identified solely based on these timestamps. This could mean that there is likely other influences affecting the exchange rates outside of the given time factor.

    3. Noting any outliers, or instances where the exchange rate differs significantly from what would be expected based on the trend or seasonality

    In the provided dataset, there seems to be no significant outliers or deviations from the overall trend. The exchange rate values seem to be fluctuating around a certain range. However, there are few instances where jumps appear to be larger than typical, for instance, around 09:15:03 and 12:00:03. These changes suggest that while the overall pattern in this dataset is relatively smooth, moments of greater change do occur. These could be influenced by various factors not provided in the dataset.