Aruban Florin Forecast

Summary of Yesterday

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Statistical Measures

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Trend

Overall Trend Analysis

After assessing the provided dataset, the overall trend in the exchange rates reveals a gradual decrease. This trend is characterized by minor fluctuations, where the peak rate is 0.76156 and the lowest rate reaches 0.75816. Although there is no sharp increase or decrease within the period, the rates generally decline over time.

Seasonality or Recurring Patterns

Within this specific dataset, clear seasonality or recurring patterns in the exchange rates are not prominent. While some minor fluctuations occur approximately at the same time on different days, these observations do not form significant, deterministic repetitive patterns. Thus, any major decision on rate prediction based on just seasonality within this dataset may not be accurate.

Highlighting Outliers

An outlier is observed at the timestamp of '2024-04-25 07:30:04', where the rate suddenly increases to 0.7601 from 0.75897. This rate is significantly higher than the immediate preceding and succeeding exchange rates. Another similar situation occurs at timestamps '2024-04-25 08:05:03' to '2024-04-25 08:40:02', where the rates go well above 0.7600 which did not follow the gradual decline trend. Such exceptions can be characterized as outliers in this dataset.

In conclusion, the provided dataset overall shows a slow decline in exchange rates. However, there is an absence of clear seasonality or recurring patterns, and a few outliers are present as well. Therefore, any investment or financial decision should consider these factors and possibly integrate more comprehensive and external elements for a more accurate prediction.

Summary of Yesterday

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Statistical Measures

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Trend

Overall Trend of the Exchange Rates

The data indicates few ups and downs in the exchange rates over the given timeframe. Generally, the rates started from 0.75919 and ended at 0.75960, showing a slight increase. There are regular fluctuations in rates ranging from a low of 0.75902 to a high of 0.76221. The general trend seems to be somewhat consistent with slight increments in the exchange rates.

Seasonality or Recurring Patterns

This analysis does not indicate any clear-cut seasonal or recurring patterns in this dataset. The exchange rates are regularly changing throughout the entire time period, going both up and down without a specific identifiable pattern. While there are some repeated fluctuations, these do not seem to be tied to a specific time or cycle. If there's any existing seasonality, it is likely to be data-driven and may require more sophisticated techniques to detect.

Outliers

There are few instances where the exchange rate experienced significant jumps. For example, at timestamp 2024-04-24 07:40:03, the exchange rate jumped from 0.76022 to 0.76126, and at 2024-04-24 07:45:03, it jumped again to 0.76168. These instances can be assumed as potential outliers as they show a substantial change in the exchange rate which differs from the normal average increase or decrease based on the surrounding data points.

It is advisable to further analyze these outliers to understand their origin better as they may impact any inferences drawn from this data.

Please note that due to the request, no external factors like market timings, weekends, etc., have been considered.

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Summary of Yesterday

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

Statistical Measures

• Mean:
• Standard Deviation:

Trend

The provided dataset is a set of timestamps and corresponding AWG exchange rates from April 23, 2024. Here is a high-level overview of the observations I made from the data:

1. Overall trend of the exchange rates

The average exchange rate of the AWG started at 0.75997 and ended at 0.75918 over the given period of time. It implies a slight downward trend over that period. However, the changes in the exchange rate are not linear, rather quite fluctuating.

2. Seasonality or recurring patterns

As far as seasonality is concerned, there are no clear patterns upon initial inspection. However, the repeated peaks and troughs in the data suggest slight temporal patterns that might be discerned with more complex time-series analysis techniques.

3. Outliers

The highest value in the data is 0.76081 and the lowest is 0.75791. But without more concrete information on what constitutes a standard deviation in this context, it is difficult to conclusively identify any outliers. However, there doesn't seem to be any value that dramatically differs from the other ones, which suggests the lack of significant outliers.

It is important to note that this analysis does not take into account any external factors such as market opening/closing hours, weekends/holidays, or the release of key financial news because these elements were not requested for considering in this particular analysis. Information compiled from the data is mainly based on observed patterns without any additional contextual reasoning for why these patterns might exist.

It should be kept in mind that while these findings provide valuable insights into the behavior of the exchange rates, they should not be used to generate forecasts for future rates as the analysis was done strictly within the confines of the provided data.

Summary of Last Month

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Statistical Measures

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Trend

Overall Trend Analysis

First, let's look at the overall trend of the exchange rate data from the given time series data. The exchange rate starts from 0.76266 and concludes at 0.75997. From this, it is clear that there is a slight decline in the exchange rate in the given time period. However, it's important to note that this decrease is relatively minor and the rate has seen several fluctuations up and down during this period. Consequently, we cannot consider this trend as a substantial drop.

Recurring Patterns and Seasonality

As for seasonality and recurring patterns, these could typically be observed in daily or hourly cycles in such data. In the current dataset, due to the small amount of timestamps provided, discerning a noticeable or significant seasonal pattern is quite challenging. That being said, smaller fluctuations can be observed on a day-to-day basis. Therefore, further data collection and analysis with a more extensive dataset might reveal more defined patterns.

Outliers Identification

Outliers in this context would be instances where there's a substantial rise or drop in the exchange rate, varying significantly from the surrounding data points. A crucial moment in the dataset is the drop from 0.76213 (timestamp 2024-04-22 11:40:03) to 0.76092 (timestamp 2024-04-22 11:50:03). However, it's crucial to note that without knowledge of the potential external influences at these times, we wouldn't categorize these points as definitive outliers. They could be the result of external factors not included in this dataset.

Notes

We must take into consideration that this analysis is solely based on the given dataset and does not account for any other variables that might influence the exchange rate. Factors such as financial market conditions, significant global events, and shifts in economic policy could all have potential impacts on these rates, and these have not been taken into account in this analysis.

Summary of Last Week

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Statistical Measures

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Trend

1. Understanding the overall trend of the exchange rate

Overall, the exchange rate data shows a somewhat stable trend with minor fluctuations. The rate moves from the initial point at 0.7535 to the peak at 0.76573 before settling back down to a lower rate at the end of the data period at 0.76343. Throughout this time series data, the rates have shown both increase and decrease which indicates a volatile currency market. However, the overall change is relatively small, signaling a relatively stable currency environment.

2. Seasonality or recurring patterns

There does not appear to be an immediately observable seasonality or recurring pattern in the dataset. The movement of the rates throughout the data period seems to be random rather than having a particular periodic repetition. Nonetheless, a further and more in-depth analysis using statistical tests would be required to confirm the absence of any seasonal or cyclical component.

3. Outliers in the exchange rates

Upon review of the data, there doesn't appear to be any significant extreme values or outliers within the dataset. The dataset mostly ranges from 0.74857 to 0.76573, a relatively minor fluctuation. Although some points temporarily deviate from the main trend of the data, they return to the average embodiment soon after, thus cannot be considered true outliers. However, a more formal statistical analysis may help to identify any subtle outliers that may not be immediately noticeable in a manual review process.

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

The exchange rates data provided is a time-series data spanning multiple days. Upon inspecting the data closely, the overall trend in the exchange rate appears to be fluctuating within a defined range. There doesn't seem to be a straight upward or downward trend over the provided period.

2. Seasonality and Recurring Patterns

The dataset provided does not show clear evidence of seasonality given the limited nature of the data. However, there appear to be small fluctuations, both increases and decreases in the rates, within the day which could imply some intraday patterns. These patterns could be investigated further with a larger dataset.

3. Identifying Outliers

With the limited dataset as provided, the exchange rates do not seem to have significant deviances, or 'outliers', from the general trend, which is a slight fluctuation within a range. Exchange rates usually move due to factors not depicted in the dataset such as economic indicators, political news, and market sentiment among other factors. These factors often cause abrupt changes in the exchange rates that can be considered 'outliers', however, no such instances can be identified in the given data.

Please note that this analysis is entirely based on the data provided and ignores external factors like market news, socio-political events, or other financial variables that can vastly influence the exchange rate.

Summary of Yesterday

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

Statistical Measures

• Mean:
• Standard Deviation:

Trend

After analyzing the dataset, here is the comprehensive analysis:

1. Understanding the overall trend of the exchange rates

The given exchange rate data depicts a slight decreasing trend over time. The rate begins at 0.76442 and ends at 0.76399. Although there are multiple fluctuations during different time periods, generally the pattern is declining. However, the change is minimal and we can broadly consider the rate as fairly stable.

2. Identifying Seasonality or Recurring Patterns

Given the short period of time covered in this dataset, it's challenging to accurately identify clear seasonal patterns or cycles. However, there are several periods of temporary consistent rises and falls. For example, between the timestamps of '2024-04-19 00:00:02' - '2024-04-19 01:30:02', there is a consistent increasing pattern, and between the timestamps of '2024-04-19 01:30:02' - '2024-04-19 02:20:01', there's a clear decreasing trend. These recurring patterns are short lived but do give indication of periodical fluctuations within the day.

3. Noting Outliers

An outlier is not clearly noticeable in the given dataset as most fluctuations stay within a very narrow range. There are a few instances where the rates show sudden changes. For example, at timestamp '2024-04-19 01:10:02' the rate increases to 0.76486 from a consistent pattern of a lower range. But immediately after, it falls back to the previous range. This could be considered an anomaly, however, given the amount of fluctuation in the market throughout the day, this sharp increase and then immediate decrease doesn't qualify as a significant deviation or outlier.