Ngultrum Forecast

Summary of Yesterday

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Statistical Measures

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Trend

Overall Trend Analysis

The overall trend of the BTN exchange rates is relatively stable. The rates seem to fluctuate around a mean value of approximately 0.01644. The slight fluctuation pattern appears to be fairly consistent throughout the dataset, with no significant uptrend or downtrend. However, there is a slight, gradual decrease in the rates between the timestamps '2024-04-25 00:00:02' and '2024-04-25 14:15:03', with a slight increase thereafter.

Seasonality and Recurring Patterns

In this dataset, no clear seasonality or recurring patterns are immediately identifiable. The rates do not demonstrate a consistent pattern of increase or decrease at specific intervals. However, it should be noted that a more thorough time series analysis with advanced techniques such as autocorrelation and spectral analysis would provide a more conclusive answer regarding seasonal trends.

Outliers and Unexpected Values

Considering the steady nature of the data, the occurrence of any significant outliers is highly unexpected. As per the data presented, there are no significant outliers or extremely unexpected values. Nonetheless, against the backdrop of the steady decrease in rates, slight upticks, such as the one at '2024-04-25 08:10:02' from 0.01646 to 0.01650, could be seen as minor inconsistencies, though they do not constitute statistical outliers.

A comprehensive overview would necessitate statistical analysis tools for identifying outliers, threshold fluctuations and more precise trend detection. Remember, financial markets are dynamic, the absence of noticeable patterns or outliers in this dataset does not imply future datasets on BTN exchange rate would remain the same.

Summary of Yesterday

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Statistical Measures

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Trend

1. Overall Trend of Exchange Rates

Given the dataset, the overall trend of the exchange rates appears to be fluctuating within a minor range. The rate starts at 0.01648, hovering at this level for a considerable duration before descending to the lowest point of 0.01642. Eventually, it slightly recovers to hovering around the 0.01646 level towards the end. The exchange rates seem relatively stable overall with no significant increase or decrease trend can be recognized from the data.

2. Identification of Seasonality or Recurring Patterns

In viewing a time-series dataset, particularly in the case of exchange rates, seasonality or recurring patterns often appear. This case, however, is mildly challenging to distinguish any clear recurring pattern or seasonality based on the dataset provided due to the small fluctuation range. The values only fluctuate within a range of 0.00008, which, while noteworthy in the financial world, is not significant for raw visual interpretation.

3. Outliers Identification

Regarding the identification of outliers, it can be challenging as the data seems quite stable overall. Considering the fact that the BTN exchange rate only fluctuates within a tiny margin, the volatility is not significant. It remains consistent throughout the timeframe provided. Therefore, the lack of more extreme fluctuations makes outlier identification less visible within this dataset.

4. External Factors Consideration

It was mentioned not to take into consideration any specific events or external factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports. Therefore, this entire analysis was conducted solely based on the dataset provided, without any additional context for further insight. Better interpretation could have been made with context as important details could drastically affect how the financial figures should be analyzed and interpreted.

Conclusion

In conclusion, this time-series dataset showcases a mild fluctuation of the BTN exchange rate within a small range, without any significant increase or decrease trend observed. Despite the narrow margin of change, every single shift carries weight in the financial world. To improve the outcome, the dataset would benefit from a wider timeframe for more accurate trends and pattern recognition and the impact of external factors.

Summary of Yesterday

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• Difference of Daily High & Low:

Statistical Measures

• Mean:
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Trend

Overall Trend Analysis

Observing the given data, it appears that the BTN exchange rate seen here displays a relatively stable trend over the period shown, with only slight fluctuations in its value. The rate starts at 0.01645 and ends at 0.01648, showing a marginal increase over the period. Without considering any external factors, we can infer that the general trend of the exchange rate is stable with a tiny upward leaning.

Seasonality or Recurring Patterns

Given the data, it's somewhat challenging to pinpoint any clear, recurring seasonal pattern. The rate remains relatively stable throughout the timeframe captured by the data, and while there are minor fluctuations here and there, no discernable pattern or periodicity can be definitively identified.

Outlier Analysis

In the provided dataset, no significant outliers or extreme shifts in the exchange rate are observable. Most of the changes in the exchange rate are in the third and fourth decimal place, which suggests minor fluctuations but no drastic leaps or drops. This analysis solely considers the given dataset and does not take into account the potential impacts of external events or influences.

Overall, based solely on this data, the BTN exchange rate has been quite stable during this period, with small fluctuations but no significant changes or outliers. The absence of seasonal patterns suggests that the changes in the exchange rate might not be strongly tied to the time of year. Of course, a more thorough analysis or model might be required to fully understand the underlying factors influencing the exchange rate dynamics.

Summary of Last Month

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Statistical Measures

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Trend

Overall trend of exchange rates

Looking at the provided data, there's remarkably little variation in the exchange rate over the course of the given time frame. Specifically, the exchange rate starts at 0.01646 on 2024-04-22 00:00:02 and essentially remains stable, fluctuating marginally throughout the given time period. An occasional drop to 0.01645 and a slight rise to 0.01647 is noted occasionally, but overall it's relatively stable around 0.01646. Therefore, we can conclude that the overall trend of these exchange rates is of stability.

Seasonality or recurring patterns

Given the lack of significant fluctuation in exchange rates, discerning any distinct seasonality or recurring patterns becomes a challenge. The exchange rate does fluctuate between 0.01645 and 0.01646 a few times, but we can't necessarily conclude that this is evidence of a clear pattern without further data or context. Therefore, based solely on this data, it's not possible to definitively identify any seasonality or recurring patterns in the changes of exchange rates.

Outliers

Outliers in a data set are values that significantly differ from the other observations. In this data, since most of the values range between 0.01645 and 0.01646, an outlier would be a value is significantly higher or lower than these. From the given data, we note a few instances of values going to 0.01647 and down to 0.01644 which deviates from the range of majority of data points. However, these are not significantly different and therefore we don't observe any major outliers in this data set.

Summary of Last Week

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Statistical Measures

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Trend

To analyze the given data set, it's best that we go through it in three steps: understanding overall trends, identifying recurring patterns (seasonality), and noting any significant outliers. Please note that this analysis does not account for external factors such as market opening/closing hours, weekends/holidays, or the release of key financial news and reports.

Understanding the Overall Trend

From a broad perspective, the BTN exchange rate within the given timeline is generally stable with slight fluctuations. Standard deviation of the data is extremely low which suggests there isn’t a significant change in the value of BTN over this period.

Identifying Recurring Patterns

In terms of seasonality, it's difficult to identify a clear pattern just by analysing this data set without considering the times. The data is not giving any straightforward evidence about an intra-day or weekly pattern in the fluctuations.

Noting Significant Outliers

Given the overall stability of the exchange rate, any significant peaks or troughs could be considered outliers. However, these must be determined with a robust statistical test, which isn't included in the current scope of the analysis. Even so, the data doesn't present any extreme values that would likely classify as outliers. It is quite consistent with small fluctuations.

Please note that the fluctuations in the financial markets are highly dependent on numerous variables with complex interrelationships. Therefore, comprehensive forecasts require a more in-depth analysis and sophisticated modelling techniques.

Summary of Yesterday

• Opening:
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• 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 Exchange Rates

From the raw data provided, the btn exchange rate doesn't show a strong trend in either direction. The rates are generally hovering around 0.01649 to 0.01655 over a few days. There are mild fluctuations within this range, but there isn't a clear pattern of either an increasing or decreasing overall trend over this period. This suggests a relatively stable exchange rate over this time.

2. Identifying Seasonality or Recurring Patterns

For seasonality or recurring patterns, it might be difficult to discern without the aid of graphical representation. However, based on the raw data provided, it appears that there are micro-fluctuations occurring seemingly at regular intervals. These might suggest some form of hourly seasonality, but it's impossible to definitively conclude without more extended observation or visual aids.

3. Noting Outliers

An outlier in a data set is a value that is significantly higher or lower than the majority of values. In the given data set, there doesn't seem to be a marked abnormality or extreme fluctuation that could be flagged as an outlier. All rates stay within a very tight range, suggesting there's little variation in the exchange rate over this period.

Please note that this analysis is over only a very short period, and for more comprehensive insights it would be better to have a more extensive dataset that spans over a longer timescale. Additionally, a visual graphic representation of the data would aid substantially in identifying trends, seasonality, and outliers.

Summary of Yesterday

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

Statistical Measures

• Mean:
• Standard Deviation:

Trend

Understanding the Overall Trend

Based on the provided data, the overall trend of the exchange rate appears to be relatively stable. The rate fluctuates only slightly between a minimum of 0.01640 and a maximum of 0.01650 within the period that the data covers. Although minor fluctuations occur, these represent normal volatility in exchange rates and do not indicate a clear upward or downward trend.

Identifying Seasonality or Recurring Patterns

To identify any seasonality or recurring patterns, we can look at the frequency of specific exchange rates. However, given the limited span of the data (only around a day's worth), it may not be possible to extract significant seasonal trends or recurring patterns. In this period, the minor fluctuations in the rate do not seem to follow a specific, repeatable pattern. A larger dataset spread over a more extended period (weekly, monthly, or yearly data) would be more suitable for identifying seasonality or recurring patterns.

Noting any Outliers

From the presented data, there do not appear to be any outstanding outliers. While the rate does fluctuate slightly over time, these changes fall within a tight range of 0.00010, and no single data point deviates significantly from this range. The fluctuations can be attributed to normal market volatility rather than any significant market events. Further statistical analysis such as visualization (box plot), or calculation (Z-score or IQR score) could provide a more precise detection of any potential outliers.

Conclusion

In conclusion, the overall trend of the exchange rate is stable within the provided dataset. The small variations in the rate suggest normal market volatility rather than any significant changes. The short time span of the dataset makes it challenging to identify seasonal or recurring patterns, and there were no noticeable outliers in the given time period.