Bahamian Dollar Forecast

Not for Invesment, Informational Purposes Only

Summary of Yesterday

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Statistical Measures

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  • Trend

    Analysis

    The data shows fluctuations in the BSD exchange rate on what appears to be a minute-by-minute basis. The time periods span from midnight to the last minute of the day, spotlighting a comprehensive view of the daily BSD trends. From a cursory look at the data, there does not appear to be a strong trend of increase or decrease over the time period shown. Instead, there are constant fluctuations within specific range.

    Understanding Overall Trends

    The overall change range of the exchange rate during this particular day goes from a minimum value of 1.35416 to a maximum value of 1.36085. There are no clear linear upward or downward trends recognizable from the given dataset. instead, the exchange rate appears to fluctuate around its mean value of approximately 1.3568, suggesting a mildly volatile day with no distinct trend of increase or decrease.

    Seasonality or Recurring Patterns

    From the data, there's no clear seasonal or recurring pattern. There are, however, noticeable hourly fluctuations. For instance, between 02:10:02 to 03:15:02, there was a notable increase in the BSD rate, and then a moderate decrease happened between 06:20:01 to 07:40:02 suggesting some intraday volatility. Identifying specific seasonality or recurring patterns would require a longer time series data set.

    Outliers

    There are a few instances throughout the day where there are fairly significant jumps or drops in the exchange rate. For example, at timestamp 06:20:01, the rate dropped significantly from 1.36064 to 1.35837. At 07:35:03, the rate dropped further to 1.35763 from 1.35836, previous minute. Another significant rise can also be seen at 02:10:02 where the rate jumped from 1.35923 to 1.3599. These can be considered as outliers in the dataset. But to significantly determine outliers, a statistical metric like IQR or Z-Score can be used.

    In conclusion, the BSD exchange rates fluctuate throughout the day with evident volatility at certain time frames. It's difficult to determine a clear trend, pattern or outlier from this single day of data. A more detailed analysis would require a longer timespan and potentially, the consideration of other external factors.

Summary of Yesterday

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Statistical Measures

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  • Trend

    Understanding the Overall Trend

    Based on the data provided, the overall trend of the exchange rates seems to be increasing. The value starts from approximately 1.35263 and later reaches a maximum value of approximately 1.3613. Please note that this analysis does not consider factors such as market opening/closing hours, weekends/holidays, or the release of key financial reports and news.

    Seasonality or Recurring Patterns

    In terms of seasonality or recurring patterns, the exchange rate data does not seem to show a clear pattern over the time series provided. It would require more data and detailed analysis to definitively conclude if there are any recurring patterns in the exchange rates over a longer time frame. It's important to note that seasonality is often an essential factor in financial data but may not be as visible in this particular dataset because it covers only a brief period.

    Outliers

    Outliers are instances that significantly differ from the trend or seasonality. In this dataset, it does not appear to have significant outliers. The data appears to be gradually increasing with minor fluctuations in between. Once again, this analysis does not consider specific events that might cause drastic changes to the exchange rate, such as financial crises, geopolitical events, or sudden economic policy changes. To detect potential outliers more rigorously, statistical analyses such as identifying values that are a certain number of standard deviations away from the mean can be employed.

    Conclusion

    In conclusion, the overall trend of the BSD exchange rate in this dataset seems to be increasing, although minor fluctuations are observed throughout. There's no distinct seasonality or pattern discernible from the data presented. It does not appear to have significant outliers, with the majority of values following the general trend. Please consider that this analysis is rather basic and only provides a high-level overview. Detailed and accurate analyses often call for more comprehensive data and complex analytical methods.

Summary of Yesterday

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Statistical Measures

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  • Trend

Summary of Last Month

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Statistical Measures

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    Overall Trend Analysis

    After carefully analyzing the provided time-series data, it appears that the exchange rates do not remain stable, but rather experience slight fluctuations over different time intervals. While they do not show significant increases or decreases, there is a marginal upward trend towards the end of the dataset. Such small value adjustments are common in the exchange rates, and they can be influenced by various factors including the overall economic environment and the demand-supply equilibrium.

    Seasonality and Recurring Patterns

    Upon inspecting the dataset, there doesn't seem to be a clear pattern of seasonality in the exchange rates - the values are subject to change and do not appear to follow a specific time-based cycle. However, some recurring patterns can be discerned, such as fluctuations around certain values. It's also noticeable that there are instances where the rates remain unchanged for consecutive periods, implying a short-term stabilization of the exchange rate before the next fluctuation occurs.

    Identification of Outliers

    Although the market in which these exchange rates operate is highly efficient, causing the rates to swiftly incorporate any new information, outliers can still present themselves in the form of sudden large changes within short time frames. In the data provided, there aren't any substantial spikes or drops that indicate outliers. The rates mostly tend to oscillate around certain decimal points, and any deviation from this is within a reasonable range. This suggests that there were no significant spontaneous events during these periods that could massively affect the demand or supply of the BSD currency.

    Remember, while these provided insights depend on the interpretation of historical data, they may not always predict future behavior due to the inherently uncertain nature of the market.

Summary of Last Week

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Statistical Measures

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    Overall Trend of the Exchange Rates

    Based on the provided dataset, it is observed that the overall trend of the BSD exchange rate shows fluctuations over the given period. Although no continuous rise or fall in rates can be directly identified from the dataset, there are certainly periods of increased and decreased values. At some points, the rate also remains relatively stable. It's important to note that further computational/statistical tools may be required for a more accurate understanding of the trend.

    Seasonality or Recurring Patterns

    It's challenging to identify seasonality or recurring patterns in exchange rate data based just on a visual inspection of the given data. Exchange rates are influenced by myriad factors and often do not follow simple seasonal patterns. However, computational techniques such as time series decomposition could unveil potential seasonality, cyclicity, or recurrent patterns. More data, particularly over a series of full annual cycles, would be more useful to make such an assessment.

    Outliers in the Exchange Rates

    Identifying outliers in time-series goes beyond searching for single data points. It involves looking for points that significantly deviate from the trend, unexpected spikes or dips, or periods of unusually high volatility. It seems like there are a few instances in the provided data where the rate changes suddenly and substantially, which could be termed as outliers. However, accurate identification would require a computational analysis using methods like standard deviations, the Z-score method, or the use of a machine learning model to identify these outliers accurately.

    Its also important to keep in mind that sudden large changes in exchange rates may reflect real-world economic events and should not always be dismissed as 'noise' in the data.

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

    Based on the data provided, the exchange rates (BSD) shows a mild fluctuating behaviour. The rate started at 1.34763 on 2024-02-19 01:00:02 and ended at 1.34979 on 2024-02-23 14:00:01. The highest rate observed during this period is 1.35476 on 2024-02-21 03:00:02, while the lowest rate was 1.34398 on 2024-02-23 02:00:02. Overall, the rates have seen minor fluctuations, with upward and downward movements throughout these days.

    2. Identifying Seasonality of the Exchange rates

    From the dataset provided, it was difficult to identify a concrete pattern of seasonality because only a five-day window was provided. For a more accurate observation of seasonality, we need a more extended dataset that contains data from a full year at minimum. However, it can be noted that some minor daily fluctuations occurred regularly, implying possible intraday seasonality, with certain times perhaps showing a slight rise and fall pattern.

    3. Outliers in the Exchange Rates

    Outliers in the data are instances where the exchange rate differs significantly from the general trend. For the provided dataset, there are no apparent outliers at a glance, as the rates fluctuate within a relatively tight range. However, without a rigorous outlier analysis using statistical methods, we cannot conclusively determine the presence of outliers.

    Summary

    From the provided data, the BSD exchange rate displayed minor fluctuations over the five-day period. We can also observe some intra-day seasonality, but it's hard to accurately gauge without a larger dataset. There seemed to be no significant outliers in the past five days. A more extensive dataset would provide deeper insights into the trend, seasonality, and possible 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

    First, it is important to understand that given the granular time intervals per data entry (5 minute intervals), we are dealing with intraday data. Intraday data analysis allows us to understand the behavior of the exchange rate throughout each day, instead of looking at closing day prices.

    1. Overall Trend of the Exchange Rates

    By observing the given dataset and considering that the smallest value is 1.34356 BSD, the highest being 1.3513 BSD, and there seem to be many fluctuations between these two values. Various peaks and troughs are noted, which suggests volatility in the exchange rate and this makes it difficult to indicate a clear overarching upward or downward trend. Instead, the exchange rate appears to have a lot of intraday fluctuations, hinting towards a somewhat oscillating behavior rather than a pronounced general increasing or decreasing trend. To derive a significant conclusion, a statistical measure such as linear regression may be needed to analyze, envision, and grasp such a trend efficiently.

    2. Seasonality or Recurring Patterns

    From the given data, it's a challenge to conclusively state any definitive seasonality or recurring patterns. Generally, exchange rates are influenced by a multitude of different factors, including but not limited to macroeconomic indicators and international trade balances. Furthermore, given that the data covers a very short period of just a single day, it's almost impossible to identify any seasonality. As such, longer duration data would be necessary to adequately identify any potential patterns or seasonality in the exchange rates.

    3. Outliers in the Exchange Rates

    When comparing each exchange rate to its immediate neighbors, no extreme price jumps that might be classified as outliers can be immediately detected. Nonetheless, the notable leap from 1.34434 BSD to 1.34766 BSD within a 5-minute window might be something worth investigating further. A detailed statistical analysis using methods like the Z-Score could help in identifying potential outliers more accurately. However, it is crucial to remember that in financial markets, the perception of what constitutes an 'outlier' can often be subjective and dependent on market context.

    In conclusion, the given dataset exhibits noticeable intraday volatility, a lack of observable overarching trend, and a potential absence of recognizable seasonality. Finally, while potential outliers are present, they are scarce and somewhat consistent with the intraday variability that is common in financial markets.