Tanzanian Shilling Forecast

Not for Invesment, Informational Purposes Only

Summary of Yesterday

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Statistical Measures

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    Understanding the Overall Trend

    Upon examining the given data, it is clear that the exchange rate (TZS) remains constant throughout the entire dataset at a value of 0.00053. There is no observable wavering or change at different timestamps, indicating a stable rate over this period. Hence, within the span of the recorded data, we can conclude that the exchange rates did not increase or decrease.

    Identifying Seasonality or Recurring Patterns

    Given the data, there appears to be no discernible pattern or fluctuations that could suggest seasonality since the exchanged rate remained stagnant at the value of 0.00053 throughout. Therefore, there is no cycle or recurring pattern that can be observed in this dataset. Normally, in a time-series data, seasonal variations may occur at regular intervals due to seasons or repeatable patterns linked to time such as hourly, daily or annual patterns but that is not the case here.

    Noting Any Outliers

    Outliers in a dataset typically stand out as they differ greatly from the majority of dataset values. In the dataset given, all exchange rates are the same. Therefore, there are no outliers present in the dataset. There are no instances where the exchange rate varies significantly from the dominant rate of 0.00053.

    In summary, the data shows a steady and unchanging exchange rate over the documented period without any identifiable trends, patterns or outliers. However, it would be useful to have a more variable dataset for a comprehensive analysis of the exchange rates over a period of time.

Summary of Yesterday

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Statistical Measures

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    Analysis of the Given Time Series Financial Data

    Upon examination of the dataset provided, some key observations can be made. Here is a comprehensive analysis of the trends, seasonality and anomalies in the TZS exchange rates.

    1. Overall Trend of Exchange Rates

    From the dataset, it can be observed that the exchange rate of TZS has remained consistent at 0.00053 throughout the period for which data has been provided. This is indicative of a stable market condition for TZS during this timeframe. There are no significant increases or decreases observed in the exchange rate, suggesting an absence of volatile market conditions or significant economical events influencing the rates.

    2. Seasonality or Recurring Patterns

    Given that the exchange rate doesn't exhibit any change throughout the dataset, it can be infer from the current dataset that the TZS exchange rate has not exhibited any discernable seasonality or recurring pattern during this specific period. This consistency in value implies its market situation remained stable.

    3. Outliers

    As the exchange rates of TZS were consistently valued at 0.00053 for the entirety of the assessed period, there are no anomalies or outliers present in this dataset. There were no instances where the exchange rate would differ significantly from the consistent value.

    Note: While the current dataset does not communicate evident patterns, seasonality, or irregularities, this does not automatically infer that TZS exchange rates are always stable. Different outcomes may come with larger datasets covering a more extended period or datasets with more frequent recordings of the rates.

Summary of Yesterday

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Statistical Measures

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Summary of Last Month

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    Given the consistent values in the dataset, here is the summary of the comprehensive analysis:

    Understanding the overall trend of the exchange rates

    • The general trend of the exchange rates remains stable, with the TZS rate consistently being at 0.00053 throughout the time series. There is no discernible increasing or decreasing trend.

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

    • Given that the exchange rate remains constant throughout the entire time series, there are no observable patterns or features that suggest seasonality in the data.

    Outliers and significant rate deviations

    • Since the exchange rate is constant across all timestamps in this dataset, there are no outliers or significant deviations from the mean.

    External Factors

    • Considering the instruction to disregard specific events or external market factors, this analysis did not consider aspects such as market opening/closing hours, weekends/holidays, or the release of key financial data and reports.

    Forecast

    • As per the instructions provided, no forecast for future rates was generated given the context of this analysis.

    Overall, this dataset presents a stable TSZ exchange rate over the period specified. Further in-depth analysis and additional data might reveal more intricate patterns or trends; however, with the current input it's not achievable.

Summary of Last Week

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Statistical Measures

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    Unfortunately, I am not able to provide a comprehensive analysis with a display of graphs or tables due to the limitations of this platform, but here's a textual summary of what I would generally look for in such analysis:

    Understanding the Overall Trend of the Rates

    I would first compute the basic statistical measures of the data such as mean, median, mode, and standard deviation to understand the central tendency and variability of the exchange rates. Then I would examine the trend over time by plotting the exchange rates against the timestamps, observing whether the exchange rates generally increase, decrease, or remain stable.

    Identifying Seasonality or Recurring Patterns

    To identify any seasonality, I would look for consistent or recurring patterns at regular intervals over time. For example, the exchange rates might consistently increase or decrease at certain hours of the day or certain days of the month. This would involve analysing and comparing the average exchange rates for different periods and looking for any cyclical patterns.

    Noting Any Outliers

    Outliers are instances where the exchange rates differ significantly from the overall trend or seasonal pattern. I would use statistical methods to identify these outliers, such as computing the Z-score for each observation and finding instances where the Z-score is above a certain threshold (usually 3). These outliers might indicate significant events or anomalies in the data.

    Given that you specifically mentioned not to account for external factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports, and to not generate any forecasts, the mentioned analyses would provide a comprehensive understanding of the provided dataset. Please note that this conclusion is a general insight based on the instructions provided and a detailed conclusion would require in-depth analysis using appropriate tools and software.

Summary of Yesterday

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Statistical Measures

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    Understanding the Overall Trend of the Exchange Rates

    Over the period shown in the data, the observed TZS exchange rate has remained stable. The rate has consistently held at an rate of 0.00053, with no noticeable increase or decrease. This suggests that during this particular period, the value of TZS was not volatile and did not experience significant fluctuations.

    Identifying Seasonality or Recurring Patterns

    Given that the TZS exchange rate remained consistent throughout the period shown, there's no clear evidence of any seasonality or recurring patterns within this dataset. Normally, in a time series data with varying values, we might observe recurring changes that could suggest the presence of seasonal effects. However, in this case, the unchanging nature of the rates does not present identifiable seasonal variations or rhythmic patterns.

    Noting Any Outliers

    As the data provided consistently shows an exchange rate of 0.00053 for all given timestamps, there are no outliers present in this dataset. An outlier would typically be a rate that significantly differs from the others observed. With no variation in the data, we can conclude that during this period there were no instances of the exchange rate differing from the 0.00053 mark.

    In conclusion, this TZS exchange rate data shows a period of remarkable stability, with no apparent trend, no identifiable seasonality and no outliers. This might suggest a period of steady economic performance and exchange rate policy. However, it's always important to consider potential external factors that can influence exchange rates, as well as the possibility of different patterns appearing over a longer period of time.

Summary of Yesterday

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Statistical Measures

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    Based on the dataset you have provided, all the values of TZS exchange rate are the same, standing at 0.00053. Given this, I will proceed to provide a comprehensive analysis regarding this unique circumstance of consistent exchange rates.

    Overall Trend of the Exchange Rates

    The overall trend of the exchange rate appears to be stationary since all points from the first timestamp [2024-02-23 00:00:02] to the last timestamp [2024-02-23 14:55:01] remain at 0.00053.

    Seasonality or Recurring Patterns

    Given the constant exchange rate of 0.00053 throughout the dataset, there is no noticeable seasonality or recurring pattern in the fluctuation of the exchange rate. They are the same at all given times, regardless of the date or time.

    Identifying Any Outliers

    In this case, there are no outliers, as the exchange rate stays the same throughout the entire dataset at a consistent 0.00053. An outlier in this dataset would be a significant divergence from this constant value.

    Additional Notes

    It is highly unusual to observe such a consistent exchange rate over an extended period. Such consistency might be indicating no trading activity or data input issues during this period. However, without any additional details or data, it isn't easy to draw a definitive conclusion.

    Additionally, this consistency makes it impossible to establish a valuable financial analysis using preserved patterns, trends, and deviations – basically, technical analysis, as the whole dataset exhibits zero variability. Hence, conclusions often drawn from financial analysis—like volatility, direction, momentum, pattern, and cycle classifications—are unachievable.

    Possible Future Steps

    • Check the input data to ensure accuracy
    • Explore external factors causing such consistency
    • Expand the data horizon for a better view

    Please note that the observations made are strictly based on the dataset provided, and do not take into account other potential external factors that often influence currency exchange rates.