Fiji Dollar Forecast

Not for Invesment, Informational Purposes Only

Summary of Yesterday

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Statistical Measures

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    Overall Trend of the Exchange Rates

    Upon analyzing the given data set, I noticed that the exchange rate appears to have a slight fluctuation. Despite these slight variations, the FJD exchange rate has shown a trend of moderate increase over the given timestamps. However, a significant surge in the value can be observed around the timestamp of '14:05:03', where it jumped from approx. 0.5966 to 0.6033. This trend continued with minor fluctuations until the end of the day, closing at 0.60348.

    Seasonality or Recurring Patterns

    Given the data is for a single day only (i.e., 29th February 2024), it's difficult to accurately spot any yearly or monthly seasonality. However, considering this one-day data, it can be seen that the exchange rate was relatively steady for the most part of the morning, followed by a significant increase in the afternoon, and remained stable again for the rest of the evening with minor ups and downs. This may indicate an intraday pattern, but for an in-depth understanding, data over multiple days is necessary.

    Outliers in the Data

    Based on the raw numerical data provided, there appears to be an outlier around '14:05:03' timestamp where the FJD exchange rate increased suddenly from around 0.5966 to approximately 0.6033. Except this, there doesn't seem to be any other significant discrepancies in the data that would require further investigation.

    Please note that as per the requirement, this analysis has been conducted purely based on numerical data trends and does not take into account any external factors such as market opening/closing hours, weekends/holidays, or the release of key financial news and reports. Additionally, I haven't generated any forecast for future rates.

Summary of Yesterday

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Statistical Measures

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    Overall Trend of Exchange Rates Analysis

    Upon evaluating the dataset, there is an undeniable upward trend in the exchange rates (FJD) over time. Starting at an exchange rate of 0.59855 at the beginning of the given period (2024-02-28 00:00:02), the rate consistently rose to a peak level of 0.60105 (2024-02-28 07:00:03) before descending to a low point of 0.59668 (2024-02-28 23:05:02). There was a slight increase before the end of the series. The upward trajectory signals an appreciation of the currency, despite small declines within the period. This needs to be affirmed with more sophisticated trend analysis techniques such as regression or moving average models.

    Seasonality Analysis

    To discern recurring patterns or seasonality in the changes of exchange rates, more sophisticated time-series analysis methods like Autoregressive Integrated Moving Average (ARIMA) models, Exponential Smoothing state space model (ETS), or Seasonal Decomposition of Time Series by Loess (STL) should be executed. The discovery of patterns can be dependent on various factors including daily fluctuations, monthly analysis, or yearly trends depending on the specifics of the data. From the raw data, however, no immediate clear seasonal or recurring patterns can be observed.

    Identification of Outliers

    Outliers can be identified by looking for drastic and abrupt changes in the exchange rates between two timestamps. Whereas the general trend is gradual and progressive, outliers would be characterized by sharp rises or declines that don't align with the overriding pattern. In the current dataset, we could look at variations that exceed standard deviations to pinpoint potential outliers. Given the subtle nature of the exchange rate fluctuations, such instances need more time and a careful examination, using techniques such as the z-score or modified z-score method.

Summary of Yesterday

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Statistical Measures

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Summary of Last Month

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    1. Understanding the Overall Trend of the Exchange Rates

    Upon examining the data, it appears that the exchange rate of FJD mostly fluctuates within a small range. The highest value in the series is 0.60455 and the lowest is 0.59645, indicating a range of 0.0081. There is a decreasing trend from the start of the time series till about midway. However, this is followed by an increasing trend till about three quarters of the duration, after which the trend is decreasing again. The overall trend over the time period provided seems relatively stable with minor fluctuations, within the identified rate range.

    2. Seasonality or Recurring Patterns in Exchange Rates

    While it's challenging to identify specific recurring patterns or strong seasonality elements in the given exchange rate data, some mild changes can be detected. For instance, the rate tends to increase slightly during certain hours of the day. However, it's important to note that in such time-series data, the lack of clear seasonality or cyclical patterns might indicate a largely efficient market, where rates react quickly to new information as it becomes available, rather than following predictable patterns.

    3. Noting Any Outliers

    The exchange rate data show few instances where the rate appears to significantly differ from the overall trend. The moments when rates reach the identified highest and lowest points could be viewed as outliers within this dataset. However, the small range of rate fluctuation suggests there's no extreme outlier way far from the majority of the data points.

Summary of Last Week

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    Financial Analysis of Exchange Rate Data

    Overall Trend Analysis

    Looking at the timestamps and corresponding exchange rates, it seems that the rates slightly fluctuate around the figure of 0.60. There doesn't appear to be a clear and sustained increase or decrease in exchange rates over time. Instead, the rates seem to be relatively constant, with small periodic fluctuations. However, this constant rate varies slightly from time to time but does not exhibit a clear increasing or decreasing long-term trend.

    Seasonality Analysis

    Based on the time-series data provided, it is difficult to establish a clear seasonality or recurring pattern in the exchange rates. The fluctuations seem to follow a random pattern rather than a cyclical one. There is no notable trend or pattern observed based on the day of the week, day of the month, or month of the year. These findings suggest that the changes in exchange rates are likely due to random fluctuations rather than seasonal or cyclical patterns.

    Identification of Outliers

    Based on a broad overview of the dataset, there are a few instances where the exchange rate dips significantly to around the 0.59 - 0.594 mark. These moments stand out as they differ markedly from the observed tendency for the rate to hover around the 0.60 mark. Nevertheless, these occurrences do not appear to disrupt the overall pattern, and the rate quickly returns to its usual range after these dips.

    Please note that financial data is heavily influenced by a multitude of factors beyond the scope of this basic analysis. For a more in-depth understanding of exchange rate behaviours, it is necessary to consider additional financial, economic, and geopolitical factors.

Summary of Yesterday

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Statistical Measures

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    1. Understanding the Overall Trend of The Exchange Rates

    From the data provided, we can observe some general trends in the exchange rates. The overall exchange rate started at 0.60115 on 2024-02-19 and ended at 0.60387 on 2024-02-23. This shows that there has been a general increase in the exchange rates over the period shown, indicating appreciation in the value of FJD against the referenced currency.

    2. Identifying Seasonality or Recurring Patterns in The Changes of Exchange Rates

    Discerning a clear pattern of seasonality from this dataset is somewhat challenging due to its complexity. However, noticeable repetitive fluctuations can be seen present in the dataset which suggests that there could be some degree of seasonality at play. More detailed or longer-term data may be required to fully understand these potential patterns.

    3. Noting Any Outliers

    In the given dataset, there are few data points that stand out as potential outliers where the rate changes significantly. For instance, observing the rate drop from 0.60162 to 0.59526 between time periods 2024-02-19 14:00:03 and 2024-02-19 16:00:03. Also, there are significant fluctuations such as the rate spiking from 0.59583 on 2024-02-21 22:00:02 to 0.60265 on 2024-02-22 01:00:02, marking a considerable increase. Such abrupt changes could be due to numerous economic factors that go beyond the observable dataset.

    In conclusion, this time-series analysis of exchange rates provides a broad overview of the currency trends, possible patterns, and potential outliers within the provided dataset. For a more accurate and detailed analysis, one might require additional data and possibly consider external market influences and global economic factors as well.

Summary of Yesterday

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Statistical Measures

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    Overall Trend Analysis

    The dataset shows a gradual fluctuation in the FJD exchange rates data from 2024-02-23 00:00:02 to 2024-02-23 14:55:01. The beginning value is at 0.59639 which troughs to 0.59631 and peaks to 0.60444. On average, the exchange rate increases over the time period of the data set as we can see the general trend is upwards.

    Seasonality or Recurring Patterns Analysis

    In terms of seasonality or recurring patterns, given the 24 hours ranged data, it is difficult to conclusively identify any specific cyclical pattern. However, a slight upward trend is noticed at certain intervals of time which could potentially mean more activity in the FJD exchange during those specific times.

    Outliers Analysis

    Close observation of the data indicates no significant outliers, i.e., there are no instances where the exchange rate differs overly from the maintained or expected rate. Most rates revolve around the 0.60 mark. However, analysis of more data could potentially provide more accurate outlier detection.

    External Factors Review

    As per the request, no specific external factors such as market opening/closing hours, weekends/holidays, or release of key financial news and reports have been considered in this analysis. Distinguishing any specific causes or correlations with such events would require more comprehensive data and a more detailed analysis than is provided from this singular day's dataset.

    Please note that these findings are based on this limited set of data. For more comprehensive insights, analyzing a larger dataset over a more extended period is highly recommended.