Guernsey Pound 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

    By observing the given data in sequence, we can determine that the exchange rates had some fluctuations but demonstrates a slight upward momentum, suggesting that the rates generally increase over time. The low point was observed as 1.71425 and the high point at 1.72233.

    Seasonality or Recurring Patterns

    For recurring patterns or seasonality, it would require a more intricate statistical analysis. However, at the first glance, no obvious seasonality or recurring pattern can be observed in the dataset. In order to draw a detailed conclusion regarding this, further time series analyses such as autocorrelation function (ACF) or partial autocorrelation function (PACF) might be needed.

    Outliers in Exchange Rates

    Unusually significant changes, or 'outliers,' in the exchange rate are worth noting because they could represent unique events or shifts in the market. By scanning through the data, one potential outlier is noticed around the timestamp '2024-02-29 23:20:02' when the exchange rate dropped to 1.71442, which deviates significantly from the rates immediately before and after. These outliers may need further analysis to understand their causes and implications.

    It is important to note that these assessments are based on an initial review of the data and further, more detailed analysis may uncover additional trends, patterns, or outliers not immediately obvious.

Summary of Yesterday

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Statistical Measures

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    Overall Trend Analysis

    From the provided data set, it appears that the exchange rate (GGP) has undergone several fluctuations over the given time period. It started at a value of 1.71941 and ended at 1.71916. Search for key points of interest within these fluctuations can provide indications of an overall trend.

    Seasonality and Recurring Patterns

    Identifying seasonality and recurring patterns within the exchange rates requires a detailed and close look at the data. Keeping in mind the nature of financial markets and their response to various factors like market hours, public sentiment, and financial news, we expect some level of periodic change. However, from a preliminary glance at the provided data, it’s hard to clearly define a seasonal or recurring pattern. A more robust statistical analysis might be required to establish a strong understanding of the data's seasonality or recurring pattern.

    Outliers

    Identifying outliers or instances where the exchange rate differs significantly from what would be expected based on the trend or seasonality involves comparing the exchange rates with their respective past values. The dataset provided does not contain any obvious drastically large or small values compared to the rest of the time series, and no repetitive patterns are immediately obvious. Without deeper statistical analysis, it's hard to confidently identify the presence of outliers in the data.

    Note: The observations made above are moderate surface-level interpretations and may require a more in-depth statistical analysis to attract more robust claims about the data's nature.

Summary of Yesterday

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Statistical Measures

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Summary of Last Month

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Statistical Measures

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    Overall Trend of the Exchange Rates

    Looking at the dataset from a macroscopic perspective, we notice that the exchange rates do not remain constant, they fluctuate over time. However, the fluctuation is quite small, which means the rates are relatively stable but not completely so. The exchange rate started at 1.71103 and ended at 1.71224. It is important to note that examining an overall trend merely from an opening and closing perspective is a bit simplistic, but it appears that there is a slightly upward trend in the currency exchange rate.

    Seasonality and Recurring Patterns

    Identifying seasonality or recurring patterns in this set of data is a complex task because it requires a large dataset (e.g., monthly or yearly data). With just a one-day dataset, it becomes particularly challenging to identify any seasonality changes or significant recurring patterns. However, more thorough seasonality or pattern analysis would need data spread across multiple cycles or periods (e.g., spanning through several years).

    Outliers in the Exchange Rates

    By definition, an outlier refers to an observation that lies an abnormal distance from other values in a random sample from a population. In time series data like this, outliers could result from extreme events or errors. From a cursory review, there does not appear to be significant deviation in the values given (ranging between 1.70984 and 1.71341), suggesting a lack of obvious outliers. To be absolutely sure, detailed statistical tests can be conducted to formally identify outliers.

    Important considerations

    It is important to recognize that financial time series data like this exchange rate data solely reflects the outcomes of underlying behaviors and events in the financial markets. It is influenced by countless variables, including changes in global economic outlook, political developments, trader sentiment, and much more. As such, while it can be analyzed to identify past patterns, changes, and anomalies, it should be understood in the context of these underlying factors. Moreover, future trends and patterns may not necessarily mirror the ones identified in the past data due to the ever-changing nature of economic and financial markets.

Summary of Last Week

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Statistical Measures

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    Overall Trend Analysis

    Looking at your dataset, it appears that the exchange rates for GGP fluctuate over time, with no clear trend of overall increase or decrease. While there are periods of both upward and downward movement, these do not follow a consistent pattern and the rates often return to around their previous levels after a certain amount of time. This suggests a reasonably volatile market in which value can change rapidly, but also one in which changes are generally temporary rather than indicative of a long-term trend.

    Seasonality and Recurrent Patterns Analysis

    Given the timeframe covered by the dataset, obvious seasonality or recurring patterns are challenging to identify. While there are periods of more significant increase or decrease, these do not appear to occur at regular intervals nor do they correlate in a way that suggests seasonality. Nevertheless, a more robust analysis with more sophisticated tools such as Autoregressive Integrated Moving Average (ARIMA) models or Fourier transformations could unveil more subtle seasonal effects or cyclical patterns that may not be readily apparent.

    Outliers

    In the dataset, the GGP exchange rates seem to fluctuate within a reasonable range for most of the period. However, there are instances where dramatic changes in rates are observed. While "outliers" are less clearly defined in financial time series data like this, as large changes can be driven by a variety of factors and do not necessarily indicate anomalies or errors, these points do represent significant deviations from the average rate at the time. Though without additional context or information, it would be speculative to definitively label these points as outliers.

    Final Note

    Please note that this analysis is purely observational and descriptive. It neither considers any external factors (like market opening/closing hours, weekends/holidays, key financial news, etc.) that could impact the exchange rates, nor does it predict future trends or movements.

Summary of Yesterday

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  • Difference of Daily High & Low:

Statistical Measures

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    Overall Trend of Exchange Rates

    By interpreting the time-series data for the exchange rates, it is evident that the overall trend from the provided date of 19th February to 23rd February 2024, shows a general increase. The exchange rate starts at around 1.69747 and ends at around 1.70732. Therefore, the exchange rate tends to increase over the period shown.

    Seasonality and Recurring Patterns

    Upon examining the dataset, there may not be apparent seasonality or recurring patterns within this short timeframe. However, for a more extended period, such patterns could emerge more prominently. It is worth noting, for more profound insights into seasonality or recurring patterns in the data, a more extended period, preferably a few years of data points, would be advisable.

    Outliers in the dataset

    While examining the data, one key point that stands out is a significant jump in the exchange rate that occurred on 20th February 21:00:02, where the rate increased from around 1.70126 to 1.70831, which seems to be an outlier. This type of spike is worth investigating, as it could be an error, or it could represent a legitimate yet rare event that had a significant impact on the exchange rate.

Summary of Yesterday

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Statistical Measures

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    Here is the requested analysis:

    Overall Trend

    Upon analyzing the provided data, it is observed that the overall trend of GGP exchange rates fluctuates between minor increases and decreases over time. The exchange rate starts at 1.70483 and ends at 1.70750, signifying a marginal increase across the given time stamps. However, it is worth noting that the exchange rate exhibits considerable fluctuations within this range during the time period.

    Seasonality or Recurring Patterns

    From the data, it is less apparent to identify any clear seasonality or recurring patterns in the GGP exchange rates. While we do see some small oscillations across the data, these changes do not exhibit a clear or consistent seasonal pattern. This lack of a pattern might be due to the relatively short period, as seasonal patterns typically emerge over longer periods. Hence, the data analyzed does not indicate any regular intervals of increases or decreases in exchange rates that would suggest seasonality.

    Outliers

    Evaluating the outliers within this dataset, no substantial unexpected spikes or drops in the exchange rate are identified. Most fluctuations in this data set fit within a plausible range based on the general trend of the data, with the rate oscillating between 1.70245 and 1.70923. Hence, no distinct outliers are found which deviate significantly from the overall trend of the exchange rate.

    Impact of External Factors

    As per the request, we do not consider specific events that could potentially impact the GGP exchange rate. Factors like market opening/closing hours, weekends/holidays or key financial news, and reports have not been taken into account in this particular analysis. Thus, the framework for this analysis is based solely on the available numerical data.

    It's important to note that for a more detailed or predictive analysis, considering such factors would likely be beneficial, as these parameters can have a significant impact on exchange rates. However, such a study would require more detailed data than that provided.