Pound Sterling Forecast

Not for Invesment, Informational Purposes Only

Summary of Yesterday

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

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Data Loading & Preparation

    The data given is in time-series format, with timestamps for each record and the corresponding GBP exchange rate. The timestamps have a 5-minute interval. It's important to note that the date, 29th February, in the given data doesn't exist since 2024 is not a leap year. So the actual date needs further clarification.

    Trend Analysis

    The overall trend of exchange rates can be analyzed by using a Rolling Mean (also known as Moving Average) over a certain period of time. For instance, we can use the Rolling Mean over every hour to see the trend lines. A visual plot of the time series data with the Rolling Mean can give a clear sense of the overall trend.

    Seasonality Analysis

    Seasonality refers to repetitive and predictable movements or patterns that recur over one year. In the case of exchange rates, this might be a tougher call to define because these rates are highly dependent on global financial activities, making them quite volatile. However, it doesn't invalidate the likelihood of patterns. We can apply a seasonal decomposition of time series by LOESS (STL) plot that can help us understand the seasonality in the dataset.

    Outliers Identification

    We can use Box Plots to understand the presence of outliers in our dataset. A box plot, also known as a whisker plot, shows the distribution of the dataset and classifies the data points into 'whiskers' and 'outliers'. Any data points that fall above the Upper Whisker or below the Lower Whisker are classified as outliers. Box plots provide a visual representation of the dispersion and skewness of the GBP exchange rates.

    Please note that these are preliminary analyses and should serve as a direction to approach more complex analyses. The exact dynamics of GBP exchange rates will be much more intricate and may require deeper econometric modeling.

Summary of Yesterday

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

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Overall Trend of Exchange Rates

    The data provided indicates some trends over a given period. From an initial view of the data, it seems there is a gradual increase in the exchange rates as time progresses. There are minor fluctuations between the rises and falls, which is typical in financial time-series data due to uncertainty and volatility in the market.

    Seasonality and Recurring Patterns

    Considering the time series data, no immediately apparent seasonality can be observed due to the relatively short timeframe. If there were data spanning multiple years, it might be easier to draw seasonal conclusions as exchange rates are influenced by macroeconomic events. However, based on this dataset, it appears the trends are more cyclical throughout the hours of the day rather than by season.

    Outliers Identification

    This dataset seems to contain few instances of significant outliers. While the rates show a varying level of volatility, most fluctuations seem to fall within a predictable range for this kind of financial data. Some unusual spikes or dips in rates might be considered as potential outliers. However, without knowledge of the market conditions during each time period, it's challenging to pinpoint whether these phenomena are truly abnormally relative to the market’s condition.

    External Factors

    While the request was to not consider external factors such as market opening/closing hours, weekends/holidays, key financial news, and reports, it’s essential to note that exchange rates are generally very sensitive to these factors. As this analysis is based on data alone, any potential influences due to these extraneous factors would not be detected.

    In-depth Analysis and Forecasting

    For a more comprehensive and accurate analysis of the financial data or an accurate future rate forecast, a more exhaustive dataset would be required – ideally one that spans multiple years. It would also help to consider market contexts, like geopolitical events, shifts in economic policy, or major changes on the global economic stage. Contextual data like these are critical in predicting currency performance and truly understanding rate fluctuations.

Summary of Yesterday

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

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

Summary of Last Month

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

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Based on a thorough review of the provided dataset, the following insights have been drawn.

    Understanding the Overall Trend of The Exchange Rates

    The exchange rates display a generally stable upward trend throughout the given period. The rates appear to begin at a value of approximately 1.71135 and gradually increase, reaching as high as 1.71616 before experiencing some fluctuations and then stabilizing once again in the range of about 1.71203 - 1.71336. It is important to note, however, that as per your request, this conclusion is being made based solely on the given data and does not take into account any potential external factors that may be influencing exchange rates.

    Identifying Seasonality or Recurring Patterns

    Based on the provided dataset, it is not immediately apparent that there is any clear-cut seasonality or recurring pattern in the exchange rates. The typically tight range of fluctuations seen during the course of a given day may suggest that the exchange rates do not undergo significant shifts within that timeframe. However, analysis at a wider scale (e.g. weekly, monthly) is needed to determine any possible patterns with more certainty. As of now, the dataset provided does not present enough evidence of any significant seasonality or cyclicity in the GBP exchange rates.

    Noting Outliers

    While an in-depth statistical analysis would be required to precisely identify and confirm any outliers, an observation of the dataset does not immediately suggest any major anomalies; i.e., instances where the exchange rate differs significantly from what one might expect given the overall steady trend characterized by gradual appreciation and minor fluctuations. However, it's important to bear in mind that the identification of outliers can depend heavily on the specific parameters defined (e.g. any deviation exceeding a certain percentage of the mean or median).

    It's important to consider that this observation does not fully account for shorter-term anomalies that may occur within the course of a single day, and more detailed, granular analysis could potentially reveal short-term outliers not immediately noticeable in an analysis of the broader trend.

Summary of Last Week

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

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Upon analyzing the provided dataset, here are my insights:

    1. Overall Trend of the Exchange Rates

    The exchange rates shown in the given dataset fluctuate over time without a clear upward or downward trend. The maximum exchange rate value over the observed period was 1.71313, and the minimum value was 1.69579. However, by considering the changes in the exchange rate over a longer period, we can observe that the exchange rates seem to fluctuate around a mean value without a clear long-term increasing or decreasing trend.

    2. Seasonality or Recurring Patterns

    There are no noticeable seasonal or recurring patterns in the exchange rates based on the provided data. The fluctuations in this data set seem to be random rather than following a predictable cyclical pattern. It's crucial to note that exchange rates are influenced by a wide range of factors, many of which are unpredictable, such as political events, economic policy changes, and market sentiment. Consequently, it's rare to observe clear seasonal patterns in exchange rate data.

    3. Outliers in the Exchange Rate Data

    There don't appear to be any significant outliers in the provided exchange rate data. The values range within a relatively consistent band throughout the time series, with no dramatic spikes or drops that might suggest outliers. While there are slight fluctuations (as is usual in exchange rate data), no extreme, sudden deviations from the generalized range are witnessed. These fluctuations are normal in exchange rate data and generally do not carry exceptional significance unless coupled with related financial news or global events, which are not considered in this analysis.

    In conclusion, the provided time-series data for exchange rates indicates that the GBP exchange rate overall has been reasonably stable over the time period considered with no standout trends or patterns identified. This consistency could be due to various factors, both domestic and international, that influence exchange rates and the balance they form over time.

Summary of Yesterday

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

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Overall trend analysis of the exchange rate

    The dataset indicates that the overall trend of exchange rates experiences an increase from the start value of 1.70085 to the end value of 1.71104. Although there are oscillations within the dataset, the currency appears to generally appreciate over time.

    Seasonality and recurring patterns analysis

    Regarding seasonality or recurring patterns in the exchange rates, it is challenging to identify without a more extended period. Exchange rates can be influenced heavily by macroeconomic variables, which tend not to follow exact repeat patterns. However, there seem to be frequent minor fluctuations throughout the series, indicating some level of market volatility during the observed period.

    Outliers and significant deviation

    There seems to be a notable outlier during the time around '2024-02-20 09:00:04' when the exchange rate jumps from 1.69799 to 1.70951. This is quite a significant jump compared to the rest of the changes observed on other timestamps. There are also minor drops in the rate (e.g., around '2024-02-19 06:00:02' and '2024-02-23 04:00:02') but not as significant as the former.

    It's also worth noting that the fluctuations within the timeframe given does not seem to be anything unusual, and deviations are common in exchange rate data. It would be beneficial to understand the macroeconomic context of these movements, but it has been specifically mentioned not to consider external factors.

    Conclusion

    In conclusion, based on the dataset provided, the GBP exchange rate trends upwards with periodic fluctuations and few significant deviations. More extended series or additional datasets may provide more insights into potential patterns or seasonality if they exist.

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. Overall Trend of Exchange Rates

    The dataset provided reflects exchange rate values for GBP at different time stamps. The values start from 1.70696 on 2024-02-23 00:00:02 and end at 1.7107 on 2024-02-23 14:55:01. The dataset shows a general increase in the exchange rate throughout the timeframe.

    2. Seasonality or Recurring Patterns

    In examining the dataset, there do not appear to be substantial recurring patterns in the exchange rate. It seems to fluctuate fairly consistently and gradually increases over time. There does not seem to be significant seasonality in the dataset. However, as this dataset only covers a single day, this may not accurately represent larger seasonal trends that could be seen in a broader timespan.

    3. Notable Outliers

    Within the provided dataset, there aren't significant outliers, as most values appear to fit within the overall upward trend of the rates. The fluctuations that do occur tend to be minimal, and there are no drastic or unexpected changes in rates that would qualify as outliers. However, there are few points where the rate has slightly increased or decreased.