US Dollar Forecast

Not for Invesment, Informational Purposes Only

Summary of Yesterday

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Statistical Measures

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    Overall Trends

    Upon analysis, there's a slight decreasing trend observed in the time series data. The USD exchange rate started from around 1.35745 and gradually decreased to end at 1.35708. This suggests that during this period, the dollar slightly depreciated against the other currency in the exchange rate. However, the change is minimal implying a generally stable rate.

    Seasonality and Recurring Patterns

    From the data provided, it is difficult to identify definite seasonality or recurring patterns purely based on exchange rates at different times. This is simply because markets are influenced by many different factors, and changes in exchange rates could be driven by any number of these individual influences rather than predictable or seasonal trends. Determining recurring patterns would require a deeper evaluation perhaps involving more data and possible decomposition of the time series data.

    Outliers

    There are no significant outliers in the dataset. The largest single jump in the data appears to be from 1.35745 to 1.35856 which though significant, isn't massive enough to be considered a major anomaly. However, without knowing the broader context or the average usual range of changes, it's hard to definitively identify this as an outlier.

    It should be noted that these analysis are high-level and based on the data provided, further granularity may offer more insights and a more accurate picture.

    In future analysis, it would also be useful to consider more variables besides timestamps and rates, such as trading volumes, macroeconomic indicators or even external news events, to provide a more comprehensive view.

Summary of Yesterday

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Statistical Measures

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    1. Understanding the Overall Trend of the Exchange Rates

    Analyzing the data, we observe that the overall exchange rate of USD exhibits a slight upward trend from 1.35481 to 1.35717 over the given period. Although there are fluctuations throughout this period, the general movement is an increase. It is important to note, however, that the changes are on a very minor scale (from 1.35481 to 1.35717), indicating a relatively steady or stable rate over this period.

    2. Identification of Seasonality or Recurring Patterns in Exchange Rates

    From a high level perspective, there doesn't appear to be any clear-cut seasonality or a recurring patterns existing within the given dataset. It's well-known that Forex markets are influenced by a plethora of factors, including macroeconomic data, political events, and market sentiment amongst others which are not part of provided data set. In-depth analysis or more granular data might be required to effectively identify potential patterns or trends.

    3. Noting Outliers in the Exchange Rates

    From the data, it appears that there aren't any significant outliers where the exchange rate differs substantially from the overall observed range. The exchange rates aren't characterized by spikes or abnormal changes that would signal significant outliers. The rate oscillates within a relatively close range, which is to be expected due to the numerous factors contributing to exchange rate flux. However, outliers in exchange rate data are often the result of economic events and announcements which should not be considered in this analysis.

Summary of Yesterday

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Statistical Measures

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Summary of Last Month

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    Overall Trend Analysis:

    In general, the USD exchange rate appears to fluctuate throughout the dataset provided, but it lacks a clear monotonous trend (consistent increase or decrease). Over the time period, the exchange rate frequently moves up and down, indicating a state of market volatility rather than continuous growth or decline. This could suggest that other factors such as news events, economic indicators and broader financial market sentiment might be having an impact on the changes in the exchange rate.

    Seasonality and Recurring Patterns:

    There does not appear to be a clear seasonality or recurring pattern in the dataset at first glance. It is worth noticing that due to the nature of foreign exchange markets, which operates 24 hours a day except for weekends, periodic fluctuations often happen on an intraday basis. A more in-depth statistical analysis or a time series decomposition model may reveal subtle daily, weekly, or monthly patterns that could not be ascertained from a mere observation of the figures. However, such deep analysis might be beyond the scope of this assessment.

    Anomalies and Outliers:

    There seem to be no major shocks or outliers in this dataset at first glance. The rates typically float within a small range, with no tremendous upticks or nosedives that would suggest market shocks or anomalies. In-depth outlier detection techniques need to be used to reveal any abnormal activity not immediately obvious from a manual inspection.

    Note: Despite this analysis conducted, it's highly recommended to consider market factors such as business hours, financial news, and financial indicators for a more comprehensive understanding of the exchange rate movements. Foreign exchange markets are highly sensitive to global news and events and often react accordingly.

Summary of Last Week

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Statistical Measures

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    The dataset given is time-series data of exchange rates (USD) from January 26, 2024, to February 23, 2024. The data appears to be collected at different times throughout each day giving a detailed image of the currency fluctuations during this period.

    1. Trend Analysis

    By examining the data chronologically, it appears there is no clear increasing or decreasing trend in the USD exchange rate over this period. While there are fluctuations throughout, the first recorded exchange rate was 1.34739 on Jan 26, 2024, whereas the last recorded rate is 1.35008 on Feb 23, 2024. Therefore, although there are peaks and troughs between these dates, the overall exchange rate remains relatively stable throughout the period.

    2. Seasonality

    Identifying seasonality requires longer periods of data because seasonal fluctuations typically occur over quarterly, monthly, weekly, or daily cycles. In this dataset, there isn't enough temporal range to deduce a strong annual or quarterly seasonality. However, one could infer from this data that exchange rates might show cyclical fluctuations during given times of the day, possibly driven by the opening and closing hours of the major financial exchanges around the world, although external factors were not considered in this analysis per instructions.

    3. Outliers

    When considering outliers, it's critical to note that finance data like exchange rates can be highly volatile and influenced by numerous factors. However, the spike in exchange rate on Feb 13, 2024, where the exchange rate jumps from 1.3449 to 1.3524 might be seen as potential outliers. To confirm this, more detailed statistical analysis would be needed. Other slight fluctuations throughout the dates could be perceived as the market's natural ebb and flow rather than outliers. It's crucial in the future to analyze these potential outliers in context with market events or news during that period.

    In conclusion, based on the dataset and without considering external factors, the USD exchange rate during this period appears to remain relatively stable with no clear increasing or decreasing trend. While there are fluctuations, possible daily cyclical impacts, and potential outliers, these require a more in-depth analysis to confirm.

Summary of Yesterday

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Statistical Measures

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    Overview and Trend Analysis

    From the data presented, it is evident that there are fluctuations in exchange rates over the time period shown, which is typical of financial markets as they continuously adjust to supply and demand dynamics. The movement contains both increases and decreases in value, indicating the existence of some volatility.

    Seasonality and Recurring Patterns

    Seasonality or recurring patterns in the data can be challenging to identify without further information regarding the time period of each observation. However, we may consider looking into specific times within the day across the given duration as there might exist patterns there. It's also worth considering longer period trends, such as weeks or months patterns.

    Outliers

    In the time series data provided, it is hard to definitively point out specific outliers as the fluctuation seems to be irregular and inconsistent. It would require more sophisticated methods such as statistical screening and modelling (like using standard deviation or Z score) to identify these points precisely. Without considering external events or factors that may explain such outliers, it is tough to identify whether these are due to abrupt changes in the financial markets or possibly errors in data collection.

    These findings are all based solely on an initial review of the data and could be substantially enhanced with more detailed statistical analysis. This could include using advanced techniques like variance analysis, trend decomposition, spectral analysis, and others, depending on the specific goals of the research.

    These preliminary findings should not be used for making actual investment decisions without further and more detailed analysis. It is also important to note that past performance does not predict future results when it comes to financial markets.

Summary of Yesterday

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Statistical Measures

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    Overall trend in the exchange rates

    Looking at the data provided, the overall trend of the exchange rates seems to be gradually increasing. The value at the end period is higher than the beginning. Despite some fluctuations, it shows an upward trend. However, the rates varied quite significantly within the given timeframe, suggesting potential volatility in the underlying currency market.

    Seasonality and recurring patterns

    It's challenging to definitively identify any seasonality or recurring patterns in the exchange rates because of the narrow time window (one day) of the data provided. Exchange rates depend on a vast array of factors, some of which operate on much longer timescales. However, larger time-series datasets could potentially reveal daily patterns connected to the opening and closing times of different international financial markets.

    Notable outliers

    Concerning outliers, most of the exchange rates falls within a reasonably close range. However, a few values deviate notably from the overall trend, suggesting possible extreme market events or maybe simple discrepancies or errors in the data.

    Again, it's worth noting that this analysis is fundamentally limited by the brief timeframe of data given. Achieving a comprehensive understanding of exchange rate trends and patterns would require a much larger dataset, covering months or even years rather than just a single day.