New Israeli Sheqel Forecast

Not for Invesment, Informational Purposes Only

Summary of Yesterday

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Statistical Measures

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    Overall Trend of Exchange Rates

    Analysing the provided dataset, we can ascertain a slight rising trend in the exchange rates over the given time period. The exchange rate starts at approximately 0.37768 and ends at 0.37993, indicating a minor increase over the data points. However, it's important to note that the trend is not a constant climb - there are several points of adjustment where the rate dips or plateaus momentarily before continuing its upward rise.

    Seasonality and Recurring Patterns

    Upon close inspection of the trends, there appears to be a certain amount of seasonality or recurring patterns in the given ILS exchange rates. Typically, there are short periods of steady or slightly increasing values, followed by shorter periods of decline, after which the pattern repeats. It's noteworthy that these patterns don't occur with consistent frequency or severity, indicating possible influence from uncontrolled external factors.

    Outliers and Unusual Observations

    The dataset does not have any explicit outliers, meaning all the exchange rates fall in a very close range. However, some points do break from the typical pattern and can be considered atypical if not outliers in the strict sense. Specifically, there are few instances where the exchange rate either increases or decreases slightly more steeply than is typical for this dataset. It's worth noting that these atypical points may be due to random variation and do not necessarily indicate a significant shift in the underlying trend or pattern.

    Conclusion

    In conclusion, this is a decently comprehensive financial analysis of the exchange rates, giving vital insights into the overall trends, patterns, and possible anomalies within the data. Despite the minor inconsistencies and fluctuations, the ILS exchange rates show a general increasing pattern, but the upward trend is relatively flat, and the rates remain in a relatively narrow range. Notwithstanding, an understanding of these innate trends and patterns can prove to be beneficial for financial forecasting and decision-making.

Summary of Yesterday

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Statistical Measures

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    Overview of the Exchange Rate Trend

    The data provided spans roughly a day, starting from midnight and extending till close to midnight of the next day. The overall trend observed indicates a relatively mild increase in the exchange rates over this period. The exchange rate started at approximately 0.37547, and by day-end, it had risen to around 0.3776. This suggests an upward trend in the exchange rate over the given day.

    Seasonality and Recurring Patterns

    Due to the limited scope of the data provided (only one day's worth of timestamps), it is not possible to ascertain seasonality or recurring patterns with absolute confidence. For seasonality identification, typically, a longer duration of data is needed, encompassing several instances of the seasonality period (daily, weekly, monthly, etc.). However, within this single day of data, some minor fluctuations in the exchange rate can be observed throughout the day that could potentially indicate intra-day trading patterns.

    Outliers in Exchange Rates

    Outliers, or values that deviate significantly from the overall pattern, are not abundantly clear in this data. The exchange rates do not show any significant spikes or drops within the given day. Generally, the changes from one timestamp to the next are quite small, indicating relatively stable rates throughout the day. Nonetheless, more sophisticated statistical tests would be needed to confirm the presence or absence of outliers, which is beyond the scope of this preliminary analysis.

    Non-consideration of External Factors

    Please note, this analysis is purely based on the data given 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. While such factors can significantly impact exchange rates, they were not considered in this analysis due to the limitations stated in the instructions.

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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    1. Overall Trend of Exchange Rates

    Upon analyzing the time-series data, the overall trend of the exchange rates shows fluctuation but no clearly identifiable upward or downward trend. There are spikes and falls, however, the exchange rate value starts at 0.37206 and ends at 0.37082, showing a slight decrease over the period.

    2. Seasonality or Recurring Patterns

    The dataset does not exhibit a clear pattern of seasonality. Seasonal trends are most obvious when changes occur at regular intervals, and while there are certain cycles of increase and decrease throughout the dataset, they do not appear to follow a predictable pattern that repeats at specific intervals.

    3. Notes on Outliers

    Outliers in time series data represent periods where the exchange rate differed significantly from the average rate. Identifying exact outliers without statistical modeling is challenging, but at a glance, several points in the data might be considered as outliers such as the slight peaks and troughs throughout the data. However, without a prior reference point of what standard range should be, it is difficult to label them definitively as outliers. It's advised to employ a statistical method for outlier detection if precise identification is necessary.

Summary of Last Week

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Statistical Measures

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    Understanding the Overall Trend

    From a cursory look at the dataset, an overall upward trend in the ILS exchange rate can be observed throughout the specified period. This is demonstrated by the data starting at a rate of 0.36351 on 2024-01-26 and concluding at a rate of 0.37188 on 2024-02-23. However, the rate does not increase consistently, evident from several dips below the general trend line. This signifies that the exchange rate experiences fluctuation over this period, although an upward trend is still discernable.

    Identifying Seasonality or Recurring Patterns

    Due to the limited duration of the dataset provided, identifying significant recurring patterns or seasonal trends can prove challenging. Generally, in such datasets, seasonal trends could be seen within a yearly cycle, or patterns might be visible on a weekly basis such as higher or lower rates on certain days of the weeks. In relation to the dataset in question, no clear recurrent daily patterns could be recognized at first glance. However, a more detailed or statistical analysis might reveal such subtle patterns.

    Noting Any Outliers

    In this dataset, no prominent outliers are immediately visible, signifying instances where the exchange rate differs noticeably from the general trend or expected values. Most values appear to remain within a reasonable proximity to their preceding and following values, indicating a level of consistency in the rate changes. It must be noted that a deeper analysis using statistical methods may identify minor outliers or anomalies that aren't readily perceptible through visual inspection of the data.

    In conclusion, while the dataset reflects an overall upward trend in the ILS exchange rate, numerous fluctuations do occur, and determining detailed patterns or anomalies may necessitate a more robust statistical analysis.

Summary of Yesterday

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Statistical Measures

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    1. Overall trend of the exchange rates

    The provided dataset spans a few days in February 2024. A simple overview seems to show an oscillating pattern with slight fluctuation; the exchange rates do not showcase a very clear increasing or decreasing trend. The values tend to fluctuate between the ranges of approximately 0.366 to 0.373. There does, however, appear to be a more noticeable drop around the 20th, to lows near 0.367 from a high of near 0.373 the days prior. Towards the end of the dataset, the exchange rate seems to be increasing again.

    2. Identification of seasonality and recurring patterns

    Due to the short period of the provided dataset, it's challenging to identify any significant seasonality or recurring patterns. In financial series data, patterns usually emerge over long periods, generally a year or more so as to take into account monthly and yearly cyclical economic activities. With just several days of data, even intraday patterns may not be accurately judged. However, there seem to be minor fluctuations throughout the day, with smaller changes during the early hours and larger changes during the later hours.

    3. Outliers in the data

    An outlier examination would normally involve a deep statistical analysis considering mean, median, quartiles, and standard deviation. With only this rudimentary view, it is difficult to define certain points as outliers directly as our dataset is quite compact. Highs of around 0.373 and lows of 0.366 could be worth noting, but without proper statistical analysis, it's not viable to single them out as definitive outliers.

    That being said, the rate generally seems to be quite stable during the plotted days, staying between 0.366 and 0.373. This does not dismiss the possibility of outliers within this range, but there are no glaring deviations that draw one's attention immediately.

Summary of Yesterday

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Statistical Measures

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    1. Understanding the overall trend of the exchange rates

    After analyzing the given data, it's been noticed that the exchange rate starts at 0.37064, reaches the maximum of 0.37230 and then drops to the closing rate of 0.37192. The data does not show a clear upward or downward trend in the exchange rate over the given period. The currency seems to be relatively stable, with small fluctuations throughout the time range. The most frequent exchange rate range being from around 0.371 and 0.372. There is no clear ascending or descending pattern identified in the limited time series provided.

    2. Identifying seasonality in the exchange rates

    Considering that the time-stamped data is within a small and short-lived time window, it is impossible to accurately identify any seasonal trends or patterns. The exchange rates seem to fluctuate relatively randomly within a small range, suggesting they could be influenced by minute-by-minute marketplace factors, which are typically very complex and multifaceted.

    3. Noting any outliers in the dataset

    Most of the values in the dataset move between 0.370 and 0.372; hence all figures are within this range and hence do not have any outliers. All values seem to be closely packed to each other, indicating the absence of massive shifts within the overall trend. Each rate change from one timestamp to the next appears to be small and within an expected range, therefore we cannot determine any widespread volatility or unexpected outliers in the given dataset.

    In conclusion, in the given time range, the exchange rate is relatively stable with minor fluctuations. There doesn't appear to be a notable trend or repeated patterns due to the short time frame of the dataset. Similarly, the dataset doesn't include any significant outliers, with exchange rate changes being consistently small from one timestamp to the next.

    Note: The analysis is limited to the data set provided and does not take into account broader market trends or external influencing factors that might cause larger trends or changes in the exchange rate over a longer period or at different times.