Jordanian Dinar Forecast

Summary of Yesterday

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Statistical Measures

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Trend

Overall Trend of Exchange Rates

From the given data, it seems the exchange rates fluctuate within a certain range rather than showing a consistent increase or decrease over time. There is an observable fluctuation between 1.925 to 1.937, showing a fairly stable trend with no drastic rises or falls in exchange rate. However, a careful note should be made that this trend is not a predictive measure for future performance and is only based on the given data set.

Seasonality and Recurring Patterns

No clear seasonal trend or recurring pattern can be conclusively identified from the provided data. For a robust analysis of seasonality, a more granular level data for multiple cycles (e.g., yearly or monthly data for multiple years) would be required. In time-series analyses, seasonality often refers to specific and regular patterns throughout the data during specific times (like weekdays vs weekends, month-start vs month-end, etc.). Given the provided data only covers a single day, it is not possible to determine if any robust daily pattern exists or to infer a longer-term seasonality.

Outlying Observations

While there are small fluctuations in the exchange rate throughout the given time period, there is no apparent outlier in the data. All observed changes are relatively minor and there are no instances of extreme peaks or troughs. However, it's crucial to note that 'outliers' in financial markets are often subjective and can be better identified with the context of the market situation, event timelines, or abnormal trading behaviors.

External Factors Consideration

As per your instructions, external factors such as market opening/closing hours, weekends/holidays, or the release of key financial news and reports are not considered in this analysis. These factors can have significant effects on the exchange rates, often leading to spikes or dips in the values. Nonetheless, these factors were not included in our analysis, and the overview provided is strictly based on the numerical time-series data provided.

Summary of Yesterday

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Statistical Measures

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Trend

Analysis of Exchange Rates

Based on the provided dataset, the following trend analysis, seasonality identification, and outlier inspection were made.

1. Understanding the Overall Trend:

The general trend of the exchange rates (JOD) within the provided period seems to be slightly increasing. The rates moved from 1.92796 as an initial value to 1.93196 as a final value. However, the fluctuation in rates is relatively minor within the considered time period, which suggests a relatively stable rate.

2. Identifying Seasonality or Recurring Patterns:

Identifying seasonal changes necessitates longer intervals, such as annual or quarterly data. Considering the dataset, which only spans one day, no seasonality or recurring patterns seem to be identified within the timeframe of the given data.

3. Noting any Outliers:

In terms of identifying outliers where the exchange rate differs significantly from the trend, it is difficult to note any significant outliers without a graphical representation or statistical analysis. However, one spike does appear at 07:45:03 with the value of 1.93455, which seems to be significantly higher in comparison to the closely surrounding data points. Yet, these are preliminary observations and further statistical investigations are suggested for concrete conclusions.

Conclusion:

In conclusion, the trend of the exchange rate for the time period analyzed is relatively stable with a slight increase. No recurring patterns or seasonality were identified in this data set, and a few potential outliers are noted. To gain a more in-depth understanding of these observations, it would require a larger dataset spanning a longer time frame, and potentially more rigorous statistical or machine learning based time-series analysis methods.

Summary of Yesterday

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• Difference of Daily High & Low:

Statistical Measures

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Trend

Overall trend of the exchange rates

The first step in analyzing this data involves parsing the timestamps and examining the associated exchange rates at these times to understand the overall trend. By plotting the exchange rates against time, we can identify if rates generally increase, decrease, or remain stable over the period shown in the data.

Seasonality or recurring patterns

Seasonal decomposition analysis would be useful in revealing any recurring patterns or seasonality in the data. The exchange rate time series can be broken down into a trend, seasonality, and residual components. This helps us to see clearly the underlying patterns in the data, if any. Certain times of the day or specific days may demonstrate regularly higher or lower rates than the rest of the data.

Outliers

Outliers may be identified by examining points where the exchange rate deviates significantly from the trend or the seasonal pattern. This can be achieved by plotting a boxplot of the amount of change between consecutive periods, and identifying any significant deviations from the median change. These may be instances where the exchange rate differs significantly from what would be expected based on trend or seasonality.

External Factors

Please note that in this analysis, we have not considered external factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports. Though they can significantly affect exchange rates, these external factors are outside the scope of this analysis as specified in the provided requirements.

Forecast

As per the goal specified, we have not generated any forecasts for future rates.

Summary of Last Month

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Trend

Understanding the Overall Trend of the Exchange Rates

Based on the time series data provided, the JOD exchange rate seems to experience both slight increases and decreases throughout the duration, but generally, it maintains relative stability. The rate starts at 1.93706 on 2024-04-22 00:00:02 and ends at 1.93263 on 2024-04-22 23:55:02, indicating a slight overall decrease.

Identifying Seasonality or Recurring Patterns

Due to the limited size of the time series data (covering just a single day), precise identification of seasonality can be challenging. However, an observation of the data suggests some periods of increased fluctuation in the exchange rate during certain hours of the day. More data covering a more extended period may be required to precisely identify and analyze any potential seasonality or recurring patterns though.

Noting Outliers

In reviewing the JOD exchange rate data, several instances show a relatively significant change that may be considered outliers. For example, at 08:35:03, the exchange rate spiked to 1.93979, higher than the surrounding data points. However, outliers in financial time series can often have very reasonable explanations (major financial news, market trends, etc.) but as per your instructions, we won't consider external factors for this analysis.

In summary, the exchange rate depicted in this dataset mainly maintains stability with minor fluctuations. There are periods of increased fluctuation, but a single day's data limits identifying recurring patterns or seasonality. Some outliers are noticeable, but their causes are not analyzed due to restriction on considering external factors.

Summary of Last Week

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Trend

JOD Exchange Rate Overall Trend Analysis

From a preliminary review of the data provided, the JOD exchange rates have shown a certain level of fluctuation. For a comprehensive understanding of the overall trend of the exchange rates, the JOD rate would be plotted against the timestamps. The purpose of such a plot is to provide a visual understanding of the trend - if it's increasing, decreasing or stable over time. This analysis does not predict future exchange rates but rather demonstrates the trend within the limited timeframe of the dataset.

Identifying Seasonality/Recurring Patterns

Another aspect of time series data analysis is the recognition of any seasonality or recurrent patterns in data. Seasonality refers to periodic fluctuations. For instance, retailers may experience higher sales volume before holidays. Seasonality is always of a fixed and known frequency. The dataset provided features a timestamp which suggests that the JOD rates change more than once within a day, therefore intraday seasonality might be identified if there is a recurrent change in rates within the trading hours. This remains to be determined after further advanced analysis.

Outliers Detection

Outliers in data can distort predictions and affect the accuracy, if you don’t detect and handle them appropriately especially in forecasting where machine learning algorithms are involved. In terms of the JOD exchange rate, outliers could possibly be the rates that significantly vary from the general trend and pattern detected. Outliers might suggest a significant change in the market, high volatility or possibly a data collection error. Detecting outliers in this dataset will be conducted by plotting the rate changes, where significant spikes or drops beyond the expected consistency might suggest an outlier. However, determining an outlier also depends on the context of the data and the methodology used for detection.

Not Considering Specific Events or External Factors

Although identifying specific events and considering external factors might highly improve the understanding and prediction scope of the financial analysis, this analysis is limited to understanding the patterns and trends of the historical data provided. Hence, this analysis did not consider any external factors such as market opening/closing hours, weekend/holidays, or the release of key financial news and reports.

Please note, it's crucial to understand every piece of methodology and analysis mentioned has its own assumptions and limitations. So, the results should be interpreted under these assumptions and limitations only.

Summary of Yesterday

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Statistical Measures

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Trend

1. Understanding the Overall Trend of the Exchange Rates

Looking at the dataset, the exchange rates show slight upward and downward movements within a range between approximately 1.93757 and 1.95134. This indicates fluctuations in the exchange rates. However, there's a subtle upward trend noticeable from the start to the end of the provided dataset. It is crucial to understand that even minor changes in these rates can offer significant implications in financial transactions.

2. Identifying Recurring Patterns or Seasonality

From a first glance, there seems to be no clear evidence of distinct seasonality or recurring patterns in this dataset. The exchange rate values don't appear to follow a strong regular or periodic trend within the given timestamps. Typically, seasonality is more evident in longer-term data, encompassing variations over multiple quarters or year-on-year changes. However, without additional details on the timing or particular events occurring within each timestamp, it is challenging to accurately identify any specific seasonality in these hourly exchange rates.

3. Identifying Outliers

In this dataset, no evident outliers are noticed from a preliminary perspective. The exchange rates stay within the specific range as stated earlier and don't depict any extreme values or sudden jumps that would characterize outliers. Nevertheless, a more accurate identification would entail employing statistical methods such as the standard deviation method, Z-score method, or the IQR method.

Please note that in financial analysis, it's essential to consider macroeconomic factors, market conditions, and external events like key financial news, which might significantly influence the exchange rates. However, as per the request, these factors haven't been considered in this analysis.

Summary of Yesterday

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

Statistical Measures

• Mean:
• Standard Deviation:

Trend

1. Overall Trend of the Exchange Rates

From the given dataset, the exchange rate of JOD currency appears to be mostly fluctuating within a certain range. The highest value it reaches is approximately 1.94508 and the lowest being around 1.93700. However, there isn't a clearly defined increasing or decreasing trend, instead, the value seems to oscillate in an unpredictable manner. This suggests that the exchange rates are being influenced by a multitude of factors and do not follow a strict linear pattern.

2. Seasonality and Recurring Patterns

Upon continuous observation and evaluation of the dataset, it's challenging to pinpoint any distinct seasonal or recurring patterns. The rates seemingly vary within a set boundary rather than showing any cyclical changes which is often characteristic of seasonality. Thus, we can infer that any shifts in these specific exchange rates are not necessarily attributed to a precise time frame or pattern.

3. Detection of Outliers

Outlier detection in financial analysis is a key step in ensuring data integrity. From the provided data, the JOD exchange rate remains within a relatively tight range. This means there are no observable outliers or instances where the rate drastically deviates from the overall trend. However, it's important to note that the interpretation of 'outliers' can vary and some might consider minor spikes or dips in exchange rates as potential outliers depending on their impact on financial models or predictions.