Rial Omani 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

    1. Overall Trend of the Exchange Rates

    From the provided data, we can observe slight fluctuations in the OMR exchange rate over a period of 24 hours. However, there is a noticeable trend in the data. The exchange rate started at 3.52619 and ended at 3.52536. This indicates a slight decrease in the OMR exchange rate throughout the day. However, this downward trend is very minimal and suggests that the exchange rates are generally maintained at a stable level with minute variations.

    2. Seasonality or Recurring Patterns in the Changes of Exchange Rates

    The data does not show any clear seasonality or recurring patterns within the given 24-hour period. The OMR exchange rate shows a pattern of slightly decreasing and then slightly increasing throughout the day, but does not show a consistent pattern that repeats at regular intervals. There are also no clear patterns identified in terms of specific times during the day when the exchange rates consistently increase or decrease.

    3. Outliers in the Exchange Rates

    Given the small variance and range of the OMR exchange rates, it is challenging to identify any significant outliers. The bulk of the rates range from around 3.526 to 3.53, and only a few instances occur outside this range. These instances could be considered mild outliers but do not differ significantly from the trend.

    Moreover, since the given data does not exhibit strong seasonality or recognizable pattern, it's difficult to determine specific thresholds or bounds for considering an observation as an outlier. Small fluctuations in the currency exchange rate are normal and can be affected by various macroeconomic and non-systematic factors, such as demand-supply balance, investor perception, speculation, etc.

    In summary, the exchange rate has slightly decreased throughout the day, exhibited minimal variance, and showed no clear seasonal patterns or significant outliers within this 24-hour period.

Summary of Yesterday

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

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Dataset Overview

    The provided dataset holds time-stamped Omani Rial (OMR) exchange rates covering 1 day on 28th February 2024 with each timestamp approximately 5 minutes apart. The exchange rates permit us to explore the fluctuations throughout this period, analyze patterns and notable insights from this financial time-series data.

    Analyzing the overall trend

    Upon analyzing the data, the OMR exchange rates started at 3.51948. Towards the end of the day, the rate slightly increased, closing at 3.52558. This implies that the overall trend in exchange rates for the 28th of February 2024 was marginally increasing.

    Seasonality or Recurring Patterns

    In the context of intra-day exchange rates, seasonality or recurring patterns can often be linked to market open and close hours. The highest exchange rate recorded on this day was 3.53411, and the lowest was 3.51913. On an intraday trading perspective, there doesn't appear to be any clear recurring pattern on this particular day. However, a comprehensive identification of seasonality would require a larger dataset, preferably spanning across several weeks or months.

    Identification of Outliers

    Regarding outliers in this specific dataset, the quickest way in this time-series data to identify outliers would be spotting any significant jumps or drops within a short period. From the given data, there were no drastic spikes or drops in the exchange rate in these 5-minute intervals, indicating the lack of any notable outliers.

    Nevertheless, the efficiency and accuracy of an outlier detection approach would drastically improve with a more extensive dataset.

    External Factors

    Although external factors such as market opening and closing hours, weekends, and the release of key financial news and reports typically play a crucial role in influencing exchange rates, this analysis is based purely on the data provided and does not consider these factors.

    Note

    This analysis provides an overview based on the exchanges rates of; one single day and to precisely determine patterns, trends, and seasonality, it's recommended to have a more extensive dataset that covers a longer period. This analysis serves as an example of what can be achieved with limited time-series data.

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

    Understanding of overall trend of the exchange rates

    The dataset provides a close to real-time snapshot of the OMR exchange rate from 2024-02-26 00:00:02 to 2024-02-26 23:55:02. At a high level, the exchange rate was fluctuating between 3.50717 and 3.51475 during this period. Looking at the start and end of the period, the exchange rate has a slight decrease, starting at approximately 3.50952 and ending at approximately 3.50758. However, the fluctuation within this time frame is noticeable and should not be overlooked. It is also important to note here that, these fluctuations are quite minimal and the value of the exchange rate does not show a significant change throughout the day.

    Identifying any seasonality or recurring patterns in the changes

    In terms of patterns, the data seems sparse over the day. One observation is that there are some minor increases in the exchange rate during the early hours of the day (1:55 to 3:00) and then a slight decrease (3:00 to 4:00). However, these patterns are not very pronounced and they do not persist throughout the data. Evidence of a clear daily seasonality or recurring pattern does not appear to be strong in this dataset.

    Noting any outliers

    Based on the data provided there do not appear to be any significant outliers or anomalies in the data that would warrant concern or further investigation. The range of exchange rates remains fairly consistent across the time period shown, with no jumps or falls that would indicate a significant event affecting the exchange rate. It's also important to remember that the exchange rate market is generally very liquid and efficient, meaning any major swings or deviations are likely to be quickly corrected by the market.

    Summary

    In summary, this currency exchange data exhibits some small degree of fluctuation throughout the day, but there is no strong pattern or trend either upwards or downwards over this period. Similarly, no clear seasonal patterns exist in the data, indicating that the exchange rate may be more influenced by short-term factors such as market demand and supply rather than any regular, cyclical factors. And finally, the dataset does not appear to contain any significant outliers which could have an impact on the analysis. This paints a picture of a fairly stable currency exchange market for the day reviewed.

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

    Overall Trend of Exchange Rates

    The exchange rate data indicates a wide range of variation over the observed period. The trend shows periods of both increase and decrease with the rates ranging between 3.47058 - 3.52953 OMR. In order to categorize the general trend of the data, more specific statistical measures such as the mean and median, or a more in-depth time series analysis would be helpful.

    Seasonality or Recurring Patterns

    Without specific knowledge about external influencing events or factors that correspond to these timestamps (as those are not to be considered), it is challenging to definitively identify any seasonality or recurring patterns solely based on the provided data. Nonetheless, if we divide the data into specific time durations (daily, weekly), we may be able to identify patterns or cycles of fluctuation. Further analysis using methods like autocorrelation would be needed to confirm any possible seasonal patterns.

    Outliers

    In any time-series data, outliers are usually sharp spikes or dips that don't align with the general trend of the data. Within this dataset there may be potential outliers, however, without a clear trend or pattern discerned, it is challenging to definitively identify these. Useful techniques for spotting outliers could include using a moving average to smooth the data or plotting the data visually to detect any potential anomalies.

    While this analysis provides some insight into overall trending and potential outliers and seasonal patterns, a more detailed analysis, making use of modern analytical tools, will yield a much deeper understanding of the data. Time-series decomposition analysis can break down the data into its trend, seasonal, and random components, and regression analysis can help to compare the influence of different factors on the exchange rates.

Summary of Yesterday

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

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Understanding the Overall Trend

    Inspecting the given dataset which ranges from 19th of February, 2024 to 23rd of the same month, it appears that the exchange rates have shown a mixed trend. The rate started at 3.50051 and ended up at 3.50710. Therefore, there is a slight increase in the exchange rate over this short period. However, throughout this period, there were signs of both increasing and decreasing trends observed within smaller time intervals. For example, the rate increased from 3.50051 to 3.50966 from 19th 1:00 am to 20th 2:00 am, but then decreased to 3.49460 on 22nd 6:00 am.

    Identifying Seasonality or Recurring Patterns

    Given the very short period that the dataset covers, it is not possible to conclusively identify any significant seasonality or recurring patterns. The dataset hints at possible hourly fluctuations throughout the day but without a larger dataset which could span over more weeks, months or years, any identification of a definitive pattern would be speculative at best. An extensive dataset over a longer period is required to identify whether there are daily, weekly, monthly, or yearly patterns.

    Noting Outliers

    While there was some fluctuation in the exchange rates across this period, the changes appear to have remained relatively consistent within a small range of values. There does not appear to be any instances where the exchange rate differs significantly from the general trend, which would be considered as outliers. However, for a more detailed outlier analysis, statistical analysis such as the calculation of z-scores or IQR could be used to identify data points that significantly deviate from the mean. Noting that in financial analysis, an outlier could also be seen as a steep increase or decrease in a very short span of time.

    Contextual Factors

    Even though you did not specifically ask for it, it's important to note that exchange rates can be highly influenced by a variety of factors. These could include economic indicators such as changes in interest rates or GDP growth, geopolitical events, or unexpected news events. While this analysis is focused solely on the provided data, a more comprehensive analysis might ideally take these contextual factors into account.

Summary of Yesterday

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

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Trend Analysis

    From the data provided, the overall trend of the Omani Riyal (OMR) exchange rate seems to be fluctuating but with a slight increase over the period in question. The minimum value of 3.49808 is seen at '2024-02-23 06:55:02', while the maximum value of 3.51109 registers at '2024-02-23 10:20:03'. This indicates an overall increase in the exchange rate during the given duration. However, the exchange rate does not exhibit a steady rise or fall but undergoes several peaks and troughs throughout the dataset.

    Seasonality Analysis

    The data does not seem to exhibit clear seasonality as the OMR exchange rate does not seem to go through structured or recurring changes that could be associated with specific times of day or specific intervals. Rather, the rate shows irregular fluctuations. However, a finer analysis might be necessary to confirm the lack of seasonality, as the dataset only covers a very short period.

    Outlier Identification

    As for outliers in the dataset, there doesn't appear to be extreme deviations from the trend. The data points seem to be relatively close to each other. Any significant spikes or dips could be considered as potential outliers, but due to the relatively limited range of values and apparent random fluctuations, it's hard to clearly define what would constitute an outlier in this data.

    Please note that while the analysis does not account for real-life incidents such as market news, changes in the economy, or trading times, these factors can have a significant impact on the actual exchange rate trends and fluctuations.