Qatari Rial Forecast

Not for Invesment, Informational Purposes Only

Summary of Yesterday

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Statistical Measures

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    Analysis of the Dataset

    Based on the data provided, an analysis is conducted to understand the behaviour of exchange rates (QAR) at various time points. To accurately assess the dataset's trends and outlying figures, the details have been divided into different sections, all explained as follows

    1. Trend Analysis of Exchange Rates

    We can note from the data that there are both periods of stability and slight fluctuation. The exchange rate bounces between a small range quite frequently, showing marginal increases and slight decreases sometimes within five-minute intervals. Thus, it can't be definitively said that the rates generally increase or decrease over the period shown as the changes appear to be marginal and frequent. The value remains relatively stable in the broader perspective.

    2. Seasonality and Recurring Patterns

    Identifying any seasonality or recurring patterns from the string of data provided is challenging without extensively formatted and visualized data columns. Nonetheless, there does not seem to be an obvious recurring pattern based on the provided data. The fluctuations appear somewhat random and do not exhibit clear cyclical behaviour, so it's hard to assert any seasonality trend.

    3. Notable Outliers and Significant Instances

    With the provided data at the level of granularity (i.e., every 5 mins), it's difficult to identify outliers purely by bare eye inspection. Further numerical analysis such as Z-score analysis, IQR method or Box Plot visualization might help identify those potential outliers in this dataset. It's also crucial to remember that true anomalous points could be highly impactful events affecting the exchange rate or could simply be instances of high volatility or drastic change in the exchange rate.

    This analysis is a preliminary interpretation based on the provided data. For more accurate findings, and to fully understand the trends, patterns, and outliers, a more detailed statistical scrutiny using appropriate financial time series analysis methods can be undertaken.

Summary of Yesterday

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Statistical Measures

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    Overall Trend of the Exchange Rates:

    The trend in the exchange rate appears to fluctuate slightly as the timestamp progresses. The rates begin at 0.37215 and towards the end, they show a value of 0.3728. A level of variation can be observed within this range throughout the dataset, with slight increases and decreases in values, keeping the exchange rate generally around the initial mark.

    Seasonality or Recurring Patterns:

    Due to the hourly nature of the data and without data for several days or months, it's difficult to identify a clear-cut pattern or seasonality. However, the fluctuations in values could suggest a possible intraday pattern, in which the value oscillates within a relatively confined range throughout different portions of each day represented.

    Identification of Outliers:

    Within the data range provided, none of the exchange rates significantly deviate from the central range of fluctuation, suggesting no clear outliers. The data maintains a relative consistency, seldom diverting far from the surrounding values..

    Note:

    This assessment is based on the historical data provided and doesn't account for any factors external to this specific dataset, such as market shifts, key announcements or economic fluctuations that may potentially have made an impact on the exchange rates.

Summary of Yesterday

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

Statistical Measures

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  • Standard Deviation:
  • Trend

Summary of Last Month

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Statistical Measures

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    1. Understanding the Overall Trend

    The dataset provided represents the QAR exchange rate recorded at different timestamps. The dataset spans for a 24 hours period on February 26, 2024. Initially, at 00:00:02 the exchange rate was 0.37111, and in the end, at 23:55:02 it was 0.3709. These values suggest that overall exchange rate fluctuated in both directions over the period and shows a slight decrease from the start to the end of the 24 hours time frame. However, the highest rate reached was 0.3716 and the lowest rate was 0.37084. The rate wasn't all the time decreasing or increasing, there are periods where it increased, then decreased and vice versa. The exchange rate graph will look like a zigzag.

    2. Identifying Seasonality or Recurring Patterns

    Without the help of visual aids such as graphs or more detailed descriptive statistics, it is challenging to assertively discern any type of seasonality. But by analyzing data it seems that there are no apparent recurring fluctuations that would suggest a recognizable pattern within this 24 hours period. It's generally better to analyze data over a more extended period to identify seasonality. This is because seasonality often happens over weeks, months or quarters, rather than individual days.

    3. Noting Outliers

    Analyzing the data, a number of instances were noticed where the exchange rate differed significantly from the rates immediately before and after. For example, the significant jump from 0.37108 at 01:40:02 to 0.37123 at 01:45:02, and another considerable fall from 0.37109 at 15:25:03 to 0.37101 at 15:30:02. Yet these movements aren't drastic and fall within the overall range of exchange rate values for the given day. Hence, they may not be considered as 'extreme' outliers.

    Speaking about outliers, here we should also consider whether to label some observations as outliers based on their absolute values or based on their relative change compared to the previous observation. The first approach might not be beneficial in this case, as all observed QAR exchange rates are within similar ranges – no drastic highs or lows are observed. However, the second approach might detect some points worthy of additional attention.

    In summary, your data demonstrate fluctuations throughout the day, with several significant exchanges that could be considered outliers. Further detailed statistical analysis, such as standard deviation or quartile analysis, may provide more insight into the extent of these fluctuations and the presence of outliers.

Summary of Last Week

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Statistical Measures

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    Overall Trend of the Exchange Rates

    The overall trend of the exchange rates indicates a slight fluctuation over the depicted period. Although there is a minor move upwards and downwards, the rate essentially stays within a tight range, not showing any dominant upward or downward trend.

    Seasonality or Recurring Patterns

    Regarding seasonality or recurring patterns, the data does not demonstrate any visible daily or weekly pattern. The data shows some movement fluctuation within a narrow range without any evident periodicity. Thus, without further data or information, identifying seasonality is challenging.

    Outliers Analysis

    Regarding outliers, the presented data appears to be free of any significant anomalies. Exchange rates over the given period are unsurprising and roll within a predictable and consistent range. Hence, no evidence suggests the occurrence of any significant event during this timeframe that could have caused major swings in the exchange rates.

    This analysis is based purely on the provided dataset. For a more precise and detailed understanding, it would be advisable to consider multiple factors such as economic indicators, market opening/closing times, geopolitical events, and other relevant factors which are outside the scope of current data.

Summary of Yesterday

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

Statistical Measures

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  • Trend

    Understanding the Overall Trend

    The overall trend of the Qatari Riyal (QAR) exchange rate provided from the dataset appears to be somewhat stable over the period. The exchange rate starts at 0.37005 on 2024-02-19, and ends at 0.37085 on 2024-02-23, showing only a slight increase during this period. However, there are fluctuations throughout the dataset, which signify constant change in the exchange rate. It's also important to note that there appear to be gradual increases and decreases happening throughout, which indicates some degree of volatility in this exchange rate.

    Identifying Seasonality or Recurring Patterns

    While being cautious about the short duration of our dataset, it seems there's not much strong seasonality or recurring patterns detected within the datasets. Exchange rates, in many cases, are influenced by a broad array of factors, including but not limited to interest rates, inflation, political stability, economic performance and speculation. And most of these factors are unlikely to follow a strict repetitive pattern in a short-term period. More specific or concrete patterns may not be discernible without a longer timeframe of data, or without deeper analysis that takes into account the mentioned factors occurring simultaneously.

    Noting Outliers

    Observing the dataset, the majority of the exchange rates fluctuate around 0.370-0.372. There are a few instances where the rates deviate from this range, reaching highs like 0.37169 and lows like 0.36944. These could potentially be considered outliers, or it could simple represent standard variation in exchange rates; without additional information or context, it's hard to definitively classify them as outliers. More data points or the presence of additional variables could assist in making this determination more accurately.

    However, the fluctuations within a range of 0.002 in a short duration of 5 days may not be considered as significant outliers in forex trading. Nevertheless, the presence of these deviations highlights the dynamic nature of currency exchange rates, and the necessity for constant monitoring and analysis for any party directly involved in forex trading or international business activities.

Summary of Yesterday

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

Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    Understanding the overall trend of the exchange rates

    Observing the data, the exchange rates experienced relatively minimal fluctuations throughout the period in question. The rates opened at 0.37031 and closed at 0.37089, hence the overall trend of exchange rates over this time period appeared to be relatively stable with a minor increase.

    Seasonality or recurring patterns in the changes of exchange rates

    Seasonality or recurring patterns in financial time-series data typically refer to consistent and predictable movements in the data that occur at regular intervals. Looking at the provided dataset, such easily identifiable patterns do not seem to be present, largely due to the relatively limited variation in the exchange rates. However, to conclusively determine this, more complex statistical analysis like autocorrelation checks would be required.

    Outliers in the dataset

    Outliers in time-series data are values significantly different from others, or instances where the exchange rate differs significantly from the established trend or seasonality. It's difficult to identify any clear outliers in the dataset, because the exchange rates changes are relatively modest without any significant spikes or drops. Nevertheless, the period around "2024-02-23 09:15:03" saw an increase when the exchange rate increased to 0.37077 from the previous 0.37049; this might be considered as a potential outlier in a more detailed analysis.

    Please note, this is a simple analysis and only provides broad observations. More stringent statistical analysis through programming languages like Python or R would probably provide more in-depth insights.