Som Forecast

Not for Invesment, Informational Purposes Only

Summary of Yesterday

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Statistical Measures

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    1. Understanding the Overall Trend of Exchange Rates

    The exchange rates given in this dataset seem to be predominantly stable throughout the period. The data ranges between 0.01515 and 0.01521, which suggests minor fluctuation. Despite the fluctuations, the primary trend appears to be stable. The value, for most of the period, hovers around the 0.01518 mark. The data does not reveal any substantial increase or decrease trend in the exchange rate value over the period displayed.

    2. Seasonality or Recurring Patterns in Changes of Exchange Rates

    By examining the data, it is challenging to draw a concrete conclusion about any seasonality or recurring patterns. The small range of fluctuations doesn't provide any apparent cycle or periodic variations that might suggest a specific pattern. So, the exchange rate, within the range detailed above, seems to be changing randomly rather than following a seasonal trend.

    3. Outliers in Exchange Rates

    An outlier in this context would be a rate that deviates significantly from the average value of 0.01518. The dataset provided doesn't seem to contain any such data points, as all values are inside a tight range of 0.01515 to 0.01521. Hence, there do not seem to be any significant outliers in this dataset. The exchange rate consistently falls within the same small range, suggesting stability rather than volatile shifts.

Summary of Yesterday

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Statistical Measures

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    Overall Trend Analysis

    After carefully observing the provided dataset, the overall exchange rate trend throughout the period appears to be relatively stable. The majority of the rates fall within the range of 0.01515 to 0.01521. There are slight fluctuations over time, but they are marginal and do not suggest a clear and consistent upward or downward trend.

    Seasonality or Recurring Patterns

    Regarding the identification of any seasonal or repeating patterns, the dataset does not appear to show a clear seasonal trend. Additionally, due to the limited range of the exchange rate and the lack of any noticeable recurring patterns, it could be concluded that the exchange rates do not exhibit strong seasonality in the given time period.

    Identification of Outliers

    The provided dataset seems to be highly stable and consistent, with no apparent abrupt or significant fluctuations. As such, there are no clear outliers in the dataset. The slight inconsistencies observed do not deviate substantially from the average exchange rate, thus can not be considered outliers.

    Conclusion

    • The overall exchange rates remained largely stable over the given period with minor fluctuations - no clear increasing or decreasing trend was noticed.
    • No significant seasonal or recurring patterns were identified in the dataset.
    • The data does not appear to contain any significant outliers or unexpected instances.

    Please note, this analysis is purely based on the provided dataset and does not take into account any external factors like market dynamics, opening/closing hours, weekends/holidays, or the release of key financial news and reports. Including such factors could potentially provide a more comprehensive picture of the observed trends.

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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    Analysis of Time-Series Exchange Rate Data

    The analyzed data set consists of values of the exchange rate of the Kyrgyzstani Som (KGS) at different time intervals covering a single day. Being a time series dataset, it shows the changes in this rate over time.

    Understanding the Overall Trend

    Observing the recorded values, we could conclude that the exchange rate does not show significant fluctuations during the day. It started at 0.01511 and ended at 0.0151. Although the rate had slightly increased to 0.01513 during the mid-time, it stabilized towards the end of the day. Thus, the exchange rate seems to remain generally stable over the period shown.

    Identifying Recurring Patterns

    Looking to identify potential seasonality or recurrent patterns in the data set, it is not clear due to the fact that the available data only covers a single day. Time-series datasets often require longer periods (covering multiple months or years) to properly identify seasonal patterns or trends.

    Outliers Identification

    Upon inspection of the data, there does not appear to be any significant outliers or instances where the exchange rate differs dramatically. The fluctuations that do occur are very marginal, indicating stability in this particular exchange rate.

    It's important to note that this analysis does not take into account specific events, such as market opening/closing hours, weekends/holidays, or the release of key financial news and market reports, that may have influenced the exchange rate. However, mostly such external factors wouldn't have a drastic impact on the intra-day rates unless an extreme market event took place.

    Conclusion

    From the given data, it can be concluded that the KGS exchange rate remained relatively stable throughout the day with very minor fluctuations. The data doesn't provide evidence for any noteworthy seasonality or pattern. Hence, for a more comprehensive understanding, and to identify trends or patterns, it is recommended to analyze the exchange rate data over a greater timespan.

Summary of Last Week

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Statistical Measures

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    Alright, let's analyze the data you provided:

    1. Overall Trend of Exchange Rates

    Upon reviewing the data provided, it's clear that the KGS exchange rate has been quite stable over the period covered. Although there are slight variations, the rates fluctuate between approximately 0.01496 and 0.01519, with many instances falling within the 0.01504 and 0.01508 range. Therefore, we can state that there was neither a definite appreciating nor depreciating trend in the exchange rate during this period.

    2. Seasonality or Recurring Patterns

    In a time series data set like this, it would be common to identify patterns or cycles repeated over time. This phenomenon, known as seasonality, is very common in financial data. For instance, demand for certain stocks might go up at a specific time due to a predictable event. However, since the hourly data provided spans only slightly more than a month, it is difficult to determine with confidence any seasonality or recurring patterns in the timescale presented. Further analyses with a longer dataset might be required for a more accurate detection of possible patterns.

    3. Outliers in the Data

    Outlier detection involves determining the data points that significantly deviate from other observations. These outliers may be due to variability in the data or errors. In this dataset, there seem to be no significant outliers in the exchange rate data. The rate adheres within a relatively small range, and any "extreme" values we see are still close to the majority of the data. It's also important to note that these apparent extremes are normal in financial data. Exchange rates can be influenced by various factors such as macroeconomic indicators and international events, so volatility can be expected. As with the previous sections, a more complex outlier detection method may provide further insights, especially when considering a longer period and more diverse data.

    I hope this analysis sheds some light on your dataset. Please remember that analyzing financial data or economic indicators may require a deeper understanding of the underlying factors that can influence these numbers.

Summary of Yesterday

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Statistical Measures

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    Overall trend of the exchange rates

    The overall trend of the exchange rates (KGS) seems to be relatively stable throughout the data period provided. The exchange rates fluctuated between 0.01504 to 0.01513, which indicates a negligible volatility. It appears that the rate slightly increased from 0.01507 in the beginning to peak at 0.01513 in the middle and then reverted back to its original levels towards the end of the given series. Thus, the exchange rate is showing a temporary upward movement, followed by a correction.

    Seasonality or recurring patterns in the changes of exchange rates

    Given the limited amount of data and the very slight variation in exchange rates, it is difficult to identify any strong seasonality or recurring patterns within this dataset. The movements in the exchange rate seem to be random rather than following a specific seasonal pattern. More data points, particularly those covering a longer time frame, would be required to identify any potential seasonality or other recurring patterns.

    Outliers in the dataset

    Within the provided timeframe and data, no significant outliers can be identified. The variation in exchange rates is minor, and all values fall within the narrow range of 0.01504 to 0.01513. However, the dataset reveals a minute upward and downward movement that may be due to certain isolated events or fluctuations in the market. But given the minute variation in the rates, it is safe to say that these movements do not qualify as significant outliers as they do not deviate significantly from the overall observed trend.

Summary of Yesterday

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Statistical Measures

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  • Trend

    Before starting a detailed analysis of the data, it is important to note that the frequency of the recorded exchange rates is every 5 minutes. Therefore, we are working with high-frequency data, which can be particularly noisy.

    1. Overall Trend of the Exchange Rates

    The exchange rate during the time frame given fluctuates between 0.01505 and 0.01511, indicating a notably stable exchange rate. Overall, a slight upward trend is evident, where the exchange rate starts at 0.01507 and ends at 0.01510, but this increase is rather insignificant due to the minor differences in the rate.

    2. Seasonality or Recurring Patterns

    Given the available data, it is difficult to identify any seasonality or recurring pattern in the way the KGS exchange rate changes. Seasonality usually refers to regular and predictable changes that recur every calendar year. The provided data, however, spans a single day, which is not sufficient to observe such seasonality.

    3. Outliers

    There are no noticeable outliers in the data. An outlier would be a sudden sizable change in the exchange rate, either increase or decrease, that doesn't align with the general trend. All the changes in the exchange rate throughout the day remain within a very tight range, and the rate is following a relatively consistent pattern.

    In conclusion, the KGS exchange rate has been steady with a minor increase during the observed period, and there have been no irregular, unexpected changes in the rates. The data does not present enough information to identify a clear pattern or seasonality in the rate changes.