Unidad de Fomento Forecast

Not for Invesment, Informational Purposes Only

Summary of Yesterday

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Statistical Measures

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    Analysis of Dataset

    The dataset provided contains time-series data detailing the changes in CLF exchange rates at various timestamps. In analyzing this data, several factors were considered to gain a comprehensive understanding of the trends, seasonality, and anomalies that may exist.

    1. Overall Trend of Exchange Rates

    After careful examination of the dataset, it is evident that the exchange rates have indeed exhibited a general incline over the span of the timestamps provided. Beginning at an initial value of 38.25408 at the start (2024-02-29 00:00:02), the data reveals an upward trajectory, eventually concluding at a higher value of 38.73267 (2024-02-29 23:55:02). Despite various fluctuations throughout, the long-term progression demonstrates a growth in the exchange rates when comparing the start and end points.

    2. Seasonality & Recurring Patterns

    Identifying seasonality in this dataset is challenging due to the fact that the timestamps provided only cover a single 24-hour period. Generally, seasonality in financial data refers to regular and predictable changes that reoccur every calendar year. As such, detecting any definite seasonal trends or recurring patterns from this single-day snapshot of data may not yield reliable insights. However, from the given dataset, we can observe some micro-trends. For instance, we see a rapid and above-average increase in the exchange rate starting around 8:15 and peaking around 10:10 before gradually decreasing again.

    3. Outliers and Anomalies

    Outliers or anomalies refer to instances in the data that deviate significantly from the expected trend or norm. Again, due to the short duration of the provided data, identifying reliable outliers is challenging. Nevertheless, certain points qualify as potential outliers or anomalies. Primarily, the sharp increases observed between 7:55 to 8:20 and the subsequent sharp decrease observed from the 8:20 to 8:30 datapoints present unusual variation in the otherwise gradual rate changes. However, these would need to be validated by cross-checking with external events or market conditions at the time, which is not within the scope of this analysis.

    Note: Although we cannot provide definitive explanations or inferences about these irregularities in this report, such outliers typically might be influenced by a myriad of factors including but not limited to, major financial news releases, central bank interventions, or unforeseen market conditions.

Summary of Yesterday

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Statistical Measures

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    Understanding the overall trend

    The overall trend of exchange rates shows a general increase within the given period. The lowest value of the rate is 38.08508 at the beginning of the specified time range on 2024-02-28 00:05:02, and it increased gradually to the highest rate of 38.2863 at the latter part of the dataset on 2024-02-28 18:55:02. It is important to note that while there is a general increase, the rates also experienced many fluctuations within this period.

    Identifying seasonality or recurring patterns

    Examining the dataset, it's not immediately obvious if there are any strong periods of seasonality due to the varying fluctuations in the data and the single day's worth of data provided. To accurately identify seasonality or recurring patterns, a more extended period may be required. However, there seems to be a pattern of increased volatility during certain hours, suggesting possible effects of the opening or closing of certain foreign exchange markets.

    Noting any outliers

    Looking at the dataset, several moments of significant change can be observed. For example, On 2024-02-28 at around 06:45:02, the rate increases drastically from 38.18251 to 38.25555. Another dip can be seen at around 07:40:02 where it drops to 38.19272. These significant changes suggest the influence of events which would need further investigation.

    Please note these observations are preliminary and a more in-depth analysis involving statistical methods is needed for a definitive understanding of the data.

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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    Overall Trend of The Exchange Rates

    From the initial observation of the data, the exchange rate starts from 38.09088 and ends at 37.74582. There seems to be a gradual decrease in the exchange rates based on these figures. However, this does not provide a detailed trend over the entire period and several fluctuations within this period can significantly affect the performance analysis. Thus, it is recommended to use measures such as moving averages for a group of data points to get a clearer picture of the overall trend.

    Identifying Seasonality or Recurring Patterns

    To understand the pattern and seasonality in the data set, time series decomposition should be performed which involves isolating the components of the time series - trend, seasonality, and residuals. Once these components are isolated, we can identify if there's any consistent seasonality or pattern through a period-by-period comparison - daily, weekly, monthly, or yearly.

    Identifying Potential Outliers

    Identifying outliers requires the examination of sudden spikes or drops in the exchange rates that don't align with the overall pattern. These outliers can be clearly seen with a visual plot of the rates over time. Other statistical methods, such as Z-score or IQR (Interquartile Range) analyses, could also be used to identify potential outliers.

    It is worth noting that outliers might suggest a potential data entry error, but they could also signal critical events of significant interest in the financial analysis context. They might indicate periods when the exchange rate was affected by exceptional global or sector-specific events.

    From the data provided, the largest single drop in exchange rates was observed on 2024-02-26 from 05:10:02 to 05:15:03, where the rate went from 38.11266 to 38.04306, a significant switch in such a short period. That could consider being a potential outlier that demands further analysis to determine its cause.

    Potential Impact of External Factors

    Although you've stated that external factors such as market opening/closing hours, weekends/holidays, and the release of key financial news and reports, aren't to be considered in this analysis. It's worth noting that these factors often play a significant role in influencing exchange rates. Any comprehensive analysis in a real-world context should ideally account for these factors to ensure accuracy and relevancy.

    In conclusion, remember that this is a high-level analysis based on the data provided. For a more granular understanding of the trend, seasonality, and identification of outliers, more sophisticated time series analysis methods, and visualization tools would be required.

Summary of Last Week

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Statistical Measures

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    1. Overall Trend of the Exchange Rates

    The overall trend of the exchange rates for this time series data presented indicates fluctuation, although a slow and possibly overall degradation in terms of value can be seen from the series. If it was to be viewed in a linear trend, you might suggest that there is a mild decrease in rates. The data started at an exchange rate of about 40.86136 on 2024-01-26 and ended around 38.00547 on 2024-02-23. Although there are ups and downs in rates, the overall trend suggests a reduction.

    2. Seasonality or Recurring Patterns

    Upon review of the given data, it is challenging to detect any clear, consistency or recurring patterns in the exchange rates based on the time and date. Even though there are instances where price hikes are followed by drastic drops (or vice versa), they do not occur with enough regularity to infer a specific seasonal pattern or trend. Further analysis would be required over a more extended period to decisively establish any seasonality or recurring patterns.

    3. Outliers in the Exchange Rates

    As for outliers, this term refers to values significantly above or below the trend. In the present dataset, since we are dealing with exchange rates, significant changes could be relatively small in absolute terms, but still have a substantial economic impact. The dataset presents a few notable sharp increases and decreases, which could be technically considered as outliers. However, defining an ‘outlier’ in this dataset truly depends on what kind of financial risk tolerance or threshold you are willing to accept.

Summary of Yesterday

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Statistical Measures

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    Based on your data, here are the insights from your dataset, please note that this analysis was done without any external factors considered.

    1. Understanding the overall trend of the exchange rates.

    Looking at the data, we can see that the exchange rate has experienced a slight downward trend. The initial data point on 2024-02-19 01:00:02 was 38.56686, and the final data point on 2024-02-23 14:00:01 was 38.00547. This suggests that the rate has somewhat decreased over the period in question. However, there are fluctuations within this overall downward trend, with individual values at times rising or falling to some extent.

    2. Identifying any seasonality or recurring patterns in the changes of exchange rates.

    • When reviewing the data, we don't seem to have sufficient data to construct a reliable seasonality model. Normally, for reliable identification of seasonal patterns, multiple cycles of a presumed seasonality need to be present in the data.
    • In theory, by examining the data at similar intervals, patterns may emerge. For instance, if the exchange rates regularly rise at 3:00 and fall at 15:00, this would indicate a recurring pattern. However, upon examining the data, no such consistent daily pattern can be discerned.

    3. Noting any outliers, or instances where the exchange rate differs significantly from what would be expected based on the trend or seasonality.

    It's important to note that there were some instances of notable changes in the exchange rate - for instance, between the timestamps 2024-02-19 05:00:02 and 2024-02-19 06:00:02, or between 2024-02-22 09:00:02 and 2024-02-22 10:00:03, where the rate dropped significantly more than the typical fluctuation. These cases could potentially be considered outliers in the given dataset.

    In conclusion, while the general trend shows a slight decrease, the changes in exchange rates do not appear to follow a specific pattern within the provided time frame and there are several significant fluctuations that could be considered as outliers.

Summary of Yesterday

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Statistical Measures

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  • Trend

    Understanding the Overall Trend of the Exchange Rates

    The overall trend of the exchange rates in the dataset seems to show a consistent fluctuation. This suggests a volatile or highly dynamic market where the value of CLF exchange rate does not follow a clearly defined increasing, decreasing or stable pattern over time. As the data range from 37.85 to around 38.05, the changes in exchange rates are not drastic but they are rather frequent, indicating a fluctuating market situation.

    Identifying Seasonality and Recurring Patterns

    In terms of seasonality, a comprehensive analysis of time-series data would require data spanning a longer period of time because seasonality refers to recurring patterns or cycles that are observed within a specific year or month. However, based on the data provided, there does not appear to be clear seasonality. The fluctuations don't seem to follow a distinctly visible seasonal or recurring pattern and vary greatly at different timestamps. Therefore, without further long-term data, it is difficult to draw conclusions about any seasonality.

    Noting Outliers in the Exchange Rates

    Generally, outliers in exchange rate data can be significant because they might indicate unusual market situations. Yet in this dataset, there do not appear to be extreme values that could be characterized as outliers or instances where the exchange rate is significantly different from the majority of observations. All rates are within a relatively close range as mentioned earlier. Thus, it seems that there are no clear outliers based on the provided data.

    Please note that, this analysis is purely data-driven, meaning that it only considers the numbers in the dataset and their statistical properties. While external factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports may have significant impacts on exchange rates, these factors are not considered in this analysis, as requested.