Swiss Franc 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

    Overall trend of the exchange rates

    Looking at the data, the exchange rate generally fluctuates between a minimum value of approximately 1.535 and a maximum value of approximately 1.547 during the time period. The highest value occurs at 04:00 am and the lowest point at 14:55 pm. One trend that appears to emerge from the data is a slow decrease over time.

    Seasonality and recurring patterns

    Upon the analysis of the time-series data, no clear seasonality or recurring pattern is visibly prominent. However, it appears that there might be slightly more fluctuation during the early morning hours compared to the rest of the day. Furthermore, the data shows a slight dip around 14:55 pm.

    Instances of significant variation from the trend (Outliers)

    Analyzing this data for outliers, we can observe two potential instances where the exchange rate varies significantly from the expected trend. These occur around 04:00 am and 14:55 pm, where we see the highest and lowest values respectively in the data.

    However, these observations could be the result of market fluctuations or random variations rather than true outliers. Further investigation would be necessary to determine the cause of these deviations from the trend.

    Excluding External Factors

    In this analysis, we have considered the data in isolation and have not taken into account external factors, such as market opening/closing hours, weekends/holidays, or the release of key financial news and reports. These factors can significantly affect exchange rates and introduce volatility into the data.

    Note that this analysis does not generate a forecast for future rates. It is merely a descriptive analysis of past trends and patterns.

    Conclusion

    In conclusion, although the overall trend of the data seems to indicate a fluctuation between a certain range of exchange rates, there is no clear evidence of consistent seasonal patterns or rhythmic fluctuations. It's also important to keep in mind that external factors that have not been considered in this analysis could significantly impact the observed trends and patterns.

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 of CHF Exchange Rates

    From the provided dataset, it appears that the value of CHF fluctuated within a specific range over the period. The rates started around 1.53905 and ended around 1.54514, showing a slight increase overall. However, the changes within this period weren't unidirectional and presented periods of both rise and decline. In general, despite the presence of fluctuations, it seems the exchange rate remained relatively stable with minor increments.

    Identifying Any Seasonality or Recurring Patterns

    Upon initial inspection, it's hard to discern any clear indications of seasonality or specific recurring patterns from the data, given the limited duration of data and without information about a larger timeframe. It is important to bear in mind that exchange rate movements can be influenced by numerous factors and may not exhibit typical seasonal patterns.

    However, with more comprehensive long-term data set, applying techniques such as decomposition of time series into trend, seasonal and residual components or autocorrelation function (ACF) and partial autocorrelation function (PACF) plots might help ascertain any seasonality or recurring patterns.

    Noting any Outliers

    In the absence of graphical representation, it would be challenging to accurately identify any outliers. Outliers in such dataset are typically rates that significantly deviate from the general trend. It's essential to consider outliers in any analysis since these extreme values can significantly affect the mean and standard deviation of the data, thereby skewing analytical results. Nevertheless, without a series plot or a box plot, outlier identification within this exchange rate data is not feasible.

    It's suggested to use visualization techniques like boxplots, scatter plots or simply plotting the values against time to identify potential outliers effectively. Statistical methods of identifying outliers like determining values that fall outside of Mean ± 2*SD or using the Inter-Quartile Range (IQR) could also be employed once the basic statistic values of the dataset are calculated.

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

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Statistical Measures

  • Mean:
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  • Trend

    Understanding the Overall Trend

    As a financial analysis expert, I first look at the overall trend of the exchange rates throughout the provided data. As the CHF exchange rate fluctuates between 1.53341 CHF at the lowest and 1.53775 CHF at the highest, the overall trend seems to be mixed with both increasing and decreasing movements. There is no clear universal upward or downward trend present and the exchange rate remains relatively stable within the given range.

    Identifying Seasonality Patterns

    A consistent pattern or seasonality within the data is not apparent immediately. While there is a lot of fluctuation, it does not show any repeated pattern at a regular interval within the dataset. This could also be due to the fact that the dataset only covers a single day and it is hard to identify any seasonality on such a short timeframe.

    Identifying Outliers

    Regarding outliers in this dataset, as the variability in CHF exchange rate is not very high, there aren’t any significant deviations or outliers. The exchange rates remain within a close range for the entire dataset without any extreme spike or dip, which could be considered as an outlier.

    However, note that this analysis is purely based on the data provided and does not consider external factors such as market conditions, news, or other events that could greatly impact currency exchange rates, as per the provided instructions.

Summary of Last Week

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Statistical Measures

  • Mean:
  • Standard Deviation:
  • Trend

    1. Understanding the Overall Trend of The Exchange Rates

    Computing the overall trend of a dataset often involves using statistical measures such as the mean, median, and mode to determine the central tendency of the data. Alternatively, visual methods such as scatter plots can be used to visualize the distribution of data points and identify patterns or trends. From the dataset provided, the overall trend of the CHF exchange rate varies significantly over time, ranging from a low of approximately 1.52 to a high of approximately 1.56.

    2. Identifying any Seasonality or Recurring Patterns in The Changes of Exchange Rates

    Another important technique in time-series analysis is identifying patterns or periodicity in data, known as seasonality. However, it appears that this data does not present any apparent seasonal pattern at a glance. A more in-depth time-series analysis might reveal hidden patterns not initially apparent. But based on the provided dataset and the constraints of the problem, we do not identify any clear recurring pattern.

    3. Noting Any Outliers

    An outlier is a data point that significantly deviates from other observations in the dataset. Identifying outliers can be essential in financial analysis, as these can indicate volatility or abnormalities in the financial market. The data provided appears to contain occasional abrupt changes in the CHF exchange rate. However, a more in-depth analysis using statistical outlier detection methods could be performed to identify and quantify these potential outliers. But again, we are limited by the constraints of the problem, which does not request this kind of analysis.

    In conclusion, this time-series data analysis found variations in the exchange rate over time without identifying any clear overall trend or seasonality. Outliers appear to be present, suggesting occasional abrupt market changes. However, a more detailed statistical analysis could provide additional insights into these phenomena.

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

    By observing the provided dataset, the overall trend in the exchange rates of CHF seems slightly upward. The rate starts from 1.52948 and concludes at a higher rate of 1.53191. However, the increase is not massive over the time period provided, suggesting that the currency's value isn't dramatically appreciating overall, but rather seems to increase at a modest pace.

    2. Seasonality or Recurring Patterns

    Given the data that extends over a few days, clear patterns or seasons are difficult to pinpoint definitively. However, looking at the values, a certain daily volatility is noticeable, with highs and lows often taking place within a single day. This pattern suggests that the rate is influenced by daily activities and events. To make a stronger assertion about seasonality, we would require more data spanning over longer time intervals such as months or years.

    3. Identification of Outliers

    The dataset provided doesn't include any severe outliers or dramatic spikes or drops in the exchange rate. The values have small fluctuations throughout the period, which are expected in a functioning, active foreign exchange market. Again, this minor volatility suggests that everyday buys and sells by multitudes of traders and institutions might be contributing to small-scale ups and downs within a larger, more moderate upward trend.

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. Understanding the overall trend of the exchange rates

    In analyzing the given dataset, over the period shown, the exchange rates of CHF fluctuate between roughly 1.530 and 1.533. The lowest recorded rate is approximately 1.530, and the highest is around 1.533. The CHF exchange rate shows a general upward trend throughout the data, starting from 1.530 and ending at around 1.532. There are regular increases and decreases within this overall upward motion.

    2. Identifying Seasonality or Recurring Patterns

    An analysis of the data does not immediately reveal any strong seasonality or recurring patterns. The fluctuations appear to be more sporadic and less tied to a specific, recurring time period (e.g., hourly, daily). While there are no obvious repeated patterns in the data, the exchange rate does seem to oscillate within a specific range.

    3. Noting any Outliers or Significant Variations

    Throughout the dataset, the value of the CHF exchange rate does not diverge significantly from the range described above. There do not appear to be any outlier values based strictly on the range and fluctuation of the data. Generally, the exchange rate stays within a relatively consistent range of values. However, further domain-specific analysis may be required to conclusively identify and interpret any outliers.

    Please note that the analysis provided here is solely based on the numerical trends observed in the dataset and does not take into account real-world events or factors that can significantly affect exchange rates.