Balboa Forecast

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

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

The data shows a fluctuating trend in the exchange rates. It starts at 1.37365 on 2024-04-22 at 01:00:02, and ends at 1.36635 on 2024-04-26 at 14:00:01. Although there is a general decrease, the rates have several increases and decreases throughout. The highest rate was 1.37521 on 2024-04-24 at 05:00:02, and the lowest was 1.36503 on 2024-04-26 at 04:00:02. The range of these rates is relatively small, indicating that there are no drastic changes in the trends over the five days.

Seasonality and Recurring Patterns

In terms of seasonality and recurring patterns, it is difficult to ascertain from the data available. Most financial time series data, including exchange rates, demonstrate seasonality depending on the market opening and closing times, weekends, holidays, and key financial news release timings. These external factors influence trading volumes and volatility, thereby leading to fluctuations in the exchange rates. However, as the data spans only five days and we are instructed not to consider these external factors, it is not possible to accurately identify any seasonality or recurring patterns within this dataset. A longer dataset is necessary to determine seasonality as these kinds of patterns often occur over longer periods of time (months or years).

Outliers

Outliers in exchange rate data typically represent significant and sudden changes in the rates that deviate from the typical range of fluctuations. Given the relatively small variance in the data, it doesn't seem like there are any major outliers in this dataset. The fixed-width frequency of the data over the five-day period does not show any drastic fluctuations that could be considered as outliers. However, without historical context or statistical analysis, it's not possible to definitively identify outliers based purely on this 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

Data Analysis Result

The given dataset consists of time-stamped values of one financial variable, the PAB exchange rate. Here is an interpretation of the dataset based on the trend, seasonality, and outliers:

Overall Trend of The Exchange Rates

It appears that the PAB exchange rate exhibits both upward and downward movement during the given time period. The value starts from approximately 1.367 and ends around the same value. However, it does not remain stable throughout the entire duration. It first decreases, reaching a temporary minimum at around 1.364, before rising again to around the starting value. This suggests that the exchange rate is mean-reverting here - fluctuates around a certain mean value.

Seasonality or Recurring Patterns

In analysing the recurrent changes in the exchange rate, it can be observed that there is no clear seasonality in the genetic sense in the data. The values do not follow a rhythmic pattern on a specific time basis like daily or weekly. However, an alternation of periods of relative stability and more substantial change can be noticed. There is no clear statement if this is not just random fluctuations or indeed a regular pattern.

Outliers

There don't seem to be any major outliers, i.e. large unexpected spikes or dips, in the dataset. The exchange rates fluctuate within a relatively narrow range, and any larger changes are consistent with the general trend and don't seem extremely unusual for this type of financial time series.

In conclusion, this dataset represents a typical financial time series with a relatively stable mean-reverting behaviour and some minor fluctuations. Please remember that an understanding of the dataset does not necessarily infer prediction accuracy, as financial markets are largely influenced by factors outside the dataset.

Summary of Yesterday

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

Statistical Measures

• Mean:
• Standard Deviation:

Trend

Analysis

An overall trend analysis of the provided dataset shows a cycle of increases and decreases of the PAB exchange rates over time. To have a proper understanding of the exact trend, more in-depth statistical analysis may be required, such as detrending the data and doing a time series decomposition.

Trends

In the data provided, the observed trend shows an initial rise in the exchange rate, followed by a fall in the middle hours, and then another rise later. There seems to be a daily trend here, with the exchange rates peaking in the early hours, dipping in the middle and then rising again later.

Seasonality

In the given exchange rate data, the pattern of rises and falls in exchange rates suggests that there may be some form of seasonality. Seasonality refers to predictable and periodic fluctuations in a time-series data, which usually occurs over short-term time periods, such as hours, weeks or months. These may be due to market opening and closing hours, weekends and holidays, among other things. However, in line with your instructions, these factors have not been considered in this analysis.

Outliers

Looking at the data points, there appear to be a few instances where there are steep declines or rises in the exchange rate. These could be considered outliers. However, whether these would technically be classified as outliers would depend on detailed statistical analysis. These could potentially be indicative of sudden changes in the market demand and supply or major macroeconomic news.

As per the instruction given, no forecasting has been done for the future rates or any consideration given to external factors that might have impacted these exchange rates. Also, please note that further statistical analysis would be required for a concrete conclusion on the trends, seasonality and outliers in the data.

I hope this analysis provides some preliminary insights into patterns and behaviours of the exchange rates during this time period. Do bear in mind that exchange rates are influenced by numerous factors and a more thorough analysis may be necessary to fully understand the dynamics at play.

Summary of Yesterday

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

Statistical Measures

• Mean:
• Standard Deviation:

Trend

Analysis of the provided dataset

The data you've provided is a timestamped series of foreign exchange rates. The dates range from the 24th of April, 2024 00:00:02 to 24th of April, 2024 23:55:02. It's important to remember that the results of this analysis are subject to many external factors including market volatility, geopolitical events, and macroeconomic data releases which have not been considered in this analysis.

1. Understanding the overall trend

Observing the data, it appears that there is a slight general increase in the exchange rates as time progresses through the 24-hour period. However, there are periods where the exchange rate peaks and troughs, possibly due to market activities or changes in supply and demand.

2. Identifying any seasonality or recurring patterns

There might be some intraday (within the day) patterns present in the data. For instance, rates tend to increase towards the latter part of the hour, then decrease towards the beginning of the next. To fully discern such patterns, we will need larger data sets covering multiple days, preferably over weeks or months. This will offer a broader perspective on whether such patterns hold over the long term.

3. Noting any outliers or instances where the rate changes significantly

There is a significant change in the exchange rate around 06:50:02 when the rate drops from 1.37584 to 1.36868. This substantial decrease stands out from the remaining data and could be due to a major buy or sell event in the market. Another notable fluctuation occurs at 20:05:04 when the rate jumps from 1.36963 to 1.37192. These could be treated as outliers in the data set.

Conclusion

Through this analysis, it's evident that exchange rates fluctuate throughout the day, influenced by a myriad of factors including market sentiment, economic indicators, and global events. Monitoring these fluctuations enables traders and investors to make informed decisions on buying and selling currencies. For a more thorough and accurate analysis, consider incorporating larger data sets and external factors into the analysis process.

Summary of Yesterday

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

Statistical Measures

• Mean:
• Standard Deviation:

Trend

Analysis

Looking at the timestamps, the data spans from 2024-04-23 00:00:02 to 2024-04-23 23:55:02. This indicates that we are observing exchange rates over a period of 24 hours. The PAB exchange rates range between approximately 1.367 and 1.373. In this timestamp, the number of changes is 289 changes.

Trend

When evaluating a trend within this data, we can suggest that the exchange rate slightly increased over the course of the 24 hours. The exchange rate started low, around 1.370 at 00:00:02 in the morning of April 23, 2024. Within the first few hours, the rate stayed around this value, suggesting a fairly stable beginning of the day. There was a slight noticeable increase in the rate midway through the day, with a peak at about 1.373 at around 22:45:02. Nevertheless, the change in value is relatively minimal, indicating that the exchange rate held relatively stable within this 24-hour timeframe.

Seasonality

Approaching the problem of seasonality or recurring patterns, this can be a little complex given the 24 hours data span. It is typically better suited to longer periods, as a daily interval can be subject to many external factors, random variations, or fluctuations that are not recurring. However, such factors would need substantial data, spanning across multiple weeks or months, for solid detection and confirmation of patterns. That being said, the data might hint some level of pattern repetition during the same day but cannot be strictly confirmed with this small timeframe.

Outliers

Looking for outliers in the data, there were minor instances where the exchange rate spiked or dipped slightly compared to values around their time. For instance, we can see that at 1:25:02, the value went to 1.37166 but came down to 1.37147 at 1:30:02. Another notable event was around 20:05:02, where there was a sudden spike in the value to 1.37286. However, these fluctuations do not seem too significant and appear consistent with the overall data distribution.

As you'd noted, this analysis didn't take into account any external factors, such as the release of economic announcements or market opening/closing times, which would have had a meaningful impact on the exchange rate.

None of these trends, patterns, or outliers are definitive since exchange rates can be influenced by myriad factors, and predictive trends or patterns at a specific time of day may not necessarily hold in the future. But the above analysis points out what we have observed in the provided time-series dataset.

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

Overall Trend of Exchange Rates

Observing the dataset provided, the overall trend of the exchange rates shows noticeable fluctuations. The initial rate is 1.37368 and it appears to progressively decline mostly, with a few rises and falls, till it reaches an approximate point of 1.36796. Subsequent to this point, there is an upward trend till it hits a point of 1.37456. Post this, the data shows a generalized downward trend hitting a trough of around 1.36811. In the end, the rates rise again to reach 1.37085.

Seasonality or Recurring Patterns

Upon review, the dataset does not depict a clear seasonality or reoccurring pattern. The exchange rates appear to fluctuate in both positive and negative directions. Generally, a rise seems to follow a sharp drop and this pattern could be suggestive of some form of cyclical trend. However, a deeper analytical approach would be required to confirm this observation and determine the exact cycle period, if any.

Outliers

Based on a visual glance at the dataset, there are no glaring outliers where the exchange rate differs significantly from its surrounding data points. This indicates that most changes in the exchange rates were gradual and didn't involve any abrupt leaps or falls that could be considered outliers. However, a detailed statistical analysis would be required to definitively identify and confirm any outliers in the data.