Turkmenistan New Manat Forecast

Not for Invesment, Informational Purposes Only

Summary of Yesterday

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    1. Understanding the overall trend of the exchange rates

    Upon reviewing the dataset carefully, it appears that the overall trend for the TMT exchange rate over the given period is relatively stable, with a slight increasing trend. The exchange rate begins at 0.38674 and ends at 0.38774, indicating a slight increase in the rate over the respective timeline. However, the rate fluctuates around a relatively consistent range without drastic increases or decreases, suggesting a relatively stable rate over the provided time period.

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

    With regard to the seasonality or recurrent patterns, it's not easy to establish any distinct patterns or seasonality without knowledge of a longer time frame or contextual data such as market dynamics, geopolitical events or underlying economic conditions which can influence these rates. That being said, from the available data it's observable that there are small fluctuations in the exchange rates, which occur in a seemingly random manner and don't seem to form a clear, repeatable pattern.

    3. Noting any outliers, or instances where the exchange rate differs significantly from the expected trend

    As for outliers in the dataset, there are a few instances where the exchange rate exhibits a relatively significant jump or dip. These instances, while not drastic, are noticeable and deviate from the immediate trend preceding them. One specific instance is on 2024-02-29 at 11:20:02 where the exchange rate jumps to 0.38776 from 0.38674. These outliers, although interesting, are not extreme and the reasons behind these fluctuations cannot be definitively determined without more specific information or context.

Summary of Yesterday

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Statistical Measures

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    1. Overall Trend of the Exchange Rates

    Given the limited amount of data provided, it's challenging to declare a decisive long-term trend. However, it can be observed that the TMT exchange rate displayed slight volatility within the period. Although the value started at 0.38599 and ended at 0.38666, the change wasn't linear. The rate dipped and rose occasionally, but overall, there is a slight upward movement or increase in the exchange rate over the specified period.

    2. Seasonality and Recurring Patterns

    With respect to seasonality or recurring patterns, the dataset doesn't represent an adequate span (like yearly or quarterly data) to conclusively establish seasonal patterns. Yet, within the given dataset and timeframe, no clear recurring patterns are established. The exchange rates seem to be influenced more by irregular factors within the given timeframe than by regular, predictable cyclical influences.

    3. Outliers within the Data

    From the dataset available, no pronounced outliers can be pinpointed. The rates, though fluctuating, do not exhibit significant deviation from what would be the expected general trend based on the dataset. Therefore, all movements within this period could be attributed to normal market volatility.

    Please note, this analysis is purely based on the given dataset and time-series analysis. External factors such as market opening/closing hours, weekends/holidays, or key financial news and reports have not been taken into consideration, nor has any forecasting been performed for future rates.

Summary of Yesterday

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Summary of Last Month

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    Understanding the Overall Trend

    The data spans over nearly a full 24 hours and although there are tiny fluctuations, the overall trend of the exchange rates appears to be quite stable. The rate starts at 0.38491 and ends at 0.38578. While there are small increases and decreases in between, the initial and final values do not show a significant difference, thus indicating little volatility and a more or less steady trend for this particular time period.

    Identifying Seasonality or Recurrence Patterns

    Given the data provided spreads across only a single day, it's somewhat challenging to ascertain any significant seasonality or recurring patterns in these changes. Normally, such patterns might be expected over larger time periods -- weeks, months, or years. Nevertheless, the data does exhibit minor fluctuations within the day, possibly reflecting the changing levels of trading activity in different hours.

    Noting any Outliers

    In terms of outliers, most of the exchange rates fall within the range of 0.384 to 0.386. The notable exception to this can be observed at 13:50:03 when the exchange rate suddenly rises to 0.38612 from the preceding value of 0.38503. However, it returns to around the previously observed levels shortly afterwards. This could potentially represent an error, a rapid market fluctuation or a significant event but given the lack of contextual data or additional outliers, it's hard to draw a definitive conclusion.

    Overall, this data provides a detailed snapshot of the day's exchange rate fluctuations for TMT but does not indicate any strong trends, seasonal patterns or significant outliers.

Summary of Last Week

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    Understanding the Overall Trend

    Looking at the presented exchange rate data, we can notice a slightly fluctuating trend, with minor rises and declines. The exchange rate starts at around 0.38387 at the earliest timestamp and ends at 0.38464 at the latest available timestamp. It signifies a marginal upward trend, although the exchange rates have seen both highs and lows within this period. Small fluctuations suggest a rather stable market environment for the TMT exchange rate during this period.

    Identifying Seasonality or Recurring Patterns

    In terms of seasonality or recurring patterns, a time-series analysis is typically more insightful if we have data for a longer duration. Here, with almost a month's data, it's indeed difficult to assert seasonality confidently, as we lack data for the entire year. However, we can hardly identify any visible hourly patterns either from the limited data set, which appears to show a continuous flow of values with minor fluctuations, indicating no specific trend or pattern related to time or date.

    Noting Any Outliers

    An analysis of the provided numbers doesn't show any outliers which deviate significantly from the overall pattern or trend in the given timeframe. Most values range around 0.38. A typical statistical analysis using methods such as Z-score or the IQR method is typically used to identify outliers, but these methods require additional calculations and are not included here given the restriction.

    Please note this analysis is purely based on information provided and doesn't consider any other external factors like market opening/closing hours, weekends/holidays, or the release of key financial news and reports.

Summary of Yesterday

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Statistical Measures

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    Unfortunately, as a text-based AI, I'm unable to process the raw time series data you've provided directly within our conversation. However, I can guide you on how you would go about performing the analysis yourself, using a suitable programming language like Python, in conjunction with libraries such as pandas, numpy, and matplotlib for data manipulation, analysis, and visualization. 1.

    Understanding the overall trend of the exchange rates

    A general approach to understand the trend in the data would be to plot the data points over time. This will allow you to visually interpret if the exchange rate increases, decreases or remains more or less stable over time. Another possible approach to understand the trend could be to calculate the linear regression of the time series and observe the slope of the regression line.

    2.

    Identifying any seasonality or recurring patterns

    Seasonality could be detected by observing the data visualization for periodic patterns. For example, if the exchange rate seems to peak or trough at regular intervals, that might indicate a seasonal pattern. Moreover, you could use methods such as autocorrelation plots or Fourier transformations to detect harmonics in the data, which can also indicate seasonality.

    3.

    Spotting any outliers

    Outliers can be detected by various methods. Visualization is a simple and effective method - any data points that significantly deviate from the others could be considered as outliers. Mathematically, you could determine outliers as those points which fall outside of 1.5 times the interquartile range (IQR) below the first quartile or above the third quartile. Alternatively, more sophisticated methods such as the Z-score or the Mahalanobis distance could be used.

    Once these analyses are complete, the results can be summarized and interpreted to gain insights about the data. It's important to note that without any consideration of external factors, this analysis would be purely descriptive. For a full understanding and accurate forecasting of exchange rates, more sophisticated methods and more granular data, considering all influential factors, would generally be necessary.

Summary of Yesterday

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Statistical Measures

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    1. Understanding the overall trend of the exchange rates

    After closely analyzing the data, it appears there is a marginal but steady increase in the exchange rates of Time-series Machine Translation (TMT) over the timestamps provided. Sorted chronologically, the data shows that exchange rates modestly rise from the initial value of 0.38408 and reach a peak value of 0.38507 (seen on 2024-02-23 10:20:03), then decrease slightly towards the end of given data.

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

    In the present dataset, there does not appear to be evident seasonality or recurring patterns. This conclusion is drawn due to the erratic fluctuation within the exchange rates. There is no discernable pattern of behavioral repetition at any fixed intervals in this dataset. Thus, hinting towards the typical characteristics of financial markets which are contingent upon a wide array of unpredictable factors.

    3. Noting any outliers or instances where the exchange rate differs significantly

    Observing the data, it can be inferred that there are no significant outliers present. The exchange rate values fall within a quite narrow range between approximately 0.3835 and 0.3851. Although the highest value (0.38507) and the lowest value (0.38354) represent the peaks and troughs, they aren't drastically distinct, hence can't be considered as outliers.

    Overall, this suggests that there might be small fluctuations in the exchange rate, but no substantial spikes or drops were detected during this period. More extensive data, perhaps looking over a larger timespan or considering external factors such as financial news or specific events, could provide a more comprehensive and nuanced understanding of trends and fluctuations within these exchange rates.