Fast Finance Pay Stock Market Value

FFPP Stock  USD 40.00  0.00  0.00%   
Fast Finance's market value is the price at which a share of Fast Finance trades on a public exchange. It measures the collective expectations of Fast Finance Pay investors about its performance. Fast Finance is selling at 40.00 as of the 26th of December 2025; that is No Change since the beginning of the trading day. The stock's last reported lowest price was 40.0.
With this module, you can estimate the performance of a buy and hold strategy of Fast Finance Pay and determine expected loss or profit from investing in Fast Finance over a given investment horizon. Check out Fast Finance Correlation, Fast Finance Volatility and Fast Finance Alpha and Beta module to complement your research on Fast Finance.
Symbol

Please note, there is a significant difference between Fast Finance's value and its price as these two are different measures arrived at by different means. Investors typically determine if Fast Finance is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Fast Finance's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.

Fast Finance 'What if' Analysis

In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Fast Finance's pink sheet what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Fast Finance.
0.00
11/26/2025
No Change 0.00  0.0 
In 31 days
12/26/2025
0.00
If you would invest  0.00  in Fast Finance on November 26, 2025 and sell it all today you would earn a total of 0.00 from holding Fast Finance Pay or generate 0.0% return on investment in Fast Finance over 30 days. Fast Finance is related to or competes with Tyro Payments, Automatic Bank, Smart Eye, Pexip Holding, Tecsys, Computer Modelling, and Amper SA. More

Fast Finance Upside/Downside Indicators

Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Fast Finance's pink sheet current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Fast Finance Pay upside and downside potential and time the market with a certain degree of confidence.

Fast Finance Market Risk Indicators

Today, many novice investors tend to focus exclusively on investment returns with little concern for Fast Finance's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Fast Finance's standard deviation. In reality, there are many statistical measures that can use Fast Finance historical prices to predict the future Fast Finance's volatility.
Hype
Prediction
LowEstimatedHigh
29.8740.0050.13
Details
Intrinsic
Valuation
LowRealHigh
26.4936.6246.76
Details
Naive
Forecast
LowNextHigh
31.1741.3151.44
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
19.3332.8046.27
Details

Fast Finance Pay Backtested Returns

Fast Finance is somewhat reliable given 3 months investment horizon. Fast Finance Pay secures Sharpe Ratio (or Efficiency) of 0.18, which denotes the company had a 0.18 % return per unit of risk over the last 3 months. We were able to interpolate data for sixteen different technical indicators, which can help you to evaluate if expected returns of 1.81% are justified by taking the suggested risk. Use Fast Finance Variance of 98.11, mean deviation of 3.35, and Standard Deviation of 9.9 to evaluate company specific risk that cannot be diversified away. Fast Finance holds a performance score of 14 on a scale of zero to a hundred. The firm shows a Beta (market volatility) of -1.81, which means a somewhat significant risk relative to the market. As returns on the market increase, returns on owning Fast Finance are expected to decrease by larger amounts. On the other hand, during market turmoil, Fast Finance is expected to outperform it. Use Fast Finance treynor ratio and day median price , to analyze future returns on Fast Finance.

Auto-correlation

    
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No correlation between past and present

Fast Finance Pay has no correlation between past and present. Overlapping area represents the amount of predictability between Fast Finance time series from 26th of November 2025 to 11th of December 2025 and 11th of December 2025 to 26th of December 2025. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Fast Finance Pay price movement. The serial correlation of 0.0 indicates that just 0.0% of current Fast Finance price fluctuation can be explain by its past prices.
Correlation Coefficient0.0
Spearman Rank Test1.0
Residual Average0.0
Price Variance0.0

Fast Finance Pay lagged returns against current returns

Autocorrelation, which is Fast Finance pink sheet's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Fast Finance's pink sheet expected returns. We can calculate the autocorrelation of Fast Finance returns to help us make a trade decision. For example, suppose you find that Fast Finance has exhibited high autocorrelation historically, and you observe that the pink sheet is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
   Current and Lagged Values   
       Timeline  

Fast Finance regressed lagged prices vs. current prices

Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Fast Finance pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Fast Finance pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Fast Finance pink sheet over time.
   Current vs Lagged Prices   
       Timeline  

Fast Finance Lagged Returns

When evaluating Fast Finance's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Fast Finance pink sheet have on its future price. Fast Finance autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Fast Finance autocorrelation shows the relationship between Fast Finance pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Fast Finance Pay.
   Regressed Prices   
       Timeline  

Pair Trading with Fast Finance

One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Fast Finance position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Fast Finance will appreciate offsetting losses from the drop in the long position's value.

Moving against Fast Pink Sheet

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The ability to find closely correlated positions to Fast Finance could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Fast Finance when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Fast Finance - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Fast Finance Pay to buy it.
The correlation of Fast Finance is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Fast Finance moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Fast Finance Pay moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Fast Finance can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.
Pair CorrelationCorrelation Matching

Additional Tools for Fast Pink Sheet Analysis

When running Fast Finance's price analysis, check to measure Fast Finance's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Fast Finance is operating at the current time. Most of Fast Finance's value examination focuses on studying past and present price action to predict the probability of Fast Finance's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Fast Finance's price. Additionally, you may evaluate how the addition of Fast Finance to your portfolios can decrease your overall portfolio volatility.