Tflm Stock Market Value

TFLM Stock   0.16  0.00  0.00%   
TFLM's market value is the price at which a share of TFLM trades on a public exchange. It measures the collective expectations of TFLM investors about its performance. TFLM is selling at 0.16 as of the 25th of December 2025; that is No Change since the beginning of the trading day. The stock's lowest day price was 0.16.
With this module, you can estimate the performance of a buy and hold strategy of TFLM and determine expected loss or profit from investing in TFLM over a given investment horizon. Check out World Market Map to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in industry.
Symbol

TFLM '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 TFLM'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 TFLM.
0.00
06/28/2025
No Change 0.00  0.0 
In 5 months and 30 days
12/25/2025
0.00
If you would invest  0.00  in TFLM on June 28, 2025 and sell it all today you would earn a total of 0.00 from holding TFLM or generate 0.0% return on investment in TFLM over 180 days.

TFLM 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 TFLM'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 TFLM upside and downside potential and time the market with a certain degree of confidence.

TFLM Market Risk Indicators

Today, many novice investors tend to focus exclusively on investment returns with little concern for TFLM's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as TFLM's standard deviation. In reality, there are many statistical measures that can use TFLM historical prices to predict the future TFLM's volatility.

TFLM Backtested Returns

TFLM owns Efficiency Ratio (i.e., Sharpe Ratio) of -0.12, which indicates the firm had a -0.12 % return per unit of standard deviation over the last 3 months. TFLM exposes sixteen different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please validate TFLM's risk adjusted performance of (0.09), and Variance of 0.5407 to confirm the risk estimate we provide. The entity has a beta of -0.0076, which indicates not very significant fluctuations relative to the market. As returns on the market increase, returns on owning TFLM are expected to decrease at a much lower rate. During the bear market, TFLM is likely to outperform the market. At this point, TFLM has a negative expected return of -0.0919%. Please make sure to validate TFLM's information ratio and rate of daily change , to decide if TFLM performance from the past will be repeated at future time.

Auto-correlation

    
  0.08  

Virtually no predictability

TFLM has virtually no predictability. Overlapping area represents the amount of predictability between TFLM time series from 28th of June 2025 to 26th of September 2025 and 26th of September 2025 to 25th 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 TFLM price movement. The serial correlation of 0.08 indicates that barely 8.0% of current TFLM price fluctuation can be explain by its past prices.
Correlation Coefficient0.08
Spearman Rank Test-0.29
Residual Average0.0
Price Variance0.0

TFLM lagged returns against current returns

Autocorrelation, which is TFLM 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 TFLM's pink sheet expected returns. We can calculate the autocorrelation of TFLM returns to help us make a trade decision. For example, suppose you find that TFLM 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  

TFLM 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 TFLM pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if TFLM pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in TFLM pink sheet over time.
   Current vs Lagged Prices   
       Timeline  

TFLM Lagged Returns

When evaluating TFLM's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of TFLM pink sheet have on its future price. TFLM 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, TFLM autocorrelation shows the relationship between TFLM pink sheet current value and its past values and can show if there is a momentum factor associated with investing in TFLM.
   Regressed Prices   
       Timeline  

Building efficient market-beating portfolios requires time, education, and a lot of computing power!

The Portfolio Prophet is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.

Try AI Portfolio Prophet