Molecular Data's market value is the price at which a share of Molecular Data trades on a public exchange. It measures the collective expectations of Molecular Data investors about its performance. Molecular Data is trading at 1.0E-4 as of the 23rd of January 2026; that is No Change since the beginning of the trading day. The stock's open price was 1.0E-4. With this module, you can estimate the performance of a buy and hold strategy of Molecular Data and determine expected loss or profit from investing in Molecular Data over a given investment horizon. Check out Molecular Data Correlation, Molecular Data Volatility and Molecular Data Alpha and Beta module to complement your research on Molecular Data.
Please note, there is a significant difference between Molecular Data's value and its price as these two are different measures arrived at by different means. Investors typically determine if Molecular Data is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Molecular Data'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.
Molecular Data '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 Molecular Data'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 Molecular Data.
0.00
10/25/2025
No Change 0.00
0.0
In 3 months and 1 day
01/23/2026
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If you would invest 0.00 in Molecular Data on October 25, 2025 and sell it all today you would earn a total of 0.00 from holding Molecular Data or generate 0.0% return on investment in Molecular Data over 90 days. Molecular Data is related to or competes with Showa Denko, Nitto Denko, Showa Denko, AGC, Evonik Industries, IMCD NV, and Orica. More
Molecular Data 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 Molecular Data'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 Molecular Data upside and downside potential and time the market with a certain degree of confidence.
Today, many novice investors tend to focus exclusively on investment returns with little concern for Molecular Data's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Molecular Data's standard deviation. In reality, there are many statistical measures that can use Molecular Data historical prices to predict the future Molecular Data's volatility.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Molecular Data's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Molecular Data is out of control given 3 months investment horizon. Molecular Data has Sharpe Ratio of 0.0972, which conveys that the firm had a 0.0972 % return per unit of risk over the last 3 months. We were able to interpolate and analyze data for sixteen different technical indicators, which can help you to evaluate if expected returns of 2.47% are justified by taking the suggested risk. Use Molecular Data Standard Deviation of 24.65, risk adjusted performance of 0.0793, and Mean Deviation of 7.97 to evaluate company specific risk that cannot be diversified away. Molecular Data holds a performance score of 7 on a scale of zero to a hundred. The company secures a Beta (Market Risk) of 3.4, which conveys a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Molecular Data will likely underperform. Use Molecular Data variance and rate of daily change , to analyze future returns on Molecular Data.
Auto-correlation
-0.29
Weak reverse predictability
Molecular Data has weak reverse predictability. Overlapping area represents the amount of predictability between Molecular Data time series from 25th of October 2025 to 9th of December 2025 and 9th of December 2025 to 23rd of January 2026. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Molecular Data price movement. The serial correlation of -0.29 indicates that nearly 29.0% of current Molecular Data price fluctuation can be explain by its past prices.
Correlation Coefficient
-0.29
Spearman Rank Test
-0.43
Residual Average
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Price Variance
0.0
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Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.
Additional Tools for Molecular Pink Sheet Analysis
When running Molecular Data's price analysis, check to measure Molecular Data'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 Molecular Data is operating at the current time. Most of Molecular Data's value examination focuses on studying past and present price action to predict the probability of Molecular Data's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Molecular Data's price. Additionally, you may evaluate how the addition of Molecular Data to your portfolios can decrease your overall portfolio volatility.