Molecular Data Stock Technical Analysis
| MKDTY Stock | USD 0.0001 0.00 0.00% |
As of the 26th of January, Molecular Data secures the Mean Deviation of 7.97, risk adjusted performance of 0.0787, and Standard Deviation of 24.65. In connection with fundamental indicators, the technical analysis model lets you check existing technical drivers of Molecular Data, as well as the relationship between them.
Molecular Data Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Molecular, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to MolecularMolecular |
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.
| 10/28/2025 |
| 01/26/2026 |
If you would invest 0.00 in Molecular Data on October 28, 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. 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.
| Information Ratio | 0.0911 | |||
| Maximum Drawdown | 216.67 |
Molecular Data Market Risk Indicators
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.| Risk Adjusted Performance | 0.0787 | |||
| Jensen Alpha | 2.72 | |||
| Total Risk Alpha | 0.0122 | |||
| Treynor Ratio | (0.39) |
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 January 26, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0787 | |||
| Market Risk Adjusted Performance | (0.38) | |||
| Mean Deviation | 7.97 | |||
| Coefficient Of Variation | 1060.92 | |||
| Standard Deviation | 24.65 | |||
| Variance | 607.51 | |||
| Information Ratio | 0.0911 | |||
| Jensen Alpha | 2.72 | |||
| Total Risk Alpha | 0.0122 | |||
| Treynor Ratio | (0.39) | |||
| Maximum Drawdown | 216.67 | |||
| Skewness | 3.91 | |||
| Kurtosis | 24.14 |
Molecular Data Backtested Returns
Molecular Data is out of control given 3 months investment horizon. Molecular Data has Sharpe Ratio of 0.0965, which conveys that the firm had a 0.0965 % return per unit of risk over the last 3 months. We were able to interpolate and analyze data for seventeen different technical indicators, which can help you to evaluate if expected returns of 2.43% are justified by taking the suggested risk. Use Molecular Data Risk Adjusted Performance of 0.0787, mean deviation of 7.97, and Standard Deviation of 24.65 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 -5.9, which conveys a somewhat significant risk relative to the market. As returns on the market increase, returns on owning Molecular Data are expected to decrease by larger amounts. On the other hand, during market turmoil, Molecular Data is expected to outperform it. Use Molecular Data variance and rate of daily change , to analyze future returns on Molecular Data.
Auto-correlation | -0.49 |
Modest reverse predictability
Molecular Data has modest reverse predictability. Overlapping area represents the amount of predictability between Molecular Data time series from 28th of October 2025 to 12th of December 2025 and 12th of December 2025 to 26th 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 -0.49 indicates that about 49.0% of current Molecular Data price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.49 | |
| Spearman Rank Test | -0.33 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Molecular Data technical pink sheet analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, pink sheet market cycles, or different charting patterns.
Molecular Data Technical Analysis
The output start index for this execution was twenty-four with a total number of output elements of thirty-seven. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of Molecular Data volatility. High ATR values indicate high volatility, and low values indicate low volatility.
About Molecular Data Technical Analysis
The technical analysis module can be used to analyzes prices, returns, volume, basic money flow, and other market information and help investors to determine the real value of Molecular Data on a daily or weekly bases. We use both bottom-up as well as top-down valuation methodologies to arrive at the intrinsic value of Molecular Data based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Molecular Data price pattern first instead of the macroeconomic environment surrounding Molecular Data. By analyzing Molecular Data's financials, daily price indicators, and related drivers such as dividends, momentum ratios, and various types of growth rates, we attempt to find the most accurate representation of Molecular Data's intrinsic value. As compared to a bottom-up approach, our top-down model examines the macroeconomic factors that affect the industry/economy before zooming in to Molecular Data specific price patterns or momentum indicators. Please read more on our technical analysis page.
Molecular Data January 26, 2026 Technical Indicators
Most technical analysis of Molecular help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Molecular from various momentum indicators to cycle indicators. When you analyze Molecular charts, please remember that the event formation may indicate an entry point for a short seller, and look at different other indicators across different periods to confirm that a breakdown or reversion is likely to occur.
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0787 | |||
| Market Risk Adjusted Performance | (0.38) | |||
| Mean Deviation | 7.97 | |||
| Coefficient Of Variation | 1060.92 | |||
| Standard Deviation | 24.65 | |||
| Variance | 607.51 | |||
| Information Ratio | 0.0911 | |||
| Jensen Alpha | 2.72 | |||
| Total Risk Alpha | 0.0122 | |||
| Treynor Ratio | (0.39) | |||
| Maximum Drawdown | 216.67 | |||
| Skewness | 3.91 | |||
| Kurtosis | 24.14 |
Molecular Data January 26, 2026 Daily Trend Indicators
Traders often use several different daily volumes and price technical indicators to supplement a more traditional technical analysis when analyzing securities such as Molecular stock. With literally thousands of different options, investors must choose the best indicators for them and familiarize themselves with how they work. We suggest combining traditional momentum indicators with more near-term forms of technical analysis such as Accumulation Distribution or Daily Balance Of Power. With their quantitative nature, daily value technical indicators can also be incorporated into your automated trading systems.
| Accumulation Distribution | 0.00 | ||
| Daily Balance Of Power | 0.00 | ||
| Rate Of Daily Change | 1.00 | ||
| Day Median Price | 0.00 | ||
| Day Typical Price | 0.00 | ||
| Price Action Indicator | 0.00 |
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.