Life Insurance Stock Technical Analysis
| LINSA Stock | USD 9.75 0.00 0.00% |
As of the 23rd of January, Life Insurance secures the Risk Adjusted Performance of 0.0939, standard deviation of 1.44, and Mean Deviation of 0.4944. In connection with fundamental indicators, the technical analysis model lets you check existing technical drivers of Life Insurance, as well as the relationship between them.
Life Insurance Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Life, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to LifeLife |
Life Insurance '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 Life Insurance'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 Life Insurance.
| 10/25/2025 |
| 01/23/2026 |
If you would invest 0.00 in Life Insurance on October 25, 2025 and sell it all today you would earn a total of 0.00 from holding Life Insurance or generate 0.0% return on investment in Life Insurance over 90 days. Life Insurance is related to or competes with SOL Global, Billy Goat, Standard Premium, and ITEX Corp. Life Insurance Company Of Alabama operates as a life insurance company in the United States More
Life Insurance 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 Life Insurance'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 Life Insurance upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | 0.0484 | |||
| Maximum Drawdown | 11.44 |
Life Insurance Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Life Insurance's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Life Insurance's standard deviation. In reality, there are many statistical measures that can use Life Insurance historical prices to predict the future Life Insurance's volatility.| Risk Adjusted Performance | 0.0939 | |||
| Jensen Alpha | 0.1933 | |||
| Total Risk Alpha | (0.02) | |||
| Treynor Ratio | (0.52) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Life Insurance'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.
Life Insurance January 23, 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 | 0.0939 | |||
| Market Risk Adjusted Performance | (0.51) | |||
| Mean Deviation | 0.4944 | |||
| Coefficient Of Variation | 829.5 | |||
| Standard Deviation | 1.44 | |||
| Variance | 2.08 | |||
| Information Ratio | 0.0484 | |||
| Jensen Alpha | 0.1933 | |||
| Total Risk Alpha | (0.02) | |||
| Treynor Ratio | (0.52) | |||
| Maximum Drawdown | 11.44 | |||
| Skewness | 4.58 | |||
| Kurtosis | 26.16 |
Life Insurance Backtested Returns
Life Insurance appears to be not too volatile, given 3 months investment horizon. Life Insurance has Sharpe Ratio of 0.16, which conveys that the firm had a 0.16 % return per unit of risk over the last 3 months. We have found seventeen technical indicators for Life Insurance, which you can use to evaluate the volatility of the firm. Please exercise Life Insurance's Risk Adjusted Performance of 0.0939, standard deviation of 1.44, and Mean Deviation of 0.4944 to check out if our risk estimates are consistent with your expectations. On a scale of 0 to 100, Life Insurance holds a performance score of 12. The company secures a Beta (Market Risk) of -0.31, which conveys possible diversification benefits within a given portfolio. As returns on the market increase, returns on owning Life Insurance are expected to decrease at a much lower rate. During the bear market, Life Insurance is likely to outperform the market. Please check Life Insurance's coefficient of variation, jensen alpha, as well as the relationship between the Jensen Alpha and rate of daily change , to make a quick decision on whether Life Insurance's current price movements will revert.
Auto-correlation | -0.91 |
Near perfect reversele predictability
Life Insurance has near perfect reversele predictability. Overlapping area represents the amount of predictability between Life Insurance 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 Life Insurance price movement. The serial correlation of -0.91 indicates that approximately 91.0% of current Life Insurance price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.91 | |
| Spearman Rank Test | -0.26 | |
| Residual Average | 0.0 | |
| Price Variance | 0.01 |
Life Insurance 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.
Life Insurance 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 Life Insurance volatility. High ATR values indicate high volatility, and low values indicate low volatility.
About Life Insurance 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 Life Insurance 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 Life Insurance based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Life Insurance price pattern first instead of the macroeconomic environment surrounding Life Insurance. By analyzing Life Insurance'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 Life Insurance'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 Life Insurance specific price patterns or momentum indicators. Please read more on our technical analysis page.
Life Insurance January 23, 2026 Technical Indicators
Most technical analysis of Life 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 Life from various momentum indicators to cycle indicators. When you analyze Life 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 | 0.0939 | |||
| Market Risk Adjusted Performance | (0.51) | |||
| Mean Deviation | 0.4944 | |||
| Coefficient Of Variation | 829.5 | |||
| Standard Deviation | 1.44 | |||
| Variance | 2.08 | |||
| Information Ratio | 0.0484 | |||
| Jensen Alpha | 0.1933 | |||
| Total Risk Alpha | (0.02) | |||
| Treynor Ratio | (0.52) | |||
| Maximum Drawdown | 11.44 | |||
| Skewness | 4.58 | |||
| Kurtosis | 26.16 |
Life Insurance January 23, 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 Life 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 | 9.75 | ||
| Day Typical Price | 9.75 | ||
| Price Action Indicator | 0.00 |
Complementary Tools for Life Pink Sheet analysis
When running Life Insurance's price analysis, check to measure Life Insurance'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 Life Insurance is operating at the current time. Most of Life Insurance's value examination focuses on studying past and present price action to predict the probability of Life Insurance's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Life Insurance's price. Additionally, you may evaluate how the addition of Life Insurance to your portfolios can decrease your overall portfolio volatility.
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