Life Insurance Stock Market Value
| LINS Stock | USD 35.02 0.00 0.00% |
| Symbol | Life |
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.
| 04/26/2025 |
| 07/25/2025 |
If you would invest 0.00 in Life Insurance on April 26, 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 Life Insurance, Lyons Bancorp, Pekin Life, and Merchants National. 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 | 0.0869 | |||
| Maximum Drawdown | 275.27 |
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 | 0.0891 | |||
| Jensen Alpha | 4.34 | |||
| Total Risk Alpha | (5.26) | |||
| Treynor Ratio | (0.38) |
Life Insurance Backtested Returns
Life Insurance is relatively risky given 3 months investment horizon. Life Insurance has Sharpe Ratio of 0.0992, which conveys that the firm had a 0.0992 % return per unit of risk over the last 3 months. We were able to interpolate seventeen different technical indicators, which can help you to evaluate if expected returns of 2.94% are justified by taking the suggested risk. Use Life Insurance Mean Deviation of 8.26, standard deviation of 28.47, and Risk Adjusted Performance of 0.0891 to evaluate company specific risk that cannot be diversified away. Life Insurance holds a performance score of 7 on a scale of zero to a hundred. The company secures a Beta (Market Risk) of -7.03, which conveys a somewhat significant risk relative to the market. As returns on the market increase, returns on owning Life Insurance are expected to decrease by larger amounts. On the other hand, during market turmoil, Life Insurance is expected to outperform it. Use Life Insurance coefficient of variation, maximum drawdown, as well as the relationship between the Maximum Drawdown and day typical price , to analyze future returns on Life Insurance.
Auto-correlation | 0.26 |
Poor predictability
Life Insurance has poor predictability. Overlapping area represents the amount of predictability between Life Insurance time series from 26th of April 2025 to 10th of June 2025 and 10th of June 2025 to 25th of July 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 Life Insurance price movement. The serial correlation of 0.26 indicates that nearly 26.0% of current Life Insurance price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.26 | |
| Spearman Rank Test | -0.31 | |
| Residual Average | 0.0 | |
| Price Variance | 8.99 |
Life Insurance lagged returns against current returns
Autocorrelation, which is Life Insurance 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 Life Insurance's pink sheet expected returns. We can calculate the autocorrelation of Life Insurance returns to help us make a trade decision. For example, suppose you find that Life Insurance 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 |
Life Insurance 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 Life Insurance pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Life Insurance pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Life Insurance pink sheet over time.
Current vs Lagged Prices |
| Timeline |
Life Insurance Lagged Returns
When evaluating Life Insurance's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Life Insurance pink sheet have on its future price. Life Insurance 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, Life Insurance autocorrelation shows the relationship between Life Insurance pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Life Insurance.
Regressed Prices |
| Timeline |
Thematic Opportunities
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Additional 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.