Life Insurance (India) Price Prediction
| LICI Stock | 985.50 46.90 5.00% |
Oversold Vs Overbought
39
Oversold | Overbought |
Quarterly Earnings Growth 0.095 | EPS Estimate Next Quarter 15.65 | EPS Estimate Current Year 54.07 | EPS Estimate Next Year 59.55 | Wall Street Target Price 1.2 K |
Using Life Insurance hype-based prediction, you can estimate the value of Life Insurance from the perspective of Life Insurance response to recently generated media hype and the effects of current headlines on its competitors.
The fear of missing out, i.e., FOMO, can cause potential investors in Life Insurance to buy its stock at a price that has no basis in reality. In that case, they are not buying Life because the equity is a good investment, but because they need to do something to avoid the feeling of missing out. On the other hand, investors will often sell stocks at prices well below their value during bear markets because they need to stop feeling the pain of losing money.
Life Insurance after-hype prediction price | INR 984.81 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Life |
Life Insurance After-Hype Price Prediction Density Analysis
As far as predicting the price of Life Insurance at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in Life Insurance or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Stock prices, such as prices of Life Insurance, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Life Insurance Estimiated After-Hype Price Volatility
In the context of predicting Life Insurance's stock value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Life Insurance's historical news coverage. Life Insurance's after-hype downside and upside margins for the prediction period are 983.27 and 986.35, respectively. We have considered Life Insurance's daily market price in relation to the headlines to evaluate this method's predictive performance. Remember, however, there is no scientific proof or empirical evidence that news-based prediction models outperform traditional linear, nonlinear models or artificial intelligence models to provide accurate predictions consistently.
Current Value
Life Insurance is very steady at this time. Analysis and calculation of next after-hype price of Life Insurance is based on 3 months time horizon.
Life Insurance Stock Price Prediction Analysis
Have you ever been surprised when a price of a Company such as Life Insurance is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Life Insurance backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Stock price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with Life Insurance, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.10 | 1.54 | 0.69 | 1.30 | 2 Events / Month | 0 Events / Month | In a few days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | ||
985.50 | 984.81 | 0.07 |
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Life Insurance Hype Timeline
Life Insurance is now traded for 985.50on National Stock Exchange of India of India. The entity has historical hype elasticity of -0.69, and average elasticity to hype of competition of -1.3. Life is projected to decline in value after the next headline, with the price expected to drop to 984.81. The average volatility of media hype impact on the company price is about 22.32%. The price decline on the next news is expected to be -0.07%, whereas the daily expected return is now at -0.1%. The volatility of related hype on Life Insurance is about 11.81%, with the expected price after the next announcement by competition of 984.20. About 96.0% of the company outstanding shares are owned by corporate insiders. The company recorded earning per share (EPS) of 65.61. Life Insurance last dividend was issued on the 19th of July 2024. Assuming the 90 days trading horizon the next projected press release will be in a few days. Check out Life Insurance Basic Forecasting Models to cross-verify your projections.Life Insurance Related Hype Analysis
Having access to credible news sources related to Life Insurance's direct competition is more important than ever and may enhance your ability to predict Life Insurance's future price movements. Getting to know how Life Insurance's peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how Life Insurance may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| RELIANCE | Reliance Industries Limited | (40.40) | 5 per month | 0.00 | (0.28) | 1.68 | (2.07) | 5.53 | |
| IOC | Indian Oil | 1.29 | 5 per month | 0.00 | (0.26) | 2.00 | (3.67) | 9.09 | |
| ONGC | Oil Natural Gas | 0.00 | 2 per month | 0.00 | (0.29) | 2.10 | (2.37) | 6.42 |
Life Insurance Additional Predictive Modules
Most predictive techniques to examine Life price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Life using various technical indicators. When you analyze Life charts, please remember that the event formation may indicate an entry point for a short seller, and look at 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 |
About Life Insurance Predictive Indicators
The successful prediction of Life Insurance stock price could yield a significant profit to investors. But is it possible? The efficient-market hypothesis suggests that all published stock prices of traded companies, such as Life Insurance, already reflect all publicly available information. This academic statement is a fundamental principle of many financial and investing theories used today. However, the typical investor usually disagrees with a 'textbook' version of this hypothesis and continually tries to find mispriced stocks to increase returns. We use internally-developed statistical techniques to arrive at the intrinsic value of Life Insurance based on analysis of Life Insurance hews, social hype, general headline patterns, and widely used predictive technical indicators.
We also calculate exposure to Life Insurance's market risk, different technical and fundamental indicators, relevant financial multiples and ratios, and then comparing them to Life Insurance's related companies.
Story Coverage note for Life Insurance
The number of cover stories for Life Insurance depends on current market conditions and Life Insurance's risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Life Insurance is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about Life Insurance's long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
Other Macroaxis Stories
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Life Insurance Short Properties
Life Insurance's future price predictability will typically decrease when Life Insurance's long traders begin to feel the short-sellers pressure to drive the price lower. The predictive aspect of Life Insurance often depends not only on the future outlook of the potential Life Insurance's investors but also on the ongoing dynamics between investors with different trading styles. Because the market risk indicators may have small false signals, it is better to identify suitable times to hedge a portfolio using different long/short signals. Life Insurance's indicators that are reflective of the short sentiment are summarized in the table below.
| Common Stock Shares Outstanding | 6.3 B | |
| Cash And Short Term Investments | 418.2 B |
Additional Tools for Life Stock 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.