1 Year (Pakistan) Chance of Future Stock Price Finishing Under 95.72
| P01GIS090525 | 96.07 0.05 0.05% |
P01GIS090525 |
1 Year Target Price Odds to finish below 95.72
The tendency of P01GIS090525 Stock price to converge on an average value over time is a known aspect in finance that investors have used since the beginning of the stock market for forecasting. However, many studies suggest that some traded equity instruments are consistently mispriced before traders' demand and supply correct the spread. One possible conclusion to this anomaly is that these stocks have additional risk, for which investors demand compensation in the form of extra returns.
| Current Price | Horizon | Target Price | Odds to drop to 95.72 or more in 90 days |
| 96.07 | 90 days | 95.72 | over 95.25 |
Based on a normal probability distribution, the odds of 1 Year to drop to 95.72 or more in 90 days from now is over 95.25 (This 1 Year GIS probability density function shows the probability of P01GIS090525 Stock to fall within a particular range of prices over 90 days) . Probability of 1 Year GIS price to stay between 95.72 and its current price of 96.07 at the end of the 90-day period is about 1.57 .
Assuming the 90 days trading horizon 1 Year GIS has a beta of -0.0023 indicating as returns on the benchmark increase, returns on holding 1 Year are expected to decrease at a much lower rate. During a bear market, however, 1 Year GIS is likely to outperform the market. Additionally 1 Year GIS has an alpha of 0.0917, implying that it can generate a 0.0917 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). 1 Year Price Density |
| Price |
Predictive Modules for 1 Year
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as 1 Year GIS. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.1 Year Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. 1 Year is not an exception. The market had few large corrections towards the 1 Year's value, including both sudden drops in prices as well as massive rallies. These swings have made and broken many portfolios. An investor can limit the violent swings in their portfolio by implementing a hedging strategy designed to limit downside losses. If you hold 1 Year GIS, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of 1 Year within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.09 | |
β | Beta against Dow Jones | -0.0023 | |
σ | Overall volatility | 1.83 | |
Ir | Information ratio | -0.1 |
1 Year Technical Analysis
1 Year's future price can be derived by breaking down and analyzing its technical indicators over time. P01GIS090525 Stock technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of 1 Year GIS. In general, you should focus on analyzing P01GIS090525 Stock price patterns and their correlations with different microeconomic environments and drivers.
1 Year Predictive Forecast Models
1 Year's time-series forecasting models is one of many 1 Year's stock analysis techniques aimed to predict future share value based on previously observed values. Time-series forecasting models are widely used for non-stationary data. Non-stationary data are called the data whose statistical properties, e.g., the mean and standard deviation, are not constant over time, but instead, these metrics vary over time. This non-stationary 1 Year's historical data is usually called time series. Some empirical experimentation suggests that the statistical forecasting models outperform the models based exclusively on fundamental analysis to predict the direction of the stock market movement and maximize returns from investment trading.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards 1 Year in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, 1 Year's short interest history, or implied volatility extrapolated from 1 Year options trading.