Tangerine Equity Growth Fund Probability of Future Fund Price Finishing Under 13.98
| 0P0001KUBJ | 14.90 0.13 0.88% |
Tangerine |
Tangerine Equity Target Price Odds to finish below 13.98
The tendency of Tangerine Fund 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 13.98 or more in 90 days |
| 14.90 | 90 days | 13.98 | about 42.08 |
Based on a normal probability distribution, the odds of Tangerine Equity to drop to 13.98 or more in 90 days from now is about 42.08 (This Tangerine Equity Growth probability density function shows the probability of Tangerine Fund to fall within a particular range of prices over 90 days) . Probability of Tangerine Equity Growth price to stay between 13.98 and its current price of 14.9 at the end of the 90-day period is about 55.28 .
Assuming the 90 days trading horizon Tangerine Equity has a beta of 0.0787. This suggests as returns on the market go up, Tangerine Equity average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Tangerine Equity Growth will be expected to be much smaller as well. Additionally Tangerine Equity Growth has an alpha of 0.1628, implying that it can generate a 0.16 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). Tangerine Equity Price Density |
| Price |
Predictive Modules for Tangerine Equity
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Tangerine Equity Growth. Regardless of method or technology, however, to accurately forecast the fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the fund 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.Tangerine Equity Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Tangerine Equity is not an exception. The market had few large corrections towards the Tangerine Equity'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 Tangerine Equity Growth, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Tangerine Equity within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.16 | |
β | Beta against Dow Jones | 0.08 | |
σ | Overall volatility | 0.42 | |
Ir | Information ratio | 0.10 |
Tangerine Equity Technical Analysis
Tangerine Equity's future price can be derived by breaking down and analyzing its technical indicators over time. Tangerine Fund technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Tangerine Equity Growth. In general, you should focus on analyzing Tangerine Fund price patterns and their correlations with different microeconomic environments and drivers.
Tangerine Equity Predictive Forecast Models
Tangerine Equity's time-series forecasting models is one of many Tangerine Equity's fund 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 Tangerine Equity'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 fund 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 Tangerine Equity 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, Tangerine Equity's short interest history, or implied volatility extrapolated from Tangerine Equity options trading.
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