Loomis Sayles Small Fund Probability of Future Mutual Fund Price Finishing Under 21.51
| LCGRX Fund | USD 26.20 0.31 1.17% |
Loomis |
Loomis Sayles Target Price Odds to finish below 21.51
The tendency of Loomis Mutual 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 $ 21.51 or more in 90 days |
| 26.20 | 90 days | 21.51 | near 1 |
Based on a normal probability distribution, the odds of Loomis Sayles to drop to $ 21.51 or more in 90 days from now is near 1 (This Loomis Sayles Small probability density function shows the probability of Loomis Mutual Fund to fall within a particular range of prices over 90 days) . Probability of Loomis Sayles Small price to stay between $ 21.51 and its current price of $26.2 at the end of the 90-day period is about 43.04 .
Assuming the 90 days horizon Loomis Sayles has a beta of 0.31. This indicates as returns on the market go up, Loomis Sayles average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Loomis Sayles Small will be expected to be much smaller as well. Additionally Loomis Sayles Small has an alpha of 0.0395, implying that it can generate a 0.0395 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). Loomis Sayles Price Density |
| Price |
Predictive Modules for Loomis Sayles
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Loomis Sayles Small. Regardless of method or technology, however, to accurately forecast the mutual fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the mutual 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.Loomis Sayles Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Loomis Sayles is not an exception. The market had few large corrections towards the Loomis Sayles' 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 Loomis Sayles Small, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Loomis Sayles within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.04 | |
β | Beta against Dow Jones | 0.31 | |
σ | Overall volatility | 1.03 | |
Ir | Information ratio | 0.02 |
Loomis Sayles Alerts and Suggestions
In today's market, stock alerts give investors the competitive edge they need to time the market and increase returns. Checking the ongoing alerts of Loomis Sayles for significant developments is a great way to find new opportunities for your next move. Suggestions and notifications for Loomis Sayles Small can help investors quickly react to important events or material changes in technical or fundamental conditions and significant headlines that can affect investment decisions.| The fund generated three year return of 0.0% | |
| Loomis Sayles Small maintains 96.94% of its assets in stocks |
Loomis Sayles Technical Analysis
Loomis Sayles' future price can be derived by breaking down and analyzing its technical indicators over time. Loomis Mutual Fund technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Loomis Sayles Small. In general, you should focus on analyzing Loomis Mutual Fund price patterns and their correlations with different microeconomic environments and drivers.
Loomis Sayles Predictive Forecast Models
Loomis Sayles' time-series forecasting models is one of many Loomis Sayles' mutual 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 Loomis Sayles' 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 mutual fund market movement and maximize returns from investment trading.
Things to note about Loomis Sayles Small
Checking the ongoing alerts about Loomis Sayles for important developments is a great way to find new opportunities for your next move. Our stock alerts and notifications screener for Loomis Sayles Small help investors to be notified of important events, changes in technical or fundamental conditions, and significant headlines that can affect investment decisions.
| The fund generated three year return of 0.0% | |
| Loomis Sayles Small maintains 96.94% of its assets in stocks |
Other Information on Investing in Loomis Mutual Fund
Loomis Sayles financial ratios help investors to determine whether Loomis Mutual Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Loomis with respect to the benefits of owning Loomis Sayles security.
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