Rural Funds Stock Forecast - Polynomial Regression
| RFF Stock | 1.96 0.02 1.01% |
The Polynomial Regression forecasted value of Rural Funds Group on the next trading day is expected to be 1.99 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.40. Rural Stock Forecast is based on your current time horizon.
At this time The relative strength index (RSI) of Rural Funds' share price is above 80 indicating that the stock is significantly overbought by investors. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards. Momentum 99
Buy Peaked
Oversold | Overbought |
Quarterly Earnings Growth (0.47) | EPS Estimate Current Year 0.1167 | EPS Estimate Next Year 0.1206 | Wall Street Target Price 2.2781 | Quarterly Revenue Growth 0.178 |
Using Rural Funds hype-based prediction, you can estimate the value of Rural Funds Group from the perspective of Rural Funds response to recently generated media hype and the effects of current headlines on its competitors.
The Polynomial Regression forecasted value of Rural Funds Group on the next trading day is expected to be 1.99 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.40. Rural Funds after-hype prediction price | AUD 1.96 |
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.
Rural |
Rural Funds Additional Predictive Modules
Most predictive techniques to examine Rural price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Rural using various technical indicators. When you analyze Rural 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 |
Rural Funds Polynomial Regression Price Forecast For the 7th of January
Given 90 days horizon, the Polynomial Regression forecasted value of Rural Funds Group on the next trading day is expected to be 1.99 with a mean absolute deviation of 0.02, mean absolute percentage error of 0.0008, and the sum of the absolute errors of 1.40.Please note that although there have been many attempts to predict Rural Stock prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Rural Funds' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Rural Funds Stock Forecast Pattern
| Backtest Rural Funds | Rural Funds Price Prediction | Buy or Sell Advice |
Rural Funds Forecasted Value
In the context of forecasting Rural Funds' Stock value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Rural Funds' downside and upside margins for the forecasting period are 0.93 and 3.06, respectively. We have considered Rural Funds' daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Rural Funds stock data series using in forecasting. Note that when a statistical model is used to represent Rural Funds stock, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | 112.8093 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0226 |
| MAPE | Mean absolute percentage error | 0.0117 |
| SAE | Sum of the absolute errors | 1.4023 |
Predictive Modules for Rural Funds
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Rural Funds Group. 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.Other Forecasting Options for Rural Funds
For every potential investor in Rural, whether a beginner or expert, Rural Funds' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Rural Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Rural. Basic forecasting techniques help filter out the noise by identifying Rural Funds' price trends.Rural Funds Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Rural Funds stock to make a market-neutral strategy. Peer analysis of Rural Funds could also be used in its relative valuation, which is a method of valuing Rural Funds by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Rural Funds Group Technical and Predictive Analytics
The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Rural Funds' price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Rural Funds' current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Rural Funds Market Strength Events
Market strength indicators help investors to evaluate how Rural Funds stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Rural Funds shares will generate the highest return on investment. By undertsting and applying Rural Funds stock market strength indicators, traders can identify Rural Funds Group entry and exit signals to maximize returns.
| Accumulation Distribution | 19628.13 | |||
| Daily Balance Of Power | (0.40) | |||
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 1.99 | |||
| Day Typical Price | 1.98 | |||
| Price Action Indicator | (0.04) | |||
| Period Momentum Indicator | (0.02) | |||
| Relative Strength Index | 99.14 |
Rural Funds Risk Indicators
The analysis of Rural Funds' basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Rural Funds' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting rural stock prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
| Mean Deviation | 0.7448 | |||
| Semi Deviation | 0.9729 | |||
| Standard Deviation | 1.04 | |||
| Variance | 1.08 | |||
| Downside Variance | 1.76 | |||
| Semi Variance | 0.9465 | |||
| Expected Short fall | (0.93) |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
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Additional Tools for Rural Stock Analysis
When running Rural Funds' price analysis, check to measure Rural Funds' 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 Rural Funds is operating at the current time. Most of Rural Funds' value examination focuses on studying past and present price action to predict the probability of Rural Funds' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Rural Funds' price. Additionally, you may evaluate how the addition of Rural Funds to your portfolios can decrease your overall portfolio volatility.