Realty Income Stock Forecast - Polynomial Regression
| O Stock | USD 58.32 0.57 0.99% |
The Polynomial Regression forecasted value of Realty Income on the next trading day is expected to be 56.38 with a mean absolute deviation of 0.99 and the sum of the absolute errors of 61.38. Realty Stock Forecast is based on your current time horizon. Although Realty Income's naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of Realty Income's systematic risk associated with finding meaningful patterns of Realty Income fundamentals over time.
Realty |
Realty Income Polynomial Regression Price Forecast For the 29th of November
Given 90 days horizon, the Polynomial Regression forecasted value of Realty Income on the next trading day is expected to be 56.38 with a mean absolute deviation of 0.99, mean absolute percentage error of 1.61, and the sum of the absolute errors of 61.38.Please note that although there have been many attempts to predict Realty 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 Realty Income's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Realty Income Stock Forecast Pattern
| Backtest Realty Income | Realty Income Price Prediction | Buy or Sell Advice |
Realty Income Forecasted Value
In the context of forecasting Realty Income's 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. Realty Income's downside and upside margins for the forecasting period are 55.34 and 57.42, respectively. We have considered Realty Income's 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 Realty Income stock data series using in forecasting. Note that when a statistical model is used to represent Realty Income 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 | 120.4271 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.9899 |
| MAPE | Mean absolute percentage error | 0.0163 |
| SAE | Sum of the absolute errors | 61.3751 |
Predictive Modules for Realty Income
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Realty Income. 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 Realty Income
For every potential investor in Realty, whether a beginner or expert, Realty Income's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Realty Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Realty. Basic forecasting techniques help filter out the noise by identifying Realty Income's price trends.Realty Income 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 Realty Income stock to make a market-neutral strategy. Peer analysis of Realty Income could also be used in its relative valuation, which is a method of valuing Realty Income by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Realty Income 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 Realty Income's 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 Realty Income's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Realty Income Market Strength Events
Market strength indicators help investors to evaluate how Realty Income stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Realty Income shares will generate the highest return on investment. By undertsting and applying Realty Income stock market strength indicators, traders can identify Realty Income entry and exit signals to maximize returns.
| Accumulation Distribution | 26643.88 | |||
| Daily Balance Of Power | 0.8769 | |||
| Rate Of Daily Change | 1.01 | |||
| Day Median Price | 58.46 | |||
| Day Typical Price | 58.41 | |||
| Price Action Indicator | 0.15 | |||
| Period Momentum Indicator | 0.57 |
Realty Income Risk Indicators
The analysis of Realty Income's 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 Realty Income's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting realty 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 | 0.7657 | |||
| Standard Deviation | 1.03 | |||
| Variance | 1.06 |
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.
Pair Trading with Realty Income
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Realty Income position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Realty Income will appreciate offsetting losses from the drop in the long position's value.Moving together with Realty Stock
Moving against Realty Stock
| 0.74 | UE | Urban Edge Properties | PairCorr |
| 0.65 | WELL | Welltower | PairCorr |
| 0.58 | AKR | Acadia Realty Trust | PairCorr |
| 0.54 | EQIX | Equinix | PairCorr |
| 0.5 | PK | Park Hotels Resorts | PairCorr |
The ability to find closely correlated positions to Realty Income could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Realty Income when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Realty Income - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Realty Income to buy it.
The correlation of Realty Income is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Realty Income moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Realty Income moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Realty Income can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out Historical Fundamental Analysis of Realty Income to cross-verify your projections. To learn how to invest in Realty Stock, please use our How to Invest in Realty Income guide.You can also try the Idea Breakdown module to analyze constituents of all Macroaxis ideas. Macroaxis investment ideas are predefined, sector-focused investing themes.
Is Retail REITs space expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Realty Income. If investors know Realty will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Realty Income listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth (0.09) | Dividend Share 3.111 | Earnings Share 1.05 | Revenue Per Share 6.077 | Quarterly Revenue Growth 0.286 |
The market value of Realty Income is measured differently than its book value, which is the value of Realty that is recorded on the company's balance sheet. Investors also form their own opinion of Realty Income's value that differs from its market value or its book value, called intrinsic value, which is Realty Income's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Realty Income's market value can be influenced by many factors that don't directly affect Realty Income's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Realty Income's value and its price as these two are different measures arrived at by different means. Investors typically determine if Realty Income is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Realty Income's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.