Digital Realty Stock Forecast - Polynomial Regression

DLR Stock  USD 192.82  2.98  1.57%   
The Polynomial Regression forecasted value of Digital Realty Trust on the next trading day is expected to be 192.27 with a mean absolute deviation of 3.56 and the sum of the absolute errors of 216.97. Digital Stock Forecast is based on your current time horizon.
  
Digital Realty polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Digital Realty Trust as well as the accuracy indicators are determined from the period prices.

Digital Realty Polynomial Regression Price Forecast For the 26th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Digital Realty Trust on the next trading day is expected to be 192.27 with a mean absolute deviation of 3.56, mean absolute percentage error of 18.12, and the sum of the absolute errors of 216.97.
Please note that although there have been many attempts to predict Digital 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 Digital Realty's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Digital Realty Stock Forecast Pattern

Backtest Digital RealtyDigital Realty Price PredictionBuy or Sell Advice 

Digital Realty Forecasted Value

In the context of forecasting Digital Realty'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. Digital Realty's downside and upside margins for the forecasting period are 190.52 and 194.02, respectively. We have considered Digital Realty'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.
Market Value
192.82
190.52
Downside
192.27
Expected Value
194.02
Upside

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 Digital Realty stock data series using in forecasting. Note that when a statistical model is used to represent Digital Realty 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.
AICAkaike Information Criteria121.0075
BiasArithmetic mean of the errors None
MADMean absolute deviation3.5569
MAPEMean absolute percentage error0.0213
SAESum of the absolute errors216.9722
A single variable polynomial regression model attempts to put a curve through the Digital Realty historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm

Predictive Modules for Digital Realty

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Digital Realty Trust. 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.
Hype
Prediction
LowEstimatedHigh
187.85189.60191.35
Details
Intrinsic
Valuation
LowRealHigh
150.88152.63208.82
Details
Bollinger
Band Projection (param)
LowMiddleHigh
175.68183.76191.85
Details
26 Analysts
Consensus
LowTargetHigh
114.81126.16140.04
Details

Other Forecasting Options for Digital Realty

For every potential investor in Digital, whether a beginner or expert, Digital Realty's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Digital Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Digital. Basic forecasting techniques help filter out the noise by identifying Digital Realty's price trends.

Digital Realty 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 Digital Realty stock to make a market-neutral strategy. Peer analysis of Digital Realty could also be used in its relative valuation, which is a method of valuing Digital Realty by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Digital Realty Trust 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 Digital Realty'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 Digital Realty's current price.

Digital Realty Market Strength Events

Market strength indicators help investors to evaluate how Digital Realty stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Digital Realty shares will generate the highest return on investment. By undertsting and applying Digital Realty stock market strength indicators, traders can identify Digital Realty Trust entry and exit signals to maximize returns.

Digital Realty Risk Indicators

The analysis of Digital Realty'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 Digital Realty's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting digital 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.
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 Digital Realty

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 Digital Realty 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 Digital Realty will appreciate offsetting losses from the drop in the long position's value.

Moving against Digital Stock

  0.85FR First Industrial RealtyPairCorr
  0.76AMT American Tower CorpPairCorr
  0.7ARE Alexandria Real EstatePairCorr
  0.68O Realty IncomePairCorr
  0.65VICI VICI PropertiesPairCorr
The ability to find closely correlated positions to Digital Realty could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Digital Realty 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 Digital Realty - 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 Digital Realty Trust to buy it.
The correlation of Digital Realty 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 Digital Realty moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Digital Realty Trust 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 Digital Realty 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.
Pair CorrelationCorrelation Matching

Additional Tools for Digital Stock Analysis

When running Digital Realty's price analysis, check to measure Digital Realty's 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 Digital Realty is operating at the current time. Most of Digital Realty's value examination focuses on studying past and present price action to predict the probability of Digital Realty's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Digital Realty's price. Additionally, you may evaluate how the addition of Digital Realty to your portfolios can decrease your overall portfolio volatility.