Digital Realty Stock Forecast - 8 Period Moving Average
| FQI Stock | EUR 170.64 5.60 3.18% |
The 8 Period Moving Average forecasted value of Digital Realty Trust on the next trading day is expected to be 176.11 with a mean absolute deviation of 4.49 and the sum of the absolute errors of 237.85. Digital Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Digital Realty's historical fundamentals, such as revenue growth or operating cash flow patterns.
Digital |
Digital Realty 8 Period Moving Average Price Forecast For the 19th of December
Given 90 days horizon, the 8 Period Moving Average forecasted value of Digital Realty Trust on the next trading day is expected to be 176.11 with a mean absolute deviation of 4.49, mean absolute percentage error of 31.44, and the sum of the absolute errors of 237.85.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
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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 174.44 and 177.79, 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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the 8 Period Moving Average 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.| AIC | Akaike Information Criteria | 106.8555 |
| Bias | Arithmetic mean of the errors | -2.735 |
| MAD | Mean absolute deviation | 4.4878 |
| MAPE | Mean absolute percentage error | 0.0267 |
| SAE | Sum of the absolute errors | 237.8513 |
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.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.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
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.
| Accumulation Distribution | 3.43 | |||
| Daily Balance Of Power | (1.00) | |||
| Rate Of Daily Change | 0.97 | |||
| Day Median Price | 173.44 | |||
| Day Typical Price | 172.51 | |||
| Market Facilitation Index | 0.0519 | |||
| Price Action Indicator | (5.60) | |||
| Period Momentum Indicator | (5.60) |
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.
| Mean Deviation | 1.18 | |||
| Semi Deviation | 0.7624 | |||
| Standard Deviation | 1.65 | |||
| Variance | 2.73 | |||
| Downside Variance | 1.15 | |||
| Semi Variance | 0.5813 | |||
| Expected Short fall | (1.51) |
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 Information and Resources on Investing in Digital Stock
When determining whether Digital Realty Trust is a strong investment it is important to analyze Digital Realty's competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact Digital Realty's future performance. For an informed investment choice regarding Digital Stock, refer to the following important reports:Check out Historical Fundamental Analysis of Digital Realty to cross-verify your projections. You can also try the Bonds Directory module to find actively traded corporate debentures issued by US companies.