SPDR ICE Etf Forecast - Simple Regression

PSK Etf  USD 34.22  0.05  0.15%   
The Simple Regression forecasted value of SPDR ICE Preferred on the next trading day is expected to be 33.96 with a mean absolute deviation of 0.17 and the sum of the absolute errors of 10.41. SPDR Etf Forecast is based on your current time horizon.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through SPDR ICE price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

SPDR ICE Simple Regression Price Forecast For the 13th of December 2024

Given 90 days horizon, the Simple Regression forecasted value of SPDR ICE Preferred on the next trading day is expected to be 33.96 with a mean absolute deviation of 0.17, mean absolute percentage error of 0.04, and the sum of the absolute errors of 10.41.
Please note that although there have been many attempts to predict SPDR Etf 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 SPDR ICE's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

SPDR ICE Etf Forecast Pattern

Backtest SPDR ICESPDR ICE Price PredictionBuy or Sell Advice 

SPDR ICE Forecasted Value

In the context of forecasting SPDR ICE's Etf 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. SPDR ICE's downside and upside margins for the forecasting period are 33.45 and 34.47, respectively. We have considered SPDR ICE'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
34.22
33.96
Expected Value
34.47
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of SPDR ICE etf data series using in forecasting. Note that when a statistical model is used to represent SPDR ICE etf, 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 Criteria116.8208
BiasArithmetic mean of the errors None
MADMean absolute deviation0.1679
MAPEMean absolute percentage error0.0049
SAESum of the absolute errors10.4074
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as SPDR ICE Preferred historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Predictive Modules for SPDR ICE

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as SPDR ICE Preferred. Regardless of method or technology, however, to accurately forecast the etf market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the etf 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.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of SPDR ICE's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Hype
Prediction
LowEstimatedHigh
33.7134.2234.73
Details
Intrinsic
Valuation
LowRealHigh
33.7834.2934.80
Details
Bollinger
Band Projection (param)
LowMiddleHigh
33.9534.1734.39
Details

Other Forecasting Options for SPDR ICE

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

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

SPDR ICE Preferred Technical and Predictive Analytics

The etf market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of SPDR ICE'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 SPDR ICE's current price.

SPDR ICE Market Strength Events

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

SPDR ICE Risk Indicators

The analysis of SPDR ICE'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 SPDR ICE's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting spdr etf 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.

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When determining whether SPDR ICE Preferred is a good investment, qualitative aspects like company management, corporate governance, and ethical practices play a significant role. A comparison with peer companies also provides context and helps to understand if SPDR Etf is undervalued or overvalued. This multi-faceted approach, blending both quantitative and qualitative analysis, forms a solid foundation for making an informed investment decision about Spdr Ice Preferred Etf. Highlighted below are key reports to facilitate an investment decision about Spdr Ice Preferred Etf:
Check out Historical Fundamental Analysis of SPDR ICE to cross-verify your projections.
You can also try the Alpha Finder module to use alpha and beta coefficients to find investment opportunities after accounting for the risk.
The market value of SPDR ICE Preferred is measured differently than its book value, which is the value of SPDR that is recorded on the company's balance sheet. Investors also form their own opinion of SPDR ICE's value that differs from its market value or its book value, called intrinsic value, which is SPDR ICE'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 SPDR ICE's market value can be influenced by many factors that don't directly affect SPDR ICE'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 SPDR ICE's value and its price as these two are different measures arrived at by different means. Investors typically determine if SPDR ICE is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, SPDR ICE'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.