GEX Index Forecast - Naive Prediction
| GEX Index | 2,601 22.39 0.85% |
Most investors in GEX cannot accurately predict what will happen the next trading day because, historically, index markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the GEX's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets GEX's price structures and extracts relationships that further increase the generated results' accuracy.
A naive forecasting model for GEX is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of GEX value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period. GEX Naive Prediction Price Forecast For the 9th of June
Given 90 days horizon, the Naive Prediction forecasted value of GEX on the next trading day is expected to be 2,546 with a mean absolute deviation of 55.38, mean absolute percentage error of 4,118, and the sum of the absolute errors of 3,434.Please note that although there have been many attempts to predict GEX Index 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 GEX's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
GEX Index Forecast Pattern
GEX Forecasted Value
In the context of forecasting GEX's Index 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. GEX's downside and upside margins for the forecasting period are 2,545 and 2,547, respectively. We have considered GEX'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 Naive Prediction forecasting method's relative quality and the estimations of the prediction error of GEX index data series using in forecasting. Note that when a statistical model is used to represent GEX index, 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 | 128.2715 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 55.382 |
| MAPE | Mean absolute percentage error | 0.0227 |
| SAE | Sum of the absolute errors | 3433.6818 |
Predictive Modules for GEX
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as GEX. Regardless of method or technology, however, to accurately forecast the index market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the index 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 GEX'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.
Please note, it is not enough to conduct a financial or market analysis of a single entity such as GEX. Your research has to be compared to or analyzed against GEX's peers to derive any actionable benefits. When done correctly, GEX's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in GEX.
Other Forecasting Options for GEX
For every potential investor in GEX, whether a beginner or expert, GEX's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. GEX Index price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in GEX. Basic forecasting techniques help filter out the noise by identifying GEX's price trends.GEX 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 GEX index to make a market-neutral strategy. Peer analysis of GEX could also be used in its relative valuation, which is a method of valuing GEX by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
GEX Technical and Predictive Analytics
The index market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of GEX'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 GEX's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
GEX Market Strength Events
Market strength indicators help investors to evaluate how GEX index reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading GEX shares will generate the highest return on investment. By undertsting and applying GEX index market strength indicators, traders can identify GEX entry and exit signals to maximize returns.
| Accumulation Distribution | 12918.71 | |||
| Daily Balance Of Power | (0.64) | |||
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 2611.6 | |||
| Day Typical Price | 2608.05 | |||
| Price Action Indicator | (21.82) | |||
| Period Momentum Indicator | (22.39) |
GEX Risk Indicators
The analysis of GEX'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 GEX's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting gex index 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 | 1.02 | |||
| Semi Deviation | 0.9522 | |||
| Standard Deviation | 1.28 | |||
| Variance | 1.64 | |||
| Downside Variance | 1.28 | |||
| Semi Variance | 0.9066 | |||
| Expected Short fall | (1.20) |
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.