AMS Small Index Forecast - Polynomial Regression
| ASCX Index | 1,166 21.81 1.84% |
AMS Small Polynomial Regression Price Forecast For the 28th of November
Given 90 days horizon, the Polynomial Regression forecasted value of AMS Small Cap on the next trading day is expected to be 1,152 with a mean absolute deviation of 13.03, mean absolute percentage error of 255.96, and the sum of the absolute errors of 794.93.Please note that although there have been many attempts to predict AMS 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 AMS Small's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
AMS Small Index Forecast Pattern
AMS Small Forecasted Value
In the context of forecasting AMS Small'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. AMS Small's downside and upside margins for the forecasting period are 1,151 and 1,153, respectively. We have considered AMS Small'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 AMS Small index data series using in forecasting. Note that when a statistical model is used to represent AMS Small 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 | 123.6555 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 13.0316 |
| MAPE | Mean absolute percentage error | 0.0107 |
| SAE | Sum of the absolute errors | 794.9275 |
Predictive Modules for AMS Small
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as AMS Small Cap. 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.Other Forecasting Options for AMS Small
For every potential investor in AMS, whether a beginner or expert, AMS Small's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. AMS Index price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in AMS. Basic forecasting techniques help filter out the noise by identifying AMS Small's price trends.AMS Small 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 AMS Small index to make a market-neutral strategy. Peer analysis of AMS Small could also be used in its relative valuation, which is a method of valuing AMS Small by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
AMS Small Cap 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 AMS Small'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 AMS Small's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
AMS Small Market Strength Events
Market strength indicators help investors to evaluate how AMS Small index reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading AMS Small shares will generate the highest return on investment. By undertsting and applying AMS Small index market strength indicators, traders can identify AMS Small Cap entry and exit signals to maximize returns.
| Accumulation Distribution | 0.0135 | |||
| Daily Balance Of Power | (1.37) | |||
| Rate Of Daily Change | 0.98 | |||
| Day Median Price | 1174.02 | |||
| Day Typical Price | 1171.36 | |||
| Market Facilitation Index | 15.94 | |||
| Price Action Indicator | (18.87) | |||
| Period Momentum Indicator | (21.81) | |||
| Relative Strength Index | 41.28 |
AMS Small Risk Indicators
The analysis of AMS Small'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 AMS Small's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting ams 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 | 0.6915 | |||
| Standard Deviation | 0.9558 | |||
| Variance | 0.9136 |
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.