Logistics Innovation Stock Forecast - Polynomial Regression

LITTDelisted Stock  USD 10.24  0.00  0.00%   
The Polynomial Regression forecasted value of Logistics Innovation Technologies on the next trading day is expected to be 10.23 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.19. Logistics Stock Forecast is based on your current time horizon.
  
Logistics Innovation polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Logistics Innovation Technologies as well as the accuracy indicators are determined from the period prices.

Logistics Innovation Polynomial Regression Price Forecast For the 16th of December 2024

Given 90 days horizon, the Polynomial Regression forecasted value of Logistics Innovation Technologies on the next trading day is expected to be 10.23 with a mean absolute deviation of 0.02, mean absolute percentage error of 0, and the sum of the absolute errors of 1.19.
Please note that although there have been many attempts to predict Logistics 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 Logistics Innovation's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Logistics Innovation Stock Forecast Pattern

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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 Logistics Innovation stock data series using in forecasting. Note that when a statistical model is used to represent Logistics Innovation 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 Criteria111.2988
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0196
MAPEMean absolute percentage error0.0019
SAESum of the absolute errors1.1941
A single variable polynomial regression model attempts to put a curve through the Logistics Innovation 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 Logistics Innovation

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Logistics Innovation. 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.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Logistics Innovation'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
10.2410.2410.24
Details
Intrinsic
Valuation
LowRealHigh
8.708.7011.26
Details
Bollinger
Band Projection (param)
LowMiddleHigh
10.2310.2510.27
Details

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

Logistics Innovation Market Strength Events

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

Logistics Innovation Risk Indicators

The analysis of Logistics Innovation'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 Logistics Innovation's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting logistics 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.

Thematic Opportunities

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Build portfolios using Macroaxis predefined set of investing ideas. Many of Macroaxis investing ideas can easily outperform a given market. Ideas can also be optimized per your risk profile before portfolio origination is invoked. Macroaxis thematic optimization helps investors identify companies most likely to benefit from changes or shifts in various micro-economic or local macro-level trends. Originating optimal thematic portfolios involves aligning investors' personal views, ideas, and beliefs with their actual investments.
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Check out Correlation Analysis to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in estimate.
You can also try the Portfolio File Import module to quickly import all of your third-party portfolios from your local drive in csv format.

Other Consideration for investing in Logistics Stock

If you are still planning to invest in Logistics Innovation check if it may still be traded through OTC markets such as Pink Sheets or OTC Bulletin Board. You may also purchase it directly from the company, but this is not always possible and may require contacting the company directly. Please note that delisted stocks are often considered to be more risky investments, as they are no longer subject to the same regulatory and reporting requirements as listed stocks. Therefore, it is essential to carefully research the Logistics Innovation's history and understand the potential risks before investing.
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