LAM RESEARCH Stock Forecast - Naive Prediction

LAR Stock   74.08  0.93  1.24%   
The Naive Prediction forecasted value of LAM RESEARCH P on the next trading day is expected to be 75.99 with a mean absolute deviation of 1.72 and the sum of the absolute errors of 104.89. LAM Stock Forecast is based on your current time horizon.
  
A naive forecasting model for LAM RESEARCH is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of LAM RESEARCH P 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.

LAM RESEARCH Naive Prediction Price Forecast For the 13th of December 2024

Given 90 days horizon, the Naive Prediction forecasted value of LAM RESEARCH P on the next trading day is expected to be 75.99 with a mean absolute deviation of 1.72, mean absolute percentage error of 4.80, and the sum of the absolute errors of 104.89.
Please note that although there have been many attempts to predict LAM 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 LAM RESEARCH's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

LAM RESEARCH Stock Forecast Pattern

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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 LAM RESEARCH stock data series using in forecasting. Note that when a statistical model is used to represent LAM RESEARCH 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 Criteria119.6788
BiasArithmetic mean of the errors None
MADMean absolute deviation1.7195
MAPEMean absolute percentage error0.0244
SAESum of the absolute errors104.8922
This model is not at all useful as a medium-long range forecasting tool of LAM RESEARCH P. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict LAM RESEARCH. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Predictive Modules for LAM RESEARCH

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as LAM RESEARCH P. 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 LAM RESEARCH'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
71.2774.0876.89
Details
Intrinsic
Valuation
LowRealHigh
58.2661.0781.49
Details
Bollinger
Band Projection (param)
LowMiddleHigh
63.7569.4675.16
Details

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

LAM RESEARCH Market Strength Events

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

LAM RESEARCH Risk Indicators

The analysis of LAM RESEARCH'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 LAM RESEARCH's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting lam 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

Explore Investment Opportunities

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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Additional Tools for LAM Stock Analysis

When running LAM RESEARCH's price analysis, check to measure LAM RESEARCH's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy LAM RESEARCH is operating at the current time. Most of LAM RESEARCH's value examination focuses on studying past and present price action to predict the probability of LAM RESEARCH's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move LAM RESEARCH's price. Additionally, you may evaluate how the addition of LAM RESEARCH to your portfolios can decrease your overall portfolio volatility.