LYFT Stock Forecast - Simple Regression

LYFT Stock  USD 16.79  0.50  3.07%   
The Simple Regression forecasted value of LYFT Inc on the next trading day is expected to be 16.86 with a mean absolute deviation of 0.81 and the sum of the absolute errors of 49.55. LYFT Stock Forecast is based on your current time horizon.
  
Receivables Turnover is likely to gain to 16.36 in 2024, whereas Inventory Turnover is likely to drop (3.16) in 2024. . Common Stock Shares Outstanding is likely to drop to about 326.5 M in 2024. Net Loss is likely to drop to about (1.5 B) in 2024.
Simple Regression model is a single variable regression model that attempts to put a straight line through LYFT 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.

LYFT Simple Regression Price Forecast For the 23rd of November

Given 90 days horizon, the Simple Regression forecasted value of LYFT Inc on the next trading day is expected to be 16.86 with a mean absolute deviation of 0.81, mean absolute percentage error of 1.09, and the sum of the absolute errors of 49.55.
Please note that although there have been many attempts to predict LYFT 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 LYFT's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

LYFT Stock Forecast Pattern

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LYFT Forecasted Value

In the context of forecasting LYFT's Stock 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. LYFT's downside and upside margins for the forecasting period are 12.94 and 20.79, respectively. We have considered LYFT'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
16.79
16.86
Expected Value
20.79
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 LYFT stock data series using in forecasting. Note that when a statistical model is used to represent LYFT 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 Criteria118.198
BiasArithmetic mean of the errors None
MADMean absolute deviation0.8123
MAPEMean absolute percentage error0.0569
SAESum of the absolute errors49.5475
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 LYFT Inc 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 LYFT

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as LYFT Inc. 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.
Hype
Prediction
LowEstimatedHigh
12.3216.2320.14
Details
Intrinsic
Valuation
LowRealHigh
11.3715.2819.19
Details
Bollinger
Band Projection (param)
LowMiddleHigh
11.6315.5719.51
Details
45 Analysts
Consensus
LowTargetHigh
11.1912.3013.65
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as LYFT. Your research has to be compared to or analyzed against LYFT's peers to derive any actionable benefits. When done correctly, LYFT'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 LYFT Inc.

Other Forecasting Options for LYFT

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

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

LYFT Inc Technical and Predictive Analytics

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

LYFT Market Strength Events

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

LYFT Risk Indicators

The analysis of LYFT'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 LYFT's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting lyft 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 LYFT Stock Analysis

When running LYFT's price analysis, check to measure LYFT'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 LYFT is operating at the current time. Most of LYFT's value examination focuses on studying past and present price action to predict the probability of LYFT's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move LYFT's price. Additionally, you may evaluate how the addition of LYFT to your portfolios can decrease your overall portfolio volatility.