Oxford Industries Stock Forecast - Simple Regression

OXM Stock  USD 77.80  1.55  2.03%   
The Simple Regression forecasted value of Oxford Industries on the next trading day is expected to be 73.65 with a mean absolute deviation of 2.56 and the sum of the absolute errors of 155.88. Oxford Stock Forecast is based on your current time horizon. Although Oxford Industries' naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of Oxford Industries' systematic risk associated with finding meaningful patterns of Oxford Industries fundamentals over time.
  
At this time, Oxford Industries' Inventory Turnover is very stable compared to the past year. As of the 25th of November 2024, Payables Turnover is likely to grow to 12.56, while Receivables Turnover is likely to drop 6.56. . As of the 25th of November 2024, Common Stock Shares Outstanding is likely to drop to about 13.8 M. In addition to that, Net Income Applicable To Common Shares is likely to drop to about 46.3 M.
Simple Regression model is a single variable regression model that attempts to put a straight line through Oxford Industries 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.

Oxford Industries Simple Regression Price Forecast For the 26th of November

Given 90 days horizon, the Simple Regression forecasted value of Oxford Industries on the next trading day is expected to be 73.65 with a mean absolute deviation of 2.56, mean absolute percentage error of 8.90, and the sum of the absolute errors of 155.88.
Please note that although there have been many attempts to predict Oxford 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 Oxford Industries' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Oxford Industries Stock Forecast Pattern

Backtest Oxford IndustriesOxford Industries Price PredictionBuy or Sell Advice 

Oxford Industries Forecasted Value

In the context of forecasting Oxford Industries' 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. Oxford Industries' downside and upside margins for the forecasting period are 71.86 and 75.44, respectively. We have considered Oxford Industries' 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
77.80
73.65
Expected Value
75.44
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 Oxford Industries stock data series using in forecasting. Note that when a statistical model is used to represent Oxford Industries 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 Criteria120.2969
BiasArithmetic mean of the errors None
MADMean absolute deviation2.5554
MAPEMean absolute percentage error0.0325
SAESum of the absolute errors155.8786
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 Oxford Industries 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 Oxford Industries

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Oxford Industries. 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 Oxford Industries' 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
76.0977.8879.67
Details
Intrinsic
Valuation
LowRealHigh
70.0296.2798.06
Details
Bollinger
Band Projection (param)
LowMiddleHigh
74.4177.0679.70
Details
5 Analysts
Consensus
LowTargetHigh
103.56113.80126.32
Details

Other Forecasting Options for Oxford Industries

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

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

Oxford Industries 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 Oxford Industries' 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 Oxford Industries' current price.

Oxford Industries Market Strength Events

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

Oxford Industries Risk Indicators

The analysis of Oxford Industries' 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 Oxford Industries' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting oxford 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.

Building efficient market-beating portfolios requires time, education, and a lot of computing power!

The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.

Try AI Portfolio Architect
When determining whether Oxford Industries is a strong investment it is important to analyze Oxford Industries' competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact Oxford Industries' future performance. For an informed investment choice regarding Oxford Stock, refer to the following important reports:
Check out Historical Fundamental Analysis of Oxford Industries to cross-verify your projections.
To learn how to invest in Oxford Stock, please use our How to Invest in Oxford Industries guide.
You can also try the Pair Correlation module to compare performance and examine fundamental relationship between any two equity instruments.
Is Apparel, Accessories & Luxury Goods space expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Oxford Industries. If investors know Oxford will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Oxford Industries listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth
(0.20)
Dividend Share
2.64
Earnings Share
1.89
Revenue Per Share
99.24
Quarterly Revenue Growth
(0)
The market value of Oxford Industries is measured differently than its book value, which is the value of Oxford that is recorded on the company's balance sheet. Investors also form their own opinion of Oxford Industries' value that differs from its market value or its book value, called intrinsic value, which is Oxford Industries' true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Oxford Industries' market value can be influenced by many factors that don't directly affect Oxford Industries' underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Oxford Industries' value and its price as these two are different measures arrived at by different means. Investors typically determine if Oxford Industries is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Oxford Industries' price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.