Star Fashion Stock Forward View

STFS Stock   4.00  -0.03  -0.74%   
Star Fashion's Naive Prediction reference data is generated by applying the model to available daily closing prices. Accuracy metrics including mean absolute deviation are provided alongside the projection.
The Naive Prediction forecasted value of Star Fashion Culture on the next trading day is expected to be 3.72 with a mean absolute deviation of 0.16 and the sum of the absolute errors of 9.76.This model is not at all useful as a medium-long range forecasting tool of Star Fashion Culture. 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 Star Fashion. 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. Star Fashion's Naive Prediction reference data is provided for informational and analytical purposes and does not constitute a trading recommendation.

Star Fashion Cash Forecast

Predicting Star Fashion's cash flow requires a variety of statistical methods, techniques, and algorithms. Probabilistic estimates of future performance inform valuation and risk management decisions for Star Fashion.
 
Cash  
 First Reported
2010-12-31
 Previous Quarter
539 K
 Current Value
497.8 K
 Quarterly Volatility
327.3 K
Macro event markers
 
Credit Downgrade
 
Yuan Drop
 
Covid
 
Interest Hikes
A naive forecasting model for Star Fashion is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Star Fashion Culture 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.

Naive Prediction Price Forecast For the 28th of March

Given 90 days horizon, the Naive Prediction forecasted value of Star Fashion Culture on the next trading day is expected to be 3.72 with a mean absolute deviation of 0.16 , mean absolute percentage error of 0.05 , and the sum of the absolute errors of 9.76 .
Please note that although there have been many attempts to predict Star Stock prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Star Fashion's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Stock Forecast Pattern

Backtest Star Fashion  Star Fashion Price Prediction  Research Analysis  

Forecasted Value

Forecasting Star Fashion Culture for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. The projected forecast band currently runs from roughly 0.04 on the downside to about 11.02 on the upside.
Market Value
4.00
3.72
Expected Value
11.02
Upside

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 Star Fashion stock data series using in forecasting. Note that when a statistical model is used to represent Star Fashion 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 Criteria115.1682
BiasArithmetic mean of the errors None
MADMean absolute deviation0.16
MAPEMean absolute percentage error0.0386
SAESum of the absolute errors9.7598
This model is not at all useful as a medium-long range forecasting tool of Star Fashion Culture. 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 Star Fashion. 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.

Other Forecasting Options for Star Fashion

Analyzing Star Fashion's price movement through moving averages at different time horizons reveals whether short-term momentum aligns with the longer-term trend. Touches of the upper or lower band in Star Fashion's chart can signal overbought or oversold conditions.

Star Fashion Related Equities

Checking Star Fashion against related firms within the Communication Services space helps investors see where the stock stands among peers. Checking Star Fashion against peers on P/E, margins, and return on equity helps put its position in context. Persistent outperformance or underperformance by specific peers relative to Star Fashion often signals structural advantages or weaknesses.
 Risk & Return  Correlation

Star Fashion Market Strength Events

Market strength indicators for Star Fashion stock provide a framework for assessing security responsiveness. These metrics are widely used to refine market timing and identify favorable moments to trade Star Fashion.

Star Fashion Risk Indicators

Assessing Star Fashion's risk indicators is a critical component of any rigorous approach to forecasting its future price. Forecasting Star Fashion's future price accurately requires understanding and quantifying the risks present in the investment.
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.

Story Coverage note for Star Fashion

A coverage review of Star Fashion Culture shows when the security is attracting above-average attention from contributors and market observers. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.

Other Macroaxis Stories

Macroaxis story coverage is designed for a broad investing audience that ranges from self-directed traders to advisers, researchers, and institutional market participants. The content is intended to support people who want a more structured path from headline information to portfolio action.

Star Fashion Short Properties

Short-interest signals around Star Fashion Culture can help investors judge whether skeptical positioning is starting to pressure price predictability and market tone. This is most valuable when investors want to know whether bearish pressure is starting to shape the market's reaction function.
Common Stock Shares Outstanding348.8 K
Cash And Short Term Investments468.7 K

Additional Tools for Star Stock Analysis

Investing Opportunities
Build portfolios using our predefined set of ideas and optimize them against your investing preferences
Alpha Finder
Use alpha and beta coefficients to find investment opportunities after accounting for the risk
Commodity Directory
Find actively traded commodities issued by global exchanges
Aroon Oscillator
Analyze current equity momentum using Aroon Oscillator and other momentum ratios
Share Portfolio
Track or share privately all of your investments from the convenience of any device
ETF Categories
List of ETF categories grouped based on various criteria, such as the investment strategy or type of investments
Positions Ratings
Determine portfolio positions ratings based on digital equity recommendations. Macroaxis instant position ratings are based on combination of fundamental analysis and risk-adjusted market performance
Stock Tickers
Use high-impact, comprehensive, and customizable stock tickers that can be easily integrated to any websites
Watchlist Optimization
Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm