Kemper Stock Forward View
| KMPR Stock | USD 29.69 0.26 0.88% |
Kemper's Naive Prediction reference page covers the model's projected value and error measures from recent price data. The forecast output and associated deviation metrics are shown for informational use.
The Naive Prediction forecasted value of Kemper on the next trading day is expected to be 28.23 with a mean absolute deviation of 0.82 and the sum of the absolute errors of 49.85.This model is not at all useful as a medium-long range forecasting tool of Kemper. 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 Kemper. 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. All Naive Prediction forecast figures shown for Kemper are reference data reflecting model output based on available historical prices. Naive Prediction Price Forecast For the 23rd of March
Given 90 days horizon, the Naive Prediction forecasted value of Kemper on the next trading day is expected to be 28.23 with a mean absolute deviation of 0.82 , mean absolute percentage error of 1.11 , and the sum of the absolute errors of 49.85 .Please note that although there have been many attempts to predict Kemper 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 Kemper's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Stock Forecast Pattern
| Backtest Kemper | Kemper Price Prediction | Research Analysis |
Forecasted Value
For the next trading day, Macroaxis evaluates Kemper's predictive range by looking for statistically meaningful downside and upside boundaries. The projected forecast band currently runs from roughly 25.95 on the downside to about 30.50 on the 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 Kemper stock data series using in forecasting. Note that when a statistical model is used to represent Kemper 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.| AIC | Akaike Information Criteria | 118.214 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.8173 |
| MAPE | Mean absolute percentage error | 0.024 |
| SAE | Sum of the absolute errors | 49.8539 |
Other Forecasting Options for Kemper
Bollinger Bands applied to Kemper Stock price data measure how far Kemper has deviated from its recent average relative to its own volatility. This distinction drives the choice of forecasting model applied to Kemper's price data.Kemper Related Equities
The peer firms below within the Financials space can help frame Kemper's pricing and running costs in context. Growth rate gaps between Kemper and its peers often explain pricing differences in the market. Peer pricing works best when the firms compared share similar business models and end markets. Peer review is one of the most widely used methods in stock research and portfolio building.
| Risk & Return | Correlation |
Kemper Market Strength Events
For investors tracking Kemper, market strength indicators offer quantitative evaluation of stock behavior. By using these indicators, traders can make more informed decisions about when to buy or sell Kemper.
Kemper Risk Indicators
Analyzing Kemper's basic risk indicators provides investors with a structured view of the risk-return trade-off for kemper stock. By identifying the level of risk embedded in Kemper's investment, investors can make informed decisions about position sizing.
| Mean Deviation | 1.37 | |||
| Standard Deviation | 2.28 | |||
| Variance | 5.18 |
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 Kemper
A coverage review of Kemper shows when the security is attracting above-average attention from contributors and market observers. A disciplined read of coverage separates durable relevance from temporary noise.
Contributor Headline
Latest Perspective From Macroaxis
Kemper Short Properties
Short sentiment tied to Kemper matters because heavier bearish pressure can change how quickly future price expectations become unstable. The practical goal is to identify when the balance between long and short participation may be changing the quality of the setup.
| Common Stock Shares Outstanding | 62.6 M | |
| Cash And Short Term Investments | 453.9 M |
Additional Tools for Kemper Stock Analysis
| Analyst Advice Analyst recommendations and target price estimates broken down by several categories | |
| Equity Analysis Research over 250,000 global equities including funds, stocks and ETFs to find investment opportunities | |
| Instant Ratings Determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance | |
| Idea Analyzer Analyze all characteristics, volatility and risk-adjusted return of Macroaxis ideas | |
| Price Ceiling Movement Calculate and plot Price Ceiling Movement for different equity instruments | |
| Portfolio Volatility Check portfolio volatility and analyze historical return density to properly model market risk | |
| Equity Valuation Check real value of public entities based on technical and fundamental data |