CREDIT SUISSE Mutual Fund Forward View - Polynomial Regression
| CSOCX Fund | USD 9.11 -0.02 -0.22% |
Credit Suisse Strategic's Polynomial Regression 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 model is fitted to available historical daily prices for CREDIT SUISSE. This page is updated as new daily closing prices become available for CREDIT SUISSE.
The Polynomial Regression forecasted value of Credit Suisse Strategic on the next trading day is expected to be 9.13 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.82.A single variable polynomial regression model attempts to put a curve through the CREDIT SUISSE historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm All Polynomial Regression forecast figures shown for Credit Suisse Strategic are reference data reflecting model output based on available historical prices. Polynomial Regression Price Forecast For the 24th of March
Given 90 days horizon, the Polynomial Regression forecasted value of Credit Suisse Strategic on the next trading day is expected to be 9.13 with a mean absolute deviation of 0.01 , mean absolute percentage error of 0.0003 , and the sum of the absolute errors of 0.82 .Please note that although there have been many attempts to predict CREDIT Mutual Fund 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 CREDIT SUISSE's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Mutual Fund Forecast Pattern
| Backtest CREDIT SUISSE | CREDIT SUISSE Price Prediction | Research Analysis |
Forecasted Value
For the next trading day, Macroaxis evaluates CREDIT SUISSE's predictive range by looking for statistically meaningful downside and upside boundaries. The current forecast range spans downside near 8.97 and upside near 9.29.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of CREDIT SUISSE mutual fund data series using in forecasting. Note that when a statistical model is used to represent CREDIT SUISSE mutual fund, 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 | 109.8474 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0135 |
| MAPE | Mean absolute percentage error | 0.0015 |
| SAE | Sum of the absolute errors | 0.8227 |
Other Forecasting Options for CREDIT SUISSE
Bollinger Bands applied to CREDIT Mutual Fund price data measure how far CREDIT has deviated from its recent average relative to its own volatility. This distinction drives the choice of forecasting model applied to CREDIT SUISSE's price data. On-balance volume for CREDIT Mutual Fund creates a running indicator of buying versus selling pressure in CREDIT. Price departures from the channel boundary often mean-revert, offering tactical signals for CREDIT SUISSE's.CREDIT SUISSE Related Equities
These firms work in a similar space as CREDIT SUISSE within the High Yield Bond space and serve as useful points for comparison. Return on equity across these peers shows how well each firm turns capital into profit. Investors should look for peers that steadily beat or lag CREDIT SUISSE across many periods. This type of review is most useful when done often to track how positions shift over time.
| Risk & Return | Correlation |
CREDIT SUISSE Market Strength Events
For investors tracking Credit Suisse Strategic, market strength indicators offer quantitative evaluation of mutual fund behavior. By using these indicators, traders can make more informed decisions about when to buy or sell Credit Suisse Strategic. These indicators capture shifts in momentum that may precede significant price moves in CREDIT SUISSE. These metrics provide actionable context for both entry and risk management decisions around Credit Suisse Strategic.
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 9.11 | |||
| Day Typical Price | 9.11 | |||
| Price Action Indicator | -0.01 | |||
| Period Momentum Indicator | -0.02 | |||
| Relative Strength Index | 33.94 |
CREDIT SUISSE Risk Indicators
Analyzing CREDIT SUISSE's basic risk indicators provides investors with a structured view of the risk-return trade-off for credit mutual fund. By identifying the level of risk embedded in CREDIT SUISSE's investment, investors can make informed decisions about position sizing. Analyzing CREDIT SUISSE's risk indicators gives investors important context for price forecasting. Understanding the risk in CREDIT SUISSE's investment allows investors to make informed choices about mitigating exposure.
| Mean Deviation | 0.114 | |||
| Standard Deviation | 0.1552 | |||
| Variance | 0.0241 |
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 CREDIT SUISSE
A coverage review of Credit Suisse Strategic 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.