CIC INSURANCE Stock Forecast - Triple Exponential Smoothing

CIC Stock   2.20  0.02  0.92%   
The Triple Exponential Smoothing forecasted value of CIC INSURANCE GROUP on the next trading day is expected to be 2.20 with a mean absolute deviation of 0.04 and the sum of the absolute errors of 2.11. Investors can use prediction functions to forecast CIC INSURANCE's stock prices and determine the direction of CIC INSURANCE GROUP's future trends based on various well-known forecasting models. However, exclusively looking at the historical price movement is usually misleading. We recommend always using this module together with an analysis of CIC INSURANCE's historical fundamentals, such as revenue growth or operating cash flow patterns. Check out Trending Equities to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in interest.
  
Triple exponential smoothing for CIC INSURANCE - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When CIC INSURANCE prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in CIC INSURANCE price movement. However, neither of these exponential smoothing models address any seasonality of CIC INSURANCE GROUP.

CIC INSURANCE Triple Exponential Smoothing Price Forecast For the 27th of November

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of CIC INSURANCE GROUP on the next trading day is expected to be 2.20 with a mean absolute deviation of 0.04, mean absolute percentage error of 0, and the sum of the absolute errors of 2.11.
Please note that although there have been many attempts to predict CIC 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 CIC INSURANCE's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

CIC INSURANCE Stock Forecast Pattern

CIC INSURANCE Forecasted Value

In the context of forecasting CIC INSURANCE'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. CIC INSURANCE's downside and upside margins for the forecasting period are 0.02 and 4.44, respectively. We have considered CIC INSURANCE'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
2.20
2.20
Expected Value
4.44
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of CIC INSURANCE stock data series using in forecasting. Note that when a statistical model is used to represent CIC INSURANCE 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 CriteriaHuge
BiasArithmetic mean of the errors 0.0084
MADMean absolute deviation0.0358
MAPEMean absolute percentage error0.0169
SAESum of the absolute errors2.1133
As with simple exponential smoothing, in triple exponential smoothing models past CIC INSURANCE observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older CIC INSURANCE GROUP observations.

Predictive Modules for CIC INSURANCE

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as CIC INSURANCE GROUP. 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 CIC INSURANCE's 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.

Other Forecasting Options for CIC INSURANCE

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

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

CIC INSURANCE GROUP 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 CIC INSURANCE'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 CIC INSURANCE's current price.

CIC INSURANCE Market Strength Events

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

CIC INSURANCE Risk Indicators

The analysis of CIC INSURANCE'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 CIC INSURANCE's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting cic 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.

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