Kumba Iron Pink Sheet Forecast - Simple Exponential Smoothing

KIROY Stock  USD 6.25  0.04  0.64%   
The Simple Exponential Smoothing forecasted value of Kumba Iron Ore on the next trading day is expected to be 6.25 with a mean absolute deviation of 0.14 and the sum of the absolute errors of 8.40. Kumba Pink Sheet Forecast is based on your current time horizon.
  
Kumba Iron simple exponential smoothing forecast is a very popular model used to produce a smoothed price series. Whereas in simple Moving Average models the past observations for Kumba Iron Ore are weighted equally, Exponential Smoothing assigns exponentially decreasing weights as Kumba Iron Ore prices get older.

Kumba Iron Simple Exponential Smoothing Price Forecast For the 27th of November

Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Kumba Iron Ore on the next trading day is expected to be 6.25 with a mean absolute deviation of 0.14, mean absolute percentage error of 0.03, and the sum of the absolute errors of 8.40.
Please note that although there have been many attempts to predict Kumba Pink Sheet 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 Kumba Iron's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Kumba Iron Pink Sheet Forecast Pattern

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Kumba Iron Forecasted Value

In the context of forecasting Kumba Iron's Pink Sheet 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. Kumba Iron's downside and upside margins for the forecasting period are 3.52 and 8.98, respectively. We have considered Kumba Iron'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
6.25
6.25
Expected Value
8.98
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Kumba Iron pink sheet data series using in forecasting. Note that when a statistical model is used to represent Kumba Iron pink sheet, 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 Criteria114.705
BiasArithmetic mean of the errors 0.0049
MADMean absolute deviation0.1377
MAPEMean absolute percentage error0.0204
SAESum of the absolute errors8.4
This simple exponential smoothing model begins by setting Kumba Iron Ore forecast for the second period equal to the observation of the first period. In other words, recent Kumba Iron observations are given relatively more weight in forecasting than the older observations.

Predictive Modules for Kumba Iron

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Kumba Iron Ore. Regardless of method or technology, however, to accurately forecast the pink sheet market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the pink sheet 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.
Hype
Prediction
LowEstimatedHigh
3.526.258.98
Details
Intrinsic
Valuation
LowRealHigh
2.585.318.04
Details

Other Forecasting Options for Kumba Iron

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

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

Kumba Iron Ore Technical and Predictive Analytics

The pink sheet market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Kumba Iron'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 Kumba Iron's current price.

Kumba Iron Market Strength Events

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

Kumba Iron Risk Indicators

The analysis of Kumba Iron'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 Kumba Iron's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting kumba pink sheet 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.

Also Currently Popular

Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.

Additional Tools for Kumba Pink Sheet Analysis

When running Kumba Iron's price analysis, check to measure Kumba Iron's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Kumba Iron is operating at the current time. Most of Kumba Iron's value examination focuses on studying past and present price action to predict the probability of Kumba Iron's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Kumba Iron's price. Additionally, you may evaluate how the addition of Kumba Iron to your portfolios can decrease your overall portfolio volatility.