Sigiriya Village Stock Forecast - 4 Period Moving Average

SIGVN0000  LKR 41.60  2.00  4.59%   
The 4 Period Moving Average forecasted value of Sigiriya Village Hotels on the next trading day is expected to be 42.52 with a mean absolute deviation of 0.96 and the sum of the absolute errors of 54.90. Sigiriya Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Sigiriya Village stock prices and determine the direction of Sigiriya Village Hotels's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Sigiriya Village's historical fundamentals, such as revenue growth or operating cash flow patterns.
  
A four-period moving average forecast model for Sigiriya Village Hotels is based on an artificially constructed daily price series in which the value for a given day is replaced by the mean of that value and the values for four preceding and succeeding time periods. This model is best suited to forecast equities with high volatility.

Sigiriya Village 4 Period Moving Average Price Forecast For the 26th of November

Given 90 days horizon, the 4 Period Moving Average forecasted value of Sigiriya Village Hotels on the next trading day is expected to be 42.52 with a mean absolute deviation of 0.96, mean absolute percentage error of 1.59, and the sum of the absolute errors of 54.90.
Please note that although there have been many attempts to predict Sigiriya 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 Sigiriya Village's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Sigiriya Village Stock Forecast Pattern

Sigiriya Village Forecasted Value

In the context of forecasting Sigiriya Village'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. Sigiriya Village's downside and upside margins for the forecasting period are 40.25 and 44.80, respectively. We have considered Sigiriya Village'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
41.60
42.52
Expected Value
44.80
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 4 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Sigiriya Village stock data series using in forecasting. Note that when a statistical model is used to represent Sigiriya Village 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 Criteria111.2246
BiasArithmetic mean of the errors -0.2684
MADMean absolute deviation0.9632
MAPEMean absolute percentage error0.0263
SAESum of the absolute errors54.9
The four period moving average method has an advantage over other forecasting models in that it does smooth out peaks and troughs in a set of daily price observations of Sigiriya Village. However, it also has several disadvantages. In particular this model does not produce an actual prediction equation for Sigiriya Village Hotels and therefore, it cannot be a useful forecasting tool for medium or long range price predictions

Predictive Modules for Sigiriya Village

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Sigiriya Village Hotels. 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.
Hype
Prediction
LowEstimatedHigh
39.3341.6043.87
Details
Intrinsic
Valuation
LowRealHigh
31.0833.3545.76
Details
Bollinger
Band Projection (param)
LowMiddleHigh
35.0139.8344.65
Details

Other Forecasting Options for Sigiriya Village

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

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

Sigiriya Village Hotels 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 Sigiriya Village'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 Sigiriya Village's current price.

Sigiriya Village Market Strength Events

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

Sigiriya Village Risk Indicators

The analysis of Sigiriya Village'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 Sigiriya Village's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting sigiriya 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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Other Information on Investing in Sigiriya Stock

Sigiriya Village financial ratios help investors to determine whether Sigiriya Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Sigiriya with respect to the benefits of owning Sigiriya Village security.