Sigiriya Village Stock Forecast - Polynomial Regression
| SIGVN0000 | LKR 84.10 14.50 20.83% |
The Polynomial Regression forecasted value of Sigiriya Village Hotels on the next trading day is expected to be 82.96 with a mean absolute deviation of 1.72 and the sum of the absolute errors of 104.79. 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.
Sigiriya |
Sigiriya Village Polynomial Regression Price Forecast For the 16th of December 2024
Given 90 days horizon, the Polynomial Regression forecasted value of Sigiriya Village Hotels on the next trading day is expected to be 82.96 with a mean absolute deviation of 1.72, mean absolute percentage error of 5.14, and the sum of the absolute errors of 104.79.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 79.11 and 86.80, 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.
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 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.| AIC | Akaike Information Criteria | 119.7476 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 1.7178 |
| MAPE | Mean absolute percentage error | 0.0391 |
| SAE | Sum of the absolute errors | 104.7877 |
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.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.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
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.
| Mean Deviation | 2.55 | |||
| Semi Deviation | 1.38 | |||
| Standard Deviation | 3.82 | |||
| Variance | 14.57 | |||
| Downside Variance | 6.14 | |||
| Semi Variance | 1.9 | |||
| Expected Short fall | (3.33) |
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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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.