Himalaya Shipping Stock Forecast - Double Exponential Smoothing
| HSHP Stock | 92.20 3.20 3.60% |
Momentum 49
Impartial
Oversold | Overbought |
Using Himalaya Shipping hype-based prediction, you can estimate the value of Himalaya Shipping from the perspective of Himalaya Shipping response to recently generated media hype and the effects of current headlines on its competitors.
The Double Exponential Smoothing forecasted value of Himalaya Shipping on the next trading day is expected to be 92.18 with a mean absolute deviation of 1.55 and the sum of the absolute errors of 91.73. Himalaya Shipping after-hype prediction price | NOK 92.2 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Himalaya |
Himalaya Shipping Additional Predictive Modules
Most predictive techniques to examine Himalaya price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Himalaya using various technical indicators. When you analyze Himalaya charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Himalaya Shipping Double Exponential Smoothing Price Forecast For the 20th of January
Given 90 days horizon, the Double Exponential Smoothing forecasted value of Himalaya Shipping on the next trading day is expected to be 92.18 with a mean absolute deviation of 1.55, mean absolute percentage error of 4.37, and the sum of the absolute errors of 91.73.Please note that although there have been many attempts to predict Himalaya 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 Himalaya Shipping's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Himalaya Shipping Stock Forecast Pattern
Himalaya Shipping Forecasted Value
In the context of forecasting Himalaya Shipping'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. Himalaya Shipping's downside and upside margins for the forecasting period are 89.89 and 94.47, respectively. We have considered Himalaya Shipping'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 Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Himalaya Shipping stock data series using in forecasting. Note that when a statistical model is used to represent Himalaya Shipping 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 | Huge |
| Bias | Arithmetic mean of the errors | -0.1939 |
| MAD | Mean absolute deviation | 1.5547 |
| MAPE | Mean absolute percentage error | 0.0177 |
| SAE | Sum of the absolute errors | 91.7284 |
Predictive Modules for Himalaya Shipping
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Himalaya Shipping. 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 Himalaya Shipping
For every potential investor in Himalaya, whether a beginner or expert, Himalaya Shipping's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Himalaya Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Himalaya. Basic forecasting techniques help filter out the noise by identifying Himalaya Shipping's price trends.Himalaya Shipping 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 Himalaya Shipping stock to make a market-neutral strategy. Peer analysis of Himalaya Shipping could also be used in its relative valuation, which is a method of valuing Himalaya Shipping by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Himalaya Shipping 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 Himalaya Shipping'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 Himalaya Shipping's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Himalaya Shipping Market Strength Events
Market strength indicators help investors to evaluate how Himalaya Shipping stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Himalaya Shipping shares will generate the highest return on investment. By undertsting and applying Himalaya Shipping stock market strength indicators, traders can identify Himalaya Shipping entry and exit signals to maximize returns.
Himalaya Shipping Risk Indicators
The analysis of Himalaya Shipping'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 Himalaya Shipping's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting himalaya 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 | 1.8 | |||
| Semi Deviation | 2.17 | |||
| Standard Deviation | 2.34 | |||
| Variance | 5.49 | |||
| Downside Variance | 6.28 | |||
| Semi Variance | 4.69 | |||
| Expected Short fall | (1.93) |
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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