AppHarvest Stock Forecast - Double Exponential Smoothing
| APPHDelisted Stock | USD 0.01 0.0004 2.84% |
The Double Exponential Smoothing forecasted value of AppHarvest on the next trading day is expected to be 0.01 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.05. AppHarvest Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast AppHarvest stock prices and determine the direction of AppHarvest's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of AppHarvest'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 tightly coupled with the direction of predictive economic indicators such as signals in american community survey. AppHarvest |
Most investors in AppHarvest cannot accurately predict what will happen the next trading day because, historically, stock markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the AppHarvest's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets AppHarvest's price structures and extracts relationships that further increase the generated results' accuracy.
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for AppHarvest works best with periods where there are trends or seasonality. AppHarvest Double Exponential Smoothing Price Forecast For the 20th of April
Given 90 days horizon, the Double Exponential Smoothing forecasted value of AppHarvest on the next trading day is expected to be 0.01 with a mean absolute deviation of 0.02, mean absolute percentage error of 0, and the sum of the absolute errors of 1.05.Please note that although there have been many attempts to predict AppHarvest 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 AppHarvest's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
AppHarvest Stock Forecast Pattern
| Backtest AppHarvest | AppHarvest Price Prediction | Buy or Sell Advice |
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 AppHarvest stock data series using in forecasting. Note that when a statistical model is used to represent AppHarvest 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 | -0.0067 |
| MAD | Mean absolute deviation | 0.0179 |
| MAPE | Mean absolute percentage error | 0.2043 |
| SAE | Sum of the absolute errors | 1.0538 |
Predictive Modules for AppHarvest
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as AppHarvest. 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 AppHarvest'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.
AppHarvest 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 AppHarvest stock to make a market-neutral strategy. Peer analysis of AppHarvest could also be used in its relative valuation, which is a method of valuing AppHarvest by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
AppHarvest Market Strength Events
Market strength indicators help investors to evaluate how AppHarvest stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading AppHarvest shares will generate the highest return on investment. By undertsting and applying AppHarvest stock market strength indicators, traders can identify AppHarvest entry and exit signals to maximize returns.
AppHarvest Risk Indicators
The analysis of AppHarvest'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 AppHarvest's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting appharvest 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 | 10.08 | |||
| Standard Deviation | 15.03 | |||
| Variance | 225.94 |
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.
Pair Trading with AppHarvest
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if AppHarvest position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in AppHarvest will appreciate offsetting losses from the drop in the long position's value.Moving together with AppHarvest Stock
| 0.71 | CNF | CNFinance Holdings Financial Report 24th of May 2024 | PairCorr |
Moving against AppHarvest Stock
| 0.91 | DIS | Walt Disney Report 8th of May 2024 | PairCorr |
| 0.89 | AXP | American Express Earnings Call Today | PairCorr |
| 0.84 | WMT | Walmart Financial Report 16th of May 2024 | PairCorr |
| 0.82 | CAT | Caterpillar Earnings Call This Week | PairCorr |
| 0.74 | PIFMF | PT Indofood Sukses | PairCorr |
The ability to find closely correlated positions to AppHarvest could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace AppHarvest when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back AppHarvest - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling AppHarvest to buy it.
The correlation of AppHarvest is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as AppHarvest moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if AppHarvest moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for AppHarvest can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out Trending Equities to better understand how to build diversified portfolios. Also, note that the market value of any company could be tightly coupled with the direction of predictive economic indicators such as signals in american community survey. You can also try the Global Markets Map module to get a quick overview of global market snapshot using zoomable world map. Drill down to check world indexes.
Other Consideration for investing in AppHarvest Stock
If you are still planning to invest in AppHarvest check if it may still be traded through OTC markets such as Pink Sheets or OTC Bulletin Board. You may also purchase it directly from the company, but this is not always possible and may require contacting the company directly. Please note that delisted stocks are often considered to be more risky investments, as they are no longer subject to the same regulatory and reporting requirements as listed stocks. Therefore, it is essential to carefully research the AppHarvest's history and understand the potential risks before investing.
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