Fresh Harvest Pink Sheet Forecast - Simple Exponential Smoothing
| IMTH Stock | USD 0.85 0.09 9.57% |
The Simple Exponential Smoothing forecasted value of Fresh Harvest Products on the next trading day is expected to be 0.84 with a mean absolute deviation of 0.11 and the sum of the absolute errors of 6.84. Fresh Pink Sheet Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Fresh Harvest stock prices and determine the direction of Fresh Harvest Products's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Fresh Harvest's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Fresh Harvest to cross-verify your projections. Fresh |
Most investors in Fresh Harvest 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 Fresh Harvest's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Fresh Harvest's price structures and extracts relationships that further increase the generated results' accuracy.
Fresh Harvest 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 Fresh Harvest Products are weighted equally, Exponential Smoothing assigns exponentially decreasing weights as Fresh Harvest Products prices get older. Fresh Harvest Simple Exponential Smoothing Price Forecast For the 26th of April
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Fresh Harvest Products on the next trading day is expected to be 0.84 with a mean absolute deviation of 0.11, mean absolute percentage error of 0.03, and the sum of the absolute errors of 6.84.Please note that although there have been many attempts to predict Fresh 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 Fresh Harvest's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Fresh Harvest Pink Sheet Forecast Pattern
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Fresh Harvest Forecasted Value
In the context of forecasting Fresh Harvest'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. Fresh Harvest's downside and upside margins for the forecasting period are 0.01 and 129.62, respectively. We have considered Fresh Harvest'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 Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Fresh Harvest pink sheet data series using in forecasting. Note that when a statistical model is used to represent Fresh Harvest 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.| AIC | Akaike Information Criteria | 112.8145 |
| Bias | Arithmetic mean of the errors | 0.0045 |
| MAD | Mean absolute deviation | 0.114 |
| MAPE | Mean absolute percentage error | 0.3244 |
| SAE | Sum of the absolute errors | 6.8415 |
Predictive Modules for Fresh Harvest
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Fresh Harvest Products. 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Fresh Harvest'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.
Other Forecasting Options for Fresh Harvest
For every potential investor in Fresh, whether a beginner or expert, Fresh Harvest's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Fresh Pink Sheet price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Fresh. Basic forecasting techniques help filter out the noise by identifying Fresh Harvest's price trends.Fresh Harvest 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 Fresh Harvest pink sheet to make a market-neutral strategy. Peer analysis of Fresh Harvest could also be used in its relative valuation, which is a method of valuing Fresh Harvest by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Fresh Harvest Products 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 Fresh Harvest'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 Fresh Harvest's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Fresh Harvest Market Strength Events
Market strength indicators help investors to evaluate how Fresh Harvest 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 Fresh Harvest shares will generate the highest return on investment. By undertsting and applying Fresh Harvest pink sheet market strength indicators, traders can identify Fresh Harvest Products entry and exit signals to maximize returns.
| Daily Balance Of Power | (9,223,372,036,855) | |||
| Rate Of Daily Change | 0.9 | |||
| Day Median Price | 0.85 | |||
| Day Typical Price | 0.85 | |||
| Price Action Indicator | (0.04) | |||
| Period Momentum Indicator | (0.09) | |||
| Relative Strength Index | 38.49 |
Fresh Harvest Risk Indicators
The analysis of Fresh Harvest'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 Fresh Harvest's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting fresh 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.
| Mean Deviation | 37.16 | |||
| Semi Deviation | 15.73 | |||
| Standard Deviation | 133.92 | |||
| Variance | 17934.94 | |||
| Downside Variance | 1472.42 | |||
| Semi Variance | 247.28 | |||
| Expected Short fall | (126.10) |
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.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Fresh Harvest in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Fresh Harvest's short interest history, or implied volatility extrapolated from Fresh Harvest options trading.
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Try AI Portfolio ArchitectCheck out Historical Fundamental Analysis of Fresh Harvest to cross-verify your projections. You can also try the Theme Ratings module to determine theme ratings based on digital equity recommendations. Macroaxis theme ratings are based on combination of fundamental analysis and risk-adjusted market performance.
Complementary Tools for Fresh Pink Sheet analysis
When running Fresh Harvest's price analysis, check to measure Fresh Harvest'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 Fresh Harvest is operating at the current time. Most of Fresh Harvest's value examination focuses on studying past and present price action to predict the probability of Fresh Harvest's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Fresh Harvest's price. Additionally, you may evaluate how the addition of Fresh Harvest to your portfolios can decrease your overall portfolio volatility.
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