GreenPower Stock Forecast - Naive Prediction
| GP Stock | USD 1.16 0.04 3.57% |
The Naive Prediction forecasted value of GreenPower Motor on the next trading day is expected to be 1.26 with a mean absolute deviation of 0.08 and the sum of the absolute errors of 4.98. GreenPower Stock Forecast is based on your current time horizon. Although GreenPower's naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of GreenPower's systematic risk associated with finding meaningful patterns of GreenPower fundamentals over time.
GreenPower |
Open Interest Against 2024-06-21 GreenPower Option Contracts
Although open interest is a measure utilized in the options markets, it could be used to forecast GreenPower's spot prices because the number of available contracts in the market changes daily, and new contracts can be created or liquidated at will. Since open interest in GreenPower's options reflects these daily shifts, investors could use the patterns of these changes to develop long and short-term trading strategies for GreenPower stock based on available contracts left at the end of a trading day.
Please note that to derive more accurate forecasting about market movement from the current GreenPower's open interest, investors have to compare it to GreenPower's spot prices. As Ford's stock price increases, high open interest indicates that money is entering the market, and the market is strongly bullish. Conversely, if the price of GreenPower is decreasing and there is high open interest, that is a sign that the bearish trend will continue, and investors may react by taking short positions in GreenPower. So, decreasing or low open interest during a bull market indicates that investors are becoming uncertain of the depth of the bullish trend, and a reversal in sentiment will likely follow.
Most investors in GreenPower 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 GreenPower's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets GreenPower's price structures and extracts relationships that further increase the generated results' accuracy.
A naive forecasting model for GreenPower is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of GreenPower Motor value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period. GreenPower Naive Prediction Price Forecast For the 13th of June 2024
Given 90 days horizon, the Naive Prediction forecasted value of GreenPower Motor on the next trading day is expected to be 1.26 with a mean absolute deviation of 0.08, mean absolute percentage error of 0.01, and the sum of the absolute errors of 4.98.Please note that although there have been many attempts to predict GreenPower 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 GreenPower's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
GreenPower Stock Forecast Pattern
| Backtest GreenPower | GreenPower Price Prediction | Buy or Sell Advice |
GreenPower Forecasted Value
In the context of forecasting GreenPower'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. GreenPower's downside and upside margins for the forecasting period are 0.01 and 5.61, respectively. We have considered GreenPower'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 Naive Prediction forecasting method's relative quality and the estimations of the prediction error of GreenPower stock data series using in forecasting. Note that when a statistical model is used to represent GreenPower 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 | 115.3577 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0803 |
| MAPE | Mean absolute percentage error | 0.0504 |
| SAE | Sum of the absolute errors | 4.9785 |
Predictive Modules for GreenPower
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as GreenPower Motor. 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 GreenPower'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 GreenPower
For every potential investor in GreenPower, whether a beginner or expert, GreenPower's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. GreenPower Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in GreenPower. Basic forecasting techniques help filter out the noise by identifying GreenPower's price trends.GreenPower 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 GreenPower stock to make a market-neutral strategy. Peer analysis of GreenPower could also be used in its relative valuation, which is a method of valuing GreenPower by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
GreenPower Motor 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 GreenPower'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 GreenPower's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
GreenPower Market Strength Events
Market strength indicators help investors to evaluate how GreenPower stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading GreenPower shares will generate the highest return on investment. By undertsting and applying GreenPower stock market strength indicators, traders can identify GreenPower Motor entry and exit signals to maximize returns.
| Accumulation Distribution | 9536.77 | |||
| Daily Balance Of Power | 0.3333 | |||
| Rate Of Daily Change | 1.04 | |||
| Day Median Price | 1.13 | |||
| Day Typical Price | 1.14 | |||
| Price Action Indicator | 0.05 | |||
| Period Momentum Indicator | 0.04 |
GreenPower Risk Indicators
The analysis of GreenPower'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 GreenPower's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting greenpower 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 | 2.83 | |||
| Standard Deviation | 4.27 | |||
| Variance | 18.19 |
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.
Building efficient market-beating portfolios requires time, education, and a lot of computing power!
The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.
Try AI Portfolio ArchitectAdditional Tools for GreenPower Stock Analysis
When running GreenPower's price analysis, check to measure GreenPower'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 GreenPower is operating at the current time. Most of GreenPower's value examination focuses on studying past and present price action to predict the probability of GreenPower's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move GreenPower's price. Additionally, you may evaluate how the addition of GreenPower to your portfolios can decrease your overall portfolio volatility.