Tokyo Electric Pink Sheet Forecast - Simple Moving Average
| TKECF Stock | USD 6.35 0.43 6.34% |
The Simple Moving Average forecasted value of Tokyo Electric Power on the next trading day is expected to be 6.35 with a mean absolute deviation of 0.16 and the sum of the absolute errors of 9.79. Tokyo Pink Sheet Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Tokyo Electric stock prices and determine the direction of Tokyo Electric Power's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Tokyo Electric's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Tokyo Electric to cross-verify your projections. Tokyo |
Most investors in Tokyo Electric 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 Tokyo Electric's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Tokyo Electric's price structures and extracts relationships that further increase the generated results' accuracy.
A two period moving average forecast for Tokyo Electric is based on an daily price series in which the stock price on a given day is replaced by the mean of that price and the preceding price. This model is best suited to price patterns experiencing average volatility. Tokyo Electric Simple Moving Average Price Forecast For the 25th of April
Given 90 days horizon, the Simple Moving Average forecasted value of Tokyo Electric Power on the next trading day is expected to be 6.35 with a mean absolute deviation of 0.16, mean absolute percentage error of 0.09, and the sum of the absolute errors of 9.79.Please note that although there have been many attempts to predict Tokyo 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 Tokyo Electric's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Tokyo Electric Pink Sheet Forecast Pattern
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Tokyo Electric Forecasted Value
In the context of forecasting Tokyo Electric'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. Tokyo Electric's downside and upside margins for the forecasting period are 0.64 and 12.06, respectively. We have considered Tokyo Electric'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 Moving Average forecasting method's relative quality and the estimations of the prediction error of Tokyo Electric pink sheet data series using in forecasting. Note that when a statistical model is used to represent Tokyo Electric 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 | 113.8934 |
| Bias | Arithmetic mean of the errors | -0.0263 |
| MAD | Mean absolute deviation | 0.1631 |
| MAPE | Mean absolute percentage error | 0.0273 |
| SAE | Sum of the absolute errors | 9.785 |
Predictive Modules for Tokyo Electric
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Tokyo Electric Power. 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 Tokyo Electric'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 Tokyo Electric
For every potential investor in Tokyo, whether a beginner or expert, Tokyo Electric's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Tokyo Pink Sheet price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Tokyo. Basic forecasting techniques help filter out the noise by identifying Tokyo Electric's price trends.Tokyo Electric 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 Tokyo Electric pink sheet to make a market-neutral strategy. Peer analysis of Tokyo Electric could also be used in its relative valuation, which is a method of valuing Tokyo Electric by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Tokyo Electric Power 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 Tokyo Electric'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 Tokyo Electric's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Tokyo Electric Market Strength Events
Market strength indicators help investors to evaluate how Tokyo Electric 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 Tokyo Electric shares will generate the highest return on investment. By undertsting and applying Tokyo Electric pink sheet market strength indicators, traders can identify Tokyo Electric Power entry and exit signals to maximize returns.
| Accumulation Distribution | 0.55 | |||
| Daily Balance Of Power | (43.00) | |||
| Rate Of Daily Change | 0.94 | |||
| Day Median Price | 6.36 | |||
| Day Typical Price | 6.35 | |||
| Price Action Indicator | (0.22) | |||
| Period Momentum Indicator | (0.43) |
Tokyo Electric Risk Indicators
The analysis of Tokyo Electric'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 Tokyo Electric's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting tokyo 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 | 2.54 | |||
| Semi Deviation | 3.17 | |||
| Standard Deviation | 5.48 | |||
| Variance | 30.05 | |||
| Downside Variance | 50.75 | |||
| Semi Variance | 10.08 | |||
| Expected Short fall | (6.90) |
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.
Currently Active Assets on Macroaxis
Check out Historical Fundamental Analysis of Tokyo Electric to cross-verify your projections. Note that the Tokyo Electric Power information on this page should be used as a complementary analysis to other Tokyo Electric's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Options Analysis module to analyze and evaluate options and option chains as a potential hedge for your portfolios.
Complementary Tools for Tokyo Pink Sheet analysis
When running Tokyo Electric's price analysis, check to measure Tokyo Electric'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 Tokyo Electric is operating at the current time. Most of Tokyo Electric's value examination focuses on studying past and present price action to predict the probability of Tokyo Electric's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Tokyo Electric's price. Additionally, you may evaluate how the addition of Tokyo Electric to your portfolios can decrease your overall portfolio volatility.
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