Australian Mines Pink Sheet Forecast - Simple Moving Average
| AMSLF Stock | USD 0 0.01 71.15% |
The Simple Moving Average forecasted value of Australian Mines Limited on the next trading day is expected to be 0 with a mean absolute deviation of 0 and the sum of the absolute errors of 0.12. Australian Pink Sheet Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Australian Mines stock prices and determine the direction of Australian Mines Limited's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Australian Mines' historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Australian Mines to cross-verify your projections. Australian |
Most investors in Australian Mines 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 Australian Mines' time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Australian Mines' price structures and extracts relationships that further increase the generated results' accuracy.
A two period moving average forecast for Australian Mines 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. Australian Mines Simple Moving Average Price Forecast For the 15th of May 2024
Given 90 days horizon, the Simple Moving Average forecasted value of Australian Mines Limited on the next trading day is expected to be 0 with a mean absolute deviation of 0, mean absolute percentage error of 0.000015, and the sum of the absolute errors of 0.12.Please note that although there have been many attempts to predict Australian 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 Australian Mines' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Australian Mines Pink Sheet Forecast Pattern
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Australian Mines Forecasted Value
In the context of forecasting Australian Mines' 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. Australian Mines' downside and upside margins for the forecasting period are 0.000045 and 45.91, respectively. We have considered Australian Mines' 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 Australian Mines pink sheet data series using in forecasting. Note that when a statistical model is used to represent Australian Mines 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 | 103.3353 |
| Bias | Arithmetic mean of the errors | 1.0E-4 |
| MAD | Mean absolute deviation | 0.002 |
| MAPE | Mean absolute percentage error | 0.2411 |
| SAE | Sum of the absolute errors | 0.1192 |
Predictive Modules for Australian Mines
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Australian Mines. 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 Australian Mines' 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 Australian Mines
For every potential investor in Australian, whether a beginner or expert, Australian Mines' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Australian Pink Sheet price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Australian. Basic forecasting techniques help filter out the noise by identifying Australian Mines' price trends.Australian Mines 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 Australian Mines pink sheet to make a market-neutral strategy. Peer analysis of Australian Mines could also be used in its relative valuation, which is a method of valuing Australian Mines by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Australian Mines 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 Australian Mines' 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 Australian Mines' current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Australian Mines Market Strength Events
Market strength indicators help investors to evaluate how Australian Mines 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 Australian Mines shares will generate the highest return on investment. By undertsting and applying Australian Mines pink sheet market strength indicators, traders can identify Australian Mines Limited entry and exit signals to maximize returns.
| Daily Balance Of Power | (9,223,372,036,855) | |||
| Rate Of Daily Change | 0.29 | |||
| Day Median Price | 0.0045 | |||
| Day Typical Price | 0.0045 | |||
| Price Action Indicator | (0.01) | |||
| Period Momentum Indicator | (0.01) |
Australian Mines Risk Indicators
The analysis of Australian Mines' 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 Australian Mines' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting australian 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 | 20.05 | |||
| Semi Deviation | 17.68 | |||
| Standard Deviation | 44.66 | |||
| Variance | 1994.67 | |||
| Downside Variance | 2047.65 | |||
| Semi Variance | 312.59 | |||
| Expected Short fall | (87.31) |
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 Australian Mines
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 Australian Mines 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 Australian Mines will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to Australian Mines could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Australian Mines 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 Australian Mines - 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 Australian Mines Limited to buy it.
The correlation of Australian Mines 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 Australian Mines moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Australian Mines 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 Australian Mines 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 Historical Fundamental Analysis of Australian Mines to cross-verify your projections. You can also try the Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
Complementary Tools for Australian Pink Sheet analysis
When running Australian Mines' price analysis, check to measure Australian Mines' 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 Australian Mines is operating at the current time. Most of Australian Mines' value examination focuses on studying past and present price action to predict the probability of Australian Mines' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Australian Mines' price. Additionally, you may evaluate how the addition of Australian Mines to your portfolios can decrease your overall portfolio volatility.
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