Golden Minerals Stock Forecast - Simple Exponential Smoothing
| AUMN Stock | CAD 0.14 0.01 6.67% |
The Simple Exponential Smoothing forecasted value of Golden Minerals on the next trading day is expected to be 0.14 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.12. Golden Stock Forecast is based on your current time horizon. Although Golden Minerals' naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of Golden Minerals' systematic risk associated with finding meaningful patterns of Golden Minerals fundamentals over time.
Golden |
Golden Minerals Simple Exponential Smoothing Price Forecast For the 23rd of December
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Golden Minerals on the next trading day is expected to be 0.14 with a mean absolute deviation of 0.02, mean absolute percentage error of 0.0008, and the sum of the absolute errors of 1.12.Please note that although there have been many attempts to predict Golden 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 Golden Minerals' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Golden Minerals Stock Forecast Pattern
| Backtest Golden Minerals | Golden Minerals Price Prediction | Buy or Sell Advice |
Golden Minerals Forecasted Value
In the context of forecasting Golden Minerals' 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. Golden Minerals' downside and upside margins for the forecasting period are 0 and 8.29, respectively. We have considered Golden Minerals' 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 Golden Minerals stock data series using in forecasting. Note that when a statistical model is used to represent Golden Minerals 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 | 109.1583 |
| Bias | Arithmetic mean of the errors | 0.0043 |
| MAD | Mean absolute deviation | 0.0187 |
| MAPE | Mean absolute percentage error | 0.0544 |
| SAE | Sum of the absolute errors | 1.12 |
Predictive Modules for Golden Minerals
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Golden Minerals. 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.Other Forecasting Options for Golden Minerals
For every potential investor in Golden, whether a beginner or expert, Golden Minerals' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Golden Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Golden. Basic forecasting techniques help filter out the noise by identifying Golden Minerals' price trends.Golden Minerals 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 Golden Minerals stock to make a market-neutral strategy. Peer analysis of Golden Minerals could also be used in its relative valuation, which is a method of valuing Golden Minerals by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Golden Minerals 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 Golden Minerals' 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 Golden Minerals' current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Golden Minerals Market Strength Events
Market strength indicators help investors to evaluate how Golden Minerals stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Golden Minerals shares will generate the highest return on investment. By undertsting and applying Golden Minerals stock market strength indicators, traders can identify Golden Minerals entry and exit signals to maximize returns.
| Accumulation Distribution | 0.0714 | |||
| Daily Balance Of Power | (1.00) | |||
| Rate Of Daily Change | 0.93 | |||
| Day Median Price | 0.14 | |||
| Day Typical Price | 0.14 | |||
| Market Facilitation Index | 0.01 | |||
| Period Momentum Indicator | (0.01) |
Golden Minerals Risk Indicators
The analysis of Golden Minerals' 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 Golden Minerals' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting golden 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 | 5.37 | |||
| Standard Deviation | 8.09 | |||
| Variance | 65.49 |
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 Golden Minerals
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 Golden Minerals 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 Golden Minerals will appreciate offsetting losses from the drop in the long position's value.Moving together with Golden Stock
| 0.69 | AG | First Majestic Silver | PairCorr |
| 0.82 | IE | Ivanhoe Energy | PairCorr |
| 0.72 | FDY | Faraday Copper Corp | PairCorr |
Moving against Golden Stock
| 0.74 | QNC | Quantum Numbers | PairCorr |
| 0.71 | DBO | D Box Technologies | PairCorr |
| 0.68 | OM | Osisko Metals | PairCorr |
| 0.67 | AQN-PD | Algonquin Power Utilities | PairCorr |
| 0.66 | ENB-PH | Enbridge H Cum | PairCorr |
The ability to find closely correlated positions to Golden Minerals could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Golden Minerals 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 Golden Minerals - 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 Golden Minerals to buy it.
The correlation of Golden Minerals 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 Golden Minerals moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Golden Minerals 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 Golden Minerals 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 Golden Minerals to cross-verify your projections. To learn how to invest in Golden Stock, please use our How to Invest in Golden Minerals guide.You can also try the Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.