Can You Predict Stocks and Forex Market?
I can not predict the market price. Efficient market nobody can predict. But I or you – we can make an observation, opinion, strategy – assumption. But I believe that in some moments the market is inefficient and then we traders can take the opportunity.
When traders want to predict the forex or stocks market they can only create some models (using statistics to predict outcomes). When you create a set of rules for forex trading than you create the rule-based trading model. Anyway, traders can try to make predictive modeling, test observations, validate opinions but on the end, they always figure out that market is a very complicated mathematical problem that is very hard to solve. This is the best characteristic of the market – strong liquidity, a lot of players, and fact that all most impossible to predict the next outcome.
Why is that efficient market and “random walk” good?
The answer is that a truly efficient market eliminates the possibility of beating the market because any information available to any trader is already incorporated into the market price.
Have you been noticing that you have been doing a lot of wondering about can you predict stocks and forex market? In terms of stock market prediction, this entails the action of assaying to provide a determination of the value of a company’s stock within the context of a future timeframe or some other type of financial asset that is traded via the usage of an exchange. When a prediction turns out to be successful in relation to the future price of a stock or forex currency pair, then this could result in a high level of profit for the trader. It is noted that the hypothesis of the efficient market tends to make the suggestion that prices are responsible for reflecting all information that is available at the present time in conjunction with all changes in pricing that are not linked to new data are therefore deemed as being not predictable. Others may hold a disagreeing point of view about this case and those who do favor the point of view about such a case also are realized as implementing a wide spectrum of approaches and technologies that supposedly enable them to access price information regarding the future with the end aim of hoping to achieve large sums of profits as a result.
The Hypothesis of Efficient Markets and the Link to the Random Walk
It is noted that the hypothesis of efficient markets puts forth the assumption that prices are an element of information and expectations that are rational. It also considers information that is newly produced concerning the prospects of a company that usually provides a reflection within the context of the price at the present time. This provides the implication that all information that is readily available to the public concerning a company, which is noted as taking into inclusion the history of the pricing, would truly be provided in the reflection of the pricing of the stock at the present time. Therefore, it is understood that the changes in the price do indeed contribute to making an impact on the provision of new data, general changes that happen in the market, as well as movements of randomness in regard to the value that provides a reflection of the present data set. Burton Malkiel is reputed as having written a powerful piece that is called A Random Walk Down Wall Street, which was published back in the year of 1973. He proceeded to declare that it was not possible to make accurate predictions about pricing by considering only the pricing history. This led to Malkiet presenting the claim that prices are better directed under a process that is statistical in essence. He labeled this as the random walk, which means that the deviations of each day away from the value at the center position are classified as being random. This leads to the rationalization that they cannot be predicted. Malkiel then went on to provide the conclusion that the net portfolio was more hindered than helped when someone engaged in granting payment to financial service providers for the sake of making predictions concerning the market. The application of several empirical tests tends to indicate that the theory does have a wide application since most portfolios that are under the management of professional stock predictors tend to not result in outperforming the average return of the market following the application of the fees of the manager.
Though the reality is that many financial academics tend to hold a favorable perspective toward the hypothesis of an efficient market, the critics of this hypothesis provide indications of scenarios where the reality of the experience of the market was not the same as what the hypothesis implies in terms of the prediction of unpredictability. It is noted that there is an enormous industry that has sprung up that proposes the idea that there are some analysts who are better in terms of making predictions in comparison to others. Paradoxically, this is considered to be an impossible feat when there is the application of the hypothesis of efficient markets if the stock prediction industry did not engage in providing the essence of something that customers thought to be beneficial. It is further realized that a highly notorious investor who had achieved much success, noted as being Warren Buffet, claimed that the evidence of the hypothesis of the efficient market is false when he presented a speech in the year 1984 at Columbia University.
Intrinsic value means that something has real value. This is the value that a company is perceived to have. This value can be calculated. It takes into inclusion the elements that are both tangible as well as intangible during the process of the conducting of fundamental analysis. It is also a common practice to refer to the intrinsic value as the fundamental value. This value is applied for the sake of comparing with the market value of the company as well as addressing if the company has undergone undervaluation in terms of its place on the stock market. When conducting the calculation of the intrinsic value, the investor will consider the quantitative elements of the business in conjunction with the qualitative elements of the business. Normally, the intrinsic value undergoes calculation via the provision of the sum of the discounted future income that is yielded via the assets in an effort to derive the value at the current time.
Methods of Prediction
Methodologies for engaging in predictions are regarded as being placed in three-wide classifications, which also are noted as frequently overlapping. These methodologies thus are recognized as being the fundamental analysis, the technical analysis as well as technological methods.
Fundamental Analysis and market prediction
Fundamental analysts are interested in the company that engages in underlying the stock of its own merit. They conduct an evaluation pertaining to the past performance of the company along with the credibility of the accounts that the company possesses. There is the creation of several performance ratings in order to help the fundamental analyst in terms of performing an assessment of the stock’s validity, such as the usage of the P/E ratio. Warren Buffet is regarded as being a truly famous fundamental analysis. He applies the usage of the comprehensive ration of market capitalization to GDP in order to provide an indication of the general relative value regarding the stock market. As a result, this ratio is also referred to as the Buffet ratio.
Technical Analysis and market prediction
Technical analysts are not interested in the fundamental elements pertaining to a company. They engage in determining the future pricing pertaining to a stock that is founded primarily on the trends of the past history of the pricing, which is regarded as a form of time-series analytics. A wide spectrum of patterns is applied, such as the head and shoulders. Also, it is common to use the cup and saucer. In conjunction with the usage of patterns, there is also the usage of techniques. For example, one such technique is regarded as being the exponential moving average. In addition, there is the usage of oscillators, levels of support, and resistance as well as indicators of momentum and volume. At this present time, it is a popular practice to use candlestick patterns, which were likely created by Japanese merchants. Technical analysis tends to be applied in the case of short term strategies rather than long term strategies. With this being the case, this type of analysis is more prevalently used in the areas of commodities as well as forex markets when traders are concentrating on the movements of prices in the short term. This analysis often applies the usage of some key assumptions. The first assumption is that all components that are noteworthy concerning a company are reflected in the price of the stock. The other assumption is that the price moves according to the trends. Finally, another assumption indicates that the history of pricing usually experiences repetitions, which is a result of the psychology of the market.
Machine learning as market prediction tool
As a result of the inception of computers, the prediction of the stock market and forex has shifted into the realm of machine learning.
In machine learning, we have features (economic parameters, technical indicators, price values, etc.) and target variables (close price, profit or loss, etc.).Using features we try to create a model to predict the target variable.
f(Industrial production index, RSI, Volume, B. Bands, Price1, Price2, Price3, etc.) = Close Price
The most prevalent technique today applies the usage of artificial neural networks in association with genetic algorithms. Artificial neural networks can be considered as a type of mathematical element of approximators. The most prominent form of this which is applied in the prediction of the stock market is noted as being the feedforward network that engages in the usage of the algorithm of backward propagation in terms of errors for the sake of being able to update the network. Such networks are often addressed as backward propagation networks. Then another type of artificial neural network that is considered to be better suited concerning the prediction of stocks is the recurrent neural network that is based on time. Also, there is the usage of time-delay neural networks to derive the best possible predictions with the hope of earning large profits.
Simple regression models are very often better than deep learning models in my experience. Simple trading models are usually as good as complicated machine learning models in the trading industry.
Anyway, in the future, we will have more articles on this subject.
Our goal is to find an interesting pattern, market inefficiency pattern, and to trade at that moment. It is hard but possible.