scholarly journals Can Deep Learning improve technical analysis of Forex data to predict future price movements?

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Marco Fisichella ◽  
Filippo Garolla
Author(s):  
Shishir Kumar Gujrati

Stock markets are always taken as the barometer of the economy. The price movement of their indices reflects every ups and downs of the economy. Although seem to be random, these price movements do follow a certain track which can be identified using appropriate tool over long range data. One such method is of Technical Analysis wherein future price trends are forecasted using past data. Momentum Oscillators are the important tools of technical analysis. The current paper aims to identify the previous price movements of sensex by using Relative Strength Index (RSI) and Moving Average Convergence Divergence (MACD) tools and also aims to check whether these tools are appropriate in forecasting the price trends or not.


2021 ◽  
Vol 17 (1) ◽  
pp. 3-20
Author(s):  
Sumeet Gupta

The human mind is not as good at processing large amounts of information as we might like. Psychologists have shown that human beings are only able to juggle small numbers of related and often conflicting pieces of information without making judgment errors. As a result, individuals faced with the vast amounts of information available to support investment decisions often find themselves swamped by the enormity of the task; unable to see the wood from the trees. Technical analysis is a field of financial markets research that works to address the above problem by focusing on a single, commonly available, data source that reflects all known information and activity relating to all monetary securities- Price history. Technical analysts argue that as markets are efficient, prices reflect all known information and that they move over time as participants react to new information and changing needs. As a result, the technical analysis of these price changes can provide real insight into the market dynamics and be used to develop trade strategies that exhibit superior risk/reward characteristics. While technical analysis approaches have developed significantly over the past few decades, some techniques are far more ancient. While their real origins are anonymous, Japanese candlestick charts have been recorded as being employed in the rice markets as far back as the 1600s. What is particularly interesting is that various of these ancient approaches continue to provide highly effective trading signals when applied to modern markets and securities. Crude oil price volatility is in the midst of the largest business risk that oil and gas companies face. This is followed by unstable policy regime, managing costs and risks emerging from technological advancements. The high levels and rapid fluctuations of petroleum prices have become a great concern to individual consumers, firms, policy makers and society. Technical Analysis is the forecasting of future financial price movements based on an examination of past price movements. Like weather forecasting, technical analysis does not result in absolute predictions about the future. Instead, technical analysis can help investors anticipate what is "likely" to happen to prices over time. Technical analysis uses a wide variety of charts that show price over time. Hence, to mitigate the negative impacts of price volatility and to predict about the future price movement of crude oil and natural gas we can use technical analysis. Technical analysis is the study of market action, primarily through the use of charts, for the purpose of forecasting price trends. The term “market action” includes the three principal source of action available to the technician-price, volume and open interest. This research paper highlights  fundamental factor which affects the Brent price and analysed the factor which are highly correlated with Brent price and on the basis of the results forecasted the Brent price for next five years. Fundamental analysis of Brent oil, price pattern & movement of crude oil has also been carried out using candlestick technical tool.


2021 ◽  
Vol 8 (1) ◽  
pp. 36-40
Author(s):  
Rahini M ◽  
Vivek Prabu M

The Banking industry plays a very significant role in the economy and the development of a country. It is important to our nation’s economy as it caters to the need of credit for all the section of the nation. In this paper, we are focusing on the stocks of Yes Bank Limited, Axis Bank Limited and ICICI Bank Limited and analyze them technically. Using technical analysis, we could predict the future price movements of stocks by examining the present and the past price movements of stocks.  It has many tools and indicators like SMA, EMA, RSI, MACD and P&L which are used for forecasting the future stock price and also identify the pattern, trend and it directs when to buy and sell stocks.


2006 ◽  
Vol 51 (170) ◽  
pp. 125-146 ◽  
Author(s):  
Aleksandra Bradic-Martinovic

Technical analysis (TA) is a form of analyzing market encompassing supply and demand of securities according to the study of their prices and trading volume. Using the appropriate methods, TA aims to identify price movements in the stock market, futures or currencies. In short, TA analysis is the process by which "future price movements are formulated according to the price history". TA originates from the work of Charles Dow and his conclusions about the global behavior of the market, as well as from Elliot Wave Theory. Dow did not regard its theory as a tool for stock market movement prediction, nor as a guide for investors, but as a kind of barometer of general market movements. The term TA methods encompasses all the methods used in tracking prices aiming to clearly predict future events. Many different methods, mainly statistical, are used in technical analysis, the most popular ones being: establishing and following trends using moving average, recognizing price momentum, calculating indicators and oscillators, as well as cycle analysis (structure indicators). It is also necessary to point out that TA is not a science in the true meaning of the term, and that methods it uses frequently deviate from the conventional manner of their use. The main advantage of these methods is their relative ease of use, aiming to give as clear picture as possible of price movements, while at the same time avoiding the use of complicated and complex mathematical methods. The reason for this is simple and is reflected in the dynamics of financial markets, where changes occur during short periods of time and where prompt decision-making is of vital importance.


2017 ◽  
Vol 18 (3) ◽  
Author(s):  
Luna Haningsih ◽  
Zulkifli Zulkifli ◽  
Caturida Meiwanto Doktoralina

Fundamental and technical analysis is used by analysis to predict the trend ofstock price and trading volume. Studies conducted aimed to determine the effect of fundamental analysis to technical analysis. Combining two forms of analysis can produce a more accurate prediction of the stock price movement of listed cement companies in Indonesia Stock Exchange. Research experts indicate that the fundamental and technical analysis can be used independently with the ability to predict stock price movements. This study combines both analysis in a model that can provide a more robust predictive capability in the Company's share price movements of cement. Fundamental analysis is the economy wide scope, one of the predictions of financial performance. In this study the total asset turnover, return on assets and return on equityto determine which stocks are pretty good. While technical analysis is usedaccumulation distribution line that has a better ability to predict future stock prices because the data contained technical stock price and trading volume to determine when to buy and sell momentum. These results indicate that the total asset turnover, return on assets and return on equity significantly influence the accumulation distribution line. While the individual that the return on equity has no significant effect. The results of this study are expected to improve knowledge for the readers, especially investors in order to obtain optimal benefits.


Author(s):  
Nijolė MAKNICKIENĖ ◽  
Jovita MASĖNAITĖ ◽  
Viktorija STASYTYTĖ ◽  
Raimonda MARTINKUTĖ-KAULIENĖ

Purpose – The paper analyses two different paradigms of investor behaviour that exist in the financial mar-ket – the herding and contrarian behaviour. The main objective of the paper is to determine which pattern of investor behaviour better reflects the real changes in the prices of financial instruments in the financial markets. Research methodology – Algorithms of technical analysis, deep learning and classification of sentiments were used for the research; data of positions held by investors were analysed. Data mining was performed using “Tweet Sentiment Visualization” tool. Findings – The performed analysis of investor behaviour has revealed that it is more useful to ground financial decisions on the opinion of the investors contradicting the majority. The analysis of the data on the positions held by investors helped to make sure that the herding behaviour could have a negative impact on investment results, as the opinion of the majority of investors is less in line with changes in the prices of financial instruments in the market. Research limitations – The study was conducted using a limited number of investment instruments. In the future, more investment instruments can be analysed and additional forecasting methods, as well as more records in social networks can be used. Practical implications – Identifying which paradigm of investor behaviour is more beneficial to rely on can offer ap-propriate practical guidance for investors in order to invest more effectively in financial markets. Investors could use investor sentiment data to make practical investment decisions. All the methods used complement each other and can be combined into one investment decision strategy. Originality/Value – The study compared the ratio of open positions not only with real price changes but also with data obtained from the known technical analysis, deep learning and sentiment classification algorithms, which has not been done in previous studies. The applied methods allowed to achieve reliable and original results.


2021 ◽  
Vol 92 ◽  
pp. 02010
Author(s):  
Jan Chutka ◽  
Filip Rebetak

Research background: When we start looking for tools that could give a trader a certain trading advantage, we will certainly come across the problem of analysing the trading volume. This is an advanced type of analysis where the primary price chart of the underlying asset is not analysed, but traders focus on the volume of trades that have been executed at certain price levels. Although it may seem like an innovative method, this type of analysis has been used for several decades. In our article, we elaborated the theoretical basis of the analysis of trading volume as a tool for predicting the movement of prices of financial instruments. Purpose of the article: The aim of our article is to explore the possibilities, methods and procedures of analysis of trading volumes and the possibilities of their use in maximizing earnings from trading of financial instruments. Methods: We used formal methods such as analysis and synthesis of theoretical findings and others. Findings & Value added: Based on the study of the analysis and synthesis of theoretical data, we identified and described the possibilities of using the analysis of trading volume in the process of predicting the price movements of financial instruments. We consider the aim of the article to be fulfilled and we believe that it will be a valuable contribution in the field of research on this issue.


2003 ◽  
Vol 11 (1) ◽  
pp. 57-99
Author(s):  
Geun Gwan Lyu ◽  
Gi Beom Bin ◽  
Yeong Jo Lee ◽  
Seong Jun Jo

Efficient market hypothesis implies that the past price movements do not help forecast future price movements. Thus, it is impossible to consistently benefit by a technical trading strategy. On the other hand, technical analysts claim that the historical price movements are useful in predicting future price movements. These two lines of arguments are mutually contradictory. This paper reasonably assumes that the more efficient markets are, the worse will be the investment performance of technical analysis, and that as financial market‘s trading volume grows and with the elapse of time, the efficiency of markets should improve. This implies that after the launch of a new financial asset, market efficiency would improve with increased trading and elapsed time. In this paper, the duration analysis technique is used as a forecasting model and applied to measure the efficiency of Korean futures market and the won/dollar exchange rate market.


Author(s):  
Shalini Singh ◽  
Anindita Chakraborty

<em>Technical analysis forecasts the future asset prices with the use of their historical prices, trading volumes, market action and primarily through the uses of charts that predicts the future price trends. Technical analysis guides the investor to track the market with different indicators which is convenient for their study. Technical indicators aids to analyse the short-term price movement of the shares, most importantly it indicates the turning point and helps in projecting the price movement. This paper is prepared to employ the technical analysis tool to IT index companies. Indicators have been analysed using share prices of companies for 1 years, i.e., from January 2015- December 2015. Study is performed using secondary data, which has been collected from NSE website. The Technical Indicators used for the study are Bollinger Bands and MACD (Moving Average Convergence and Divergence). The purpose of the study is to find the best technical indicator to analyse the share prices.</em>


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