scholarly journals Predictive Power of Adaptive Candlestick Patterns in Forex Market. Eurusd Case

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 802
Author(s):  
Ismael Orquín-Serrano

The Efficient Market Hypothesis (EMH) states that all available information is immediately reflected in the price of any asset or financial instrument, so that it is impossible to predict its future values, making it follow a pure stochastic process. Among all financial markets, FOREX is usually addressed as one of the most efficient. This paper tests the efficiency of the EURUSD pair taking only into consideration the price itself. A novel categorical classification, based on adaptive criteria, of all possible single candlestick patterns is presented. The predictive power of candlestick patterns is evaluated from a statistical inference approach, where the mean of the average returns of the strategies in out-of-sample historical data is taken as sample statistic. No net positive average returns are found in any case after taking into account transaction costs. More complex candlestick patterns are considered feeding supervised learning systems with the information of past bars. No edge is found even in the case of considering the information of up to 24 preceding candlesticks.

2019 ◽  
Vol 18 (2) ◽  
pp. 268-295
Author(s):  
David Peón ◽  
Manel Antelo ◽  
Anxo Calvo

Purpose The efficient market hypothesis (EMH) states that asset prices in financial markets always reflect all available information about economic fundamentals. The purpose of this paper is to provide a guide as to which predictions of the EMH seem to be borne out by empirical evidence. Design/methodology/approach Rather than following the classic three groups of tests for the different forms of EMH that are common in the literature, the authors consider how the two alternative definitions of the EMH and the joint hypothesis problem impact on the tests and leave the controversy unsolved. The authors briefly report the antecedents, the main theoretical and empirical contributions and recent literature on each type of tests. Findings Eventually, as a summary for each type of tests, the authors provide a critical view on the main sources of acrimony between the alternative schools of thought in understanding asset price formation. Originality/value The paper may be seen as an up-to-date introductory review for researchers on the different tests of the EMH performed, and for newcomers to understand the key sources of acrimony between rationalists and behaviorists.


Author(s):  
Mustafa Okur ◽  
A. Osman Gurbuz

Efficient Market Hypothesis (EMH) is a cornerstone in modern finance theory. Efficient market hypothesis states that it is impossible to make abnormal returns in financial markets because financial asset prices always reflect all available information. This chapter was undertaken in order to give a brief survey of modern finance theory by mainly focusing on the efficient market hypothesis. The authors also discuss the empirical foundations of the efficient market hypothesis. Finally, the main challenges to the efficient market hypothesis are introduced in order to point out a perspective for future research.


2016 ◽  
Vol 11 (1) ◽  
Author(s):  
Predrag Kapor

Are financial markets efficient is a question on which there is still no clear and complete answer. Position that prices of securities fully reflect available information about securities is called the efficient market hypothesis (EMH). The EMH (on the example of stocks) has three forms (or levels) of efficiency: 1) the ‘’ weak’’ form of the EMH- is the claim that stock prices reflect all information contained in previous transactions; 2) the ‘’ semi- strong’’ form of the EMH- is the claim that stock prices reflect all publicly available information, and 3) the’’ strong’’ form of the EMH- is the claim that stock prices reflect all relevant information (public and private), including the privileged (the insider) information.Numerous studies have confirmed the existence of a’’ weak’’ form of the EMH, and generally supported the existence of a’’ semi-strong’’ form of the EMH, but not of a ‘’ strong’’ form of the EMH. However, the EMH, even if it is a ‘’weak’’ or a ‘’semi-strong’’ form has a number of weaknesses. Some of the the EMH assumptions confront with the reality – there is no perfect information, transaction and information costs can be significant, markets are often imperfect, and investors do not have complete knowledge about the set of all available financial strategies for a given situation.The information ’’overload’’ confuses people and affects their ability to prioritize and make good decisions. On the other hand, electronic trading method significantly affects the information at the disposal of the different market actors. It seems that the greatest threat to the EMH comes from the field of behavioral finance, which is engaged in research on the possible impact of psychological factors (loss aversion, anchoring, overconfidence...) on the behavior of investors. The basic argument of behavioral finance is that ’’standard’’ financial theory is not paying attention to how ordinary people make decisions and that ‘’ human factor’’ can not be ignored.Tha aim of this study was to critically examine the EMH. Apperently, the EMH after numerous studes and identified anomalies, largely remains at the level of (insufficiently confirmed) hypothesis, although it is often given the status, or created an illusion, of confirmed. This is also because the EMH is an important component of the rulling ’’paradigm’’ in finance or ’’standard finance theory’’. Joperdizing the status of the EMH bring into question many other important components of this ’’paradigm’’.The EMH has not offered acceptable answers to some of the specific developments and events in the financial market, including the last global financial crisis. But, the EMH still remains one of the cornerstones of ’’standard’’ finance theory.


2009 ◽  
Vol 6 (3) ◽  
pp. 126-136
Author(s):  
JSG Strydom ◽  
JH Van Rooyen

The efficient market hypothesis is based on the assumption that individuals act rationally, processing all available information in their decision-making process. Prices therefore reflect the appropriate risk and return. However, research conducted regarding the ways that investors arrive at decisions when faced with uncertainty, has revealed that this is in fact not always the case. People often make systematic errors, the so-called cognitive biases, which lead them to less rational behavior than the traditional economic paradigm predicts. These cognitive biases have been found to be responsible for various irregular phenomena often observed in financial markets as (turbulence or, volatility, seasonable cycles, "bubbles", etc. Behavioral finance attempts to explain some of the changes in the financial markets that cannot be explained by the efficient market hypothesis. This research reviews some results from the behavioral finance and other related literature. A survey was also done to determine whether the most prominent portfolio managers in South Africa are aware of behavioral finance issues/models and consider the influence of cognitive issues when making investment decisions or giving advice to clients.


Author(s):  
Rui Dias ◽  
◽  
Hortense Santos ◽  

This paper aims to test the efficient market hypothesis, in its weak form, in the stock markets of BOTSWANA, EGYPT, KENYA, MOROCCO, NIGERIA and SOUTH AFRICA, in the period from September 2, 2019 to September 2, 2020. In order to achieve this analysis, we intend to find out if: the global pandemic (Covid-19) has decreased the efficiency, in its weak form, of African stock markets? The results therefore support the evidence that the random walk hypothesis is not supported by the financial markets analyzed in this period of global pandemic. The values of variance ratios are lower than the unit, which implies that the yields are autocorrelated in time and, there is reversal to the mean, and no differences were identified between the stock markets analyzed. The authors consider that the results achieved are of interest to investors looking for opportunities for portfolio diversification in these regional stock markets.


Author(s):  
Mustafa Okur ◽  
A. Osman Gurbuz

Efficient Market Hypothesis (EMH) is a cornerstone in modern finance theory. Efficient market hypothesis states that it is impossible to make abnormal returns in financial markets because financial asset prices always reflect all available information. This chapter was undertaken in order to give a brief survey of modern finance theory by mainly focusing on the efficient market hypothesis. The authors also discuss the empirical foundations of the efficient market hypothesis. Finally, the main challenges to the efficient market hypothesis are introduced in order to point out a perspective for future research.


2009 ◽  
Vol 7 (3) ◽  
pp. 265 ◽  
Author(s):  
Pedro Gabriel Boainain ◽  
Pedro L. Valls Pereira

Starting from an adapted version of Osler and Chang (1995) methodology, this article empirically evaluates the profitability of investment strategies based on identification of the Head and Shoulders chart pattern in the Brazilian stock market. For that purpose, several investment strategies conditioned by the identification of the Head and Shoulders pattern (in its basic and inverted forms) by a computer algorithm in daily price series of 30 stocks from January 1994 to January 2009 were defined. Confidence intervals consistent with the null hypothesis that no strategies with positive returns can be based only on historical data were constructed using the Bootstrap sample inference technique in order to test the predictive power of each strategy. More specifically, the mean returns obtained by each strategy when applied to the stock's price series were compared to those obtained by the same strategies when applied to 1.000 artificial price series -- for each stock -- generated in a parametric manner, by an E-GARCH, and in a nonparametric one. Overall, our results show that it is possible to create strategies conditioned by the occurrence of Head and Shoulders, with positive returns, which indicates that these patterns can capture from stock historical prices some signals about their future price trend that makes possible to create profitable strategies. Nevertheless, the same conclusions are not valid for the pattern in its inverted form and when the effects of taxes and transaction costs are considered, depending on their magnitude, neither in its basic form.


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
C Quercioli ◽  
G A Carta ◽  
G Cevenini ◽  
G Messina ◽  
N Nante ◽  
...  

Abstract Background Careful scheduling of elective surgery Operating Rooms (ORs) is crucial for their efficient use, to avoid low/over utilization and staff overtime. Accurate estimation of procedures duration is essential to improve ORs scheduling. Therefore analysis of historical data about surgical times is fundamental to ORs management. We analyzed the effect, in a real setting, of an ORs scheduling model based on estimated optimum surgical time in improving ORs efficiency and decreasing the risk of overtime. Methods We studied all the 2014-2019 elective surgery sessions (3,758 sessions, 12,449 interventions) of a district general hospital in Siena's Province, Italy. The hospital had3 ORs open 5 days/week 08:00-14:00. Surgery specialties were general surgery, orthopedics, gynecology and urology. Based on a pilot study conducted in 2016, which estimated a 5 times greater risk of having an OR overtime for sessions with a surgical time (incision-suture)>200 minutes, from 2017 all the ORs were scheduled using a maximum surgical time of 200 minutes calculated summing the mean surgical times for intervention and surgeon (obtained from 2014-2016 data). We carried out multivariate logistic regression to calculate the probability of ORs overtime (of 15 and 30 minutes) for the periods 2014-2016 and 2017-2019adjusting for raw ORs utilization. Results The 2017-2019 risk of an OR overtime of 15 minutes decreased by 25% compared to the 2014-2016 period (OR = 0.75, 95%CI=0.618-0.902, p = 0.003); the risk of a OR overtime of 30 minutes decreased by 33% (OR = 0.67, 95%CI= 0.543-0.831, p < 0.001). Mean raw OR utilization increase from 62% to 66% (p < 0.001). Mean number of interventions per surgery sessions increased from 3.1 to 3.5 (p < 0.001). Conclusions This study has shown that an analysis of historical data and an estimate of the optimal surgical time per surgical session could be helpful to avoid both a low and excessive use of the ORs and therefore to increase the efficiency of the ORs. Key messages An accurate analysis of surgical procedures duration is crucial to optimize operating room utilization. A data-based approach can improve OR management efficiency without extra resources.


2021 ◽  
pp. 875697282199994
Author(s):  
Joseph F. Hair ◽  
Marko Sarstedt

Most project management research focuses almost exclusively on explanatory analyses. Evaluation of the explanatory power of statistical models is generally based on F-type statistics and the R 2 metric, followed by an assessment of the model parameters (e.g., beta coefficients) in terms of their significance, size, and direction. However, these measures are not indicative of a model’s predictive power, which is central for deriving managerial recommendations. We recommend that project management researchers routinely use additional metrics, such as the mean absolute error or the root mean square error, to accurately quantify their statistical models’ predictive power.


Author(s):  
Karsten Müller

AbstractBased on German business cycle forecast reports covering 10 German institutions for the period 1993–2017, the paper analyses the information content of German forecasters’ narratives for German business cycle forecasts. The paper applies textual analysis to convert qualitative text data into quantitative sentiment indices. First, a sentiment analysis utilizes dictionary methods and text regression methods, using recursive estimation. Next, the paper analyses the different characteristics of sentiments. In a third step, sentiment indices are used to test the efficiency of numerical forecasts. Using 12-month-ahead fixed horizon forecasts, fixed-effects panel regression results suggest some informational content of sentiment indices for growth and inflation forecasts. Finally, a forecasting exercise analyses the predictive power of sentiment indices for GDP growth and inflation. The results suggest weak evidence, at best, for in-sample and out-of-sample predictive power of the sentiment indices.


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