scholarly journals “Ombro-Cabeça-Ombro”: Testando a Lucratividade do Padrão Gráfico de Análise Técnica no Mercado de Ações Brasileiro

2009 ◽  
Vol 7 (3) ◽  
pp. 265 ◽  
Author(s):  
Pedro Gabriel Boainain ◽  
Pedro L. Valls Pereira
Keyword(s):  
Null Hypothesis ◽  
Predictive Power ◽  
Historical Data ◽  
Future Price ◽  
Bootstrap Sample ◽  
Investment Strategies ◽  
Basic Form ◽  
Price Trend ◽  
Price Series ◽  
The Mean

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.

Algorithmic Models of Investor Behavior

2021 ◽  
Vol 1 (1) ◽  
pp. 1-29
Author(s):  
Andrew Lo ◽  
Alexander Remerov
Keyword(s):  
Behavioral Finance ◽  
Historical Data ◽  
Asset Returns ◽  
Investor Behavior ◽  
Investment Strategies ◽  
Investment Performance ◽  
Evolutionary Forces ◽  
Asset Class ◽  
Functional Forms ◽  
The Mean

We propose a heuristic approach to modeling investor behavior by simulating combinations of simpler systematic investment strategies associated with well-known behavioral biases—in functional forms motivated by an extensive review of the behavioral finance literature—using parameters calibrated from historical data. We compute the investment performance of these heuristics individually and in pairwise combinations using both simulated and historical asset-class returns. The mean-reversion or momentum nature of a heuristic can often explain its effect on performance, depending on whether asset returns are consistent with such dynamics. These algorithms show that seemingly irrational investor behavior may, in fact, have been shaped by evolutionary forces and can be effective in certain environments and maladaptive in others.

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
Keyword(s):  
Financial Markets ◽  
Predictive Power ◽  
Historical Data ◽  
Efficient Market Hypothesis ◽  
Learning Systems ◽  
Sample Statistic ◽  
Out Of Sample ◽  
Categorical Classification ◽  
The Mean ◽  
Available Information

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.

scholarly journals Operating Rooms efficiency: leveraging data to improve management of elective surgery

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
C Quercioli ◽  
G A Carta ◽  
G Cevenini ◽  
G Messina ◽  
N Nante ◽  
...  
Keyword(s):  
Historical Data ◽  
Elective Surgery ◽  
District General Hospital ◽  
Operating Rooms ◽  
Accurate Estimation ◽  
Surgical Time ◽  
Accurate Analysis ◽  
Management Efficiency ◽  
Scheduling Model ◽  
The Mean

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.

scholarly journals Statistical Tests of Symbolic Dynamics

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 817
Author(s):  
Fernando López ◽  
Mariano Matilla-García ◽  
Jesús Mur ◽  
Manuel Ruiz Marín
Keyword(s):  
Monte Carlo ◽  
Symbolic Dynamics ◽  
Null Hypothesis ◽  
Statistical Tests ◽  
General Applicability ◽  
Monte Carlo Experiments ◽  
The Mean ◽  
Theoretical Application ◽  
New Statistics ◽  
General Method

A novel general method for constructing nonparametric hypotheses tests based on the field of symbolic analysis is introduced in this paper. Several existing tests based on symbolic entropy that have been used for testing central hypotheses in several branches of science (particularly in economics and statistics) are particular cases of this general approach. This family of symbolic tests uses few assumptions, which increases the general applicability of any symbolic-based test. Additionally, as a theoretical application of this method, we construct and put forward four new statistics to test for the null hypothesis of spatiotemporal independence. There are very few tests in the specialized literature in this regard. The new tests were evaluated with the mean of several Monte Carlo experiments. The results highlight the outstanding performance of the proposed test.

Explanation Plus Prediction—The Logical Focus of Project Management Research

2021 ◽  
pp. 875697282199994
Author(s):  
Joseph F. Hair ◽  
Marko Sarstedt
Keyword(s):  
Project Management ◽  
Statistical Models ◽  
Predictive Power ◽  
Mean Absolute Error ◽  
Explanatory Power ◽  
Absolute Error ◽  
Model Parameters ◽  
Mean Square ◽  
Management Research ◽  
The Mean

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.

scholarly journals Facial Profile Shape, Malocclusion and Palatal Morphology in Malay Obstructive Sleep Apnea Patients

2010 ◽  
Vol 80 (1) ◽  
pp. 37-42 ◽  
Author(s):  
S. M. Banabilh ◽  
A. R. Samsudin ◽  
A. H. Suzina ◽  
Sidek Dinsuhaimi
Keyword(s):  
Obstructive Sleep Apnea ◽  
Null Hypothesis ◽  
Control Group ◽  
Class Ii Malocclusion ◽  
Chi Square ◽  
Facial Profile ◽  
Obstructive Sleep ◽  
Significant Difference ◽  
Chi Square Test ◽  
The Mean

Abstract Objective: To test the null hypothesis that there is no difference in facial profile shape, malocclusion class, or palatal morphology in Malay adults with and without obstructive sleep apnea (OSA). Materials and Methods: Subjects were 120 adult Malays aged 18 to 65 years (mean ± standard deviation [SD], 33.2 ± 13.31) divided into two groups of 60. Both groups underwent clinical examination and limited channel polysomnography (PSG). The mean OSA and control values were subjected to t-test and the chi square test. Results: Physical examination showed that 61.7% of the OSA patients were obese, and 41.7% of those obese patients had severe OSA. The mean body mass index (BMI) was significantly greater for the OSA group (33.2 kg/m2 ± 6.5) than for the control group (22.7 kg/m2 ± 3.5; P < .001). The mean neck size and systolic blood pressure were greater for the OSA group (43.6 cm ± 6.02; 129.1 mm Hg ± 17.55) than for the control group (35.6 cm ± 3.52; 114.1 mm Hg ± 13.67; P < .001). Clinical examination showed that the most frequent findings among OSA groups when compared with the control group were convex profiles (71.7%), Class II malocclusion (51.7%), and V palatal shape (53.3%), respectively; the chi square test revealed a significant difference in terms of facial profile and malocclusion class (P < .05), but no significant difference in palatal shape was found. Conclusion: The null hypothesis is rejected. A convex facial profile and Class II malocclusion were significantly more common in the OSA group. The V palatal shape was a frequent finding in the OSA group.

scholarly journals USING SUBSTUTION DRILL TECHNIQUE TO IMPROVE STUDENTS’ PRONUNCIATION ABILITY

2014 ◽  
Vol 3 (2) ◽  
pp. 178
Author(s):  
Maharida Maharida
Keyword(s):  
Experimental Method ◽  
Null Hypothesis ◽  
Alternative Hypothesis ◽  
Good Classification ◽  
Tenth Grade ◽  
Post Test ◽  
Back Vowel ◽  
Independent Variable ◽  
The Mean ◽  
Teaching Pronunciation

This research aimed to find out the improvement of the students’ pronunciation ability by using Substitution Drill that focused on English Consonants which consisted of dental and palato alveolar consonants and English Vowel which consisted mid-front,mid-central and mid-back vowel. The researcher applied Pre-Experimental method with one group pretest-posttest design and collected the data by giving pre-test and post-test. The sample of the research was class X IPA of SMA Negeri 1 Galesong Selatan which consisted of 33 students. The sample was taken by using the purposive technique. The research variables were teaching pronunciation by using Substitution Drill as an independent variable and dependent variable were English Consonants and English Vowel. The result of the research showed that the tenth-grade students of SMA Negeri 1 Galesong Selatan had fair score in the pre-test. After treatment, their pronunciation ability significant improved. The result of the research was the mean score obtained by the students through pre-test was 5.77 which was classified as fair classification and the mean score of the students on the post-test was 7.32 which was classified as good classification and the value of t-test was greater than t-table (16.48 > 2.037). It indicated that the alternative hypothesis (H1) was accepted and the null hypothesis (H0) was rejected. It was concluded that the use of Substitution Drill was effective to improve the students’ pronunciation ability.Keywords: improvement, pronunciation, substitution drill, dental, palato alveolar

scholarly journals Applying shadowing technique to improve students' listening achievement

2020 ◽  
Vol 5 (1) ◽  
pp. 47-56
Author(s):  
Fitri Maini ◽  
Rachmanita
Keyword(s):  
Null Hypothesis ◽  
Sampling Method ◽  
Critical Value ◽  
T Test ◽  
Control Group ◽  
Tenth Graders ◽  
Tenth Grade ◽  
Quasi Experimental ◽  
The Mean ◽  
Experimental Group

This study tried find the students’ improvement in listening achievement after having taught by using the shadowing technique. The method used was a quasi-experimental that involved two groups, namely the control group and experimental group. The population of this study was all the tenth graders of SMA Negeri 3 Unggulan Kayuagung with a total number of 198 tenth graders. Purposive sampling method was applied to select the sample involved 72 tenth graders. In collecting the data, try out the test was used to get the desirable questions that would be used in the pretest and posttest to both groups in the control and experimental group. To verify the hypothesis, the normality and homogeneity of the data were firstly analyzed before being continued to be analyzed by using a t-test. Based on the result of data analysis in an independent sample t-test, there were some findings found. First, the mean score of a posttest (75.56) in the experimental group was higher than the pretest (69.03) in the control group. Secondly, the value of tobtained was 2.77 at the significant level of p<0.05 in two-tailed testing with df = 70, the critical value of ttable was 1.99. Since the value of tobtained was higher than ttable, the null hypothesis (Ho) was rejected and the research hypothesis was accepted. In conclusion, it showed that the shadowing technique could improve the tenth-grade students’ listening achievement at SMA Negeri 3 Unggulan Kayuagung.

scholarly journals Mapping similarities in temporal parking occupancy behavior based on city-wide parking meter data

2018 ◽  
Vol 1 ◽  
pp. 1-5
Author(s):  
Fabian Bock ◽  
Karen Xia ◽  
Monika Sester
Keyword(s):  
Similarity Measure ◽  
Historical Data ◽  
Parking Space ◽  
Number Of Clusters ◽  
Occupancy Patterns ◽  
Silhouette Index ◽  
The Mean ◽  
Occupancy Behavior ◽  
Maximum Occupancy ◽  
Repetitive Pattern

The search for a parking space is a severe and stressful problem for drivers in many cities. The provision of maps with parking space occupancy information assists drivers in avoiding the most crowded roads at certain times. Since parking occupancy reveals a repetitive pattern per day and per week, typical parking occupancy patterns can be extracted from historical data.<br> In this paper, we analyze city-wide parking meter data from Hannover, Germany, for a full year. We describe an approach of clustering these parking meters to reduce the complexity of this parking occupancy information and to reveal areas with similar parking behavior. The parking occupancy at every parking meter is derived from a timestamp of ticket payment and the validity period of the parking tickets. The similarity of the parking meters is computed as the mean-squared deviation of the average daily patterns in parking occupancy at the parking meters. Based on this similarity measure, a hierarchical clustering is applied. The number of clusters is determined with the Davies-Bouldin Index and the Silhouette Index.<br> Results show that, after extensive data cleansing, the clustering leads to three clusters representing typical parking occupancy day patterns. Those clusters differ mainly in the hour of the maximum occupancy. In addition, the lo-cations of parking meter clusters, computed only based on temporal similarity, also show clear spatial distinctions from other clusters.

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