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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Dpp: Deep Predictor For Price Movement From Candlestick Charts, Chih-Chieh Hung, Ying-Ju (Tessa) Chen
Dpp: Deep Predictor For Price Movement From Candlestick Charts, Chih-Chieh Hung, Ying-Ju (Tessa) Chen
Mathematics Faculty Publications
Forecasting the stock market prices is complicated and challenging since the price movement is affected by many factors such as releasing market news about earnings and profits, international and domestic economic situation, political events, monetary policy, major abrupt affairs, etc. In this work, a novel framework: deep predictor for price movement (DPP) using candlestick charts in the stock historical data is proposed. This framework comprises three steps: 1. decomposing a given candlestick chart into sub-charts; 2. using CNN-autoencoder to acquire the best representation of sub-charts; 3. applying RNN to predict the price movements from a collection of sub-chart representations. An …
Tennis Anyone? Teaching Experimental Design By Designing And Executing A Tennis Ball Experiment, Laura Pyott
Tennis Anyone? Teaching Experimental Design By Designing And Executing A Tennis Ball Experiment, Laura Pyott
Mathematics Faculty Publications
Understanding the abstract principles of statistical experimental design can challenge undergraduate students, especially when learned in a lecture setting. This article presents a concrete and easily replicated example of experimental design principles in action through a hands-on learning activity for students enrolled in an experimental design course. The activity, conducted during five 50-min classes, requires the students to work as a team to design and execute a simple and safe factorial experiment and collect and analyze the data. During three in-class design meetings, the students design and plan all aspects of the experiment, including choosing the response variable and factors, …
Visualizing Bivariate Data: What’S Your Point Of View?, Mamunur Rashid, Jyotirmoy Sarkar
Visualizing Bivariate Data: What’S Your Point Of View?, Mamunur Rashid, Jyotirmoy Sarkar
Mathematics Faculty Publications
A scatter plot shows the relationship between two continuous variables x and y. If the relationship is linear or if the two variables have a bivariate normal distribution, then the least squares regression lines of y on x and x on y can predict one variable as a linear function of the other. These two regression lines suffice to identify the mean vector, the coefficient of determination, Pearson’s product moment correlation coefficient, and the ratio of the standard deviations (SD). So does a coverage ellipse! Additionally, we answer: In which direction must the points be projected to maximize (or minimize) …
Depicting Bivariate Relationship With A Gaussian Ellipse, Mamunur Rashid, Jyotirmoy Sarkar
Depicting Bivariate Relationship With A Gaussian Ellipse, Mamunur Rashid, Jyotirmoy Sarkar
Mathematics Faculty Publications
For data on two continuous variables, how should one depict the summary statistics (means, SDs, correlation coefficient, coefficient of determination, regression lines) so that their values can be read off easily from the depiction and potential outliers can be flagged also? We propose the Gaussian covariance ellipse as an answer that will benefit all users of statistics.