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Articles 61 - 90 of 153
Full-Text Articles in Econometrics
Impact Of Covid-19 Pandemic On The Nigeria Stock Market: A Sectoral Stock Prices Analysis, Peter A. Adekunle, Yakubu A. Bello, Udochukwu G. Nwachukwu
Impact Of Covid-19 Pandemic On The Nigeria Stock Market: A Sectoral Stock Prices Analysis, Peter A. Adekunle, Yakubu A. Bello, Udochukwu G. Nwachukwu
CBN Journal of Applied Statistics (JAS)
This study examines the impact of the COVID-19 pandemic on sectoral stock prices in Nigeria stock market using daily data covering from February 28, 2020 to June 26, 2020. Applying the autoregressive distributed lag (ARDL) bounds test, the study finds that COVID-19 pandemic had adverse impact on the stock market indices in the short run. Furthermore, the study documents negative response of sectoral stock prices to the pandemic while the stock prices of the banking sub-sector are the worst hit. Compared to the consumer goods, and industrial subsector indices, the speed of adjustment to long run equilibrium is faster for …
Indian Statistical Institute Placement Brochure 2021-2022, Indian Statistical Institute
Indian Statistical Institute Placement Brochure 2021-2022, Indian Statistical Institute
Poster and Presentations
The Placement Cell at the ISI Delhi Centre presents a comprehensive information brochure detailing the placement opportunities for outgoing students during 2021–2022. It outlines the placement process for M.Stat and MS-QE students at ISI Delhi. Respective companies should inform the Placement Committee of the final selected candidates, preferably within a day or two.
Liquidity Commonality With Factor Models, Ernesto Garcia Iii
Liquidity Commonality With Factor Models, Ernesto Garcia Iii
Dissertations, Theses, and Capstone Projects
Market microstructure research has recently devoted attention to a phenomenon called commonality in liquidity. In this dissertation, I will analyze commonality in liquidity using a novel factor model approach and a generalized definition of commonality in liquidity. This analysis will show that commonality in liquidity is rarely a marketwide phenomenon and is mostly restricted to stocks with a large market capitalization. Additionally, commonality in liquidity is a very recent phenomenon whose appearance coincides with a rise in passive investing after the Dotcom Bubble burst and, more so, after the 2008 Financial Crisis. I will present evidence that suggests commonality in …
Machine Learning For Stock Prediction Based On Fundamental Analysis, Yuxuan Huang, Luiz Fernando Capretz, Danny Ho
Machine Learning For Stock Prediction Based On Fundamental Analysis, Yuxuan Huang, Luiz Fernando Capretz, Danny Ho
Electrical and Computer Engineering Publications
Application of machine learning for stock prediction is attracting a lot of attention in recent years. A large amount of research has been conducted in this area and multiple existing results have shown that machine learning methods could be successfully used toward stock predicting using stocks’ historical data. Most of these existing approaches have focused on short term prediction using stocks’ historical price and technical indicators. In this paper, we prepared 22 years’ worth of stock quarterly financial data and investigated three machine learning algorithms: Feed-forward Neural Network (FNN), Random Forest (RF) and Adaptive Neural Fuzzy Inference System (ANFIS) for …
An Alternative Class Of Ratio-Regression-Type Estimator Under Two-Phase Sampling Scheme, Muhammad Isah, Zakari Yahaya, Audu Ahmed
An Alternative Class Of Ratio-Regression-Type Estimator Under Two-Phase Sampling Scheme, Muhammad Isah, Zakari Yahaya, Audu Ahmed
CBN Journal of Applied Statistics (JAS)
In this study, a new exponential ratio-regression estimator is developed using an auxiliary variable for estimating the finite population mean under a two-phase sampling system. The Bias and Mean Square Error (MSE) of the proposed estimator are derived and compared with some of the estimators in extant literature. Thus, the conditions under which the proposed estimator is better than some existing estimators are provided. Empirically, using four real datasets and simulation study, the proposed estimator performs better than the classical ratio, classical regression, exponential ratio, and exponential regression cum ratio estimator when compared using the criteria of bias, mean square …
Glivenko-Cantelli Theorems For Integrated Functionals Of Stochastic Processes, Jia Li, Congshan Zhang, Yunxiao Liu
Glivenko-Cantelli Theorems For Integrated Functionals Of Stochastic Processes, Jia Li, Congshan Zhang, Yunxiao Liu
Research Collection School Of Economics
We prove a Glivenko-Cantelli theorem for integrated functionals of latent continuous-time stochastic processes. Based on a bracketing condition via random brackets, the theorem establishes the uniform convergence of a sequence of empirical occupation measures towards the occupation measure induced by underlying processes over large classes of test functions, including indicator functions, bounded monotone functions, Lipschitz-in-parameter functions, and Hölder classes as special cases. The general Glivenko-Cantelli theorem is then applied in more concrete high-frequency statistical settings to establish uniform convergence results for general integrated functionals of the volatility of efficient price and local moments of microstructure noise.
Understanding And Contextualizing Foraging Among Recreational Opportunities In The North Central United States, Iris I. Mcfarlin
Understanding And Contextualizing Foraging Among Recreational Opportunities In The North Central United States, Iris I. Mcfarlin
School of Natural Resources: Dissertations, Theses, and Student Research
Over the past few decades, there has been a resurgence in popularity and recognition of foraging for wild products and foods. Despite the cultural importance and ubiquity of foraging, there have been relatively few scientific investigations (as compared to other consumptive outdoor activities such as hunting and fishing) of the social factors influencing foraging behavior, landscape preferences, and the types of materials foraged in the United States. As such, there is a fundamental need to understand more about the practice and about those who participate. We conducted two surveys to gather information on foragers’ motivations and demographic characteristics and to …
The Contribution Of Mining Sector To Sustainable Development In Saudi Arabia, Mourad Zmami, Ousama Ben-Salha, Sultan O. Almarshad, Houyem Chekki
The Contribution Of Mining Sector To Sustainable Development In Saudi Arabia, Mourad Zmami, Ousama Ben-Salha, Sultan O. Almarshad, Houyem Chekki
Journal of Sustainable Mining
The mining sector development is among the priorities of the Saudi Vision 2030. There is currently a lot of interest in the role of the mining sector in Saudi Arabia. This research contributes to this debate by empirically assessing the effects of mining on sustainable development in Saudi Arabia during the period 1980-2018. Unlike many previous studies, the three sustainable development dimensions, namely economic, social, and environmental, are jointly considered. The cointegration analysis, based on the ARDL, Gregory-Hansen, and combined cointegration tests, confirms the existence of long-run relationships between mining and all sustainable development dimensions. Furthermore, the findings lend substantial …
Determining The Number Of Communities In Degree-Corrected Stochastic Block Models, Shujie Ma, Liangjun Su, Yichong Zhang
Determining The Number Of Communities In Degree-Corrected Stochastic Block Models, Shujie Ma, Liangjun Su, Yichong Zhang
Research Collection School Of Economics
We propose to estimate the number of communities in degree-corrected stochastic block models based on a pseudo likelihood ratio. For estimation, we consider a spectral clustering together with binary segmentation method. This approach guarantees an upper bound for the pseudo likelihood ratio statistic when the model is over-fitted. We also derive its limiting distribution when the model is under-fitted. Based on these properties, we establish the consistency of our estimator for the true number of communities. Developing these theoretical properties require a mild condition on the average degree: growing at a rate faster than log(n), where n is the number …
Commodity Futures Returns And Policy Uncertainty, Deepa Bannigidadmath, Paresh Kumar Narayan
Commodity Futures Returns And Policy Uncertainty, Deepa Bannigidadmath, Paresh Kumar Narayan
Research outputs 2014 to 2021
© 2020 Elsevier Inc. This paper investigates whether economic policy uncertainty is predictable using three sets of commodity futures market variables, namely the equal-weighted average of futures excess returns, the excess returns on a portfolio of going long in backwardated commodities, and the excess returns on a portfolio of going short in contango commodities as predictors. We find significant evidence of both in-sample and out-of-sample predictability. Combination forecasts also reveal strong evidence of predictability. Our findings remain unchanged following several robustness tests.
The Determinations Of Public Trust In The Government Of Egypt: An Empirical Study, Mohamed Elimam
The Determinations Of Public Trust In The Government Of Egypt: An Empirical Study, Mohamed Elimam
Theses and Dissertations
Trust is a concept that is usually studied in the context of social interactions. At varying levels, we trust our families and friends, we trust strangers who share some traits with us and even trust institutions like banks with our savings and to handle our personal finances. By expansion, political trust, or the public's trust in government as a whole and as individual agencies. Trust in government forms a basis for the legitimacy. High levels of political trust facilitates the implementation of policies with more willing compliance from the public. This is more evident in situations like global and national …
Neither “Post-War” Nor Post-Pregnancy Paranoia: How America’S War On Drugs Continues To Perpetuate Disparate Incarceration Outcomes For Pregnant, Substance-Involved Offenders, Becca S. Zimmerman
Neither “Post-War” Nor Post-Pregnancy Paranoia: How America’S War On Drugs Continues To Perpetuate Disparate Incarceration Outcomes For Pregnant, Substance-Involved Offenders, Becca S. Zimmerman
Pitzer Senior Theses
This thesis investigates the unique interactions between pregnancy, substance involvement, and race as they relate to the War on Drugs and the hyper-incarceration of women. Using ordinary least square regression analyses and data from the Bureau of Justice Statistics’ 2016 Survey of Prison Inmates, I examine if (and how) pregnancy status, drug use, race, and their interactions influence two length of incarceration outcomes: sentence length and amount of time spent in jail between arrest and imprisonment. The results collectively indicate that pregnancy decreases length of incarceration outcomes for those offenders who are not substance-involved but not evenhandedly -- benefitting white …
Feature Investigation For Stock Returns Prediction Using Xgboost And Deep Learning Sentiment Classification, Seungho (Samuel) Lee
Feature Investigation For Stock Returns Prediction Using Xgboost And Deep Learning Sentiment Classification, Seungho (Samuel) Lee
CMC Senior Theses
This paper attempts to quantify predictive power of social media sentiment and financial data in stock prediction by utilizing a comprehensive set of stock-related fundamental and technical variables and social media sentiments. For conducting sentiment analysis, this study employs a pretrained finBERT model that provides three different sentiment classifications and respective softmax scores. Hence, the significance of these variables is evaluated with XGBoost regression and Shapley Additive exPlanations (SHAP) frameworks. Through investigating feature importance, this study finds that statistical properties of sentiment variables provide a stronger predictive power than a weighted sentiment score and that it is possible to quantify …
An Evaluation Of Knot Placement Strategies For Spline Regression, William Klein
An Evaluation Of Knot Placement Strategies For Spline Regression, William Klein
CMC Senior Theses
Regression splines have an established value for producing quality fit at a relatively low-degree polynomial. This paper explores the implications of adopting new methods for knot selection in tandem with established methodology from the current literature. Structural features of generated datasets, as well as residuals collected from sequential iterative models are used to augment the equidistant knot selection process. From analyzing a simulated dataset and an application onto the Racial Animus dataset, I find that a B-spline basis paired with equally-spaced knots remains the best choice when data are evenly distributed, even when structural features of a dataset are known …
Activation Of Trpa1 Nociceptor Promotes Systemic Adult Mammalian Skin Regeneration, Jenny J. Wei, Hali S. Kim, Casey A. Spencer, Donna Brennan-Crispi, Ying Zheng, Nicolette M. Johnson, Misha Rosenbach, Christopher Miller, Denis H. Y. Leung, George Cotsarelis, Thomas H. Leung
Activation Of Trpa1 Nociceptor Promotes Systemic Adult Mammalian Skin Regeneration, Jenny J. Wei, Hali S. Kim, Casey A. Spencer, Donna Brennan-Crispi, Ying Zheng, Nicolette M. Johnson, Misha Rosenbach, Christopher Miller, Denis H. Y. Leung, George Cotsarelis, Thomas H. Leung
Research Collection School Of Economics
Adult mammalian wounds, with rare exception, heal with fibrotic scars that severely disrupt tissue architecture and function. Regenerative medicine seeks methods to avoid scar formation and restore the original tissue structures. We show in three adult mouse models that pharmacologic activation of the nociceptor TRPA1 on cutaneous sensory neurons reduces scar formation and can also promote tissue regeneration. Local activation of TRPA1 induces tissue regeneration on distant untreated areas of injury, demonstrating a systemic effect. Activated TRPA1 stimulates local production of interleukin-23 (IL-23) by dermal dendritic cells, leading to activation of circulating dermal IL-17–producing γδ T cells. Genetic ablation of …
Eco 230 / Mgt 230 Introduction To Economic And Managerial Statistics, George Vachadze
Eco 230 / Mgt 230 Introduction To Economic And Managerial Statistics, George Vachadze
Open Educational Resources
Development and application of modern statistical methods, including such elements of descriptive statistics and statistical inference as correlation and regression analysis, probability theory, sampling procedures, normal distribution and binomial distribution, estimation, and testing of hypotheses.
Analyzing Competitive Balance In Professional Sport, Kevin Alwell
Analyzing Competitive Balance In Professional Sport, Kevin Alwell
Honors Scholar Theses
In this paper we review several measures to statistically analyze competitive balance and report which leagues have a wider variance of performance amongst its competitors. Each league seeks to maintain high levels of parity, making matches and overall season more unpredictable and appealing to the general audience. Here we quantify competitive advantage across major sports leagues in numbers using several statistical methods in order for leagues to optimize their revenue.
Three Essays On Health Economics And Policy Evaluation, Shishir Shakya
Three Essays On Health Economics And Policy Evaluation, Shishir Shakya
Graduate Theses, Dissertations, and Problem Reports (ETD)
This dissertation consists of three essays on the U.S. Health care policy. Each paragraph below refers to the three abstracts for the three chapters in this dissertation, respectively. I provide quantitative evidence on how much Prescription Drug Monitoring Programs (PDMPs) affects the retail opioid prescribing behaviors. Using the American Community Survey (ACS), I retrieve county-level high dimensional panel data set from 2010 to 2017. I employ three separate identification strategies: difference-in-difference, double selection post-LASSO, and spatial difference-in-difference. I compare how the retail opioid prescribing behaviors of counties, that are mandatory for prescribers to check the PDMP before prescribing controlled substances …
The Long-Run Effects Of Tropical Cyclones On Infant Mortality, Isabel Miranda
The Long-Run Effects Of Tropical Cyclones On Infant Mortality, Isabel Miranda
Master's Theses
In the United States alone, each tropical cyclone causes an average of $14.6 billion worth of damages. In addition to the destruction of physical infrastructure, natural disasters also negatively impact human capital formation. These losses are often more difficult to observe, and therefore, are over looked when quantifying the true costs of natural disasters. One particular effect is an increase in infant mortality rates, an important indicator of a country’s general socioeconomic level. This paper utilizes a model created by Anttila-Hughes and Hsiang, that takes advantage of annual variation in tropical cyclones using annual spatial average maximum wind speeds and …
A Systematic Assessment Of Socio-Economic Impacts Of Prolonged Episodic Volcano Crises, Justin Peers
A Systematic Assessment Of Socio-Economic Impacts Of Prolonged Episodic Volcano Crises, Justin Peers
Electronic Theses and Dissertations
Uncertainty surrounding volcanic activity can lead to socio-economic crises with or without an eruption as demonstrated by the post-1978 response to unrest of Long Valley Caldera (LVC), CA. Extensive research in physical sciences provides a foundation on which to assess direct impacts of hazards, but fewer resources have been dedicated towards understanding human responses to volcanic risk. To evaluate natural hazard risk issues at LVC, a multi-hazard, mail-based, household survey was conducted to compare perceptions of volcanic, seismic, and wildfire hazards. Impacts of volcanic activity on housing prices and businesses were examined at the county-level for three volcanoes with a …
Estimation Of Multivariate Asset Models With Jumps, Angela Loregian, Laura Ballotta, Gianluca Gianluca Fusai, Marcos Fabricio Perez
Estimation Of Multivariate Asset Models With Jumps, Angela Loregian, Laura Ballotta, Gianluca Gianluca Fusai, Marcos Fabricio Perez
Business Faculty Publications
We propose a consistent and computationally efficient two-step methodology for the estimation of multidimensional non-Gaussian asset models built using Levy processes. The proposed framework allows for dependence between assets and different tail behaviors and jump structures for each asset. Our procedure can be applied to portfolios with a large number of assets as it is immune to estimation dimensionality problems. Simulations show good finite sample properties and significant efficiency gains. This method is especially relevant for risk management purposes such as, for example, the computation of portfolio Value at Risk and intra-horizon Value at Risk, as we show in detail …
Step Away From Stepwise, Gary N. Smith
Step Away From Stepwise, Gary N. Smith
Pomona Economics
Stepwise regression is a popular data-mining tool that uses statistical significance to select the explanatory variables to be used in a multiple-regression model. A fundamental problem with stepwise regression is that some real explanatory variables that have causal effects on the dependent variable may happen to not be statistically significant, while nuisance variables may be coincidentally significant. As a result, the model may fit the data well in-sample, but do poorly out-of-sample. Many Big-Data researchers believe that, the larger the number of possible explanatory variables, the more useful is stepwise regression for selecting explanatory variables. The reality is that stepwise …
The Paradox Of Big Data, Gary N. Smith
The Paradox Of Big Data, Gary N. Smith
Pomona Economics
Data-mining is often used to discover patterns in Big Data. It is tempting believe that because an unearthed pattern is unusual it must be meaningful, but patterns are inevitable in Big Data and usually meaningless. The paradox of Big Data is that data mining is most seductive when there are a large number of variables, but a large number of variables exacerbates the perils of data mining.
On Cluster Robust Models, José Bayoán Santiago Calderón
On Cluster Robust Models, José Bayoán Santiago Calderón
CGU Theses & Dissertations
Cluster robust models are a kind of statistical models that attempt to estimate parameters considering potential heterogeneity in treatment effects. Absent heterogeneity in treatment effects, the partial and average treatment effect are the same. When heterogeneity in treatment effects occurs, the average treatment effect is a function of the various partial treatment effects and the composition of the population of interest. The first chapter explores the performance of common estimators as a function of the presence of heterogeneity in treatment effects and other characteristics that may influence their performance for estimating average treatment effects. The second chapter examines various approaches …
Canadian Hockey Leagues Game-To-Game Performance, Nick R. Riccardi
Canadian Hockey Leagues Game-To-Game Performance, Nick R. Riccardi
Sport Management - All Scholarship
This study examines game-to-game performance of players across the three Canadian Hockey Leagues (Western Hockey League, Ontario Hockey League, and Quebec Major Junior Hockey League) for the 2017-2018 season. It tests the importance of factors such as rest, travel, weather conditions, and more. Data for this study were collected from each of the three CHL websites and from www.weatherunderground.com. The null hypotheses of different factors affecting performance were tested through regression models using Ordinary Least Squares. The dependent variables, used across different specifications, were on-ice performance variables such as points, goals, and penalty minutes on a per-game basis.
A Snowball's Chance: Debt Snowball Vs. Debt Avalanche, Evan Mcallister
A Snowball's Chance: Debt Snowball Vs. Debt Avalanche, Evan Mcallister
Senior Honors Projects, 2010-2019
Traditional mathematical analysis states that the most efficient way to pay off interest-bearing consumer debt is to pay the individual debts in order from largest to smallest interest rate. In doing this, the debtor will eliminate the largest sources of interest first, thus shortening the overall time-to-pay. This method is known as the “Debt Avalanche.” The “Debt Snowball” method, popularized in large part by investor-author David Ramsey, recommends that consumers pay debts in order from smallest to largest, regardless of interest rate. In this paper, I conduct an empirical analysis of the Federal Reserve’s Survey of Consumer Finance (SCF), calculating …
The Principal Problem With Principal Components Regression, Heidi Margaret Artigue, Gary Smith
The Principal Problem With Principal Components Regression, Heidi Margaret Artigue, Gary Smith
Pomona Faculty Publications and Research
Principal components regression (PCR) reduces a large number of explanatory variables down to a small number of principal components. PCR is thought to be more useful, the more numerous the potential explanatory variables. The reality is that a large number of candidate explanatory variables does not make PCR more valuable; instead, it magnifies the failings of PCR.
Preferences (Partial Pre-Orders) On Complex Numbers -- In View Of Possible Use In Quantum Econometrics, Songsak Sriboonchitta, Vladik Kreinovich, Olga Kosheleva
Preferences (Partial Pre-Orders) On Complex Numbers -- In View Of Possible Use In Quantum Econometrics, Songsak Sriboonchitta, Vladik Kreinovich, Olga Kosheleva
Departmental Technical Reports (CS)
In economic application, it is desirable to find an optimal solution -- i.e., a solution which is preferable to any other possible solution. Traditionally, the state of an economic system has been described by real-valued quantities such as profit, unemployment level, etc. For such quantities, preferences correspond to natural order between real numbers: all things being equal, the more profit the better, and the smaller unemployment, the better. Lately, it turned out that to adequately describe economic phenomena, it is often convenient to use complex numbers. From this viewpoint, a natural question is: what are possible orders on complex numbers? …
Nonlinearities In The Real Exchange Rates: New Evidence From Developed And Developing Countries, Yamin S. Ahmad, Ming Chien Lo, Olena M. Staveley-O'Carroll
Nonlinearities In The Real Exchange Rates: New Evidence From Developed And Developing Countries, Yamin S. Ahmad, Ming Chien Lo, Olena M. Staveley-O'Carroll
Economics Department Working Papers
This paper investigates nonlinearities in the dynamics of real exchange rates. We use Monte Carlo simulations to establish the size properties of the Teräsvirta-Anderson (1992) and the Teräsvirta (1994) test, when the dynamics of the real exchange rate is influenced by an exogenous process. In addition, we examine the modification proposed by Ahmad, Lo and Mykhaylova (2013; Journal of International Economics) to show that the modified nonlinearity test performs much better than the original in both Monte Carlo exercises and in the actual data on 1431 bilateral real exchange rate series. Finally, we investigate the dynamics of the real exchange …
The Impact Of Wti And The Ordering Of Crude Tankers On Tanker Spot Freight Rate, Jiajia Xu
The Impact Of Wti And The Ordering Of Crude Tankers On Tanker Spot Freight Rate, Jiajia Xu
World Maritime University Dissertations
No abstract provided.