Search results for: price to earnings growth

Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

Procedia PDF Downloads 57

Authors: Ayse Cobanoglu

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Working memory can be defined as a workspace that holds and regulates active information in mind. This study investigates individual changes in children's working memory from kindergarten to first grade. The main purpose of the study is whether parental discipline methods and child impulsive/overactive behaviors affect children's working memory initial status and growth rate, controlling for gender, minority status, and socioeconomic status (SES). A linear growth curve model with the first four waves of the Early Childhood Longitudinal Study-Kindergarten Cohort of 2011 (ECLS-K:2011) is performed to analyze the individual growth of children's working memory longitudinally (N=3915). Results revealed that there is a significant variation among students' initial status in the kindergarten fall semester as well as the growth rate during the first two years of schooling. While minority status, SES, and children's overactive/impulsive behaviors influenced children's initial status, only SES and minority status were significantly associated with the growth rate of working memory. For parental discipline methods, such as giving a warning and ignoring the child's negative behavior, are also negatively associated with initial working memory scores. Following that, students' working memory growth rate is examined, and students with lower SES as well as minorities showed a faster growth pattern during the first two years of schooling. However, the findings of parental disciplinary methods on working memory growth rates were mixed. It can be concluded that schooling helps low-SES minority students to develop their working memory.

Keywords: growth curve modeling, impulsive/overactive behaviors, parenting, working memory

Procedia PDF Downloads 107

Authors: Pınar Yardımcı

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This paper tries to answer to the questions whether or not trade openness cause economic growth and trade policy changes is good for Turkey as a developing country in global economy before and after 1980. We employ Johansen cointegration and Granger causality tests with error correction modelling based on vector autoregressive. Using WDI data from the pre-1980 and the post-1980, we find that trade openness and economic growth are cointegrated in the second term only. Also the results suggest a lack of long-run causality between our two variables. These findings may imply that trade policy of Turkey should concentrate more on extra complementary economic reforms.

Keywords: globalization, trade policy, economic growth, openness, cointegration, Turkey

Procedia PDF Downloads 329

Authors: Emma Serwaa Obobisaa, Haibo Chen

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International trade and outward foreign direct investment are important factors which are generally recognized in the economic growth and development. Though several scholars have struggled to reveal the influence of trade and outward foreign direct investment (FDI) on economic growth, most studies utilized common econometric models such as vector autoregression and aggregated the variables, which for the most part prompts, however, contradictory and mixed results. Thus, there is an exigent need for the precise study of the trade and FDI effect of economic growth while applying strong econometric models and disaggregating the variables into its separate individual variables to explicate their respective effects on economic growth. This will guarantee the provision of policies and strategies that are geared towards individual variables to ensure sustainable development and growth. This study, therefore, seeks to examine the causal effect of China-Africa trade and Outward Foreign Direct Investment on the economic growth of Africa using a robust and recent econometric approach such as system dynamics model. Our study impanels and tests an ensemble of a group of vital variables predominant in recent studies on trade-FDI-economic growth causality: Foreign direct ınvestment, international trade and economic growth. Our results showed that the system dynamics method provides accurate statistical inference regarding the direction of the causality among the variables than the conventional method such as OLS and Granger Causality predominantly used in the literature as it is more robust and provides accurate, critical values.

Keywords: economic growth, outward foreign direct investment, system dynamics model, international trade

Procedia PDF Downloads 87

Authors: Sofia Stoica

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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

Procedia PDF Downloads 144

Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

Procedia PDF Downloads 58

Authors: Siphat Lim

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This study used Autoregressive Distributed Lag (ARDL) approach to cointegration. In the long-run the general price level and exchange rate have a positively significant effect on domestic output. The estimated result further revealed that fiscal stimulus help stimulate domestic output in the long-run, but not in the short-run, while monetary expansion help to stimulate output in both short-run and long-run. The result is complied with the theory which is the macroeconomic policies, fiscal and monetary policy; help to stimulate domestic output in the long-run. The estimated result of the Vector Error Correction Model (VECM) has indicated more clearly that the consumer price index has a positive effect on output with highly statistically significant. Increasing in the general price level would increase the competitiveness among producers than increase in the output. However, the exchange rate also has a positive effect and highly significant on the gross domestic product. The exchange rate depreciation might increase export since the purchasing power of foreigners has increased. More importantly, fiscal stimulus would help stimulate the domestic output in the long-run since the coefficient of government expenditure is positive. In addition, monetary expansion would also help stimulate the output and the result is highly significant. Thus, fiscal stimulus and monetary expansionary would help stimulate the domestic output in the long-run in Cambodia.

Keywords: fiscal policy, monetary policy, ARDL, VECM

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Authors: Lin-Han Chiang Hsieh, Hsiao-Yi Lin

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This study aims to determine the impact of the disclosure of flood potential map on housing prices. The disclosure is supposed to mitigate the market failure by reducing information asymmetry. On the other hand, opponents argue that the official disclosure of simulated results will only create unnecessary disturbances on the housing market. This study identifies the impact of the disclosure of the flood potential map by comparing the hedonic price of flood potential before and after the disclosure. The flood potential map used in this study is published by Taipei municipal government in 2015, which is a result of a comprehensive simulation based on geographical, hydrological, and meteorological factors. The residential property sales data of 2013 to 2016 is used in this study, which is collected from the actual sales price registration system by the Department of Land Administration (DLA). The result shows that the impact of flood potential on residential real estate market is statistically significant both before and after the disclosure. But the trend is clearer after the disclosure, suggesting that the disclosure does have an impact on the market. Also, the result shows that the impact of flood potential differs by the severity and frequency of precipitation. The negative impact for a relatively mild, high frequency flood potential is stronger than that for a heavy, low possibility flood potential. The result indicates that home buyers are of more concern to the frequency, than the intensity of flood. Another contribution of this study is in the methodological perspective. The classic hedonic price analysis with OLS regression suffers from two spatial problems: the endogeneity problem caused by omitted spatial-related variables, and the heterogeneity concern to the presumption that regression coefficients are spatially constant. These two problems are seldom considered in a single model. This study tries to deal with the endogeneity and heterogeneity problem together by combining the spatial fixed-effect model and geographically weighted regression (GWR). A series of literature indicates that the hedonic price of certain environmental assets varies spatially by applying GWR. Since the endogeneity problem is usually not considered in typical GWR models, it is arguable that the omitted spatial-related variables might bias the result of GWR models. By combing the spatial fixed-effect model and GWR, this study concludes that the effect of flood potential map is highly sensitive by location, even after controlling for the spatial autocorrelation at the same time. The main policy application of this result is that it is improper to determine the potential benefit of flood prevention policy by simply multiplying the hedonic price of flood risk by the number of houses. The effect of flood prevention might vary dramatically by location.

Keywords: flood potential, hedonic price analysis, endogeneity, heterogeneity, geographically-weighted regression

Procedia PDF Downloads 268

Authors: Katie Kilgour, Brendan Turner, Carly Catella, Michael Daniele, Stefano Menegatti

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In vivo, the extracellular matrix (ECM) provides biochemical and mechanical properties that are instructional to resident cells to form complex tissues with characteristics to develop and support vascular networks. In vitro, the development of vascular networks can be guided by biochemical patterning of substrates via spatial distribution and display of peptides and growth factors to prompt cell adhesion, differentiation, and proliferation. We have developed a technique utilizing peptide ligands that specifically bind vascular endothelial growth factor (VEGF), erythropoietin (EPO), or angiopoietin-1 (ANG1) to spatiotemporally distribute growth factors to cells. This allows for the controlled release of each growth factor, ultimately enhancing the formation of a vascular network. Our engineered tissue constructs (ETCs) are fabricated out of gelatin methacryloyl (GelMA), which is an ideal substrate for tailored stiffness and bio-functionality, and covalently patterned with growth factor specific peptides. These peptides mimic growth factor receptors, facilitating the non-covalent binding of the growth factors to the ETC, allowing for facile uptake by the cells. We have demonstrated in the absence of cells the binding affinity of VEGF, EPO, and ANG1 to their respective peptides and the ability for each to be patterned onto a GelMA substrate. The ability to organize growth factors on an ETC provides different functionality to develop organized vascular networks. Our results demonstrated a method to incorporate biochemical cues into ETCs that enable spatial and temporal control of growth factors. Future efforts will investigate the cellular response by evaluating gene expression, quantifying angiogenic activity, and measuring the speed of growth factor consumption.

Keywords: growth factor, hydrogel, peptide, angiogenesis, vascular, patterning

Procedia PDF Downloads 131

Authors: S. Sakthivel

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Currently, the global economy is based on the hydrocarbon economy, which is referencing the global hydrocarbon industry. Problems of using these fossil fuels (like oil, NG, coal) are emitting greenhouse gases (GHGs) and price fluctuation, supply/distribution, etc. These challenges can be overcome by using clean energy as hydrogen. The hydrogen economy is the use of hydrogen as a low carbon fuel, particularly for hydrogen vehicles, alternative industrial feedstock, power generation, and energy storage, etc. Engineering consulting firms have a significant role in this ambition and green hydrogen value chain (i.e., integration of renewables, production, storage, and distribution to end-users). Typically, the cost of green hydrogen is a function of the price of electricity needed, the cost of the electrolyser, and the operating cost to run the system. This article focuses on economic viability and explores the alluring business scenarios globally. Break-even analysis was carried out for green hydrogen production and in order to evaluate and compare the impact of the electricity price on the production costs of green hydrogen and relate it to fossil fuel-based brown/grey/blue hydrogen costs. It indicates that the cost of green hydrogen production will fall drastically due to the declining costs of renewable electricity prices and along with the improvement and scaling up of electrolyser manufacturing. For instance, in a scenario where electricity prices are below US$ 40/MWh, green hydrogen cost is expected to reach cost competitiveness.

Keywords: green hydrogen, cost analysis, break-even analysis, renewables, electrolyzer

Procedia PDF Downloads 114

Authors: Disha Bhanot, Vinish Kathuria

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This study focusses on the issue of distress sale in horticulture sector in India, which faces unique challenges, given the perishable nature of horticulture crops, seasonal production and paucity of post-harvest produce management links. Distress sale, from a farmer’s perspective may be defined as urgent sale of normal or distressed goods, at deeply discounted prices (way below the cost of production) and it is usually characterized by unfavorable conditions for the seller (farmer). The small and marginal farmers, often involved in subsistence farming, stand to lose substantially if they receive lower prices than expected prices (typically framed in relation to cost of production). Distress sale maximizes price uncertainty of produce leading to substantial income loss; and with increase in input costs of farming, the high variability in harvest price severely affects profit margin of farmers, thereby affecting their survival. The objective of this study is to model the occurrence of distress sale by tomato cultivators in the Indian state of Maharashtra, against the background of differential access to set of factors such as - capital, irrigation facilities, warehousing, storage and processing facilities, and institutional arrangements for procurement etc. Data is being collected using primary survey of over 200 farmers in key tomato growing areas of Maharashtra, asking information on the above factors in addition to seeking information on cost of cultivation, selling price, time gap between harvesting and selling, role of middleman in selling, besides other socio-economic variables. Farmers selling their produce far below the cost of production would indicate an occurrence of distress sale. Occurrence of distress sale would then be modelled as a function of farm, household and institutional characteristics. Heckman-two-stage model would be applied to find the probability/likelihood of a famer falling into distress sale as well as to ascertain how the extent of distress sale varies in presence/absence of various factors. Findings of the study would recommend suitable interventions and promotion of strategies that would help farmers better manage price uncertainties, avoid distress sale and increase profit margins, having direct implications on poverty.

Keywords: distress sale, horticulture, income loss, India, price uncertainity

Procedia PDF Downloads 216

Authors: Moncayo Donoso Miguelangel, Guevara Morales Johana, Kalenia Flores Kalenia, Barrera Avellaneda Luis Alejandro, Garzon Alvarado Diego Alexander

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In mammals, long bones are formed by ossification of a cartilage mold during early embryonic development, forming structures called secondary ossification centers (SOCs), a primary ossification center (POC) and growth plates. This last structure is responsible for long bone growth. During the femur growth, the morphology of the growth plate and the SOCs may vary during different developmental stages. So far there are no detailed morphological studies of the development process from embryonic to adult stages. In this work, we carried out a morphological characterization of femur development from embryonic period to adulthood in mice. 15, 17 and 19 days old embryos and 1, 7, 14, 35, 46 and 52 days old mice were used. Samples were analyzed by a computational approach, using 3D images obtained by micro-CT imaging. Results obtained in this study showed that femur, its growth plates and SOCs undergo morphological changes during different stages of development, including changes in shape, position and thickness. These variations may be related with a response to mechanical loads imposed for muscle development surrounding the femur and a high activity during early stages necessary to support the high growth rates during first weeks and years of development. This study is important to improve our knowledge about the ossification patterns on every stage of bone development and characterize the morphological changes of important structures in bone growth like SOCs and growth plates.

Keywords: development, femur, growth plate, mice

Procedia PDF Downloads 319

Authors: Gamalath M. B. P. Abeysekara

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Primary objective of any organization is to enhance the bottom line profit. Strategic procurement is one of the prominent aspects in view of receiving this ultimate objective. Strategic procurement is an activity used in each and every organization in their operations. Pharmaceutical procurement is an especially significant task for any organizations, particularly state sector concerned. The whole pharmaceutical procurement requirement of the country is procured through the State Pharmaceutical Corporation (SPC) of Sri Lanka. They follow Pharmaceutical Procurement Guideline of 2006 as the procurement principle. The main objective of this project is to identify the importance of State Pharmaceutical Corporation supplier selection criteria and critical analysis of pharmaceutical procurement procedure. State Pharmaceutical Corporations applied net price, product quality, past performance, and delivery of suppliers’ as main criteria for the selection suppliers. Data collection for this study was taken place through a questionnaire, given to fifty doctors within the Colombo district attached to five main state hospitals. Data analysis is carried out with mean and standard deviation functions. The ultimate outcomes indicated product quality, net price, and delivery of suppliers’ are the most important criteria behind the selection of suppliers. Critical analysis proved State Pharmaceutical Corporation should focus on net price reduction, improving laboratory testing facilities and effective communication between up and down stream of supply chain.

Keywords: government procurement procedure, pharmaceutical procurement supplier selection criteria, importance of SPC supplier selection criteria

Procedia PDF Downloads 426

Authors: Jyotika Chopra, Dinesh Goyal

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A study was initiated to examine the effects of corn gluten hydrolysate on seedlings growth and its development. Corn gluten is the byproduct of starch industry rich in proteins was hydrolysed by acid and alkali, and the impact of hydrolysate was studied on seed germination of Vigna radiata, Phaseolus vulagris (Fabaceae) and Triticum aestivum and Oryza sativa (Gramineae). For this, the optimum hydrolysis was obtained by 4NHCl and 4M NaOH where insoluble protein in gluten was broken down to glutamic acid, alanine, aspartic acid which was initially confirmed by biuret test, xanthoproteic, solubility and chromatographic tests. The seeds of above families were separately treated with different dilutions of corn gluten hydrolysate ranging from 1-100% to see effects produced by these dilutions on seed germination, plumule, and radical growth. The seedlings were put in the Petri plates and placed in the optimized conditions of temperature (37˚C) and photoperiod of 16:8 hours. The results indicate the plumule of all seeds shows the increase in growth pattern up to 25.75%. Whereas radical shows the increase in growth up to 25.88% till 10% of dilution of corn and wheat gluten hydrolysate with respect to water as blank. Further, there is decrease in growth from 30- 100% of dilutions of both, the hydrolysate indicates the inhibitory effects which unveil about the careful usage of gluten hydrolysate.

Keywords: corn gluten, characterization, hydrolysis, seedling growth

Procedia PDF Downloads 92

Authors: Lavanya Mohan, Suneha Sethi

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This paper seeks to study the concept of existential anguish and its relation to personal growth. Generally, existential anguish is taken to be an all-pervading negative feeling arising from an individual’s knowledge of their absolute freedom. However, this paper investigates the possible positive impact of this sense of anguish, such as its role in commencing an individual’s journey towards authentic living, characterized by an internal locus of will, and acceptance of absolute freedom. This journey towards authentic living is what is referred to as personal growth, in this paper, in the context of existential philosophy. The work of four prominent existentialists has been used to elucidate existential anguish. A human’s scope for personal growth in the existential framework has been compared to that in the teleological framework of religion. In the latter, individuals must abide by the moral code of an external authority and work towards a pre-ordained purpose of life. This is illustrated by the examination of Hinduism, Christianity, and Islam. To test people’s levels of existential anguish, religiosity, and personal growth, a survey using an originally constructed questionnaire has been undertaken. Simple and partial correlation analyses have been used to ascertain the relationships between these three variables. Contrary to the hypothesis, the results indicate that existential anguish has a detrimental effect on personal growth, while religiosity does not affect it at all. Through their responses, it was also evident that the respondents do not adhere to teleological concepts of morality, despite a belief in God. This study has further scope in determining how variations in sample demography may influence the relationship of existential anguish with personal growth.

Keywords: existential anguish, existentialism, personal growth, religiosity, teleology

Procedia PDF Downloads 172

Authors: Oliver Takawira, Thembi Hope

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This study will analyse the relationship between Bitcoin price movements and the Johannesburg stock exchange (JSE). The aim is to determine whether Bitcoin price movements affect the stock market performance. As crypto currencies continue to gain prominence as a safe asset during periods of economic distress, this raises the question of whether Bitcoin’s prosperity could affect investment in the stock market. To identify the existence of a short run and long run linear relationship, the study will apply the Autoregressive Distributed Lag Model (ARDL) bounds test and a Vector Error Correction Model (VECM) after testing the data for unit roots and cointegration using the Augmented Dicker Fuller (ADF) and Phillips-Perron (PP). The Non-Linear Auto Regressive Distributed Lag (NARDL) will then be used to check if there is a non-linear relationship between bitcoin prices and stock market prices.

Keywords: bitcoin, stock market, interest rates, ARDL

Procedia PDF Downloads 79

Authors: Koo-Yeon Kim, Eun-Hye Kim, Tae-Il Son

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Epidermal Growth Factor (EGF, Mw=6,045) has been reported to have high efficiency of wound repair and anti-wrinkle effect. However, the half-life of EGF in the body is too short to exert the biological activity effectively when applied in free form. Growth Factors can be stabilized by immobilization with carbohydrates from thermal and proteolytic degradation. Low molecular weight chitosan (LMCS) and its derivate prepared by hydrogen peroxide has high solubility. LM6A6DC was successfully prepared as a reactive carbohydrate for the stabilization of EGF by the reactions of LMCS with alkalization, tosylation, azidation and reduction. The structure of LM6A6DC was confirmed by FT-IR, 1H NMR and elementary analysis. For enhancing the stability of free EGF, EGF was attached with LM6A6DC by using water-soluble carbodiimide. EGF-LM6A6DC conjugates did not show any cytotoxicity on the Normal Human Dermal Fibroblast(NHDF) 3T3 proliferation at least under 100 ㎍/㎖. In the result, it was considered that LM6A6DC is suitable to immobilize of growth factor.

Keywords: epidermal growth factor (EGF), low-molecular-weight chitosan, immobilization

Procedia PDF Downloads 449

Authors: Srinaath Anbu Durai, Wang Zhaoxia

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Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or the housing market. This is despite an abundance of works in behavioural economics that show that sentiment or emotions caused due to an external factor impact economic decisions. To address this gap, this research studies the impact of Twitter sentiment pertaining to the Covid-19 pandemic on resale Housing Development Board (HDB) apartment prices in Singapore. It leverages SNSCRAPE to collect tweets pertaining to Covid-19 for sentiment analysis, lexicon based tools VADER and TextBlob are used for sentiment analysis, Granger Causality is used to examine the relationship between Covid-19 cases and the sentiment score, and neural networks are leveraged as prediction models. Twitter sentiment pertaining to Covid-19 as a predictor of HDB price in Singapore is studied in comparison with the traditional predictors of housing prices i.e., the structural and neighbourhood characteristics. The results indicate that using Twitter sentiment pertaining to Covid19 leads to better prediction than using only the traditional predictors and performs better as a predictor compared to two of the traditional predictors. Hence, Twitter sentiment pertaining to an external factor should be considered as important as traditional predictors. This paper demonstrates the real world economic applications of sentiment analysis of Twitter data.

Keywords: sentiment analysis, Covid-19, housing price prediction, tweets, social media, Singapore HDB, behavioral economics, neural networks

Procedia PDF Downloads 86

Authors: Antoni Wibowo, Harry Pujianto, Dewi Retno Sari Saputro

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The stock market can provide huge profits in a relatively short time in financial sector; however, it also has a high risk for investors and traders if they are not careful to look the factors that affect the stock market. Therefore, they should give attention to the dynamic fluctuations and movements of the stock market to optimize profits from their investment. In this paper, we present a nonlinear autoregressive exogenous model (NARX) to predict the movements of stock market; especially, the movements of the closing price index. As case study, we consider to predict the movement of the closing price in Indonesia composite index (IHSG) and choose the best structures of NARX for IHSG’s prediction.

Keywords: NARX (Nonlinear Autoregressive Exogenous Model), prediction, stock market, time series

Procedia PDF Downloads 220

Authors: Jackson Niyongabo

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This study addresses a notable gap in the existing literature on the relationship between energy consumption, economic growth, and CO₂ emissions, particularly within the African context. While numerous studies have explored these dynamics globally and regionally across various development levels, few have delved into the nuances of regions and income levels specific to African countries. Furthermore, the evaluation of the interplay between green growth policies, green energy technologies, and their impact on environmental quality has been underexplored. This research aims to fill these gaps by conducting a comprehensive analysis of the transition from conventional economic growth and energy consumption to a paradigm of green growth coupled with green energy utilization across the African continent from 1980 to 2018. The study is structured into three main parts: an empirical examination of the long-term effects of energy intensity, renewable energy consumption, and economic growth on CO₂ emissions across diverse African regions and income levels; an estimation of the long-term impact of green growth and green energy use on CO₂ emissions for countries implementing green policies within Africa, as well as at regional and global levels; and a comparative analysis of the impact of green growth policies on environmental degradation before and after implementation. Employing advanced econometric methods and panel estimators, the study utilizes a testing framework, panel unit tests, and various estimators to derive meaningful insights. The anticipated results and conclusions will be elucidated through causality tests, impulse response, and variance decomposition analyses, contributing valuable knowledge to the discourse on sustainable development in the African context.

Keywords: economic growth, green growth, energy consumption, CO₂ emissions, econometric models, green energy

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Authors: Meiyan Xing, Cenran Li, Liang Xiang

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Impacts of excess sludge vermicompost on the germination and early growth of plant were tested. The better effect of cow dung vermicompost (CV) on seed germination and seedling growth proved that cow dung was indeed the preferred additive in sludge vermicomposting as reported by plentiful researchers worldwide. The effects and the best amount of application of CV were further discussed. Results demonstrated that seed germination and seedling growth (seedlings number, plant height, stem diameter) were the best and heavy metal (Zn, Pb, Cr and As) contents of plant were the lowest when soil amended with CV by 15%. Additionally, CV fostered higher contents of chlorophyll a and chlorophyll b compared to the control when concentration ranged from 5 to 15%, thereafter a slight increase in chlorophyll content was observed form 15% to 25%. Thus, CV at the optimum proportion of 15% could serve as a feasible and satisfactory way of sludge agricultural utilization of sewage sludge. In summary, sewage sludge can be gainfully utilized in producing organic fertilizer via vermicomposting, thereby not only providing a means of sewage sludge treatment and disposal, but also stimulating the growth of plant and the ability to resist disease.

Keywords: cow dung vermicompost, seed germination, seedling growth, sludge utilization

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Authors: Lina Wu, Ye Li

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An equivalent relation between a harmonic form and a closed co-closed form is established on a complete non-compact manifold. This equivalence has been generalized for a differential k-form ω from Lq spaces to non-Lq spaces when q=2 in the context of p-balanced growth where p=2. Especially for a simple differential k-form on a complete non-compact manifold, the equivalent relation has been verified with the extended scope of q for from finite q-energy in Lq spaces to infinite q-energy in non-Lq spaces when with 2-balanced growth. Generalized Hadamard Theorem, Cauchy-Schwarz Inequality, and Calculus skills including Integration by Parts as well as Convergent Series have been applied as estimation techniques to evaluate growth rates for a differential form. In particular, energy growth rates as indicated by an appropriate power range in a selected test function lead to a balance between a harmonic differential form and a closed co-closed differential form. Research ideas and computational methods in this paper could provide an innovative way in the study of broadening Lq spaces to non-Lq spaces with a wide variety of infinite energy growth for a differential form.

Keywords: closed forms, co-closed forms, harmonic forms, L^q spaces, p-balanced growth, simple differential k-forms

Procedia PDF Downloads 425

Authors: Kang-Hyun Leem, Myung-Gyou Kim, Hye Kyung Kim

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Deer antler, traditionally used as a tonic and valuable drug in oriental medicine, has been considered to possess bone-strengthening activity. The upper section, mid section, and base of the antler has been known to exhibit different biological properties. Present study was performed to examine the effects of different parts of deer antler extract (DH) on osteogenic gene expressions in MG-63 cells and longitudinal bone growth in adolescent male rats. The expressions of osteogenic genes, collagen, alkaline phosphatase, osteocalcin, and osteopontin, were measured by quantitative real-time PCR. Longitudinal bone growth was measured in 3-week-old male Sprague-Dawley rats using fluorescence microscopy. To examine the effects on the growth plate metabolism, the total height of growth plate and bone morphogenetic protein-2 (BMP-2) were measured. Collagen and osteocalcin mRNA expressions were increased by all three parts of the DH treatment while osteopontin gene expression was not affected by any of the DH treatment. Alkaline phosphatase gene expression was increased by upper and mid part of DH while base part of DH fails to affect alkaline phosphatase gene expression. The upper and mid parts of the DH treatment enhanced longitudinal bone growth and total height of growth plate. The induction of BMP-2 protein expression in growth plate assessed by immunostaining was also promoted by upper and mid parts of the DH treatment. These results suggest that DH, especially upper and mid parts, stimulate osteogenic gene expressions and have the effect on bone growth in adolescent rats and might be used for the growth delayed adolescent and inherent growth failure patient.

Keywords: bone morphogenetic protein-2, deer antler, longitudinal bone growth, osteogenic genes

Procedia PDF Downloads 359

Authors: Cameron Truong, Mikhail Bhatia, Yangyang Chen, Viet Nga Cao

Abstract:

Using a sample of U.S. firms between 1996 and 2011, this paper documents a positive association between options trading volume and future stock price crash risk. This relation is evidently more pronounced among firms with higher information asymmetry, business uncertainty, and short-sale constraints. In a dichotomous cross-sectional setting, we also document that firms with options trading have higher future crash risk than firms without options trading. We further show in a difference-in-difference analysis that firms experience an increase in crash risk immediately after the listing of options. The results suggest that options traders are able of identifying bad news hoarding by management and choose to trade in a liquid options market in anticipation of future crashes.

Keywords: bad news hoarding, cross-sectional setting, options trading, stock price crash

Procedia PDF Downloads 423

Authors: Siti Rodliyah, Andrik Purwasito, Bani Sudardi, Abdullah Wakit

Abstract:

This study employs sociological-ethnographic basic method and the cultural studies paradigm as the approach in understanding the habitus within the customary marriage of the East Nusa Tenggara society who require belis as a bride-price. The conceptual basis underlying the application of habitus theory and symbolic power in East Nusa Tenggara (NTT) society refers to the Bourdieu’s framework. This study is a result of participatory observation on habitus of a marital system using belis observed by the NTT society as a cognitive structure which connects individuals to the social activities of the customary marriage and makes it unquestionable habits. Knowledge of the social world under the pretext of prosperity for the recipients (family) of a bride-price can be a political instrument for the sustainability of power relations. The ritual-mythical system in the society has never been fully present as a neutral habit. The habitus reflected in the marital relationship among the NTT society enables the men to obtain and exercise their power relations. The sustainability of power relations can be seen from the representation of the social status of a girl and the properties attached to her. This is what gave birth to a symbolic rule, in which the social rules about bride-price or belis eventually will serve the interests of those who occupy a dominant position in the social structure, namely the rich men.

Keywords: belis, habitus, East Nusa Tenggara, marital system, power, symbolic

Procedia PDF Downloads 221

Authors: Maryam Ghoreishi, Christian Larsen

Abstract:

In this paper, we investigate the effect of stochastic inputs on problem of joint optimal pricing and lot-sizing decisions where the inventory cycle is divided into advance and spot sales periods. During the advance sales period, customer can make reservations while customer with reservations can cancel their order. However, during the spot sales period customers receive the order as soon as the order is placed, but they cannot make any reservation or cancellation during that period. We assume that the inter arrival times during the advance sales and spot sales period are exponentially distributed where the arrival rate is decreasing function of price. Moreover, we assume that the number of cancelled reservations is binomially distributed. In addition, we assume that deterioration process follows an exponential distribution. We investigate two cases. First, we consider two-state case where we find the optimal price during the spot sales period and the optimal price during the advance sales period. Next, we develop a generalized case where we extend two-state case also to allow dynamic prices during the spot sales period. We apply the Markov decision theory in order to find the optimal solutions. In addition, for the generalized case, we apply the policy iteration algorithm in order to find the optimal prices, the optimal lot-size and maximum advance sales amount.

Keywords: inventory control, pricing, Markov decision theory, advance sales system

Procedia PDF Downloads 300

Authors: Ahmed Elgharably, Nivien Nafady

Abstract:

Arbuscular mycorrhizal fungi (AMF) and plant growth promoting microbes (PGPM) can promote plant growth under saline conditions. This study investigated how AMF and PGPM affected the growth and grain yield of wheat at different soil salinity levels (0, 75 and 150 mM NaCl). AMF colonization percentage, grain yield and dry weights and lengths of shoot and root, N, P K, Na, malondialdehyde, chlorophyll and proline contents and shoot relative permeability were determined. Salinity reduced NPK uptake and malondialdehyde and chlorophyll contents, and increased shoot Na concentration, relative permeability, and proline content, and thus declined plant growth. PGPM inoculation enhanced AMF colonization, P uptake, and K/Na ratio, but alone had no significant effect on plant growth and grain yield. AMF inoculation significantly enhanced NPK uptake, increased chlorophyll content and decreased shoot relative permeability, proline and Na contents, and thus promoted the plant growth. The inoculation of PGPM significantly enhanced the positive effects of AMF in controlling Na uptake and in increasing chlorophyll and NPK contents. Compared to AMF inoculation alone, dual inoculation with AMF and PGPM resulted in approximately 10, 25 and 25% higher grain yield at 0, 75 and 150 mM NaCl, respectively. The results provide that PGPM inoculation can maximize the effects of AMF inoculation in alleviating the deleterious effects of NaCl salts on wheat growth.

Keywords: mycorrhizal fungi, salinity, sodium, wheat

Procedia PDF Downloads 154

Authors: Hasan Basri Jumin

Abstract:

Using the slaughterhouse waste combined to suitable dose of nitrogen fertilizer to Apium glaviolen gives the significant effect to mean relative growth rate. The same pattern also showed significantly in net assimilation rate. The net assimilation rate increased significantly during 42 days old plants. Combination of treatment of 100 ml/l animal slaughterhouse waste and 0.1 g/kg nitrogen fertilizer/kg soil increased the vegetative growth of Apium glaviolens. The biomass of plant and mean relative growth rate of Apium glaviolens were rapidly increased in 4 weeks after planting and gradually decreased after 35 days at the harvest time. Combination of 100 ml/l slaughterhouse waste and applied 0.1 g/kg nitrogen fertilizer has increased all parameters. The highest vegetative growth, biomass, mean relative growth rate and net assimilation rate were received from 0.56 mg-l.m-2.days-1.

Keywords: Apium glaviolent, nitrogen, pollutant, slaughterhouse, waste

Procedia PDF Downloads 339

Authors: Rosie S. Abalos, John Patrick M. Dizon

Abstract:

The operation of fish cages in mariculture parks for milkfish production remains a lucrative business for aquaculture operators. Three areas in the Philippines where mariculture parks are still in active operation were identified as study sites for this research. Financial analysis was used to estimate profitability of mariculture operations in the selected study sites. Based on the result of this research, milkfish production in mariculture parks remains profitable both in terms of net profit generation and the return on investment. To improve the profitability of aquaculture operations in mariculture parks, the relatively high price of operational inputs should be managed. As a recommendation, further studies should be conducted on the profitability of aquaculture operations in mariculture parks in the country to include other factors which may cause losses on the part of the operator and factors that may affect price of produce upon harvest.

Keywords: mariculture parks, milkfish production, aquaculture, profitability

Procedia PDF Downloads 127

Authors: Olawale Johnson

Abstract:

The cry and agitation for the creation of equal opportunities is one of the major reasons behind the social menace countries of the world experience. As the poor, continue to demand for the dividends of economic growth, countries of the world are in a state of dilemma because, despite impressive growth figures, the poor are still far below the empowerment line. However, evidence from the Asian Tigers has proven that with the adoption and efficient utilization of information technology, a growth miracle is not far-fetched. With the mind-boggling pace of technological innovation, the need to ensure that the innovative products are all connected has become vital. Technologies that did not exist a few years ago have become vital equipment used to underlie every aspect of our economy from medicine to banking to sports. The need to connect things sensors, actuators and smart systems with the aim of ensuring person-to-object, object-to-object communications has promoted the need of internet of things. As developing countries struggle with delivering inclusiveness, the Internet of Everything is perceived to be the miracle that will deliver this in no time. This paper examines how the Asian Tigers have been able to promote inclusive growth through the Internet of Everything.

Keywords: inclusive growth, internet of everything, innovation, embedded systems and smart technologies

Procedia PDF Downloads 286