Search results for: Price Manipulation

Authors: F. Rahnamay Roodposhti, M. Falah Shams, H. Kordlouie

Abstract:

The aim of the article is extending and developing econometrics and network structure based methods which are able to distinguish price manipulation in Tehran stock exchange. The principal goal of the present study is to offer model for approximating price manipulation in Tehran stock exchange. In order to do so by applying separation method a sample consisting of 397 companies accepted at Tehran stock exchange were selected and information related to their price and volume of trades during years 2001 until 2009 were collected and then through performing runs test, skewness test and duration correlative test the selected companies were divided into 2 sets of manipulated and non manipulated companies. In the next stage by investigating cumulative return process and volume of trades in manipulated companies, the date of starting price manipulation was specified and in this way the logit model, artificial neural network, multiple discriminant analysis and by using information related to size of company, clarity of information, ratio of P/E and liquidity of stock one year prior price manipulation; a model for forecasting price manipulation of stocks of companies present in Tehran stock exchange were designed. At the end the power of forecasting models were studied by using data of test set. Whereas the power of forecasting logit model for test set was 92.1%, for artificial neural network was 94.1% and multi audit analysis model was 90.2%; therefore all of the 3 aforesaid models has high power to forecast price manipulation and there is no considerable difference among forecasting power of these 3 models.

Keywords: Price Manipulation, Liquidity, Size of Company, Floating Stock, Information Clarity

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Authors: Goodness C. Aye

Abstract:

This paper examines the effect of the volatility of oil prices on food price in South Africa using monthly data covering the period 2002:01 to 2014:09. Food price is measured by the South African consumer price index for food while oil price is proxied by the Brent crude oil. The study employs the GARCH-in-mean VAR model, which allows the investigation of the effect of a negative and positive shock in oil price volatility on food price. The model also allows the oil price uncertainty to be measured as the conditional standard deviation of a one-step-ahead forecast error of the change in oil price. The results show that oil price uncertainty has a positive and significant effect on food price in South Africa. The responses of food price to a positive and negative oil price shocks is asymmetric.

Keywords: Oil price volatility, Food price, Bivariate GARCH-in- mean VAR, Asymmetric.

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Authors: Abdullah Bajelan, Adel Akbarimajd

Abstract:

Object manipulation techniques in robotics can be categorized in two major groups including manipulation with grasp and manipulation without grasp. The original aim of this paper is to develop an object manipulation method where in addition to being grasp-less, the manipulation task is done in a passive approach. In this method, linear and angular positions of the object are changed and its manipulation path is controlled. The manipulation path is a helix track with constant radius and incline. The method presented in this paper proposes a system which has not the actuator and the active controller. So this system requires a passive mechanical intelligence to convey the object from the status of the source along the specified path to the goal state. This intelligent is created based on utilizing the geometry of the system components. A general set up for the components of the system is considered to satisfy the required conditions. Then after kinematical analysis, detailed dimensions and geometry of the mechanism is obtained. The kinematical results are verified by simulation in ADAMS.

Keywords: Mechanical intelligence, Object manipulation, Passive mechanism, Passive non-prehensile manipulation.

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Authors: Heroe Wijanto, Sugihartono, Suhartono Tjondronegoro, Kuspriyanto

Abstract:

The use of High Order Statistics (HOS) analysis is expected to provide so many candidates of features that can be selected for pattern recognition. More candidates of the feature can be extracted using simple manipulation through a specific mathematical function prior to the HOS analysis. Feature extraction method using HOS analysis combined with Difference to the Nth-Power manipulation has been examined in application for Automatic Modulation Recognition (AMR) to perform scheme recognition of three digital modulation signal, i.e. QPSK-16QAM-64QAM in the AWGN transmission channel. The simulation results is reported when the analysis of HOS up to order-12 and the manipulation of Difference to the Nth-Power up to N = 4. The obtained accuracy rate of AMR using the method of Simple Decision obtained 90% in SNR > 10 dB in its classifier, while using the method of Voted Decision is 96% in SNR > 2 dB.

Keywords: modulation, automatic modulation recognition, feature analysis, feature manipulation.

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Authors: R. Sammoura

Abstract:

In Lebanon, public construction projects are awarded to the contractor submitting the lowest bid price based on a competitive bidding process. The contractor has to make a strategic decision in choosing the appropriate bid price that will offer a satisfactory profit with a greater probability to win. A simulation model for bid price decision making based on the lowest bid price evaluation is developed. The model, built using Crystal Ball decisionengineering software, considers two main factors affecting the bidding process: the number of qualified bidders and the size of the project. The validity of the model is tested on twelve separate projects. The study also shows how to use the model to conduct risk analysis and help any specific contractor to decide on his bid price with associated certainty level in a scientific method.

Keywords: Bid price, Competition, Decision making, Simulation.

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Authors: Chien-Hui Yang, Che-Yang Lin, Ya-Chen Hsu

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Gold passbook is an investing tool that is especially suitable for investors to do small investment in the solid gold. The gold passbook has the lower risk than other ways investing in gold, but its price is still affected by gold price. However, there are many factors can cause influences on gold price. Therefore, building a model to predict the price of gold passbook can both reduce the risk of investment and increase the benefits. This study investigates the important factors that influence the gold passbook price, and utilize the Group Method of Data Handling (GMDH) to build the predictive model. This method can not only obtain the significant variables but also perform well in prediction. Finally, the significant variables of gold passbook price, which can be predicted by GMDH, are US dollar exchange rate, international petroleum price, unemployment rate, whole sale price index, rediscount rate, foreign exchange reserves, misery index, prosperity coincident index and industrial index.

Keywords: Gold price, Gold passbook price, Group Method ofData Handling (GMDH), Regression.

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Authors: H. D. Ibrahim, H. C. Chinwenyi, T. Danjuma

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An option is defined as a financial contract that provides the holder the right but not the obligation to buy or sell a specified quantity of an underlying asset in the future at a fixed price (called a strike price) on or before the expiration date of the option. This paper examined two approaches for derivation of Partial Differential Equation (PDE) options price valuation formula for the Heston stochastic volatility model. We obtained various PDE option price valuation formulas using the riskless portfolio method and the application of Feynman-Kac theorem respectively. From the results obtained, we see that the two derived PDEs for Heston model are distinct and non-unique. This establishes the fact of incompleteness in the model for option price valuation.

Keywords: Option price valuation, Partial Differential Equations, Black-Scholes PDEs, Ito process.

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Authors: Jung-Hun Cho, Tae-Heon Moon, Jin-Hak Lee

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Land price contains the comprehensive characteristics of urban space, representing the social and economic features of the city. Accordingly, land price can be utilized as an indicator, which can identify the changes of spatial structure and socioeconomic variations caused by urban development. This study attempted to explore the changes in land price by a new road construction. Methodologically, it adopted Space Syntax, which can interpret urban spatial structure comprehensively, to identify the relationship between the forms of road networks and land price. The result of the regression analysis showed the ‘integration index’ of Space Syntax is statistically significant and has a strong correlation with land price. If the integration value is high, land price increases proportionally. Subsequently, using regression equation, it tried to predict the land price changes of each of the lots surrounding the roads that are newly opened. The research methods or study results have the advantage of predicting the changes in land price in an easy way. In addition, it will contribute to planners and project managers to establish relevant polices and smoothing urban regeneration projects through enhancing residents’ understanding by providing possible results and advantages in their land price before the execution of urban regeneration and development projects.

Keywords: Space syntax, urban regeneration, spatial structure, official land price.

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Authors: M’hamed Outanoute, Mohamed Baslam, Belaid Bouikhalene

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The customers use the best compromise criterion between price and quality of service (QoS) to select or change their Service Provider (SP). The SPs share the same market and are competing to attract more customers to gain more profit. Due to the divergence of SPs interests, we believe that this situation is a non-cooperative game of price and QoS. The game converges to an equilibrium position known Nash Equilibrium (NE). In this work, we formulate a game theoretic framework for the dynamical behaviors of SPs. We use Genetic Algorithms (GAs) to find the price and QoS strategies that maximize the profit for each SP and illustrate the corresponding strategy in NE. In order to quantify how this NE point is performant, we perform a detailed analysis of the price of anarchy induced by the NE solution. Finally, we provide an extensive numerical study to point out the importance of considering price and QoS as a joint decision parameter.

Keywords: Pricing, QoS, Market share game, Genetic algorithms, Nash equilibrium, Learning, Price of anarchy.

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Authors: Liu Zhiyuan, Sun Zongdi

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In this paper, the BP neural network model is established to predict the carbon trading price and carbon trading volume in Shanghai City. First of all, we find the data of carbon trading price and carbon trading volume in Shanghai City from September 30, 2015 to December 23, 2016. The carbon trading price and trading volume data were processed to get the average value of each 5, 10, 20, 30, and 60 carbon trading price and trading volume. Then, these data are used as input of BP neural network model. Finally, after the training of BP neural network, the prediction values of Shanghai carbon trading price and trading volume are obtained, and the model is tested.

Keywords: Carbon trading price, carbon trading volume, BP neural network model, Shanghai City.

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Authors: Ahmet Denker, Tuğrul Adıgüzel

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In this paper, a solution is presented for a robotic manipulation problem in industrial settings. The problem is sensing objects on a conveyor belt, identifying the target, planning and tracking an interception trajectory between end effector and the target. Such a problem could be formulated as combining object recognition, tracking and interception. For this purpose, we integrated a vision system to the manipulation system and employed tracking algorithms. The control approach is implemented on a real industrial manipulation setting, which consists of a conveyor belt, objects moving on it, a robotic manipulator, and a visual sensor above the conveyor. The trjectory for robotic interception at a rendezvous point on the conveyor belt is analytically calculated. Test results show that tracking the raget along this trajectory results in interception and grabbing of the target object.

Keywords: robotics, robot vision, rendezvous planning, self organizingmaps.

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Authors: S. R. M. Prasanna, Y. V. Subba Rao, A. Mitra

Abstract:

We describe an effective method for image encryption which employs magnitude and phase manipulation using carrier images. Although it involves traditional methods like magnitude and phase encryptions, the novelty of this work lies in deploying the concept of carrier images for encryption purpose. To this end, a carrier image is randomly chosen from a set of stored images. One dimensional (1-D) discrete Fourier transform (DFT) is then carried out on the original image to be encrypted along with the carrier image. Row wise spectral addition and scaling is performed between the magnitude spectra of the original and carrier images by randomly selecting the rows. Similarly, row wise phase addition and scaling is performed between the original and carrier images phase spectra by randomly selecting the rows. The encrypted image obtained by these two operations is further subjected to one more level of magnitude and phase manipulation using another randomly chosen carrier image by 1-D DFT along the columns. The resulting encrypted image is found to be fully distorted, resulting in increasing the robustness of the proposed work. Further, applying the reverse process at the receiver, the decrypted image is found to be distortionless.

Keywords: Encryption, Carrier images, Magnitude manipulation, Phase manipulation.

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Authors: S. Chabbak

Abstract:

In a widely globalized world, the influence of audiovisual translation on the culture and identity of audiences is unmistakable. However, in the Arab World, there is a noticeable disproportion between this growing influence and the research carried out in the field. As a matter of fact, the voiced-over documentary is one of the most abundantly translated genres in the Arab World that carries lots of ideological elements which are in many cases rendered by manipulation. However, voiced-over documentaries have hardly received any focused attention from researchers in the Arab World. This paper attempts to scrutinize the process of translation of voiced-over documentaries in the Arab World, from French into Arabic in the present case study, by sub-categorizing the ideological items subject to manipulation, identifying the techniques utilized in their translation and exploring the potential extra-linguistic factors that prompt translation agents to opt for manipulative translation. The investigation is based on a corpus of 94 episodes taken from a series entitled 360° GEO Reports, produced by the French German network ARTE in French, and acquired, translated and aired by Al Jazeera Documentary Channel for Arab audiences. The results yielded 124 cases of manipulation in four sub-categories of ideological items, and the use of 10 different oblique procedures in the process of manipulative translation. The study also revealed that manipulation is in most of the instances dictated by the editorial line of the broadcasting channel, in addition to the religious, geopolitical and socio-cultural peculiarities of the target culture.

Keywords: Audiovisual translation, ideological items, manipulation, voiced-over documentaries.

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Authors: Larisa N. Pop, Irina M. Ban

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This paper aims to present the main instruments used in the economic literature for measuring the price risk, pointing out on the advantages brought by the conditional variance in this respect. The theoretical approach will be exemplified by elaborating an EGARCH model for the price returns of wheat, both on Romanian and on international market. To our knowledge, no previous empirical research, either on price risk measurement for the Romanian markets or studies that use the ARIMA-EGARCH methodology, have been conducted. After estimating the corresponding models, the paper will compare the estimated conditional variance on the two markets.

Keywords: conditional variance, GARCH models, price risk, volatility

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Authors: Ebrahim Abbasi, Amir Abouec

Abstract:

In this research, the researchers have managed to design a model to investigate the current trend of stock price of the "IRAN KHODRO corporation" at Tehran Stock Exchange by utilizing an Adaptive Neuro - Fuzzy Inference system. For the Longterm Period, a Neuro-Fuzzy with two Triangular membership functions and four independent Variables including trade volume, Dividend Per Share (DPS), Price to Earning Ratio (P/E), and also closing Price and Stock Price fluctuation as an dependent variable are selected as an optimal model. For the short-term Period, a neureo – fuzzy model with two triangular membership functions for the first quarter of a year, two trapezoidal membership functions for the Second quarter of a year, two Gaussian combination membership functions for the third quarter of a year and two trapezoidal membership functions for the fourth quarter of a year were selected as an optimal model for the stock price forecasting. In addition, three independent variables including trade volume, price to earning ratio, closing Stock Price and a dependent variable of stock price fluctuation were selected as an optimal model. The findings of the research demonstrate that the trend of stock price could be forecasted with the lower level of error.

Keywords: Stock Price forecast, membership functions, Adaptive Neuro-Fuzzy Inference System, trade volume, P/E, DPS.

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Authors: Li Li, Kai-Hsuan Chu

Abstract:

It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: Real estate price, least-square, grey correlation, macroeconomics.

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Authors: Wen-Chi Liu

Abstract:

This paper aims to examine whether a bubble is present in the housing market of China. Thus, we use the housing  price-to-income ratios and housing price-to-rent ratios of 35 cities from 1998 to 2010. The methods of the panel KSS unit root test with a  Fourier function and the SPSM process are likewise used. The panel  KSS unit root test with a Fourier function considers the problem of  non-linearity and structural changes, and the SPSM process can avoid  the stationary time series from dominating the result-generated bias.  Through a rigorous empirical study, we determine that the housing  price-to-income ratios are stationary in 34 of the 35 cities in China.  Only Xining is non-stationary. The housing price-to-rent ratios are  stationary in 32 of the 35 cities in China. Chengdu, Fuzhou, and  Zhengzhou are non-stationary. Overall, the housing bubbles are not a  serious problem in China at the time.

 

Keywords: Housing Price-to-Income Ratio, Housing Price-to-Rent Ratio, Housing Bubbles, Panel Unit-Root Test.

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Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

Abstract:

In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: Equivalent Martingale Measure, European Put Option, Girsanov Theorem, Martingales, Monte Carlo method, option price valuation, option price valuation formula.

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Authors: Ernawati Mustafa Kamal, Hasnanywati Hassan, Atasya Osmadi

Abstract:

The housing industry is crucial for sustainable development of every country. Housing is a basic need that can enhance the quality of life. Owning a house is therefore the main aim of individuals. However, affordability has become a critical issue towards homeownership. In recent years, housing price in the main cities has increased tremendously to unaffordable level. This paper investigates factors influencing the housing price from developer’s perspective and provides recommendation on strategies to tackle this issue. Online and face-to-face survey was conducted on housing developers operating in Penang, Malaysia. The results indicate that (1) location; (2) macroeconomics factor; (3) demographic factors; (4) land/zoning and; (5) industry factors are the main factors influencing the housing price. This paper contributes towards better understanding on developers’ view on how the housing price is determined and form a basis for government to help tackle the housing affordability issue.

Keywords: Factors influencing house price, housing affordability, housing developers, Malaysia.

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Authors: Roger L Goodwin

Abstract:

The US Consumer Price Indices (CPIs) measures hundreds of items in the US economy. Many social programs and government benefits index to the CPIs. The purpose of this project is to modernize an existing process. This paper will show the development of a small, visual, software product that documents the Economic Price Adjustment (EPA) for longterm contracts. The existing workbook does not provide the flexibility to calculate EPAs where the base-month and the option-month are different. Nor does the workbook provide automated error checking. The small, visual, software product provides the additional flexibility and error checking. This paper presents the feedback to project.

Keywords: Consumer Price Index, Economic Price Adjustment, contracts, visualization tools, database, reports, forms, event procedures.

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Authors: K. D. R. Jagath-Kumara, D. D. Dias

Abstract:

The sea waves carry thousands of GWs of power globally. Although there are a number of different approaches to harness offshore energy, they are likely to be expensive, practically challenging, and vulnerable to storms. Therefore, this paper considers using the near shore waves for generating mechanical and electrical power. It introduces two new approaches, the wave manipulation and using a variable duct turbine, for intercepting very wide wave fronts and coping with the fluctuations of the wave height and the sea level, respectively. The first approach effectively allows capturing much more energy yet with a much narrower turbine rotor. The second approach allows using a rotor with a smaller radius but captures energy of higher wave fronts at higher sea levels yet preventing it from totally submerging. To illustrate the effectiveness of the first approach, the paper contains a description and the simulation results of a scale model of a wave manipulator. Then, it includes the results of testing a physical model of the manipulator and a single duct, axial flow turbine in a wave flume in the laboratory. The paper also includes comparisons of theoretical predictions, simulation results, and wave flume tests with respect to the incident energy, loss in wave manipulation, minimal loss, brake torque, and the angular velocity.

Keywords: Near-shore sea waves, Renewable energy, Wave energy conversion, Wave manipulation.

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Authors: Ashiquer Rahman, Ummey Salma, Afrin Jannat

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Recently, oil has become more influential in almost every economic sector as a key material. As can be seen from the news, when there are some changes in an oil price or Organization of the Petroleum Exporting Countries (OPEC) announces a new strategy, its effect spreads to every part of the economy directly and indirectly. That’s a reason why people always observe the oil price and try to forecast the changes of it. The most important factor affecting the price is its supply which is determined by the number of wildcats drilled. Therefore, a study in relation between the number of wellheads and other economic variables may give us some understanding of the mechanism indicated the amount of oil supplies. In this paper, we will consider a relationship between the number of wellheads and three key factors: price of the wellhead, domestic output, and Gross National Product (GNP) constant dollars. We also add trend variables in the models because the consumption of oil varies from time to time. Moreover, this paper will use an econometrics method to estimate parameters in the model, apply some tests to verify the result we acquire, and then conclude the model.

Keywords: Price, domestic output, GNP, trend variable, wildcat activity.

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Authors: S. Homrossukon, W. Parinyasart

Abstract:

This is an applied research to propose the method for price quotation for a contract electronics manufacturer. It has had a precise price quoting method but such method could not quickly provide a result as the customer required. This reduces the ability of company to compete in this kind of business. In this case, the cause of long time quotation process was analyzed. A lot of product features have been demanded by customer. By checking routine processes, it was found that high fraction of quoting time was used for production time estimating which has effected to the manufacturing or production cost. Then the historical data of products including types, number of components, assembling method, and their assembling time were used to analyze the key components affecting to production time. The price quoting model then was proposed. The implementation of proposed model was able to remarkably reduce quoting time with an acceptable required precision.

Keywords: Price quoting, Contract manufacturer, Stepwise technique, Best subset technique.

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Authors: S. Pathomsiri, P. Sukaboon

Abstract:

The National Blood Center, Thai Red Cross Society is responsible for providing blood to hospitals all over the country. When any hospital needs blood, it will have to send the vehicle to pick up at the NBC. There are a lot of vehicles to pick up blood at the NBC every day. Each vehicle is usually empty for inbound trip and a little loaded for outbound. The NBC realized such waste or loss and there have been the third party offered to distribute blood and charge for fee. This paper proposes to apply the vehicle routing problem (VRP) for estimating the fair price. The idea is tested with the real data during seven-day period of 6 – 12 July 2010 to estimate the fair price for transporting blood in Bangkok Metropolitan Region.

Keywords: Blood Supply Chain, Vehicle Routing Problem, Heuristic, Saving Algorithm, Fair Price.

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Authors: Hy Dang, Bo Mei

Abstract:

The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: Classification, machine learning, time representation, stock prediction.

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Authors: Jingxian An, Wei Yu

Abstract:

The commercial value (retail price) of wine is mostly determined by the wine quality, ageing potential, and oak influence. This paper reveals that wine quality, ageing potential, and oak influence are favourably correlated, hence positively influencing the commercial value of Pinot noir wines. Oak influence is the most influential of these three sensory attributes on the price set by wine traders and estimated by experienced customers. In the meanwhile, this study gives winemakers with chemical instructions for raising total phenolics, which can improve wine quality, ageing potential, and oak influence, all of which can increase a wine’s economic worth.

Keywords: Retail price, ageing potential, wine quality, oak influence.

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Authors: Feddaoui Amina

Abstract:

Income smoothing represents an attempt on the part of the company's management to reduce variations in earnings through the manipulation of the accounting principles. In this study, we aimed to measure income smoothing practices in a sample of 30 French joint stock companies during the period (2007-2009), we used Dummy variables method and “ECKEL” model to measure income smoothing practices and Binomial test accourding to SPSS program, to confirm or refute our hypothesis. This study concluded that there are no significant statistical indicators of income smoothing practices in the sample studied of French companies during the period (2007-2009), so the income series in the same sample studied of is characterized by stability and non-volatility without any intervention of management through accounting manipulation. However, this type of accounting manipulation should be taken into account and efforts should be made by control bodies to apply Eckel model and generalize its use at the global level.

Keywords: Income, smoothing, “Eckel”, French companies.

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Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang

Abstract:

In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Keywords: Deep learning, convolutional neural network, LSTM, housing prediction.

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Authors: H. D. Ibrahim, H. C. Chinwenyi, A. H. Usman

Abstract:

Valuing derivatives (options, futures, swaps, forwards, etc.) is one uneasy task in financial mathematics. The two ways this problem can be effectively resolved in finance is by the use of two methods (Martingales and Partial Differential Equations (PDEs)) to obtain their respective options price valuation formulas. This research paper examined two different stochastic financial models which are Constant Elasticity of Variance (CEV) model and Black-Karasinski term structure model. Assuming their respective option price valuation formulas, we proved the analogous of the Martingales and PDEs options price valuation formulas for the two different Stochastic Differential Equation (SDE) models. This was accomplished by using the applications of Girsanov theorem for defining an Equivalent Martingale Measure (EMM) and the Feynman-Kac theorem. The results obtained show the systematic proof for analogous of the two (Martingales and PDEs) options price valuation formulas beginning with the Martingales option price formula and arriving back at the Black-Scholes parabolic PDEs and vice versa.

Keywords: Option price valuation, Martingales, Partial Differential Equations, PDEs, Equivalent Martingale Measure, Girsanov Theorem, Feyman-Kac Theorem, European Put Option.

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Authors: Alhaji M. H. Conteh, Xiangbin Yan, Alfred V Gborie

Abstract:

Rice, which is the staple food in Sierra Leone, is consumed on a daily basis. It is the most imperative food crop extensively grown by farmers across all ecologies in the country. Though much attention is now given to rice grain production through the small holder commercialization programme (SHCP), however, no attention has been given in investigating the limitations faced by rice producers. This paper will contribute to attempts to overcome the development challenges caused by food insecurity. The objective of this paper is thus, to analysis the relationship between rice production and the domestic retail price of rice. The study employed a log linear model in which, the quantity of rice produced is the dependent variable, quantity of rice imported, price of imported rice and price of domestic rice as explanatory variables. Findings showed that, locally produced rice is even more expensive than the imported rice per ton, and almost all the inhabitants in the capital city which hosts about 65% of the entire population of the country favor imported rice, as it is free from stones with other impurities. On the other hand, to control price and simultaneously increase rice production, the government should purchase the rice from the farmers and then sell to private retailers.

Keywords: Domestic price of rice, Econometric model, Rice production, Sierra Leone.

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