Abstract: This research seeks to investigate the frequency and
profitability of index arbitrage opportunities involving the SET50
futures, SET50 component stocks, and the ThaiDEX SET50 ETF
(ticker symbol: TDEX). In particular, the frequency and profit of
arbitrage are measured in the following three arbitrage tests: (1)
SET50 futures vs. ThaiDEX SET50 ETF, (2) SET50 futures vs.
SET50 component stocks, and (3) ThaiDEX SET50 ETF vs. SET50
component stocks are investigated. For tests (2) and (3), the problems
involve conic optimization and quadratic programming as subproblems.
This research is first to apply conic optimization and
quadratic programming techniques in the context of index arbitrage
and is first to investigate such index arbitrage in the Thai equity and
derivatives markets. Thus, the contribution of this study is twofold.
First, its results would help understand the contribution of the
derivatives securities to the efficiency of the Thai markets. Second,
the methodology employed in this study can be applied to other
geographical markets, with minor adjustments.
Abstract: In this paper, we propose a hybrid machine learning
system based on Genetic Algorithm (GA) and Support Vector
Machines (SVM) for stock market prediction. A variety of indicators
from the technical analysis field of study are used as input features.
We also make use of the correlation between stock prices of different
companies to forecast the price of a stock, making use of technical
indicators of highly correlated stocks, not only the stock to be
predicted. The genetic algorithm is used to select the set of most
informative input features from among all the technical indicators.
The results show that the hybrid GA-SVM system outperforms the
stand alone SVM system.
Abstract: In the past decade, artificial neural networks (ANNs)
have been regarded as an instrument for problem-solving and
decision-making; indeed, they have already done with a substantial
efficiency and effectiveness improvement in industries and businesses.
In this paper, the Back-Propagation neural Networks (BPNs) will be
modulated to demonstrate the performance of the collaborative
forecasting (CF) function of a Collaborative Planning, Forecasting and
Replenishment (CPFR®) system. CPFR functions the balance between
the sufficient product supply and the necessary customer demand in a
Supply and Demand Chain (SDC). Several classical standard BPN will
be grouped, collaborated and exploited for the easy implementation of
the proposed modular ANN framework based on the topology of a
SDC. Each individual BPN is applied as a modular tool to perform the
task of forecasting SKUs (Stock-Keeping Units) levels that are
managed and supervised at a POS (point of sale), a wholesaler, and a
manufacturer in an SDC. The proposed modular BPN-based CF
system will be exemplified and experimentally verified using lots of
datasets of the simulated SDC. The experimental results showed that a
complex CF problem can be divided into a group of simpler
sub-problems based on the single independent trading partners
distributed over SDC, and its SKU forecasting accuracy was satisfied
when the system forecasted values compared to the original simulated
SDC data. The primary task of implementing an autonomous CF
involves the study of supervised ANN learning methodology which
aims at making “knowledgeable" decision for the best SKU sales plan
and stocks management.
Abstract: In this paper usefulness of quasi-Newton iteration
procedure in parameters estimation of the conditional variance
equation within BHHH algorithm is presented. Analytical solution of
maximization of the likelihood function using first and second
derivatives is too complex when the variance is time-varying. The
advantage of BHHH algorithm in comparison to the other
optimization algorithms is that requires no third derivatives with
assured convergence. To simplify optimization procedure BHHH
algorithm uses the approximation of the matrix of second derivatives
according to information identity. However, parameters estimation in
a/symmetric GARCH(1,1) model assuming normal distribution of
returns is not that simple, i.e. it is difficult to solve it analytically.
Maximum of the likelihood function can be founded by iteration
procedure until no further increase can be found. Because the
solutions of the numerical optimization are very sensitive to the
initial values, GARCH(1,1) model starting parameters are defined.
The number of iterations can be reduced using starting values close
to the global maximum. Optimization procedure will be illustrated in
framework of modeling volatility on daily basis of the most liquid
stocks on Croatian capital market: Podravka stocks (food industry),
Petrokemija stocks (fertilizer industry) and Ericsson Nikola Tesla
stocks (information-s-communications industry).
Abstract: This study aims to explore the relationship between the
disposition effect and herding behavior of investors trading Taiwanese
information technology stocks. This study differs from previous
literature in two aspects. First, in contrast with the earlier studies that
focused on investigating investors’ herding behavior, this study
explores the possibility that the disposition effect drives investors’
herding behavior. Additionally, it takes an in-depth look at the
interdependence between the disposition effect and herding behavior
of investors, including lead-lag relationship and volatility transmission
effect. Empirical results show that investors trading Taiwan’s
information technology stocks exhibit pronounced herding behavior
and that the disposition effect has a great impact on their herding
behavior.
Abstract: The catalytic dehydroxylation of glycerol to propylene
glycol was investigated over Cu-ZnO/Al2O3 prepared by incipient
wetness impregnation (IWI) method with different purity feedstocks -
refined glycerol and technical grade glycerol. The main purpose is to
investigate the effects of feed impurities that cause the catalyst
deactivation. The prepared catalyst were tested for its catalytic
activity and selectivity in a continuous flow fixed bed reactor at 523
K, 500 psig, H2/feed molar ratio of 4 and WHSV of 3 h-1. The results
showed that conversion of refined glycerol and technical grade
glycerol at time on stream 6 hour are 99% and 71% and selectivity to
propylene glycol are 87% and 56% respectively. The ICP-EOS and
TPO results indicated that the cause of catalyst deactivation was the
amount of impurities in the feedstock. The higher amount of
impurities (especially Na and K) the lower catalytic activity.
Abstract: Little attention has been paid to information
transmission between the portfolios of large stocks and small stocks in the Korean stock market. This study investigates the return and volatility transmission mechanisms between large and small stocks in
the Korea Exchange (KRX). This study also explores whether bad news in the large stock market leads to a volatility of the small stock
market that is larger than the good news volatility of the large stock market. By employing the Granger causality test, we found
unidirectional return transmissions from the large stocks to medium
and small stocks. This evidence indicates that pat information about
the large stocks has a better ability to predict the returns of the medium and small stocks in the Korean stock market. Moreover, by using the
asymmetric GARCH-BEKK model, we observed the unidirectional relationship of asymmetric volatility transmission from large stocks to
the medium and small stocks. This finding suggests that volatility in
the medium and small stocks following a negative shock in the large
stocks is larger than that following a positive shock in the large stocks.
Abstract: Hydrogenated biodiesel is one of the most promising
renewable fuels. It has many advantages over conventional biodiesel,
including higher cetane number, higher heating value, lower
viscosity, and lower corrosiveness due to its absence of oxygen.
From previous work, Pd/TiO2 gave high conversion and selectivity in
hydrogenated biodiesel. In this work, the effect of biomass feedstocks
(i.e. beef fat, chicken fat, pork fat, and jatropha oil) on the production
of hydrogenated biodiesel over Pd/TiO2 has been studied. Biomass
feedstocks were analyzed by ICP-OES (inductively coupled plasma
optical emission spectrometry) to identify the content of impurities
(i.e. P, K, Ca, Na, and Mg). The deoxygenation catalyst, Pd/TiO2,
was prepared by incipient wetness impregnation (IWI) and tested in a
continuous flow packed-bed reactor at 500 psig, 325°C, H2/feed
molar ratio of 30, and LHSV of 4 h-1 for its catalytic activity and
selectivity in hydrodeoxygenation. All feedstocks gave high
selectivity in diesel specification range hydrocarbons and the main
hydrocarbons were n-pentadecane (n-C15) and n-heptadecane (n-
C17), resulting from the decarbonylation/decarboxylation reaction.
Intermediates such as oleic acid, stearic acid, palmitic acid, and esters
were also detected in minor amount. The conversion of triglycerides
in jatropha oil is higher than those of chicken fat, pork fat, and beef
fat, respectively. The higher concentration of metal impurities in
feedstock, the lower conversion of feedstock.
Abstract: Underpricing is one anomaly in initial public offerings
(IPO) literature that has been widely observed across different stock
markets with different trends emerging over different time periods.
This study seeks to determine how IPOs on the JSE performed on the
first day, first week and first month over the period of 1996-2011.
Underpricing trends are documented for both hot and cold market
periods in terms of four main sectors (cyclical, defensive, growth
stock and interest rate sensitive stocks). Using a sample of 360 listed
companies on the JSE, the empirical findings established that IPOs
on the JSE are significantly underpriced with an average market
adjusted first day return of 62.9%. It is also established that hot
market IPOs on the JSE are more underpriced than the cold market
IPOs. Also observed is the fact that as the offer price per share
increases above the median price for any given period, the level of
underpricing decreases substantially. While significant differences
exist in the level of underpricing of IPOs in the four different sectors
in the hot and cold market periods, interest rates sensitive stocks
showed a different trend from the other sectors and thus require
further investigation to uncover this pattern.
Abstract: In the present research, steam cracking of two types of
feedstocks i.e., naphtha and ethane is simulated for Pyrocrack1-1 and
2/2 coil configurations considering two key parameters of coil outlet
temperature (COT) and coil capacity using a radical based kinetic
model. The computer model is confirmed using the industrial data
obtained from Amirkabir Petrochemical Complex. The results are in
good agreement with performance data for naphtha cracking in a
wide range of severity (0.4-0.7), and for ethane cracking on various
conversions (50-70). It was found that Pyrocrack2-2 coil type is an
appropriate choice for steam cracking of ethane at reasonable
ethylene yield while resulting in much lower tube wall temperature
while Pyrocrack1-1 coil type is a proper selection for liquid
feedstocks i.e. naphtha. It can be used for cracking of liquid
feedstocks at optimal ethylene yield whereas not exceeding the
allowable maximum tube temperature.
Abstract: In this paper, we apply the FM methodology to the
cross-section of Romanian-listed common stocks and investigate the
explanatory power of market beta on the cross-section of commons
stock returns from Bucharest Stock Exchange. Various assumptions
are empirically tested, such us linearity, market efficiency, the “no
systematic effect of non-beta risk" hypothesis or the positive
expected risk-return trade-off hypothesis. We find that the Romanian
stock market shows the same properties as the other emerging
markets in terms of efficiency and significance of the linear riskreturn
models. Our analysis included weekly returns from January
2002 until May 2010 and the portfolio formation, estimation and
testing was performed in a rolling manner using 51 observations (one
year) for each stage of the analysis.
Abstract: This research focus on developing a new segmentation method for improving forecasting model which is call trend based segmentation method (TBSM). Generally, the piece-wise linear representation (PLR) can finds some of pair of trading points is well for time series data, but in the complicated stock environment it is not well for stock forecasting because of the stock has more trends of trading. If we consider the trends of trading in stock price for the trading signal which it will improve the precision of forecasting model. Therefore, a TBSM with SVR model used to detect the trading points for various stocks of Taiwanese and America under different trend tendencies. The experimental results show our trading system is more profitable and can be implemented in real time of stock market
Abstract: This article presents the boundary conditions for the problem of turbulent supersonic gas flow in a plane channel with a perpendicular injection jets. The non-reflection boundary conditions for direct modeling of compressible viscous gases are studied. A formulation using the NSCBC (Navier- Stocks characteristic boundary conditions) through boundaries is derived for the subsonic inflow and subsonic non-reflection outflow situations. Verification of the constructed algorithm of boundary conditions is carried out by solving a test problem of perpendicular sound of jets injection into a supersonic gas flow in a plane channel.
Abstract: India is currently the second most populous nation in
the world with over 1.2 billion people, growing annually at the rate of
1.5%. It is experiencing a surge in energy demands, expected to grow
more than three to four times in 25 years. Most of the energy
requirements are currently satisfied by the import of fossil fuels –
coal, petroleum-based products and natural gas. Biofuels can satisfy
these energy needs in an environmentally benign and cost effective
manner while reducing dependence on import of fossil fuels, thus
providing National Energy Security. Among various forms of
bioenergy, bioethanol is one of the major options for India because of
availability of feed stock crops.
This paper presents an overview on bioethanol production and
technology, steps taken by the Indian government to facilitate and
bring about optimal development and utilization of indigenous
biomass feedstocks for production of this biofuel.
Abstract: The study analyzed the risk and returns of commercial-property in Southwestern Nigeria and selected stocksmarket investment between 2000 and 2009; compared the inflation hedging characteristics and diversification potentials of investing in commercial-property and selected stock- market investment. Primary data were collected on characteristics, rental and capital values of commercial- properties from their property managers through the use of questionnaire. Secondary data on stock prices and dividends on banking, insurance and conglomerates sectors were sourced from the Nigerian Stock Exchange (2000-2009). The result showed that average return on all the selected stock- investments was higher than that of commercial-property. As regards risk, commercial-property indicated lower risk, compared to stocks. Also the stock-investment had better inflation hedging capacity than commercial-properties; combination of both had diversification potentials. The study concluded that stock-market investment offered attractive higher return than commercial-property although with higher risk and there could be diversification benefits in combining commercial-property with stock- investment.
Abstract: Hydrogen is regarded to play an important role in
future energy systems because it can be produced from abundant
resources and its combustion only generates water. The disposal of
waste tyres is a major problem in environmental management
throughout the world. The use of waste materials as a source of
hydrogen is particularly of interest in that it would also solve a waste
treatment problem. There is much interest in the use of alternative
feedstocks for the production of hydrogen since more than 95% of
current production is from fossil fuels. The pyrolysis of waste tyres
for the production of liquid fuels, activated carbons and gases has
been extensively researched. However, combining pyrolysis with
gasification is a novel process that can gasify the gaseous products
from pyrolysis. In this paper, an experimental investigation into the
production of hydrogen and other gases from the bench scale
pyrolysis-gasification of tyres has been investigated. Experiments
were carried using a two stage system consisting of pyrolysis of the
waste tyres followed by catalytic steam gasification of the evolved
gases and vapours in a second reactor. Experiments were conducted
at a pyrolysis temperature of 500 °C using Ni/Al2O3 as a catalyst. The
results showed that there was a dramatic increase in gas yield and the
potential H2 production when the gasification temperature was
increased from 600 to 900 oC. Overall, the process showed that high
yields of hydrogen can be produced from waste tyres.
Abstract: This interdisciplinary study is an investigation to evaluate user-interfaces in business administration. The study is going to be implemented on two computerized business administration systems with two distinctive user-interfaces, so that differences between the two systems can be determined. Both systems, a commercial and a prototype developed for the purpose of this study, deal with ordering of supplies, tendering procedures, issuing purchase orders, controlling the movement of the stocks against their actual balances on the shelves and editing them on their tabulations. In the second suggested system, modern computer graphics and multimedia issues were taken into consideration to cover the drawbacks of the first system. To highlight differences between the two investigated systems regarding some chosen standard quality criteria, the study employs various statistical techniques and methods to evaluate the users- interaction with both systems. The study variables are divided into two divisions: independent representing the interfaces of the two systems, and dependent embracing efficiency, effectiveness, satisfaction, error rate etc.
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.
Abstract: It is well known that during the developments in the
economic sector and through the financial crises occur everywhere in
the whole world, volatility measurement is the most important
concept in financial time series. Therefore in this paper we discuss
the volatility for Amman stocks market (Jordan) for certain period of
time. Since wavelet transform is one of the most famous filtering
methods and grows up very quickly in the last decade, we compare
this method with the traditional technique, Fast Fourier transform to
decide the best method for analyzing the volatility. The comparison
will be done on some of the statistical properties by using Matlab
program.