An Application of Extreme Value Theory as a Risk Measurement Approach in Frontier Markets

In this paper, we consider the application of Extreme Value Theory as a risk measurement tool. The Value at Risk, for a set of indices, from six Stock Exchanges of Frontier markets is calculated using the Peaks over Threshold method and the performance of the model index-wise is evaluated using coverage tests and loss functions. Our results show that “fattailedness” alone of the data is not enough to justify the use of EVT as a VaR approach. The structure of the returns dynamics is also a determining factor. This approach works fine in markets which have had extremes occurring in the past thus making the model capable of coping with extremes coming up (Colombo, Tunisia and Zagreb Stock Exchanges). On the other hand, we find that indices with lower past than present volatility fail to adequately deal with future extremes (Mauritius and Kazakhstan). We also conclude that using EVT alone produces quite static VaR figures not reflecting the actual dynamics of the data.

Features of Rail Strength Analysis in Conditions of Increased Force Loading

In the article are considered the problems arising at increasing of transferring from rolling stock axles on rail loading from 210 KN up to 270 KN and is offered for rail strength analysis definition of rail force loading complex integral characteristic with taking into account all affecting force factors that is characterizing specific operation condition of rail structure and defines the working capability of structure. As result of analysis due mentioned method is obtained that in the conditions of 270 KN loading the rail meets the working assessment criteria of rail and rail structures: Strength, rail track stability, rail links stability and its transverse stability, traffic safety condition that is rather important for post-Soviet countries railways.

Financial Ethics: A Review of 2010 Flash Crash

Modern day stock markets have almost entirely became automated. Even though it means increased profits for the investors by algorithms acting upon the slightest price change in order of microseconds, it also has given birth to many ethical dilemmas in the sense that slightest mistake can cause people to lose all of their livelihoods. This paper reviews one such event that happened on May 06, 2010 in which $1 trillion dollars disappeared from the Dow Jones Industrial Average. We are going to discuss its various aspects and the ethical dilemmas that have arisen due to it.

The Reliability of Management Earnings Forecasts in IPO Prospectuses: A Study of Managers’ Forecasting Preferences

This study investigates the reliability of management earnings forecasts with reference to these two ingredients: verifiability and neutrality. Specifically, we examine the biasedness (or accuracy) of management earnings forecasts and company specific characteristics that can be associated with accuracy. Based on sample of 102 IPO prospectuses published for admission on NYSE Euronext Paris from 2002 to 2010, we found that these forecasts are on average optimistic and two of the five test variables, earnings variability and financial leverage are significant in explaining ex post bias. Acknowledging the possibility that the bias is the result of the managers’ forecasting behavior, we then examine whether managers decide to under-predict, over-predict or forecast accurately for self-serving purposes. Explicitly, we examine the role of financial distress, operating performance, ownership by insiders and the economy state in influencing managers’ forecasting preferences. We find that managers of distressed firms seem to over-predict future earnings. We also find that when managers are given more stock options, they tend to under-predict future earnings. Finally, we conclude that the management earnings forecasts are affected by an intentional bias due to managers’ forecasting preferences.

Effect of Windrow Management on Ammonia and Nitrous Oxide Emissions from Swine Manure Composting

In the era of sustainability, utilization of livestock wastes as soil amendment to provide micronutrients for crops is very economical and sustainable. It is well understood that livestock wastes are comparable, if not better, nutrient sources for crops as chemical fertilizers. However, the large concentrated volumes of animal manure produced from livestock operations and the limited amount of available nearby agricultural land areas necessitated the need for volume reduction of these animal wastes. Composting of these animal manures is a viable option for biomass and pathogenic reduction in the environment. Nevertheless, composting also increases the potential loss of available nutrients for crop production as well as unwanted emission of anthropogenic air pollutants due to the loss of ammonia and other compounds via volatilization. In this study, we examine the emission of ammonia and nitrous oxide from swine manure windrows to evaluate the benefit of biomass reduction in conjunction with the potential loss of available nutrients. The feedstock for the windrows was obtained from swine farm in Kentucky where swine manure was mixed with wood shaving as absorbent material. Static flux chambers along with photoacoustic gas analyzer were used to monitor ammonia and nitrous oxide concentrations during the composting process. The results show that ammonia and nitrous oxide fluxes were quite high during the initial composting process and after the turning of each compost pile. Over the period of roughly three months of composting, the biochemical oxygen demand (BOD) decreased by about 90%. Although composting of animal waste is quite beneficial for biomass reduction, composting may not be economically feasible from an agronomical point of view due to time, nutrient loss (N loss), and potential environmental pollution (ammonia and greenhouse gas emissions). Therefore, additional studies are needed to assess and validate the economics and environmental impact of animal (swine) manure composting (e.g., crop yield or impact on climate change).

Construct the Fur Input Mixed Model with Activity-Based Benefit Assessment Approach of Leather Industry

Leather industry is the most important traditional industry to provide the leather products in the world for thousand years. The fierce global competitive environment and common awareness of global carbon reduction make livestock supply quantities falling, salt and wet blue leather material reduces and the price skyrockets significantly. Exchange rate fluctuation led sales revenue decreasing which due to the differences of export exchanges and compresses the overall profitability of leather industry. This paper applies activity-based benefit assessment approach to build up fitness fur input mixed model, fur is Wet Blue, which concerned with four key factors: the output rate of wet blue, unit cost of wet blue, yield rate and grade level of Wet Blue to achieve the low cost strategy under given unit price of leather product condition of the company. The research findings indicate that applying this model may improve the input cost structure, decrease numbers of leather product inventories and to raise the competitive advantages of the enterprise in the future.

Total Lipid of Mutant Synechococcus sp. PCC 7002

Microalgae lipid is a promising feedstock for biodiesel production. The objective of this work was to study growth factors affecting marine mutant Synechococcus sp. (PCC 7002) for high lipid production. Four growth factors were investigated; nitrogen-phosporus-potassium (NPK) concentration, light intensity, temperature and NaNO3 concentration on mutant strain growth and lipid production were studied. Design Expert v8.0 was used to design the experimental and analyze the data. The experimental design selected was Min-Run Res IV which consists of 12 runs and the response surfaces measured were specific growth rate and lipid concentration. The extraction of lipid was conducted by chloroform/methanol solvents system. Based on the study, mutant Synechococcus sp. PCC 7002 gave the highest specific growth rate of 0.0014 h-1 at 0% NPK, 2500 lux, 40oC and 0% NaNO3. On the other hand, the highest lipid concentration was obtained at 0% NPK, 3500 lux, 30oC and 1% NaNO3.

Life Cycle Assessment Comparison between Methanol and Ethanol Feedstock for the Biodiesel from Soybean Oil

As the limited availability of petroleum-based fuel has been a major concern, biodiesel is one of the most attractive alternative fuels because it is renewable and it also has advantages over the conventional petroleum-base diesel. At Present, productions of biodiesel generally perform by transesterification of vegetable oils with low molecular weight alcohol, mainly methanol, using chemical catalysts. Methanol is petrochemical product that makes biodiesel producing from methanol to be not pure renewable energy source. Therefore, ethanol as a product produced by fermentation processes. It appears as a potential feed stock that makes biodiesel to be pure renewable alternative fuel. The research is conducted based on two biodiesel production processes by reacting soybean oils with methanol and ethanol. Life cycle assessment was carried out in order to evaluate the environmental impacts and to identify the process alternative. Nine mid-point impact categories are investigated. The results indicate that better performance on abiotic depletion potential (ADP) and acidification potential (AP) are observed in biodiesel production from methanol when compared with biodiesel production from ethanol due to less energy consumption during the production processes. Except for ADP and AP, using methanol as feed stock does not show any advantages over biodiesel from ethanol. The single score method is also included in this study in order to identify the best option between two processes of biodiesel production. The global normalization and weighting factor based on ecotaxes are used and it shows that producing biodiesel form ethanol has less environmental load compare to biodiesel from methanol.

Regulation of Transfer of 137cs by Polymeric Sorbents for Grow Ecologically Sound Biomass

Soil contamination with radiocesium has a long-term radiological impact due to its long physical half-life (30.1 years for 137Cs and 2 years for 134Cs) and its high biological availability. 137Cs causes the largest concerns because of its deleterious effect on agriculture and stock farming, and, thus, human life for decades. One of the important aspects of the problem of contaminated soils remediation is understand of protective actions aimed at the reduction of biological migration of radionuclides in soil-plant system. The most effective way to bind radionuclides is the use of selective sorbents. The proposed research mainly aims to achieve control on transfer of 137Cs in a system growing media – plant due to counter ions variation in the polymeric sorbents. As research object Japanese basil - Perilla frutescens was chosen. Productivity of plants depending on the presence (control-without presence of polymer) and type of polymer material, as well as content of 137Cs in plant material has been determined. The character of different polymers influences on the 137Cs migration in growing media – plant system as well as accumulation in the plants has been cleared up.

Target and Equalizer Design for Perpendicular Heat-Assisted Magnetic Recording

Heat-Assisted Magnetic Recording (HAMR) is one of the leading technologies identified to enable areal density beyond 1 Tb/in2 of magnetic recording systems. A key challenge to HAMR designing is accuracy of positioning, timing of the firing laser, power of the laser, thermo-magnetic head, head-disk interface and cooling system. We study the effect of HAMR parameters on transition center and transition width. The HAMR is model using Thermal Williams-Comstock (TWC) and microtrack model. The target and equalizer are designed by the minimum mean square error (MMSE). The result shows that the unit energy constraint outperforms other constraints.

Migration of the Relational Data Base (RDB) to the Object Relational Data Base (ORDB)

This paper proposes an approach for translating an existing relational database (RDB) schema into ORDB. The transition is done with methods that can extract various functions from a RDB which is based on aggregations, associations between the various tables, and the reflexive relationships. These methods can extract even the inheritance knowing that no process of reverse engineering can know that it is an Inheritance; therefore, our approach exceeded all of the previous studies made for ​​the transition from RDB to ORDB. In summation, the creation of the New Data Model (NDM) that stocks the RDB in a form of a structured table, and from the NDM we create our navigational model in order to simplify the implementation object from which we develop our different types. Through these types we precede to the last step, the creation of tables. The step mentioned above does not require any human interference. All this is done automatically, and a prototype has already been created which proves the effectiveness of this approach.

Volatility Switching between Two Regimes

Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most successful and popular models in modeling time varying volatility are GARCH type models. When financial returns exhibit sudden jumps that are due to structural breaks, standard GARCH models show high volatility persistence, i.e. integrated behavior of the conditional variance. In such situations models in which the parameters are allowed to change over time are more appropriate. This paper compares different GARCH models in terms of their ability to describe structural changes in returns caused by financial crisis at stock markets of six selected central and east European countries. The empirical analysis demonstrates that Markov regime switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility when sudden switching occurs in response to financial crisis.

ATM Service Analysis Using Predictive Data Mining

The high utilization rate of Automated Teller Machine (ATM) has inevitably caused the phenomena of waiting for a long time in the queue. This in turn has increased the out of stock situations. The ATM utilization helps to determine the usage level and states the necessity of the ATM based on the utilization of the ATM system. The time in which the ATM used more frequently (peak time) and based on the predicted solution the necessary actions are taken by the bank management. The analysis can be done by using the concept of Data Mining and the major part are analyzed based on the predictive data mining. The results are predicted from the historical data (past data) and track the relevant solution which is required. Weka tool is used for the analysis of data based on predictive data mining.

Development of Efficient Fungal Biomass-Degrading Enzyme Mixtures for Saccharification of Local Lignocellulosic Feedstock

Conversion of lignocellulosic biomass is the basis process for production of fuels, chemicals and materials in the sustainable biorefinery industry. Saccharification of lignocellulosic biomass is an essential step which produces sugars for further conversion to target value-added products e.g. bio-ethanol, bio-plastic, g-valerolactone (GVL), 5-hydroxymethylfuroic acid (HMF), levulinic acid, etc. The goal of this work was to develop an efficient enzyme for conversion of biomass to reducing sugar based on crude fungal enzyme from Chaetomium globosum BCC5776 produced by submerged fermentation and evaluate its activity comparing to a commercial Acremonium cellulase. Five local biomasses in Thailand: rice straw, sugarcane bagasse, corncobs, corn stovers, and palm empty fruit bunches were pretreated and hydrolyzed with varying enzyme loadings. Saccharification of the biomass led to different reducing sugar levels from 115 mg/g to 720 mg/g from different types of biomass using cellulase dosage of 9 FPU/g. The reducing sugar will be further employed as sugar feedstock for production of ethanol or commodity chemicals. This work demonstrated the use of promising enzyme candidate for conversion of local lignocellulosic biomass in biorefinery industry.

Hydrogen Production from Dehydrogenation of Ethanol over Ag-Based Catalysts

The development of alternative energy is interesting in the present especially, hydrogen production because it is an important energy resource in the future. This paper studied the hydrogen production from catalytic dehydrogenation of ethanol through via low temperature (

Preparation and Properties of Biopolymer from L-Lactide (LL) and ε-Caprolactone (CL)

Biopolymers have gained much attention as ecofriendly alternatives to petrochemical-based plastics because they are biodegradable and can be produced from renewable feedstocks. One class of biopolyester with many potential environmentally friendly applications is polylactic acid (PLA) and polycaprolactone (PCL). The PLA/PCL biodegradable copolyesters were synthesized by bulk ring-opening copolymerization of successively added Llactide (LL) and ε-caprolactone (CL) in the presence of toluene, using 1-hexanol as initiator and stannous octoate (Sn(Oct)2) as catalyst. Reaction temperature, reaction time and amount of catalyst were evaluated to obtain optimum reaction conditions. The results showed that the %conversion increased with increases in reaction temperature and reaction time, but after a critical amount of catalyst was reached the %conversion decreased. The yield of PLA/PCL biopolymer achieved 98.02% at the reaction temperature 160 °C, amount of catalyst 0.3 mol% and reaction time of 48 h. In addition, the thermal properties of the product were determined by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA).

Improving Order Quantity Model with Emergency Safety Stock (ESS)

This study considers the problem of calculating safety stocks in disaster situations inventory systems that face demand uncertainties. Safety stocks are essential to make the supply chain, which is controlled by forecasts of customer needs, in response to demand uncertainties and to reach predefined goal service levels. To solve the problem of uncertainties due to the disaster situations affecting the industry sector, the concept of Emergency Safety Stock (ESS) was proposed. While there exists a huge body of literature on determining safety stock levels, this literature does not address the problem arising due to the disaster and dealing with the situations. In this paper, the problem of improving the Order Quantity Model to deal with uncertainty of demand due to disasters is managed by incorporating a new idea called ESS which is based on the probability of disaster occurrence and uses probability matrix calculated from the historical data. 

A Comparative Study between Discrete Wavelet Transform and Maximal Overlap Discrete Wavelet Transform for Testing Stationarity

In this paper the core objective is to apply discrete wavelet transform and maximal overlap discrete wavelet transform functions namely Haar, Daubechies2, Symmlet4, Coiflet2 and discrete approximation of the Meyer wavelets in non stationary financial time series data from Dow Jones index (DJIA30) of US stock market. The data consists of 2048 daily data of closing index from December 17, 2004 to October 23, 2012. Unit root test affirms that the data is non stationary in the level. A comparison between the results to transform non stationary data to stationary data using aforesaid transforms is given which clearly shows that the decomposition stock market index by discrete wavelet transform is better than maximal overlap discrete wavelet transform for original data.

Physical and Chemical Properties Analysis of Jatropha curcas Seed Oil for Industrial Applications

A study on the physicochemical properties of Jatropha curcas seed oil for industrial applications were carried out. Physicochemical properties of J. curcas seed oil (59.32% lipids) showed high content of LA (36.70%), iodine value (104.90 mg/g) and saponification value (203.36 mg/g). The present study shows that, J. curcas seed oil is rich in oleic and linoleic acids. The J. curcas seed oil with the highest amount of polyunsaturated fatty acids (linoleic acid) can find an application in surface coating industries and biolubricant base oil applications, whereas the high amount of monounsaturated fatty acid can find an application as a biodiesel feed stock. J. curcas seed oil contains major TAG of monounsaturated OLL, POL, SLL, PLL, OOL, OOO and POP followed by LLL. J. curcas seed oil can be classified as unsaturated oil with an unsaturated fat level of 80.42%. Hence the J. curcas seed oil has great potential for industrial applications such as in paint and surface coatings, production of biodiesel and biolubricant. Therefore, it is crucial to have more research on J. curcas seed oil in the future to explore its potential as a future industrial oilseed crop.

Effect of Open Burning on Soil Carbon Stock in Sugarcane Plantation in Thailand

Open burning of sugarcane fields is recognized to have a negative impact on soil by degrading its properties, especially soil organic carbon (SOC) content. Better understating the effect of open burning on soil carbon dynamics is crucial for documenting the carbon sequestration capacity of agricultural soils. In this study, experiments to investigate soil carbon stocks under burned and unburned sugarcane plantation systems in Thailand were conducted. The results showed that cultivation fields without open burning during 5 consecutive years enabled to increase the SOC content at a rate of 1.37 Mg ha-1y-1. Also it was found that sugarcane fields burning led to about 15% reduction of the total carbon stock in the 0-30 cm soil layer. The overall increase in SOC under unburned practice is mainly due to the large input of organic material through the use of sugarcane residues.