Asymmetric Price Impacts of Order Flow on Exchange Rate Dynamics

We generalize the portfolio shifts model advanced by Evans and Lyons (2002a; b), and develop the dynamic asymmetric portfolio shifts (DAPS) model by explicitly allowing for possible market under- and overreactions and for asymmetric pricing impacts of order flows. Using the Reuters D2000-1 daily trading data for eight currency markets over a four-month period from 1 May to 31 August 1996, we find strong evidence of a nonlinear cointegrating relationship between exchange rates and (cumulative) order flows: The price impact of negative order flows (selling pressure) is overwhelmingly stronger than that of the positive ones (buying pressure). Through the dynamic multiplier analysis, we find two typical patterns of the price discovery process. The markets following overreactions tend to display a delayed overshooting and a volatile but faster adjustment towards equilibrium whereas the markets following underreactions are generally characterized by a gradual but persistent adjustment. In our model, these heterogeneous adjustment patterns reflect different liquidity provisions associated with different market conditions following under- and overreactions. In addition, the larger is the mispricing, the faster is the overall adjustment speed, a finding consistent with Abreu and Brunnermeier (2002) and Cai et al. (2011). We also find that underreactions are followed mostly by positive feedback trading while overreactions are characterized by delayed overshooting in the short run but corrected by negative feedback trading at longer horizons, the finding is consistent with Barberis et al. (1998) who show that positive short-run autocorrelations (momentum) signal underreaction while negative long-run autocorrelations (reversal) signal overreaction.Exchange rate, order flow, under- and overreaction, asymmetric pricing impacts, asymmetric cointegrating relationship and dynamic multipliers

Sedimentological and Petrophysical Properties of Sandstone Facies belonging to Lambir Formation at Tusan Beach, Miri, Sarawak.

Understanding the sedimentological and petrophysical properties (porosity, permeability, density) of Early to Late Miocene Lambir Formation in Miri, Sarawak is essential for the reservoir characterization process of this formation’s equivalent located at offshore West Baram Delta. This project focuses on investigating a part of Lambir Formation, which is exposed in Tusan Beach area, along Miri - Bintulu coastline. The lithofacies of Lambir Formation in Tusan Beach area are originated from tidal influenced shallow marine environment, which could possibly make up good hydrocarbon reservoir. Sedimentary features related to shallow marine deposition such as ripple marks, cross beddings, and burrows are commonly seen in this formation. Two outcrops were observed and logged in order to investigate the facies characteristics and petrophysical properties of sandstones belong to Lambir Formation in the study area. In total five sandstone facies had been identified: i) Massive sandstone; ii) Trough cross-bedded sandstone; iii) Herringbone cross-bedded sandstone; iv) Tabular cross-bedded sandstone; v) Hummocky cross-bedded sandstone. Poro-perm results show high to very high permeability (1105mD to 3018mD) and very good porosity (25.3% to 28.7%) values in all samples, indicating excellent reservoir quality. Generally, samples belong to trough cross-bedded sandstone facies (sample 1, 5, and 6) recorded highest porosity and permeability values, followed by hummocky cross-bedded sandstones (sample 3 and 4) and lastly, herringbone cross-bedded sandstone (sample 2). Less mud content and coarser grain size in trough cross-bedded samples had contributed to this result. Observations also suggest that horizontal permeability is generally higher than vertical permeability of the same facies. High permeability anisotropy is observed in trough cross-bedded and hummocky cross-bedded sandstone facies, reflected through low kV/kH ratios, ranging from 0.42 to 0.55. Permeability distribution of onshore samples can be used as a proxy to predict the permeability trend of this formation offshore

異なる養生条件下におけるスラグ膨張コンクリートの性能評価

広島大学(Hiroshima University)博士(工学)Doctor of Engineeringdoctora

Solid waste management in Mekong Delta: Review Paper

Municipal solid waste (MSW) in Vietnam has been increasing quickly and became one of the most considered environmental problems in Mekong Delta (MD) region covering 13 provinces and municipalities in the south of Vietnam. With a considerably large amount of MSW, the region produces about 5% of the total amount of MSW of the country. The collection rate of solid waste is about quite high (65 - 72%) in the cities and rather low (about 40 - 55%) in the rural areas, with a high content in organic matter (about 60 - 85%). The climate of MD can be characterized as tropical and monsoonal with a high rate of humidity and a strong impact of flooding. Like other regions too, the MSW collection and treatment system is still underdeveloped and rudimentary, with disposal sites being the sole dumping method of the unsorted MSW remaining untreated by any mechanical and biological pre-treatment steps. Within this paper, the current treatment, management and operation of MSW systems are introduced, as well as the identification of advantages and disadvantages, environmental impacts, potential risks of the MSW system within the impact of global climate change. The situation of MSW treatment and management is correlated with the climate change impact and the integrated solid waste management is introduced as a new approach for adapting the environmental protection awareness by considering the climate change for the longterm sustainable development orientation.Sự gia tăng chất thải rắn ở các đô thị Việt Nam ngày càng nhanh và chất thải rắn đang là một trong những vấn đề môi trường được quan tâm hàng đầu. Đồng bằng Sông Cửu Long (ĐBSCL) nơi có đến 13 tỉnh và thành phố nằm ở phía Nam Việt Nam. Với lượng chất thải không nhỏ, chiếm khoảng 5 % tổng lượng chất thải rắn sinh hoạt của quốc gia. Tỷ lệ thu gom chất thải rắn thấp, chiếm khoảng 65 - 72 % ở thành thị, tỷ lệ này ở nông thôn thấp 40 - 55%, chất thải có hàm lượng hữu cơ cao chiếm khoảng 60 - 85%. Khí hậu nhiệt đới gió mùa với độ ẩm không khí cao và chịu ảnh hưởng lớn của lũ lụt hàng năm. Cũng như các khu vực khác, hệ thống thu gom và xử lý rác thải ở khu vực ĐBSCL còn rất thô sơ và lạc hậu, bãi rác là nơi duy nhất tiếp nhận trực tiếp hổnhợp rác thải không phân loại và qua bất kỳ công đoạn tiền xử lý nào. Trong phạm vi bài viết này, chúng tôi giới thiệu hoạt động vận hành hệ thống quản lý và xử lý rác đô thị trong khu vực đồng thời phân tích các thuận lợi và bất lợi, cũng như các tác động môi trường, những rủi ro tiềm ẩn trong điều kiện ảnh hưởng của biến đổi khí hậu toàn cầu - khu vực ĐBSCL là nơi chịu ảnh hưởng nặng nề nhất. Tình hình quản lý và xử lý rác được cân nhắc trong điều kiện tác động của biến đổi khí hậu, đồng thời quản lý tổng hợp rác thải cũng được đề xuất như một các tiếp cận mới nhằm đáp ứng nhiệm vụ bảo vệ môi trường trong điều kiện biến đổi khí hậu theo định hướng phát triển bền vững lâu dài

APPLICATION OF DATA ENVELOPMENT ANALYSIS FOR MEASURING SERVICE QUALITY FROM DISTRIBUTORS’ PERSPECTIVE IN SUPPLY CHAIN

Abstract: Vietnam’s textile and apparel sector has achieved fast and sustainable growth over the past years and played an important role in national socio-economic development. The export value of textile and garment products in recent years has ranked number two in the country’s total export revenue. In this scenario, an attempt was made to examine the service quality at the manufacturer – distributor interface of the textile supply chain and provide clear guidelines for benchmarking of service quality in multi-unit services. A sample of 144 distributors from Small and Medium Enterprises (SMEs) in major regions of South Vietnam was selected. Exploratory Factor Analysis was used to identify the critical factors of service quality. This research applies the data envelopment analysis (DEA) approach to the computation of a measure of overall service quality and benchmarking when measuring service quality with the Service Performance model. Dealing with the five dimensions of Service Performance (SERVPERF) as outputs, the proposed approach uses DEA as a tool for multiple criteria decision making (MCDM), in particular, the pure output DEA model without inputs. Data envelopment analysis measures the relative efficiency of decision-making units (DMUs) and identifies a set of corresponding efficient DMUs that can be used as benchmarks for the improvement of inefficient DMUs. The findings shed valuable insights on measures and critical underlying dimensions of service quality in the context of the supply chain in the textile industry, specifically from the distributor perspective. The results also give the best performer in textile SMEs and set the benchmarking guideline within each group among SEMsKeywords: service quality, data envelopment analysis, SERVPER

A Model for Detecting Accounting Frauds by using Machine Learning

This paper aims to develop a machine learning model that enables to predict signs of financial statement frauds by combining the domain knowledge of machine learning and accounting. Inputs of this model is a published dataset of financial statements, and outputs involve the conclusions whether the predicted financial statements indicate the signs of financial statement frauds or not. Currently, XGBoost is recognized as one of the most popular classification methods with fast performance, flexibility, and scalability. However, its default properties are not suitable for fraudulent detecting of imbalanced datasets. To overcome this drawback, this research introduces a new machine learning model based on XGBoost technique, called f(raud)-XGBoost. The proposed model not only inherits XGBoost advantages but also enables it to detect financial statement frauds. We apply the Area Under the Receiver Operating Characteristics Curve and NDCG@k to perform the evaluation process. The experimental results show that the new model performs slightly better than three existing models including logistic regression model that is based on financial ratios, Support-vector-machine model, and RUSBoost mode