Three essays on the time series of returns

This dissertation consists of three essays on the time series of asset returns. The first essay in Chapter 1--Time-Varying Drivers of Stock Prices--provides novel evidence of the time-varying roles of subjective expectations in explaining stock price variations across the market and 30 industry portfolios monthly from 1976 to 2020. Cash flow expectations matter more under financial uncertainty and recessions, especially among the hardest-hit industries such as Telecommunications during the Dot-com Bubble, Financials during the Great Recession, and Healthcare during the Covid-19 pandemic. Conversely, discount rates explain more price variations during expansionary periods. Finally, inflation expectations, while accounting for 60 percent of price fluctuations in the high inflationary environment before 2000, play a negligible role thereafter. In the second essay in Chapter 2--Investor Sentiment and Asset Returns: Actions Speak Louder than Words--I analyze daily predictability of investor sentiment across four major asset classes and compares sentiment measures based on news and social media with those based on trade information. For the majority of assets, trade-based sentiment measures outperform their text-based equivalents for both in-sample and out-of-sample predictions. This outperformance is particularly noticeable in long-term forecasts. However, real-time mean-variance investors can only achieve economic gains using Bitcoin trade sentiment, suggesting the challenge of transforming sentiment into daily profitable trading strategies. In the last essay in Chapter 3--War Discourse and Disaster Premia: 160 Years of Evidence from Stock and Bond Markets--using a semi-supervised topic model on 7,000,000 New York Times articles spanning 160 years, I test whether topics of media discourse predict future stock and bond market returns to test rational and behavioral hypotheses about market valuation of disaster risk. Focusing on media discourse addresses the challenge of sample size even when major disasters are rare. Our methodology avoids look-ahead bias and addresses semantic shifts. War discourse positively predicts market returns, with an out-of-sample R2 of 1.35 percent, and negatively predicts returns on short-term government and investment-grade corporate bonds. The predictive power of war discourse increases in more recent time periods.Includes bibliographical references

Coral reef fishes in the banks and rocky islands in the offshore waters of Binh Thuan province

Binh Thuan province is located in the South Central Coast of Vietnam with favorable conditions for living coral reefs. The coral reefs were mainly investigated in coastal water areas and Phu Quy island, meanwhile other areas such as the banks and rocky islands seem to lack information. This study was conducted to evaluate the species composition and distribution of coral reef fish communities in the Royal Bishop banks and around rocky islands in Julia shoal in the offshore waters of Binh Thuan province in April 2019. A total of 151 species belonging to 86 genera and 33 families of coral reef fishes were recorded. Among them, 4 species for the first time recorded in Vietnam are Helcogramma striata (Hansen, 1986) (Tripterygiidae), Pseudanthias squamipinnis (Peters, 1855) (Serranidae), Bodianus bilunulatus (Lacepède, 1801) and Coris aygula (Lacepède, 1801) (Labridae). The total average density of coral reef fish in the offshore waters of Binh Thuan is quite high at 1,104.9 ± 617 individuals/250 m2, most of them are small sized fish and ornamental fish group, the large sized fish and target fish group accounts for a relatively low rate, but their density here is much higher compared to that in the coastal waters of Binh Thuan province. The comparative analysis also shows that sites in coral reef around rocky islands have species richness and density of coral reef fish higher than the bank area

From Disfluency Detection to Intent Detection and Slot Filling

We present the first empirical study investigating the influence of disfluency detection on downstream tasks of intent detection and slot filling. We perform this study for Vietnamese -- a low-resource language that has no previous study as well as no public dataset available for disfluency detection. First, we extend the fluent Vietnamese intent detection and slot filling dataset PhoATIS by manually adding contextual disfluencies and annotating them. Then, we conduct experiments using strong baselines for disfluency detection and joint intent detection and slot filling, which are based on pre-trained language models. We find that: (i) disfluencies produce negative effects on the performances of the downstream intent detection and slot filling tasks, and (ii) in the disfluency context, the pre-trained multilingual language model XLM-R helps produce better intent detection and slot filling performances than the pre-trained monolingual language model PhoBERT, and this is opposite to what generally found in the fluency context.Comment: In Proceedings of INTERSPEECH 202

Statistical deconvolution of the free Fokker-Planck equation at fixed time

We are interested in reconstructing the initial condition of a non-linear partial differential equation (PDE), namely the Fokker-Planck equation, from the observation of a Dyson Brownian motion at a given time $t>0$. The Fokker-Planck equation describes the evolution of electrostatic repulsive particle systems, and can be seen as the large particle limit of correctly renormalized Dyson Brownian motions. The solution of the Fokker-Planck equation can be written as the free convolution of the initial condition and the semi-circular distribution. We propose a nonparametric estimator for the initial condition obtained by performing the free deconvolution via the subordination functions method. This statistical estimator is original as it involves the resolution of a fixed point equation, and a classical deconvolution by a Cauchy distribution. This is due to the fact that, in free probability, the analogue of the Fourier transform is the R-transform, related to the Cauchy transform. In past literature, there has been a focus on the estimation of the initial conditions of linear PDEs such as the heat equation, but to the best of our knowledge, this is the first time that the problem is tackled for a non-linear PDE. The convergence of the estimator is proved and the integrated mean square error is computed, providing rates of convergence similar to the ones known for non-parametric deconvolution methods. Finally, a simulation study illustrates the good performances of our estimator

NGUỒN LỢI VÀ NGUỒN GIỐNG HẢI SẢN TRONG VỊNH NHA TRANG

Assessments of commercial and seed resources of target marine species exploited in Nha Trang bay were conducted in 2014 - 2015 through 8 consultations with 8 local communes/wards surrounding the bay in combination with 4 field surveys (December 2014; May, August and September 2015) to assess locations of important spawning and nursery grounds of target resources. Results from this study showed that there were 25 target resources of abalones, lambis and turbo snails, top shells, strawberry conch, scallops, squids and cuttlefish, swimming crab, spiny lobsters, sea cucumbers, rabbitfishes, anchovies, breams, scads and ponyfishes with an annual commercial catch and revenue of 651.3 tonnes and 65 billion VND respectively in 2014. The reef related resources contributed similar catch and higher revenue (323.9 tons and 21.56 billion VND) than the reef resources (327.4 tons and 11.11 billion VND), in which rabbitfish was the most important group. In addition, harvesting of seeds of spiny lobsters for marine aquaculture was also important activity to fishery in the bay, giving a total catch and revenue of  212.000 seeds and 32.34 billion VND per year and this revenue was 3 times higher than that of the commercial resources directly harvested from the reefs. The Sargassum beds and coral reefs in the bay were important spawning and nursery grounds for squids, abalones, turbo snails, top shells, spiny lobsters and rabbitfishes.Đánh giá hiện trạng nguồn lợi và nguồn giống hải sản khai thác trong vịnh Nha Trang được thực hiện thông qua việc tổ chức 8 cuộc tham vấn cộng đồng tại các xã/phường ven biển (tháng 12/2014) kết hợp với 4 đợt khảo sát thực địa (tháng 12/2014; tháng 5, 8 và 9/2015) nhằm xác định khu vực phân bố của các bãi nguồn giống hải sản quan trọng vào năm 2014 và 2015. Kết quả khảo sát ghi nhận trên 25 nhóm đối tượng nguồn lợi chủ yếu (bào ngư, ốc bàn tay, ốc đụn, ốc mặt trăng, ốc nhảy đỏ lợi, điệp nhật nguyệt, điệp quạt, điệp đỏ, điệp vỏ dày, mực lá, mực nang, mực ống, ghẹ ba chấm, tôm tít, tôm đất, tôm hùm, hải sâm nận, nhum sọ, cá dìa, cá giò, cá cơm săng, cá đổng, cá hanh, cá nục, cá liệt) được khai thác với sản lượng thương phẩm và doanh thu hàng năm ước đạt 651,3 tấn và 65 tỷ đồng, trong đó nguồn lợi ngoài rạn đóng vai trò quan trọng hơn nhiều (323,9 tấn và 21,56 tỷ đồng) so với trực tiếp trên rạn san hô (327,4 tấn và 11,11 tỷ đồng) và cá là nhóm nguồn lợi quan trọng nhất (đặc biệt là cá dìa và cá giò). Bên cạnh đó, khai thác nguồn lợi tôm hùm giống hàng năm trong vịnh ước đạt trên 212.000 con và doanh thu khoảng 32,34 tỷ đồng, cao gấp 3 lần so với doanh thu khai thác nguồn lợi thương phẩm trực tiếp trên rạn. Các thảm rong mơ và rạn san hô trong vịnh Nha Trang là khu vực bãi đẻ và ương giống của các nhóm đối tượng nguồn lợi quan trọng như mực lá, bào ngư, ốc đụn, ốc mặt trăng, tôm hùm, cá dìa và cá giò

A comprehensive evaluation of polygenic score and genotype imputation performances of human SNP arrays in diverse populations

publishedVersio

Optimal Efficiency Control of Synchronous Reluctance Motors-based ANN Considering Cross Magnetic Saturation and Iron Loss

This paper presents a new idea by using the Artificial Neural Networks (ANNs) for estimating the parameters of the machine which achieving the maximum efficiency of the Synchronous Reluctance Motor (SynRM). This model take into consideration the magnetic saturation, cross-coupling and iron loss. With Finite Element Analysis (FEA), the characteristics of the SynRM including inductances and iron loss resistance are determined. Because of the non-linear characteristics, an ANN trained off-line, is then proposed to obtain the d-q inductances and iron loss resistance from Id,Iq currents and the speed. After learning process, an analytical expression of the optimal currents is given thanks to Lagrange optimization. Therefore, the optimal currents will be obtained online in real time. This method can be achieved with maximum efficiency and high-precision torque control. Simulation and experimental results are presented to confirm the validity of the proposed method

Determinants of organic food purchasing intention: an empirical study of local consumers in Da Nang city, Central Vietnam

With the rapid economic development in the past decades, Vietnamese people are more and more aware of the role of safe food for their health and that of their families. Currently, the trend of organic food consumption is happening faster, especially in urban areas. The study aims to determine the influence of transparent information and knowledge about organic products on consumers' attitudes, trust, and subjective norms affecting their purchase intention of organic products. Data were collected from 420 consumers in Da Nang city, Central Vietnam. Exploratory Factor Analysis (EFA) method and Structural Equation Modeling (SEM) were used to evaluate the scale's reliability and identify the impact factors. The results show that attitudes and trust have a positive relationship with the intention to buy organic food. In addition, research shows that trust is a predecessor of attitudes and mediates the relationship between information, knowledge about organic food, and intention to buy organic food. The study's findings are consistent with previous literature and provide implications for food managers, organic food businesses, and the community