The Asymmetric Impulse of the Sunshine Effect on Stock Returns and Volatilities

This study constructs a variety of GARCH models with the consideration of the generalized error distribution to analyze the relationship between the cloud cover and stock returns in Taiwan in the whole sample period (1986 to 2007) and in the two sub-sample periods (1986 to 1996 and 1997 to 2007). The data include Taiwan Stock Exchange Capitalization Weighted Stock Index and the U.S. Dow Jones Industrial Average index to proxy the impact of U.S. stock market on Taiwan’s stock market performance. The empirical finding of this study could be used to reconfirm the existence of the so-called sunshine effect. The empirical results suggest that the cloud cover has significantly negative impact on Taiwan’s stock market, especially in the low cloud cover periods. Moreover, we also examine the sunshine effect with the consideration of the first and second moments and find that when adding the two moments, the sunshine effect is not significant in the stock returns but in the stock return volatilities, which is different from outcomes in previous studies.behavior finance, stock returns, stock volatility, Sunshine effect, Threshold model

Peaceful Settlement of Disputes in the South China Sea through Fisheries Resources Cooperation and Management

The South China Sea dispute is complicated in terms of its nature, the sovereignty issues of the islands, delimitation issues, resources utilization as well as other matters concerning security (both traditional and non-traditional). In order to solve the dispute, cooperation is one of the main considerations. However, the practice has not been realized. In order to solve the dispute and promote cooperation in the South China Sea region, the author suggests that conserving and managing fishery resources could be established as a starting point. There are a great number of management means, institutions, and international instruments (such as conventions, treaties and arrangements), which have been developed to protect fish stocks. Nonetheless, these policies should be practiced in an integrated mechanism at the national, regional, and international levels, so that the policy objectives could be accomplished. The South China Sea, the East China Sea, and Yellow Sea comprise a large marine ecosystem (LME) in East Asia. In other words, any change of the marine ecosystem could create a serious impact on other maritime areas. This paper suggests that a regional fisheries management organization is needed in order to conserve and manage the fishery resources in the South China Sea, which could also influence other maritime areas. Furthermore, it is also the purpose of this paper that such a model could contribute the solution to the dispute in the South China Sea

Weak Measurement of Qubit Oscillations with Strong Response Detectors: Violation of the Fundamental Bound Imposed on Linear Detectors

We investigate the continuous weak measurement of a solid-state qubit by single electron transistors in nonlinear response regime. It is found that the signal-to-noise ratio can violate the universal upper bound imposed quantum mechanically to any linear response detectors. We understand the violation by means of the cross-correlation of the detector currents.Comment: 4 pages, 4 figure

HAQ: Hardware-Aware Automated Quantization with Mixed Precision

Model quantization is a widely used technique to compress and accelerate deep neural network (DNN) inference. Emergent DNN hardware accelerators begin to support mixed precision (1-8 bits) to further improve the computation efficiency, which raises a great challenge to find the optimal bitwidth for each layer: it requires domain experts to explore the vast design space trading off among accuracy, latency, energy, and model size, which is both time-consuming and sub-optimal. Conventional quantization algorithm ignores the different hardware architectures and quantizes all the layers in a uniform way. In this paper, we introduce the Hardware-Aware Automated Quantization (HAQ) framework which leverages the reinforcement learning to automatically determine the quantization policy, and we take the hardware accelerator's feedback in the design loop. Rather than relying on proxy signals such as FLOPs and model size, we employ a hardware simulator to generate direct feedback signals (latency and energy) to the RL agent. Compared with conventional methods, our framework is fully automated and can specialize the quantization policy for different neural network architectures and hardware architectures. Our framework effectively reduced the latency by 1.4-1.95x and the energy consumption by 1.9x with negligible loss of accuracy compared with the fixed bitwidth (8 bits) quantization. Our framework reveals that the optimal policies on different hardware architectures (i.e., edge and cloud architectures) under different resource constraints (i.e., latency, energy and model size) are drastically different. We interpreted the implication of different quantization policies, which offer insights for both neural network architecture design and hardware architecture design.Comment: CVPR 2019. The first three authors contributed equally to this work. Project page: https://hanlab.mit.edu/projects/haq

Asymmetric Inflation Hedge of Housing Return: A Non-linear Vector Error Correction Approach

Conclusions of past works on the inflation hedging ability of real estate investment are not consistent. The reason for this perplexity might be the neglect of separation between high and low state of inflation, which has a great influence on empirical results. In order to examine the inflation hedging effectiveness of real estate with Taiwanese monthly housing returns and inflation, this paper uses the inflation as the threshold variable to create the nonlinear vector correction model that divides the inflation rates into high and low regime. We find robust evidence that when inflation rates are higher than 0.83% threshold value, housing returns are able to hedge against inflation, and, otherwise, they are unable. Using new methodology to discover new implications is main contribution of this study.Housing prices; Inflation; Nonlinear VECM; Taiwan

Glass Beads in Iron-Age and Early-Modern Taiwan: An Introduction

Archaeological research has revealed a long history of glass bead exchange and use in Taiwan, yet it has seldom been discussed in the literature. This paper provides an introduction to this exchange from the Iron Age (ca. late 1st millennium BC – mid-2nd millennium AD) to the early modern period (ca. AD 1600-1900) by revisiting the archaeological and historical records. It is suggested that changes in bead styles and chemical compositions over time reveal the transition of bead supply in Taiwan, which further reflects two broad phases of bead trade: Phase I) the earlier involvement of Taiwan in the Indo-Pacific bead exchange (1st millennium AD) and Phase II) the later cultural and economic contacts between the indigenous people, Chinese merchants, and Europeans (2nd millennium AD)