Essays on the Chinese and the U.S. Housing Markets

Housing is one of the most important assets for households and has profound implications for the economy. Housing markets in different nations may differ in institutional backgrounds and phases of housing cycles, but people across the world are faced with some similar challenges in understanding housing markets. This dissertation is international in scope and focuses on certain aspects of the housing cycles. It consists of two chapters -- the first looks at boom-taming housing policies in China and the second investigates the role of contagion in the previous U.S. housing cycle. Chapter 1 examines the impact of major housing policy interventions in China. While research in the Chinese housing market has been hampered by severe data limitations, I propose turning to the stock market, where high quality and high frequency data on real estate firms are available. An event study analysis is conducted on the April 2010 central government announcement, which suddenly and sharply reversed prior policies and initiated efforts to cool the housing market by tightening mortgage credit supply. I find that publicly traded housing developers listed on the Shanghai, Shenzhen or Hong Kong stock exchanges suffered an average of -15% cumulative abnormal return (CAR) in a short event window around the policy announcement. This loss in firm value indicates that the policy intervention is well-received by the market. Transaction volumes are likely to decline in the short run and the steady-state house price appreciation rate is expected to drop as well. There also is noteworthy heterogeneity in the CAR, with firms that engage in some non-residential development performing about three percentage points better. Firms whose largest shareholder is a state-owned enterprise affiliated with the central government perform about five percentage points worse. This latter result provides useful insights into the relative magnitudes of the costs and benefits of having special connections to the central government. In Chapter 2, which is written jointly with Anthony DeFusco, Fernando Ferreira and Joe Gyourko, we investigate whether contagion in the housing market, which is defined as the price correlation across space between two different metropolitan areas above and beyond that justified by common local shocks, was an important factor in the last American housing cycle. We implement empirical strategies that help address concerns that plague prior contagion-related research. Besides that, the richness of our proprietary housing transaction data allows us to directly estimate the importance of contagion mechanisms. We find that contagion effects arise during the housing boom, and only from the very closest neighbor -- the elasticity of focal market prices with respect to changes in its nearest neighbor\u27s prices is in the range of 0.10-0.27. This is large enough to account for up to 30% of the jump in home prices at the beginning of local booms, on average. There is noteworthy heterogeneity in this result, with contagion impacts being much greater when transmitted from a larger to a smaller market, and also more important for the most elastically-supplied markets. Finally, local fundamentals and expectations of future fundamentals have very limited ability to account for our estimated effect. This suggests a potential role for non-rational forces in generating house price expectations

Determination of the Reserved Gap Between the Obturator Ring and the Breechblock in the Metallic Obturation Mechanism of a Large Caliber Gun Howitzer

A reserved gap between the obturator ring and the breechblock in the obturation mechanism of a large-caliber gun is required in the locked state of the gun, which is the main cause of gas leakage. In this study, the finite element analysis of the dynamic contact between the obturator ring and the breechblock and the computational fluid dynamics (CFD) analysis of the high-pressure gas flow through the gap between the obturator ring and the breechblock are conducted. The results show that the smaller the reserved gap is, the shorter the time period during which the contact pressure is zero after the obturator ring contacts with the breechblock will be under a low-bore pressure condition. The results also demonstrate that the leakage flow at the outlet of the gap and the gas flow in the external domain increase with the reserved gap size, and the gas flow in the external domain decays rapidly if the reserved gap is less than or equal to 0.02 mm under a high bore pressure condition. Based on the simulation results, the appropriate reserved gap value is determined and adopted in the studied gun, and good results are achieved in the firing tests

Investor sentiment and cross-sectional stock returns

This thesis consists of three essays on investor sentiment and the cross-sections of stock returns. The first essay extends Deling, Shieifer abd Waldman's (1990) noise trader risk module into a module with multiple risky assets to show the asymmetric effect of sentiment in the cross-section. Guided by our module, we also find that the effect of investor sentiment can be decomposed into long and short run components. The empirical tests in the first essay of the thesis present a negative relationship between long-run sentiment component and subsequent stock returns and a positive association between the short run sentiment and contemporaneous stock returns. The second essay explores a previously unexamined sentiment channel through which technical analysis can add value. We construct a daily market TA sentiment indicator from a spectrum of commonly used technical trading strategies. We find that this indicator significantly correlates with other popular sentiment measures. An increase in TA sentiment indicator is accompanied by high contemporaneous returns and predicts high near-term returns, low subsequent returns and high crash risk in the cross-section. We also design trading strategies to explore the profitability of our new TA sentiment indicator. Our trading strategies generate remarkable and robust profits. The third essay focusses on exploring the profitability of trading strategies based on Implied Volatility indicator (VIX) from the sentiment perspective. Our trading strategies involve holding sentiment-prone stocks when VIX is low and sentiment-immune stocks when VIX is high. The shifting asset allocation strategies are based on Abreu and Brunnermeier’s (2003) delayed arbitrage theory and the asymmetric effect of investor sentiment in the cross-section. We find sentiment-prone stock have larger one-day forward retunes following high sentiment and vice versa. Our trading strategies generate substantial higher returns that benchmark portfolios, and the excess returns are not subsumed by well-known risk factors or transaction costs

PivotNet: Vectorized Pivot Learning for End-to-end HD Map Construction

Vectorized high-definition map online construction has garnered considerable attention in the field of autonomous driving research. Most existing approaches model changeable map elements using a fixed number of points, or predict local maps in a two-stage autoregressive manner, which may miss essential details and lead to error accumulation. Towards precise map element learning, we propose a simple yet effective architecture named PivotNet, which adopts unified pivot-based map representations and is formulated as a direct set prediction paradigm. Concretely, we first propose a novel point-to-line mask module to encode both the subordinate and geometrical point-line priors in the network. Then, a well-designed pivot dynamic matching module is proposed to model the topology in dynamic point sequences by introducing the concept of sequence matching. Furthermore, to supervise the position and topology of the vectorized point predictions, we propose a dynamic vectorized sequence loss. Extensive experiments and ablations show that PivotNet is remarkably superior to other SOTAs by 5.9 mAP at least. The code will be available soon.Comment: Accepted by ICCV202

Coresets for Wasserstein Distributionally Robust Optimization Problems

Wasserstein distributionally robust optimization (\textsf{WDRO}) is a popular model to enhance the robustness of machine learning with ambiguous data. However, the complexity of \textsf{WDRO} can be prohibitive in practice since solving its ``minimax'' formulation requires a great amount of computation. Recently, several fast \textsf{WDRO} training algorithms for some specific machine learning tasks (e.g., logistic regression) have been developed. However, the research on designing efficient algorithms for general large-scale \textsf{WDRO}s is still quite limited, to the best of our knowledge. \textit{Coreset} is an important tool for compressing large dataset, and thus it has been widely applied to reduce the computational complexities for many optimization problems. In this paper, we introduce a unified framework to construct the $\epsilon$-coreset for the general \textsf{WDRO} problems. Though it is challenging to obtain a conventional coreset for \textsf{WDRO} due to the uncertainty issue of ambiguous data, we show that we can compute a ``dual coreset'' by using the strong duality property of \textsf{WDRO}. Also, the error introduced by the dual coreset can be theoretically guaranteed for the original \textsf{WDRO} objective. To construct the dual coreset, we propose a novel grid sampling approach that is particularly suitable for the dual formulation of \textsf{WDRO}. Finally, we implement our coreset approach and illustrate its effectiveness for several \textsf{WDRO} problems in the experiments

Magnetization and Giant Magnetoimpedance Effect of Co-Rich Microwires under Different Driven Currents

Co68.25Fe4.5Si12.25B15 amorphous microwires with a diameter of 34 μm were prepared via the melt extraction method. The dependency of AC driving current Iac and frequency on giant magnetoimpedance (GMI) effect and magnetization were investigated using a 4294A impedance analyzer and the transverse Kerr effect. The GMI effect was analyzed when Iac changed from 6 mA to 20 mA at a frequency ranging from 0.1 MHz to 15 MHz. The influence of AC current dependent on the frequency is correlated with the magnetization mechanism. The maximum transverse Kerr intensity (MTKI) decreased with the increase in Iac under direct magnetic field when the frequency was below megahertz. However, MTKI values were similar with the increase of Iac when it was over 2 MHz. Meanwhile, the GMI effect was optimized by selecting an adequate value of AC driving current Ip, at which the circular permeability was higher when the frequency was not over 2 MHz. Results showed that the influence of Iac on magnetoimpedance became weak with strong skin effect and slightly stronger GMI effect driven by a higher Iac when the frequency was between 2 MHz and 15 MHz. The skin effect turned out to be the key factor to the GMI effect; thus, there were no obvious differences in magnetization and GMI effect with AC driving current changing when the frequency was as high as 15 MHz

The Role of Contagion in the Last American Housing Cycle

Using proprietary micro data on the complete set of housing transactions between 1993 and 2009 in 99 metropolitan areas, we investigate whether contagion was an important factor in the last housing cycle. We define contagion as the price correlation between two different housing markets following a shock to one market that is above and beyond that which can be justified by common aggregate trends. Our estimates deal with the following empirical challenges: (a) defining the timing of local housing booms in a non-ad hoc way; (b) addressing specification search bias that arises when only one aggregate series is used to estimate both the timing of the housing boom and the magnitude of price volatility during that period; and (c) controlling for common variation in economic conditions. We find strong evidence of contagion during the housing boom, but not during the bust. These effects appear to arise mostly from the closest neighboring metropolitan area, with the price elasticity ranging from 0.10 to 0.27. This is large enough to account for up to 30% of the jump in prices at the beginning of local booms, on average. Estimated elasticities are greater when transmitted from a larger to a smaller market, and also more important for the most elastically-supplied markets. Finally, local fundamentals and expectations of future fundamentals have very limited ability to account for our estimated effect, suggesting a potential role for non-rational forces