Explaining Intraday Pattern of Trading Volume from the Order Flow Data

Based on a comprehensive order flow data from the Taiwan stock market, this study examines directly how the intraday pattern of trading volume is related to the trading behavior of both informed and uninformed traders. The results indicate that both informed and uninformed investors have a strong desire to place orders at the market open and the close. Most of the orders at the market open are conservative and hence are waiting orders for price priority. The findings show that intraday trading volume as well as the real orders from both types of investors are J-shaped. In addition, both information and liquidity trading can explain the intraday pattern of trading volume. However, the impact of liquidity trading on volume is slightly higher than that of information trading.     

分布异质视角下产业集聚与文化产业增长研究-基于分位数面板回归的经验证据

基于分布异质视角,依据2003-2011年省域面板数据,利用分位数面板回归模型,考量产业集聚与文化产业增长.结果表明:随分位水平的提高,各因素的作用不一.文化产业集聚对文化产业增长的正向边际贡献呈现递增趋势.因此,应遵循文化产业增长的内在规律,因地制宜,合理规划文化产业集聚区,推进文化资源、要素与资本市场的对接,调整文化消费结构,促进文化产业的可持续增长.     

The Manipulator's Poker: Order-Based Manipulation in the Chinese Stock Market

This paper investigates order-based manipulation and its effects on investor behavior and market efficiency. Using a unique data set from the Chinese stock market, we show that (1) order-based manipulation affects market liquidity and trading behavior, (2) the manipulator pretends to be informed or expects to be seen as informed by choosing a "right" time to implement the manipulation, and (3) the manipulation rapidly changes investor reaction to the market order/depth imbalance in the short run, and the effect gradually drops during the postmanipulation period. Our results are robust to alternative measures and offer clear implications for both theory and policy.     

基于面板分位数回归的住宅价格影响因素分析

采用面板分位数回归方法,以全国35个大中城市为样本,利用2006—2015年的数据,对影响住宅价格的因素进行研究。结果表明：土地价格、人均储蓄余额、在岗职工平均工资、人口密度、空气质量对住宅价格有正向影响,每亿人医院或卫生院数量对住宅价格有负向影响;并且不同分位数水平下各影响因素的作用大小具有明显差异。研究结论对不同城市依据自身特征采取相应的调控政策具有一定的参考价值。     

Futures Market Sentiment and Institutional Investor Behavior in the Spot Market: The Emerging Market in Taiwan

This paper investigates whether and how futures market sentiment and stock market returns heterogeneously affect the trading activities of institutional investors in the spot market in Taiwan. Our empirical results suggest that foreign investors are net sellers whenever futures market sentiment is bullish and net buyers when investor sentiment is bearish. The two types of domestic institutional investors have poor sentiment timing abilities and the price-pressure effect may account for the behavioral differences among institutional investors. In addition, all three institutional investors are momentum traders. Nevertheless, the momentum trading of foreigners is consistent with an information-based model and that of two local institutional investors, as behavior-based models suggest. This indicates that the same trading momentum strategy can lead to different outcomes for different investors, and both information- and behavior-based momentum trading can exist contemporaneously in the Taiwanese stock market.     

A two-state analysis of estate taxes and charitable bequests from the most generous decedents

This study uses Censored Quantile Regression (CQR) and probate records for the years 2000–2005 to analyze charitable bequests of the most generous decedents from two states, Virginia and Louisiana. We focus on the most generous decedents because they account for a large portion of total charitable bequests. The most generous decedents' charitable bequest tax price (i.e., one minus the marginal tax rate) elasticity is not significantly greater than one in both our full sample and the subsample of the decedents filing federal estate tax returns. Our finding suggests that allowing charitable bequests to be deductible is not a treasury efficient policy for the most generous decedents. We also find that the tax price and wealth effects for the most generous decedents are overestimated by the Tobit model that has been traditionally utilized by prior studies. Furthermore, filers' charitable bequests are predicted to decrease if the estate tax is repealed.     

信贷支持、政府支出与产业转型的关联机制研究

信贷配置是否能够有效地促进产业结构转型是理解中国经济增长模式的重要维度。本文通过梳理银行信贷和政府支出影响产业转型的主要渠道,采用分位数回归的估计方法,应用中国1952～2007年的数据构建相关指标,实证分析信贷因素、政府支出变量影响各产业工业产出及促进产业转型的关联机制和实际效果。结论表明,总量信贷是造成产出波动的关键因素,而信贷流向不同产业的结构仍存在不合理之处;信贷支持是产业转型的重要因素,但是政府的影响也是必要而显著的。     

Contagion from the crises in the Euro-zone: where,when and why?

The prevalence of contagion between the Euro-zone countries and other European countries since the Greek crisis of 2009 is now well – known, but the factors that influence the pattern of this contagion are not well understood. We investigate this question both within Europe and beyond to the USA and Japan, using an asymmetric M-GARCH model that focuses on extreme values of the risk premia on government bonds. We compare these extreme values with news of major events and find that they are highly correlated. We find a different pattern of contagion emanating from Ireland compared to the other crisis countries of Greece, Italy, Portugal and Spain. We also examine the factors that have made countries vulnerable to contagion and find that financial factors are more important than trade ones. However, intra-Euro-zone trade has also been a significant factor between the major Euro-zone economies. There is little evidence that global factors affect contagion between EU member states, but some evidence that nominal exchange rate movements offer a degree of insulation from contagion for the non-Euro zone states.     

财政投入和金融支持对农民农业增收贡献的比较

基于2000～2013年省级面板数据,运用固定效应模型和分位数回归模型考察了财政投入和金融支持对提升农民农业收入的影响,并采用因素分解法比较两者对农民农业增收的贡献大小,继而通过两步固定效应回归、分组回归和替换变量回归三种方式检验结果的稳健性,均得出一致结果,即财政投入和金融支持均促进农业增收,其中财政投入贡献更大,此外大规模的土地投入和完善的基础设施建设也有利于农业收入提高.     

An application of two-stage quantile regression to insurance ratemaking

Two-part models based on generalized linear models are widely used in insurance rate-making for predicting the expected loss. This paper explores an alternative method based on quantile regression which provides more information about the loss distribution and can be also used for insurance underwriting. Quantile regression allows estimating the aggregate claim cost quantiles of a policy given a number of covariates. To do so, a first stage is required, which involves fitting a logistic regression to estimate, for every policy, the probability of submitting at least one claim. The proposed methodology is illustrated using a portfolio of car insurance policies. This application shows that the results of the quantile regression are highly dependent on the claim probability estimates. The paper also examines an application of quantile regression to premium safety loading calculation, the so-called Quantile Premium Principle (QPP). We propose a premium calculation based on quantile regression which inherits the good properties of the quantiles. Using the same insurance portfolio data-set, we find that the QPP captures the riskiness of the policies better than the expected value premium principle.     

How should we estimate value-relevance models? Insights from European data

We study the consequences of unobserved heterogeneity when employing different econometric methods in the estimation of two major value-relevance models: the Price Regression Model (PRM) and the Return Regression Model (RRM). Leveraging a large panel data set of European listed companies, we first demonstrate that robust Hausman tests and Breusch-Pagan Lagrange Multiplier tests are of fundamental importance to choose correctly among a fixed-effects model, a random-effects model, or a pooled OLS model. Second, we provide evidence that replacing firm fixed-effects with country and industry fixed-effects can lead to large differences in the magnitude of the key coefficients, with serious consequences for the interpretation of the effect of changes in earnings and book values per share on firm value. Finally, we offer recommendations to applied researchers aiming to improve the robustness of their econometric strategy.     

Predicting recovery rates using logistic quantile regression with bounded outcomes

Logistic quantile regression (LQR) is used for studying recovery rates. It is developed using monotone transformations. Using Moody’s Ultimate Recovery Database, we show that the recovery rates in different partitions of the estimation sample have different distributions, and thus for predicting recovery rates, an error-minimizing quantile point over each of those partitions is determined for LQR. Using an expanding rolling window approach, the empirical results confirm that LQR with the error-minimizing quantile point has better and more robust out-of-sample performance than its competing alternatives, in the sense of yielding more accurate predicted recovery rates. Thus, LQR is a useful alternative for studying recovery rates.     

我国信贷资金区域配置失衡的实证研究

通过对我国信贷资金区域配置失衡的现状进行考察,分析了信贷资金区域配置失衡对区域经济产生的影响,对信贷资金区域失衡的形成过程与发展趋势进行β-收敛性检验,建立面板数据模型分析区域间信贷资金规模失衡的影响因素,文章最后结合分析结果与我国现实国情对推动信贷资金区域合理配置提出对策建议.     

借款描述对互联网金融信用风险的影响研究

基于互联网金融提供的客户借款描述,通过潜在语义分析挖掘借款描述文本内容的主题,运用二元分位数回归分析借款描述对互联网金融信用风险的影响。实证结果表明,借款描述中有关情感表达、个人信用和借款目的的描述与违约情况呈负相关,有关财务情况的描述与违约情况呈正相关。     

Monetary Policy Reaction Functions of the TICKs: A Quantile Regression Approach

This study investigates how Taiwan, India, China, and Korea (TICKs) set interest rates in the context of policy reaction functions using a quantile-based approach. Our results indicate the tendency of a milder response to inflation at low interest rates and greater response at higher quantiles of interest rates, where inflation is presumably higher than desired for China and South Korea. While the response to inflation over the quantiles is significant for India, yet the Taylor principle is less likely to hold. For Taiwan, the results imply that another instrument is employed to deal with its official managed floating currency.