金融资产配置与违约风险:蓄水池效应,还是逐利效应？

本文以2007—2016年中国A股上市公司为研究对象,检验了企业金融资产配置对违约风险的影响。实证研究发现:金融资产持有量越多,企业的违约风险越低,金融资产配置的“蓄水池效应”显著;在货币政策宽松时期,金融资产配置导致的代理冲突显现,宽松的货币政策会抑制金融资产投资对违约风险的降低作用。政府规制也会有一定的公司治理作用,将产业政策纳入讨论发现:对于产业政策支持的行业来说,企业金融资产配置能够降低违约风险,但是宽松的货币政策会刺激管理层的短视投资行为,抑制政府规制的公司治理作用。进一步地,本文提出会计稳健性的提升是企业金融资产配置降低违约风险的重要路径。本文的研究结论丰富了企业金融资产配置动机和违约风险影响因素的讨论,能够为政府部门防范经济运行中的内在风险提供有益借鉴。     

企业研发投入、资源特征与创新绩效关系研究

基于资源基础观，探讨了企业“资源池”中财务资源特征与技术资源特征如何与研发投入行为匹配以提升创新绩效，以创业板355家企业为样本开展泊松回归分析，研究发现：R&D投入与创新绩效存在倒U型关系；财务资源特征——资产流动性对R&D投入与创新绩效存在正向调节作用，起着“加速剂”作用；由于组织技术路径依赖，技术资源特征——技术积累程度对R&D投入与创新绩效存在负向调节作用，起着“缓冲剂”作用；资产流动性与技术积累程度提高会促进研发投入与创新绩效关系的阈值提高，促进更多研发投入有效转化。探讨了企业研发投入行为与资源特征的匹配，可为促进创新绩效提升提供理论支撑。     

Risk-managed industry momentum and momentum crashes

This paper investigates Barroso and Santa-Clara’s [J. Financ. Econ., 2008, 116, 111–120] risk-managed momentum strategy in an industry momentum setting. We investigate several traditional momentum strategies including that recently proposed by Novy-Marx [J. Financ. Econ., 2012, 103, 429–453]. We moreover examine the impact of different variance forecast horizons on average pay-offs and also Daniel and Moskowitz’s [J. Financ. Econ., 2016, 122, 221–247] optionality effects. Our results show in general that neither plain industry momentum strategies nor the risk-managed industry momentum strategies are subject to optionality effects, implying that these strategies have no time-varying beta. Moreover, the benefits of risk management are robust across volatility estimators, momentum strategies and subsamples. Finally, the ‘echo effect’ in industries is not robust in subsamples as the strategy works only during the most recent subsample.     

中国家庭股市资产价值变动对居民消费的影响——来自CHFS的微观证据

近年来针对股市资产价值变动与消费关系的研究多采用宏观数据，难以揭示股市资产价值变动对居民消费影响的细节。为克服以上缺陷，文章利用中国家庭金融调查（CHFS）数据分析股市资产价值变动对中国居民消费的影响。实证结果表明：（1）股市资产价值变动对居民消费的影响总体较弱，其中市值变动的财富效应主要体现在改善性消费上，而对饮食等日常必须消费和奢侈品消费影响较小，这可能与我国居民的收入结构和投资方式有关；（2）随着年龄增长，居民的收入分布和资产配置倾向发生改变，股市资产价值变动对不同年龄居民消费的影响呈现先减小后增大的U型分布。研究结论揭示了股市资产价值变动对居民消费影响的分布特征，为今后股市改革方向提供了建议。     

Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach

In order to challenge the existing literature that points to the detachment of Bitcoin from the global financial system, we use daily data from August 17, 2011–February 14, 2020 and apply a risk spillover approach based on expectiles. Results show reasonable evidence to imply the existence of downside risk spillover between Bitcoin and four assets (equities, bonds, currencies, and commodities), which seems to be time dependent. Our main findings have implications for participants in both the Bitcoin and traditional financial markets for the sake of asset allocation, and risk management. For policy makers, the findings suggest that Bitcoin should be monitored carefully for the sake of financial stability.     

Multidimensional brand equity and asymmetric risk

The authors investigate the extent to which central customer-based brand equity dimensions (Differentiation, Relevance, Esteem, Knowledge, and Energy) influence a firm’s systematic risk (i.e., beta) during both market upturns and downturns. The results demonstrate that aggregating upside and downside beta or different dimensions of brand equity masks the true associations which can be seen only in the disaggregate analyses. The authors find that Relevance and Knowledge play roles as stabilizers, showing negative relationships with both upside gains and downside risk, while Esteem plays the role of protector, showing a negative relationship with only downside losses and not influencing upside gains; Energy acts as a booster, being positively associated with a firm’s potential gains in a period of market growth without increasing the firm’s expected losses during a bad market. The positive relationship of Energy with aggregate risk could be misleading as it hides the beneficial effect of Energy as a booster. The authors also find that Relevance is the most important consideration when people make choices in bad market situations, while Energy becomes the most crucial deciding factor in good market situations. Taking advantage of the multidimensional constructs of brand equity while allowing for the asymmetrical characteristics of risk enables managers to capture the differential role of each brand equity dimension in influencing firm risks, which leads to more sophisticated strategic decisions regarding risk management. In addition to general brand strategy, the authors provide tailored brand strategies to firms from different industries or with different financial characteristics.     

Asset indexes and the measurement of poverty,inequality and welfare in Southeast Asia

Using data on household consumer durables from the Asian Barometer Survey, this paper examines the evolution of inequality, poverty and welfare in six countries of South East Asia: Cambodia, Indonesia, Malaysia, the Philippines, Thailand and Vietnam. We start by deriving the most common order of acquisition of these durables, using first an algorithm proposed by Paroush (1965), and then Item Response Theory. We also compute the frequency distribution of the number of durables owned by households. We then use these results to compute inequality, poverty and achievement or welfare indices adapted to the case of ordinal variables.Our empirical results confirm the existence of an order of acquisition. The results show that inequality was higher in Cambodia, Indonesia and the Philippines and lower in Vietnam, Thailand and Malaysia. A similar classification of countries was obtained when computing multidimensional poverty indices.Finally, using the welfare or achievement index recently introduced by Apouey et al. (2019), we found that welfare was generally higher in Vietnam, Thailand and Malaysia and lower in Cambodia, Indonesia and the Philippines.     

The revenue potential of a financial transaction tax for US financial markets

This paper estimates the revenue potential of a financial transaction tax (FTT) for US financial markets. We focus on analyzing the revenue potential of the Inclusive Prosperity Act that was introduced in the US House of Representatives in 2012 and the US Senate in 2015. The tax rates stipulated in this Act include 0.5% (50 basis points (bps)) for all stock transactions, 0.1% (10 bps) for all bond transactions and 0.005% (0.5 bps) on the notional value of all derivative trades. We examine three sets of evidence to generate potential revenue estimates: 1) the levels of transaction costs in US financial markets over time and within the range of financial market segments; 2) the extent of trading elasticities under various trading conditions; and 3) the current level of trading activity in US financial markets. Based on this evidence, we conclude that a US FTT operating at the tax rates stated above would generate about $220 billion per year, equal to about 1.2% of the current US GDP.     

Compensation for illiquidity in China: Evidence from an alternative measure

This paper shows that liquidity is an important source of priced risk in China. Using A-share stocks in Shanghai and Shenzhen Exchange over the period 2007–2017, we examine the influence of liquidity on stock returns. A new liquidity measure that captures multiple dimensions of liquidity is proposed. Fama-Macbeth cross-sectional regression shows that the expected return is negatively correlated with liquidity. Based on Fama and French (1993), we propose a five-factor pricing model by incorporating reversal factor and liquidity factor. Time-series regressions show that the liquidity factor makes significantly marginal contributions to explaining excess stock returns. The liquidity factor based on the proposed measure works better than alternative liquidity measures such as turnover, Amihud illiquidity measure and the measure in Liu (2006).     

Optimizing a portfolio of mean-reverting assets with transaction costs via a feedforward neural network

Optimizing a portfolio of mean-reverting assets under transaction costs and a finite horizon is severely constrained by the curse of high dimensionality. To overcome the exponential barrier, we develop an efficient, scalable algorithm by employing a feedforward neural network. A novel concept is to apply HJB equations as an advanced start for the neural network. Empirical tests with several practical examples, including a portfolio of 48 correlated pair trades over 50 time steps, show the advantages of the approach in a high-dimensional setting. We conjecture that other financial optimization problems are amenable to similar approaches.