A re-examination of the impact of credit ratings and economic factors on state bond yields

In this article we re-examine the impact of credit ratings and economic factors on state bond yields using a two-step model. In the first step, we adopt an ordered probit technique to obtain consistent estimates of state bond default risk. In the second step, we estimate state bond risk premiums using a regression analysis with a categorized risk variable obtained from the first step. Similar to Terza (1987) and Hsiao (1983), the model involves a categorized ordinal explanatory (rating) variable. However, our two-step model deals with a case where category thresholds are unknown and dependent on economic factors. The model provides consistent estimates for the effects of ratings and economic factors on state bond yields. Contrary to previous findings, we find that state bond yields are mainly affected by fundamental economic variables.     

Capital Allocation for a Sum of Dependent Compound Mixed Poisson Variables: A Recursive Algorithm Approach

The sum of independent compound Poisson random variables is a widely used stochastic model in many economic applications, including non-life insurance, credit and operational risk management, and environmental sciences. In this article we generalize this model by introducing dependence among Poisson frequency variables through a latent random variable in a linear fashion, which can be translated as a common underlying risk factors affecting the frequencies of individual compound Poisson variables. Despite its natural interpretation, this generalization leads to a highly complicated model with no closed-form distribution function. For this dependent compound mixed Poisson sum with an arbitrary severity distribution, we obtain the Laplace transform and further develop a new recursive algorithm to efficiently compute the probability mass function, extending the well-known Panjer recursion. Furthermore, based on this recursion, we derive another recursive scheme to determine the capital allocation associated with the Conditional Tail Expectation, a popular risk management exercise. A numerical example is presented for the illustration of our findings.     

我国科技企业融资的决定因素研究——基于科创板企业的机器学习分析

本文以手工收集的2019年7月至2020年12月所有申报科创板上市的企业为研究对象,研究了企业层面五大维度数十个因素对我国科技企业融资的预测效果,通过传统的OLS和机器学习降维排序方法,为科创板增量改革的实践效果提供了直接证据。研究发现:企业能否在科创板上市方面,企业研发水平、成长性和公司治理水平这三类反映企业未来发展潜力的特征占据主导作用,且研发水平最为关键,盈利的重要性最低;在众多研发变量中,企业研发人员人数占总人数比最为重要;企业能否在科创板上市和上市后二级市场表现的变量重要性排序各不相同,甚至相反;公司治理方面,国有股份占比的重要性强于其他治理机制。结合研究结论,本文从重视企业未来可持续发展、构建科研人才队伍培育和激励机制以及统筹考虑上市后的市场表现等角度,为科创企业发展提供了政策建议。     

Fundamental Economic Variables,Expected Returns,and Bond Fund Performance

In this article, we develop relative pricing (APT) models that are successful in explaining expected returns in the bond market. We utilize indexes as well as unanticipated changes in economic variables as factors driving security returns. An innovation in this article is the measurement of the economic factors as changes in forecasts. The return indexes are the most important variables in explaining the time series of returns. However, the addition of the economic variables leads to a large improvement in the explanation of the cross-section of expected returns. We utilize our relative pricing models to examine the performance of bond funds.     

A new theoretical framework to assess Multinational Corporations’ motivation for Foreign Direct Investment: A case study on Vietnamese service industries

PurposeThis paper develops a new theoretical framework, based on eclectic paradigm and institution theory, to evaluate Multinational Corporations’ (MNCs’) incentives for Foreign Direct Investment (FDI). The new framework is applied as a case study in the service sector across Vietnam.Design/methodology/approachThis study applies the Structural Equation Modelling (SEM) approach to investigate the motivational factors of MNCs by using primary data on MNCs working in service industries in Vietnam. This paper introduces five motivational factors, and conducts a Confirmatory Factor Analysis (CFA) to study the construct validity of the research measures and to cluster the variables into common factors that can be used to present relationships among sets of interrelated variables.FindingsThe SEM results reveal that the key determinants of MNCs’ incentives to invest in service industries are market-seeking government policies and culture, all of which have significantly contributed to FDI.Originality/valueThis study offers new knowledge and insights into the factors that motivate FDI by MNCs in general and in service industries in Vietnam. The findings are plausible and in line with the recent economic reforms launched in Vietnam, along with the increased FDI inflows into the country in the last twenty-five years.     

中国金融形势的动态特征与演变机理分析:1996-2016

本文分析了1996-2016年中国金融形势的变化趋势及影响金融形势的主导变量的动态特征,探究不同金融市场发展状况对中国金融整体形势及金融风险的影响力变迁。我们首次运用动态模型选择的时变因子增广向量自回归模型(DMS-TVP-FAVAR)测算了中国月度金融形势指数,考察了货币政策、外汇市场和资本流动、货币市场、银行业、股票市场、债券市场、非传统金融市场和国外金融市场对中国金融形势的差别化影响。研究发现,样本期内货币供应量一直是影响中国金融形势最主要的因素,非传统金融市场、外汇市场的影响程度日益加深;在国际金融危机期间,国外金融市场对中国金融形势表现出主导性的影响。总的来看,对中国金融形势的动态特征与演变机理分析有助于及时识别潜在金融风险。     

Benchmarking Australian fixed interest fund performance: finding the optimal factors

In this paper, we analyse the performance of Australian fixed interest managed funds and assess multiple benchmarks through which such performance can be reliably measured. We examine the effectiveness of seven indices of bond performance, as well as factors impacting on fixed interest asset values and, hence, returns, including interest rate fluctuations, economic fundamentals, maturity risk, default risk and cross‐market influences. We test all combinations of factors in cross‐section and time series to find the optimum benchmark. The results, consistent across time, show that a correct combination of a fund‐based market variable, a mixture of interest rate factors and economic factors as well as a proxy for movements in the equity markets yield the optimal benchmark.     

Modeling default probabilities: The case of Brazil

Using disaggregated data from the Brazilian stock market, we calculate default probabilities for 30 different economic sectors. Empirical results suggest that domestic macroeconomic factors can explain these default probabilities. In addition, we construct the Minimum Spanning Tree (MST) and the ultrametric hierarchical tree with the MST based on default probabilities to disclose common trends, which reveals that some sectors form clusters. The results of this paper imply that macroeconomic variables have distinct effects on default probabilities, which is important to take into account in credit risk modeling and the generation of stress test scenarios.     

Money,income, and sunspots: Measuring economic relationships and the effects of differencing

This paper discusses the question of whether economic time series regression models should be estimated between the levels or the changes of the variables of interest. We argue that many economic models should be estimated between the changes of the variables, rather than the levels of the variables. In addition, comparisons of the levels and changes regressions can be used as a crude test of model specification. These issues are illustrated with examples from Friedman and Meiselman's (1963) study of annual income and consumption and with data on sunspot activity from 1897–1958.     

Predicting the equity market with option-implied variables

We comprehensively analyze the predictive power of several option-implied variables for monthly S&P 500 excess returns and realized variance. The correlation risk premium (CRP) and the variance risk premium (VRP) emerge as strong predictors of both excess returns and realized variance. This is true both in- and out-of-sample. Our results also reveal that statistical evidence of predictability does not necessarily lead to economic gains. However, a timing strategy based on the CRP leads to utility gains of more than 5.03% per annum. Forecast combinations provide stable forecasts for both excess returns and realized variance, and add economic value.     

Exploring the components of credit risk in credit default swaps

In this paper, we test the influence of various fundamental variables on the pricing of credit default swaps. The theoretical determinants that are important for pricing credit default swaps include the risk-free rate, industry sector, credit rating, and liquidity factors. We suggest a linear regression model containing these different variables, especially focusing on liquidity factors. Unlike bond spreads which have been shown to be inversely related to liquidity (i.e., the greater the liquidity, the lower the spread), there is no a priori reason that the credit default swap spread should exhibit the same relationship. This is due to the economic characteristics of a credit default swap compared to a bond. Our empirical result shows that all the fundamental variables investigated have a significant effect on the credit default swap spread. Moreover, our findings suggest that credit default swaps that trade with greater liquidity have a wider credit default swap spread.     

Forecasting returns: New European evidence

This paper builds on the recent debate on the in-sample and out-of-sample predictability of US aggregate returns using a wide range of predictors by providing new evidence for smaller and less market-oriented European countries.We find evidence that macro and technical predictors can (statistically) improve forecast accuracy and (economically) generate gains to investors; in contrast to the US results, predictability in our sample of European countries exists in recent data. We also find that simple forecast combinations consistently yield substantial benefits both in forecast accuracy and economic gain. For example, the magnitude of the forecasting gains for our European countries is often larger than those found for the US and other G7 countries. We provide initial evidence on the link between country characteristics and out-of-sample forecast performance. Our empirical results indicate that market development is related to the forecast performance of macro variables. There is also some evidence that forecast performance is related to market size and liquidity.     

中国季度GDP的即时预测与混频分析

及时、准确地获得GDP短期预测值对于宏观调控和企业决策至关重要。本文在收集我国实时碎尾数据集的基础上,采用混频动态因子模型,将我国季度GDP的预测频率由“季度”提高到“日度”。研究结果表明,相对于混频抽样模型以及MFVAR等现有模型,混频动态因子模型能够有效解决实时预测中需要面临的数据问题,包括混频指标、碎尾特征、数据的周期性缺失等。本文模型在每个数据发布日,均可更新GDP的预测结果,这不仅将最新的经济活动信息迅速地体现到GDP预测中,而且显著提高了GDP即时预测的准确性,且预测结果随着月度数据信息的增加趋近于GDP真实值。此外,本文还估算了拟GDP季度同比增长率和GDP月度同比增长率两个月度数据序列,为我国宏观经济监测与政策分析提供一定的数据支撑。     

Determinants of the capital adequacy ratio of foreign banks’ subsidiaries: The role of interbank market and regulation

This paper examines the factors influencing the capital adequacy ratio (CAR) of foreign banks. We test whether the CAR of subsidiaries and branches in developed and developing countries depends on the same factors. We use data from 310 subsidiaries and 265 branches to test the impact of the parent banks’ fundamentals on subsidiaries’ and branches’ capital ratios. We also study how the economic condition and regulatory environment in a bank's home country determine foreign banks’ CAR. Our results provide strong evidence that the CAR of subsidiaries and branches operating in developing and developed countries do not depend on the same set of explanatory factors. We also find that the regulatory framework of a parent bank's home country affects the capitalization of its foreign subsidiaries in the host countries. Finally, we show that specific variables of the parent bank have a stronger effect for foreign banks highly related to the interbank market.     

全球性因素对中国宏观经济及货币政策有效性的影响

本文首先对全球性因素与中国主要宏观经济变量之间的协同性进行了定量研究,并探讨了协同效应的历史演变,然后实证分析了1998-2011年全球性因素对我国货币政策有效性的影响及其动态变化。通过因子增强型向量自回归模型的实证分析,我们发现,世界经济与中国宏观经济之间呈现出一定的协同性。同时,全球性因素对各经济变量的解释力度随着时间的变化有着不同的表现,但没有证据表明它已成为系统更重要的因素。全球性因素引起了中国货币政策传导机制的部分改变,然而,全球性因素在中国不同经济变量响应货币冲击中有着不同的影响,由于全球性因素,某些经济变量对货币冲击的调整幅度和方向、持续性反应和时滞期发生了一定的变化。然而,全球性因素并没有使得我国的货币政策传导机制发生系统性、根本性的改变。     

Consumer attitudes,stock market liquidity,and the macro economy: A Canadian perspective

This study addresses the impact of equity market liquidity on Canadian economic growth and investigates how consumer attitudes/sentiments affect the dynamic macro-liquidity relationship. Using various market liquidity proxies (e.g., illiquidity ratio and open interest of equity futures) while controlling for a specific set of variables, we obtain the following main results: we document the predictability role of liquidity on future economic growth, and we find that during periods of high exchange-rate volatility between the Canadian and US dollars, growth becomes highly affected by stock-market liquidity movements. Furthermore, there is some evidence that stock market liquidity contains additional information for estimating the future state of the economy but is conditional on periods of higher positive consumer attitudes—specifically, consumer confidence in the economy. Additionally, we find strong evidence consistently supporting the premise that a positive change in general consumer sentiment exhibits a direct and significant effect on some macro-economic variables including personal consumption, consumer credit, and economic growth.     

中国大宗商品期货市场定价机制研究

大宗商品期货市场是我国资本市场的重要组成部分,其定价有效性关系到投资者套期保值和价格发现等功能的实现。本文对国际前沿研究中常用的定价因子进行全面系统梳理,并对这些因子对我国商品期货合约收益率的解释和预测能力进行检验。在此基础上,本文构建了适用于我国大宗商品期货市场的包含市场、基差以及基差动量的三因子定价模型。进一步研究表明,基于大宗商品存储理论和现货存货数据构建的投资组合收益率可以被本文三因子模型有效解释,验证了经典的存储理论在我国的适用性。此外,本文对基差与基差动量两个重要因子的经济学意义进行了阐释。本文研究为进一步厘清大宗商品期货市场定价机制提供了一定参考。     

Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework

This paper empirically estimates the spatial correlation relationship of volatility spillovers and its influencing factors across G20 stock market. We apply GARCH-BEKK model to estimate volatility spillover and construct dynamic volatility networks. The connectedness analysis shows that the spatial linkage of volatility spillover is time varying and has obvious multiple superposition phenomena. As somewhat innovation results, we use the factor analysis method to obtain centrality comprehensive indicators that can clearly depict the risk contagion intensity and risk acceptance intensity. In general, the developed markets are more influential than the emerging markets during periods of turbulence, and the emerging markets are more sensitive to volatility shocks than developed markets during any period. Finally, this paper introduces quadratic assignment procedure (QAP) method to identify the major factors that influence the spatial linkage of volatility spillovers. Results show that geography influences the volatility spatial correlation differently across economic cycles, and the centrality structure factors have greater impact on the spatial correlation than the external economic factors. The QAP regression analysis shows that these influencing factors can explain about 50% of the spatial correlation variation of international financial markets' volatility spillovers.     

Market timing under multiple economic regimes

This article models the US equity premium as a regime‐switching process where the regimes are dependent on economic variables. To characterise the economic regimes, we employ the dimension reduction technique of a principal components analysis to extract business cycle signals from a set of observed macroeconomic variables. We use these conditioning agents to infer the ex ante economic regime. We then test a dynamic asset allocation strategy, which invests in equity and cash on the basis of the predicted regimes. This timing strategy is shown to outperform a simple buy and hold strategy on a risk‐adjusted basis.     

“好”的不确定性、“坏”的不确定性与股票市场定价——基于中国股市高频数据分析

不确定性并不是都是“坏”的,“好”的不确定性也同样存在。本文采用Barndorff-Nielsen et al.(2010)提出的已实现半方差作为股票市场“好”的不确定性和“坏”的不确定性的代理指标,并在此基础上构建了相对符号变差(RSV),分析RSV对中国股市定价的影响。基于2007-2017年中国A股5分钟高频数据的实证研究发现:(1)与理论解释相一致,RSV与股票收益之间呈现负相关关系。无论是基于单变量分组、双变量分组还是公司层面的截面回归,这种影响在经济上和统计上都显著。(2)RSV是独立于已实现偏度的一个重要定价因子,且RSV对股票的定价能力强于已实现偏度的定价能力。(3)RSV对中国股市的影响是状态依存的,相对于经济景气程度高的状态,在经济景气程度低的状态下RSV定价影响更大。(4)基于RSV构建的投资组合的表现明显优于市场超额收益率组合、SMB组合和HML组合的表现。