上海股市收益与波动的周内效应研究

股市周内效应一直是金融投资者关注的焦点问题，许多学者已做了大量研究，但多数文献将收益与波动的周内效应分开来进行研究和检验，忽视了波动与收益的共生性，其结果缺乏严密性和说服力。针对这种情况，提出平行数据GARCH模型并给出了参数的极大似然估计方法，进而对上海股市收益和波动的周内效应进行检验，既反映收益与风险存在共生关系，又避免了分别判断收益和波动的周内效应所致的缺点。     

高职教育实践性教学初探

加强高等职业教育的实践性教学,是高等职业教育教学改革的一个关键的突破口。只有加强实践性教学的探讨和创新,才能突出高职教育的特色。要积极探讨建立实践性教学为主的模式和运行机制,如实践性教学导师制、学生模拟实习公司等。同时,要处理好理论教学与实践教学的关系,处理好培养人才"宽"与"窄"的关系。     

资本市场开放与公司内部控制质量——基于“沪港通”的证据

以中国“沪港通”交易制度的实施为政策背景,采用多时点双重差分模型,考察资本市场开放对标的公司内部控制质量的影响,研究发现,“沪港通”交易制度的实施显著提升了公司的内部控制质量,在控制其他因素并经过安慰剂检验、去除A+H股影响、改变周期范围等稳健性检验后,结论依然成立。机制检验表明,“沪港通”主要通过内部和外部两种机制对公司内部控制质量产生影响,其中,内部机制是对股价波动性风险控制,外部机制是审计师声誉风险与政府部门监管。     

Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.     

Minnesota-type adaptive hierarchical priors for large Bayesian VARs

Large Bayesian VARs with stochastic volatility are increasingly used in empirical macroeconomics. The key to making these highly parameterized VARs useful is the use of shrinkage priors. We develop a family of priors that captures the best features of two prominent classes of shrinkage priors: adaptive hierarchical priors and Minnesota priors. Like adaptive hierarchical priors, these new priors ensure that only ‘small’ coefficients are strongly shrunk to zero, while ‘large’ coefficients remain intact. At the same time, these new priors can also incorporate many useful features of the Minnesota priors such as cross-variable shrinkage and shrinking coefficients on higher lags more aggressively. We introduce a fast posterior sampler to estimate BVARs with this family of priors—for a BVAR with 25 variables and 4 lags, obtaining 10,000 posterior draws takes about 3 min on a standard desktop computer. In a forecasting exercise, we show that these new priors outperform both adaptive hierarchical priors and Minnesota priors.     

How does news sentiment affect the states of Japanese stock return volatility?

This paper examines the impact of public news sentiment on the volatility states of firm-level returns on the Japanese Stock market. We firstly adopt a novel Markov Regime Switching Long Memory GARCH (MRS-LMGARCH), which is employed to estimate the latent volatility states of intraday stock return. By using the RavenPack Dow Jones News Analytics database, we fit discrete choice models to investigate the impact of news sentiment on changes of volatility states of the constituent stocks in the TOPIX Core 30 Index. Our findings suggest that news occurrence and sentiment, especially those of macro-economic news, are a key factor that significantly drives the volatility state of Japanese stock returns. This provides essential information for traders of the Japanese stock market to optimize their trading strategies and risk management plans to combat volatility.     

General equilibrium impact of an energy-saving policy in the public sector

We analyse a disregarded environmental policy instrument: a switch in government expenditure away from energy (or other natural resources) and toward a composite good which includes energy-saving expenditure. We first develop two variants of an analytical general equilibrium model. A composite good is produced with constant returns to scale, and energy is imported or produced domestically with diminishing returns, yielding a differential rent to its owners. The government purchases energy and composite goods from private firms. Such a policy unambiguously increases employment. It also raises private consumption and welfare under two conditions: (i) it is not too costly and (ii) the initial share of the resource is smaller in public spending than in private consumption, or the difference is small enough. We then run numerically a model featuring both importation and domestic production of energy (oil, gas and electricity), for the OECD as a whole. Simulations show that employment, welfare and private consumption rise. We provide magnitudes for different parameter values. Earlier versions of this paper have benefited from conference participants at the European Council for an Energy-Efficient Economy, International Society for Ecological Economics World Congress, CIRED seminar and EUREQua environmental economics seminar. We especially thank Michèle Sadoun and two anonymous referees. The usual disclaimer applies.     

Threshold models for trended time series

This paper presents the theoretical development of a new threshold autoregressive model based on trended time series. The theoretical arguments underlying the model are outlined and a nonlinear economic model is used to derive the specification of the empirical econometric model. Estimation and testing issues are considered and analysed. Additionally we apply the model to the empirical investigation of U.S. GDP.This paper is the result of work carried out for the author's Ph.D. thesis. I would like to thank Hashem Pesaran for his help, encouragement and insights during the preparation of this paper. I also thank Gary Koop and Sean Holly for helpful comments. Financial assistance from the Economic and Social Research Council is gratefully acknowledged.     

Noisy chaotic dynamics in commodity markets

The nonlinear testing and modeling of economic and financial time series has increased substantially in recent years, enabling us to better understand market and price behavior, risk and the formation of expectations. Such tests have also been applied to commodity market behavior, providing evidence of heteroskedasticity, chaos, long memory, cyclicity, etc. The present evaluation of futures price behavior confirms that the resulting price movements can be random, suggesting noisy chaotic behavior. Prices could thus follow a mean process that is dynamic chaotic, coupled with a variance that follows a GARCH process. Our conclusion is that models of this type could be constructed to assist in forecasting prices in the short run but not over long run time periods.First version received: June 2001/Final version received: March 2003     

The nature of the steady state in models of optimal growth under uncertainty

Summary. We study a one-sector stochastic optimal growth model with a representative agent. Utility is logarithmic and the production function is of the Cobb-Douglas form with capital exponent . Production is affected by a multiplicative shock taking one of two values with positive probabilities p and 1-p. It is well known that for this economy, optimal paths converge to a unique steady state, which is an invariant distribution. We are concerned with properties of this distribution. By using the theory of Iterated Function Systems, we are able to characterize such a distribution in terms of singularity versus absolute continuity as parameters and p change. We establish mutual singularity of the invariant distributions as p varies between 0 and 1 whenever . More delicate is the case . Singularity with respect to Lebesgue measure also appears for values such that . For and Peres and Solomyak (1998) have shown that the distribution is a.e. absolutely continuous. Characterization of the invariant distribution in the remaining cases is still an open question. The entire analysis is summarized through a bifurcation diagram, drawn in terms of pairs .Received: 9 April 2002, Revised: 29 October 2002, JEL Classification Numbers: C61, O41.Correspondence to: Tapan MitraThis research was partially supported by CNR (Italy) under the "Short-term mobility" program and by M.U.R.S.T. (Italy) National Group on "Nonlinear Dynamics and Stochastic Models in Economics and Finance" . We are indebted to Rabi Bhattacharya for providing us with the reference to Solomyak's (1995) paper. The present version has benefitted from comments by Mukul Majumdar and two anonymous referees.