中国与东南亚国家贸易潜力及影响因素研究——基于随机前沿引力模型

运用时变随机前沿引力模型和贸易非效率模型,以1998-2016年中国及东南亚九个国家面板数据为样本,测度中国对东南亚国家出口贸易潜力,并分析其主要影响因素。结果表明：1998-2016年中国对东南亚国家出口贸易潜力呈现先上升后下降趋势,依然有较大提升空间,中国对东南亚国家出口贸易潜力差异较大。航空运输货运量、货币自由度、财务自由度、商业自由度及世界贸易组织成员国均对出口贸易非效率具有显著的影响。     

1996-2005年中国农业剩余劳动力的估算——基于随机前沿模型的分析

本文采用随机前沿分析方法,利用省际面板数据对我国农业剩余劳动力的数量和比例进行了估算,并分析了剩余劳动力的变化趋势.根据本文的估算,1996年以来我国剩余劳动力没有明显的下降趋势, 目前我国农业剩余劳动力数量约为1亿人,约占全部农业劳动力的三分之一.农业剩余劳动力的变化与经济增长有着密切的联系,保持较快的经济增长速度,在非农部门创造更多就业机会,加快农业劳动力向其他部门的转移,是减少农业剩余劳动力的根本途径.     

Implied integrated variance and hedging

If the volatility is stochastic, stock price returns and European option prices depend on the time average of the variance, i.e. the integrated variance, not on the path of the volatility. Applying a Bayesian statistical approach, we compute a forward-looking estimate of this variance, an option-implied integrated variance. Simultaneously, we obtain estimates of the correlation coefficient between stock price and volatility shocks, and of the parameters of the volatility process. Due to the convexity of the Black–Scholes formula with respect to the volatility, pricing and hedging with Black–Scholes-type formulas and the implied volatility often lead to inaccuracies if the volatility is stochastic. Theoretically, this problem can be avoided by using Hull–White-type option pricing and hedging formulas and the integrated variance. We use the implied integrated variance and Hull–White-type formulas to hedge European options and certain volatility derivatives.     

Dynamic lot sizing problem with continuous-time Markovian production cost

This paper develops a polynomial algorithm for obtaining dynamic economic lot sizes in a single product multiperiod production system with the objective of minimizing total production and inventory costs over T periods. It is assumed that production costs are linear, inventory costs are concave, setup costs are zero and backlogging is not permitted in all periods. Moreover, the unit production cost is a stochastic variable, which is evolved according to a continuous-time Markov process over the planning horizon. The model is formulated as a stochastic dynamic programming (DP) optimization with the state variable being unit production cost. Then, it is solved using the backward dynamic programming approach. To justify the application of the proposed model, two practical cases are presented.     

The market price of risk of the variance term structure

In this paper I examine the market price of risk of the variance term structure. To this end, the S&P 500 option implied variance term structure is used as a proxy for aggregate variance risk. Principal component analysis shows that time variation in the variance term structure over the 1996–2012 period can be explained mainly by two factors which capture changes in the level and slope. The market price of risk of each factor is estimated in the cross-section of stock returns. The slope of the variance term structure is the most significant factor in the cross-section of stocks returns and carries a negative risk premium. The slope factor has also some predictive ability over long horizon equity returns.     

Can negative interest rates really affect option pricing? Empirical evidence from an explicitly solvable stochastic volatility model

The profound financial crisis generated by the collapse of Lehman Brothers and the European sovereign debt crisis in 2011 have caused negative values of government bond yields both in the USA and in the EURO area. This paper investigates whether the use of models which allow for negative interest rates can improve option pricing and implied volatility forecasting. This is done with special attention to foreign exchange and index options. To this end, we carried out an empirical analysis on the prices of call and put options on the US S&P 500 index and Eurodollar futures using a generalization of the Heston model in the stochastic interest rate framework. Specifically, the dynamics of the option’s underlying asset is described by two factors: a stochastic variance and a stochastic interest rate. The volatility is not allowed to be negative, but the interest rate is. Explicit formulas for the transition probability density function and moments are derived. These formulas are used to estimate the model parameters efficiently. Three empirical analyses are illustrated. The first two show that the use of models which allow for negative interest rates can efficiently reproduce implied volatility and forecast option prices (i.e. S&P index and foreign exchange options). The last studies how the US three-month government bond yield affects the US S&P 500 index.     

Short-time at-the-money skew and rough fractional volatility

The Black–Scholes implied volatility skew at the money of SPX options is known to obey a power law with respect to the time to maturity. We construct a model of the underlying asset price process which is dynamically consistent to the power law. The volatility process of the model is driven by a fractional Brownian motion with Hurst parameter less than half. The fractional Brownian motion is correlated with a Brownian motion which drives the asset price process. We derive an asymptotic expansion of the implied volatility as the time to maturity tends to zero. For this purpose, we introduce a new approach to validate such an expansion, which enables us to treat more general models than in the literature. The local-stochastic volatility model is treated as well under an essentially minimal regularity condition in order to show such a standard model cannot be dynamically consistent to the power law.     

Personalized goal-based investing via multi-stage stochastic goal programming

In this paper, we propose a goal-based investment model that is suitable for personalized wealth management. The model only requires a few intuitive inputs such as size of wealth, investment amount, and consumption goals from individual investors. In particular, a priority level can be assigned to each consumption goal and the model provides a holistic solution based on a sequential approach starting with the highest priority. This allows strict prioritization by maximizing the probability of achieving higher priority goals that are not affected by goals with lower priorities. Furthermore, the proposed model is formulated as a linear program that efficiently finds the optimal financial plan. With its simplicity, flexibility, and computational efficiency, the proposed goal-based investment model provides a new framework for automated investment management services.     

制度、增长与收敛——一个基于索洛模型的分析框架

标准的经济增长理论把制度看作是既定不变的并且不存在交易费用的,所以无法认识到制度对经济增长的重要性.将制度作为一个变量引入索洛模型,可以构造一个包含制度的、技术内生的增长模型.通过模型的推导可以得出这样的结论:制度质量越好,人均产出增长率越高;人均产出存在关于制度的条件收敛.并进一步得出这样的推论:欠发达国家想获得"后发优势"赶超发达国家,前提条件是具备良好的制度或能够持续改善其制度.