转型期内中国能源产业如何升级？基于面板数据的实证研究

在"双碳"目标下,中国能源产业升级不仅体现制度层面的要求,而且成为行为层面的必然.界定了"能源产业比较优势""能源产业优势演进"及"能源产业升级Motivation-Ability-Opportunity(MAO)",选取了2009—2019年的相关数据,从区域及全国两个层面构建计量经济模型;聚焦转型期内"产业升级的主要影响因素"和"产业升级路径选择的主要影响因素".研究表明:制度层面,中国能源产业虽有优势,但仍存在发展"惰性",应选择"渐进式"升级路径;组织层面,各区域能源产业仍普遍处于"升级未成功"或"保持比较优势"的非理想状态;产品层面,中国能源产业的能源替代-互补关系存在明显的区域差异,且化石能源产业未能达到发展预期.因此其仍需继续推进转型升级.     

基于层次结构的多标杆选拔竞优评价方法

根据竞优理论,提出了基于层次结构的多标杆选拔竞优评价方法。考虑个体选拔与群体客观推荐的特点,在此基础上构建了代理评价和民主评价模型。最后以高新技术企业研发人员绩效评价为算例,验证了该方法的适用性和有效性。     

Buy-and-hold mean-variance portfolios with a random exit strategy

We show how buy-and-hold investors can move from horizon uncertainty to profit opportunity. The analysis is conducted under a risk-averse framework rather than the standard Markowitz formulation in the case of i.i.d. asset processes. We make this practical achievement by considering a threshold stopping rule as the strategy to determine when to exit the market. The resulting investment horizon is random and can be correlated with the market. Under this setting, we first provide an analytical approximation to optimal weights, and then identify a class of reference variables associated with the stopping rule that leads to ex-ante improvements in portfolio allocation, vis-a-vis the fixed exit time alternative. The latter conclusion is based on a generalization of the Sharpe ratio, adjusted for horizon uncertainty. The obtained investment suggestion is simple and can be implemented empirically.     

Dynamic portfolio optimization across hidden market regimes

Regime-based asset allocation has been shown to add value over rebalancing to static weights and, in particular, reduce potential drawdowns by reacting to changes in market conditions. The predominant approach in previous studies has been to specify in advance a static decision rule for changing the allocation based on the state of financial markets or the economy. In this article, model predictive control (MPC) is used to dynamically optimize a portfolio based on forecasts of the mean and variance of financial returns from a hidden Markov model with time-varying parameters. There are computational advantages to using MPC when estimates of future returns are updated every time a new observation becomes available, since the optimal control actions are reconsidered anyway. MPC outperforms a static decision rule for changing the allocation and realizes both a higher return and a significantly lower risk than a buy-and-hold investment in various major stock market indices. This is after accounting for transaction costs, with a one-day delay in the implementation of allocation changes, and with zero-interest cash as the only alternative to the stock indices. Imposing a trading penalty that reduces the number of trades is found to increase the robustness of the approach.     

Price impact and bursts in liquidity provision

This paper analyses brief episodes of high-intensity quote turnover and revision—‘bursts’ in quotes—in the US equity market. Such events occur very frequently, several hundred times a day for actively traded stocks. We find significant price impact associated with these market maker initiated events, about five times higher than during non-burst periods. Bursts in quotes are concurrent with short-lived structural breaks in the informational relationship between market makers and market takers. During bursts, market makers no longer passively impound information from order flow into quotes—a departure from the traditional market microstructure paradigm. Rather, market makers significantly impact prices during bursts in quotes. Further analysis shows that there is asymmetry in adverse selection between the bid and ask sides of the limit order book and only a sub-population of market makers enjoys an informational advantage during bursts. Market makers on the side opposite the burst suffer elevated adverse selection costs, while market makers on the side of the burst realize positive spread, irrespective of the order flow direction. Our results call attention to the need for a new microstructure perspective in understanding modern high-frequency limit order book markets and the quote manipulation strategies at the disposal of the fast market makers.     

Data-driven robust mean-CVaR portfolio selection under distribution ambiguity

In this paper, we present a computationally tractable optimization method for a robust mean-CVaR portfolio selection model under the condition of distribution ambiguity. We develop an extension that allows the model to capture a zero net adjustment via a linear constraint in the mean return, which can be cast as a tractable conic programme. Also, we adopt a nonparametric bootstrap approach to calibrate the levels of ambiguity and show that the portfolio strategies are relatively immune to variations in input values. Finally, we show that the resulting robust portfolio is very well diversified and superior to its non-robust counterpart in terms of portfolio stability, expected returns and turnover. The results of numerical experiments with simulated and real market data shed light on the established behaviour of our distributionally robust optimization model.     

Dynamic portfolio choice without cash

We consider the dynamic mean–variance portfolio choice without cash under a game theoretic framework. The mean–variance criterion is investigated in the situation where an investor allocates the wealth among risky assets while keeping no cash in a bank account. The problem is solved explicitly up to solutions of ordinary differential equations by applying the extended Hamilton–Jacobi–Bellman equation system. Given a constant risk aversion coefficient, the optimal allocation without a risk-free asset depends linearly on the current wealth, while that with a risk-free asset turns out to be independent of the current wealth. We also study the minimum-variance criterion, which can be viewed as an extension of the mean–variance model when the risk aversion coefficient tends to infinity. Calibration exercises demonstrate that for large investments, the mean–variance model without cash yields the highest certainty equivalent return for both short-term and long-term investments. Furthermore, the mean–variance portfolio choices with and without cash yield almost the same Sharpe ratio for an investment with large initial wealth.     

基于DEA的模糊综合评价方法在应急物流方案选择中的应用

针对应急物流方案选择的问题,提出了基于数据包络分析的模糊综合评价方法,即把专家打分得到的样本数据采用数据包络分析方法得到个评价单元的相对效率,再对相对效率模糊化,最后进行综合评价。既能客观地体现各指标因素的相对有效性,又能很好表现出评价的模糊性和不确定性。     

Meeting Planners' Perceptions of Site Selection Characteristics

Abstract

This study aims to examine meeting planner assessments of convention site selection characteristics for international meetings/conventions and to appraise the strengths and weaknesses of six selected major convention hotels in Seoul, Korea. The principle components procedure indicated that four factors accounted for 78 percent of the cumulative variance of the eleven site selection variables listed in the study.