Index tracking with utility enhanced weighting

Passive index investing involves investing in a fund that replicates a market index. Enhanced indexation uses the returns of an index as a reference point and aims at outperforming this index. The motivation behind enhanced indexing is that the indices and portfolios available to academics and practitioners for asset pricing and benchmarking are generally inefficient and, thus, susceptible to enhancement. In this paper we propose a novel technique based on the concept of cumulative utility area ratios and the Analytic Hierarchy Process (AHP) to construct enhanced indices from the DJIA and S&P500. Four main conclusions are forthcoming. First, the technique, called the utility enhanced tracking technique (UETT), is computationally parsimonious and applicable for all return distributions. Second, if desired, cardinality constraints are simple and computationally parsimonious. Third, the technique requires only infrequent rebalancing, monthly at the most. Finally, the UETT portfolios generate consistently higher out-of-sample utility profiles and after-cost returns for the fully enhanced portfolios as well as for the enhanced portfolios adjusted for cardinality constraints. These results are robust to varying market conditions and a range of utility functions.     

开展股指期货交易--我国证券市场发展的现实选择

作为一种创新型金融衍生产品，股指期货丰富了市场交易品种，而双向交易机制的引进可以规避系统性风险，从而有利于资本市场的平稳运行。但是，股指期货交易的开展必须基于一国的基本国情，本文从股指期货的比较优势入手，结合我国当前实际情况，对我国股指期货的开展进行了分析。     

Early warning systems using dynamic factor models: An application to Asian economies

This study develops an early warning system for financial crises with a focus on small open economies. We contribute to the literature by developing macro-financial dynamic factor models that extract useful information from a rich but unbalanced mixed frequency data set that includes a range of global and domestic economic and financial indicators. The framework is applied to several Asian countries—Thailand, South Korea, Singapore, Malaysia, the Philippines and Indonesia. Logit regression models that use the extracted factors and other leading indicators have significant power in predicting systemic events. In-sample and out-of-sample test results indicate that the extracted factors help to improve the predictive power over a model that uses only sufficiently long history indicators. Importantly, models that include the dynamic factors yield consistently better out-of-sample crisis prediction results for key performance measures such as a usefulness index, the noise to signal ratio, and AUROC.     

指数保险有效性实证分析

运用Miranda模型研究发现,农户个体产量波动与所在区域产量波动存在高度正相关性,基于区域产量保险的保费率低于传统农业保险的保费率,这有利于刺激指数保险的需求。由于指数保险克服了传统农业保险市场中的逆向选择与道德风险问题,降低了交易成本,从而指数保险能够降低农户的保费支出并有效管理农业生产风险。     

我国社会融资规模的指数化构建分析

我国社会融资规模概念在2010年提出后,一直在不断完善中,2014年2月,央行也首次公布了地区社会融资规模的统计结果。社会融资规模作为一项比新增贷款更为全面的货币政策中介指标,能够反映人民币贷款体现不出来的问题,但其在要素构成方面一直有较多探讨。本文对我国2002年1月至2013年12月的社会融资规模数据进行指数化研究,得出各指标的不同权重,试将社会融资规模指数化,以便更好的利用于研究分析中。     

Forecasting stock returns with large dimensional factor models

We study equity premium out-of-sample predictability by extracting the information contained in a high number of macroeconomic predictors via large dimensional factor models. We compare the well-known factor model with a static representation of the common components with the Generalized Dynamic Factor Model, which accounts for time series dependence in the common components. Using statistical and economic evaluation criteria, we empirically show that the Generalized Dynamic Factor Model helps predicting the equity premium. Exploiting the link between business cycle and return predictability, we find accurate predictions also by combining rolling and recursive forecasts in real-time.     

Evaluating density forecasts from models of stock market returns

Density forecasts have become important in finance and play a key role in modern risk management. Using a flexible density forecast evaluation framework that extends the Berkowitz likelihood ratio test this paper evaluates in- and out-of-sample density forecasts of daily returns on the DAX, ATX and S&P 500 stock market indices from models of financial returns that are currently widely used in the financial industry. The results indicate that GARCH-t models produce good in-sample forecasts. No model considered in this study delivers fully acceptable out-of-sample forecasts. The empirical findings emphasize that proper distributional assumptions combined with an adequate specification of relevant conditional higher moments are necessary to obtain good density forecasts.     

Risk perception of mobile communication: a mental models approach

Some lay people confronted with a new base station project fear serious health consequences from the high‐frequency radiation, while experts consider exposure under the current international standards as unproblematic. These conflictive estimations may be attributed to the different mental models of lay people and experts. Less is known about lay people’s knowledge in regard to mobile communication and their intuitive understanding of the associated health risks. An adaptation of the ‘Mental Models Approach’ was used to reveal lay people’s beliefs about mobile communication and to learn more about lay people’s information requirements, potential knowledge gaps, and misconceptions. Through the means of open interviews with Swiss experts (N = 16), lay people (N = 16), and base station opponents (N = 15), different mental models were constructed and evaluated. Comparisons between the expert and the lay groups showed several qualitative differences in all identified knowledge domains. Knowledge gaps in regard to changing exposure magnitudes due to the interaction patterns of cell phones and base stations as well as misconceptions about regulation issues and scientific processes were found in both lay groups. In addition, lack of trust in responsible actors and disaffection with base station location processes were mentioned. The reported qualitative insights may be useful for the improvement of further risk communication tools.     

跨市场风险:银行系基金管理公司面临的新挑战

目前,我国设立银行系基金管理公司试点工作已经进入实质性操作阶段.允许银行设立或参与基金管理公司,有助于银行提高信托理财业务水平、增加新的利润增长点,但同时也对商业银行的风险管理水平提出了更高的要求,特别是控制跨市场风险更是商业银行办好基金管理公司的关键.当前环境下我国商业银行开办基金管理公司面临的跨市场风险主要有担保风险、流动性风险和利率攀比风险.为此,必须采取一定措施来应对和防范.     

Follow the leader: fund managers trading in signal‐strength sequence*

When fund managers trade sequentially in the same direction, the information confirmation hypothesis predicts the long‐term profitability of the leader trade to be increasing in the number of subsequent trades. The information cascade hypothesis predicts a non‐positive relationship. Using active equity funds’ daily trading data, we document a transition from information confirmation to information cascades as the number of followers increase. We find that highly disguised multiple‐broker packages exhibit higher market impact, higher long‐term returns and are associated with fewer followers. Our study also documents that lead fund managers face portfolio risk constraints in trading on private information.     

Selecting credit rating models: a cross-validation-based comparison of discriminatory power

In commercial banking, various statistical models for corporate credit rating have been theoretically promoted and applied to bank-specific credit portfolios. In this paper, we empirically compare and test the performance of a wide range of parametric and nonparametric credit rating model approaches in a statistically coherent way, based on a ‘real-world’ data set. We repetitively (k times) split a large sample of industrial firms’ default data into disjoint training and validation subsamples. For all model types, we estimate k out-of-sample discriminatory power measures, allowing us to compare the models coherently. We observe that more complex and nonparametric approaches, such as random forest, neural networks, and generalized additive models, perform best in-sample. However, comparing k out-of-sample cross-validation results, these models overfit and lose some of their predictive power. Rather than improving discriminatory power, we perceive their major contribution to be their usefulness as diagnostic tools for the selection of rating factors and the development of simpler, parametric models.

Risk assessment based on the analysis of the impact of contagion flow

This paper presents a new framework to model and calibrate the process of firm value evolution when an unanticipated exogenous event impacting one firm can contagiously affect other firms. The nature of propagation of such contagion is determined by the underlying connections between firms, which can adversely affect the tail risks of firm value, hence the securities issued by the firm. This paper combines the insights gained from the existing firm-value models and historical events into a structural model for flow of contagion among firms using a network-based approach. Rather than using stylized networks, we develop a data-driven approach for network construction where we define and calibrate several contagion variables to model the spread of contagion. This framework is applied for assessing firm-level risk under downside risk measures. Using actual data, our model illustrates how connections between firms can lead to heavy-tailed default distributions and default clustering observed in practice.     

Sharp approximations of ruin probabilities in the discrete time models

According to Solvency II directive, each insurance company could determine solvency capital requirements using its own, tailor made, internal model. This highlights the urgency of having fast numerical tools based on practically-oriented mathematical models. From the Solvency II perspective discrete time framework seems to be the most relevant one. In this paper, we propose a number of fast and accurate approximations of ruin probabilities involving some integral operator and examine them along strictly theoretical as well as numerical lines. For a few claim distributions the approximations are shown to be exact. In general, we prove that they converge with an exponential rate to the exact ruin probabilities without any restrictive assumptions on the claim distribution. A fast algorithm to approximate ruin probabilities by a numerical fixed point of the involved integral operator is given. As an application, ruin probabilities for, e.g. normally and Weibull – distributed claims are computed. Comparisons with discrete time counterparts of some continuous time approximation methods are also carried out. Numerical studies show that our approximations are precise both for small and large values of the initial surplus u. In contrast, the empirical De Vylder-type ones strongly depend on the claim distributions and are less precise for small and medium values of u.     

文化传媒上市公司全要素生产率的Globe Malmquist 研究

采用Global Malmquist指数研究我国26家文化传媒上市公司2006~2012年全要素生产率,结果表明:从总体上来说,文化传媒上市公司的全要素生产率(GM)、技术效率(EC)、技术进步指数(BPC)均呈现上下波动趋势。从平均水平来看,全要素生产率呈U型变动,而技术效率(EC)指数和技术进步(BPC)指数的平均水平变动不太稳定,说明我国文化产业的竞争力没有形成核心力,内生增长的方式需进行转型。     

保险资金入市的效应分析及其风险管理

保险资金进入资本市场，以多种方式投资于证券业务，是保险业自身经营发展的需要，也是增强我国保险业的盈利性和竞争力的需要。保险资金入市在给保险公司带来高收益的同时，必然伴随着高风险。无论是保险公司还是监管部门，建立有效的风险控制和监管机制，加强投资风险防范，保障资金安全都是十分必要的。     

Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields

We propose a Nelson–Siegel type interest rate term structure model where the underlying yield factors follow autoregressive processes with stochastic volatility. The factor volatilities parsimoniously capture risk inherent to the term structure and are associated with the time-varying uncertainty of the yield curve’s level, slope and curvature. Estimating the model based on US government bond yields applying Markov chain Monte Carlo techniques we find that the factor volatilities follow highly persistent processes. We show that yield factors and factor volatilities are closely related to macroeconomic state variables as well as the conditional variances thereof.     

Risk Management Lessons from the Credit Crisis

Risk management, even if flawlessly executed, does not guarantee that big losses will not occur. Big losses can occur because of business decisions and bad luck. Even so, the events of 2007 and 2008 have highlighted serious deficiencies in risk models. For some firms, risk models failed because of known unknowns. These include model risk, liquidity risk, and counterparty risk. In 2008, risk models largely failed due to unknown unknowns, which include regulatory and structural changes in capital markets. Risk management systems need to be improved and place a greater emphasis on stress tests and scenario analysis. In practice, this can only be based on position-based risk measures that are the basis for modern risk measurement architecture. Overall, this crisis has reinforced the importance of risk management.     

Index Revision,House Price Risk,and the Market for House Price Derivatives

It is widely recognized that options and futures markets for housing can reduce and manage the risks inherent in consumers’ large investments in housing equity. The integrity of such markets depends, however, upon the use of transparent and replicable benchmarks for house prices and settlement values. In the USA, a series of state and metropolitan indexes have been produced by a government agency (the US Office of Housing Enterprise Oversight, OFHEO), and they have been widely disseminated for over a decade. By construction, the entire historical path of each of these indexes is, in principle, subject to revision quarterly, that is, every time the index is recalculated and data are published. This paper provides the first analysis of the magnitude and bias of these revisions, and it analyzes their systematic effects on the settlement prices in housing options markets. The paper considers the implications of these magnitudes for the development of risk-reducing futures markets.

论我国企业年金管理模式改革的战略方向

通过对我国企业年金管理模式纵横两方面的比较,本文认为,从微观的企业年金管理的层面上讲,法人受托模式下的2+2和3+1捆绑模式是目前企业年金管理的两种较好方式;从宏观的企业年金改革的层面上讲,企业年金管理改革的战略方向有四:从非信托模式走向信托模式;从理事会受托模式走向法人受托模式;从法人受托分拆模式走向法人受托捆绑模式;从传统金融机构捆绑模式走向养老金管理公司捆绑模式。