基于时变β的基金绩效评价方法及实证研究

无论对投资者还是基金公司证券,投资基金的绩效评价具有重大意义。评估基金的投资绩效,不仅要考察基金的平均收益率,而且要看它承受的风险。本文利用我国基金市场数据样本,在考虑基金贝塔系数时变的情况下构造TVB指标,并且通过实证研究,对比出这种对基金绩效评价方法的优越性。     

Measuring the immeasurable — A survey of sustainability indices

Sustainability indices for countries provide a one-dimensional metric to valuate country-specific information on the three dimensions of sustainable development: economic, environmental, and social conditions. At the policy level, they suggest an unambiguous yardstick against which a country's development can be measured and even a cross-country comparison can be performed. This article reviews the explanatory power of various sustainability indices applied in policy practice. We show that these indices fail to fulfill fundamental scientific requirements making them rather useless if not misleading with respect to policy advice.     

我国社会保障支出的地区差异分析

文章首先运用GE指数分解法,分析我国社会保障支出区域差异及贡献率;然后运用GINI系数分解法,分析社会保障各项支出对总体差异的贡献率。结果表明:三大区域总体、区域内及区域间的差异基本呈下降趋势,期间略有起伏,但区域内差异远远大于区域间差异;东部、中部和西部地区差异变动趋势不一致,且对总体差异的贡献率差别较大;社会保障各项支出的贡献率差异较大,其中社会保障补助支出成为总体差异的主体因素。文章最后对实际测算结果作进一步分析,并提出相应的政策建议。     

From Returns to Tweets and Back: An Investigation of the Stocks in the Dow Jones Industrial Average

A sizeable percentage of investors are using social media to obtain information about companies (Cogent Research [2008]). As a consequence, social media content about firms may have an impact on stock prices (Hachman [2011]). Various studies utilize social media content to forecast stock market-related factors such as returns, volatility, or trading volume. The objective of this article is to investigate whether a bidirectional intraday relationship between stock returns and volatility and tweets exists. The study analyzed 150,180 minute-by-minute stock price and tweet data for the 30 stocks in the Dow Jones Industrial Average over a random 13-day interval from June 2 to June 18, 2014 using a BEKK-MVGARCH methodology. Findings indicate that 87% of stock returns are influenced by lagged innovations of the tweets data, but there is little evidence to support that the direction is reciprocal, with only 7% of tweets being influenced by lagged innovations of the stock returns. Results further show that the lagged innovations from 40 percent of stock returns affect the current conditional volatility of the tweets, while 73 percent of tweets affect the current conditional volatility of stock returns. Moreover, there is strong evidence to suggest that the volatility originating from the returns to the tweets persists for 33 percent of stocks; the volatility originating from the tweets to the returns persists for 73 percent of stocks. Last, 53 percent of stocks exhibit both immediate and persistent impacts from returns to tweets, while 90 percent of stocks exhibit both immediate and persistent impacts from tweets to returns. These results may help traders achieve superior returns by buying and selling individual stocks or options. Also, asset and mutual fund managers may benefit by developing a social media strategy.     

Measuring the liquidity part of volume

Based on the concept that the presence of liquidity frictions can increase the daily traded volume, we develop an extended version of the mixture of distribution hypothesis model (MDH) along the lines of Tauchen and Pitts (1983) to measure the liquidity portion of volume. Our approach relies on a structural definition of liquidity frictions arising from the theoretical framework of Grossman and Miller (1988), which explains how liquidity shocks affect the way in which information is incorporated into daily trading characteristics. In addition, we propose an econometric setup exploiting the volatility–volume relationship to filter the liquidity portion of volume and infer the presence of liquidity frictions using daily data. Finally, based on FTSE 100 stocks, we show that the extended MDH model proposed here outperforms that of Andersen (1996) and that the liquidity frictions are priced in the cross-section of stock returns.     

Volatility returns with vengeance: Financial markets vs. commodities

To assess how financial markets and commodities are inter-related, this paper introduces a ‘volatility surprise’ component into the asymmetric DCC with one exogenous variable (ADCCX) framework. We develop an econometric model in which returns and volatility allow to influence pairs of assets, and derive several case studies linking commodities to stocks, bonds and currencies from 1983 to 2013. The innovative feature of our model is that these volatility spillovers are modeled consistently within the correlation dynamics of the ADCCX. We find evidence that return and volatility spillovers do exist between commodity and financial markets and that in turn, their relative impact on each other is very substantial.     

Riding the swaption curve

We conduct an empirical analysis of the term structure in the volatility risk premium in the fixed income market by constructing long-short combinations of two at-the-money straddles for the four major swaption markets (USD, JPY, EUR and GBP). Our findings are consistent with a concave, upward-sloping maturity structure for all markets, with the largest negative premium for the shortest term maturity. The fact that both delta–vega and delta–gamma neutral straddle combinations earn positive returns that seem uncorrelated suggests that the term structure is affected by both jump risk and volatility risk. The results seem robust for macroeconomic announcements and the specific model choice to estimate the risk exposures for hedging.     

Growth uncertainty,generalized disappointment aversion and production-based asset pricing

We study a production economy with regime switching in the conditional mean and volatility of productivity growth. The representative agent has generalized disappointment aversion (GDA) preferences. We show that volatility risk in productivity growth carries a positive and sizable risk premium in levered equity. Our model can endogenously generate long-run risks in the volatility of consumption growth observed in the data. We show that introducing leverage with a procyclical dividend process consistent with the data is critical for the GDA preferences to have a large impact on equity returns.     

Early warning indicators? The effect of consumer and investor sentiments on the restaurant industry

This study looks at the influence of cyclical fluctuations of the consumer confidence index (CCI) and the volatility index (VIX) as early-warning indicators of the variations in restaurant performance. The industry has traditionally focused on past data and on microeconomic influences to anticipate its future performance, a procedure that does not consider possible cyclical fluctuations in restaurant performance metrics. These fluctuations are driven by sentiments of consumers and investors. The study uses the cyclical component of the applied data, followed by unit root and cointegration testing, with subsequent application of the Limited Information Maximum Likelihood technique. The results show both indicators have an effect on restaurant performance, where VIX has an impact on the current, expected, and overall restaurant performance, while the CCI’s influence is only partial (current performance). Policy-makers and planners could benefit from anticipating features of indicators to assess and steer the future performance of the restaurant industry.     

Modelling international tourism and country risk spillovers for Cyprus and Malta

Small Island Tourism Economies (SITEs) are developing sovereign countries that rely on tourism as a source of exports, and need a consistent inflow of foreign investment in order to facilitate economic growth. Access to international capital markets helps SITEs smooth out their consumption over time, while absorbing adverse domestic production shocks. This paper provides a comparison of tourism growth, country risk returns and their associated volatilities (or uncertainty) for 2 SITEs, namely Cyprus and Malta. Monthly data are available for both international tourist arrivals and composite country risk ratings compiled by the International Country Risk Guide (ICRG) for the period May 1986 to May 2002. The time-varying conditional variances of tourism growth and country risk returns for the 2 SITEs are analysed using multivariate models of conditional volatility. Empirical results show that Cyprus and Malta are complementary destinations for international tourists. Changes to tourism patterns in Cyprus lead to changes to tourism patterns in Malta. Hence, tour operators and national tourism promotion authorities in Cyprus and Malta should collaborate closely in marketing and promoting joint tourism products. Moreover, foreign entities interested in investing in the tourism sectors of Cyprus and Malta should consider investment projects that span a long period of time. The performance of the tourism sector and the associated composite risk are independent of each other for the two countries. However, there is a direct relationship between the tourism sectors of Cyprus and Malta and their respective country risk settings.