中国人力资本水平与FDI技术溢出关系研究

针对1985-2009年间中国人力资本水平和FDI技术溢出进行VECM模型检验结果表明,我国人力资本水平与FDI技术溢出存在长期稳定关系,但短期关系不显著。从动态层面看,FDI技术溢出变化对我国人力资本水平有显著的正向影响,但我国人力资本水平变化对FDI技术溢出的正向影响程度较弱。     

西部欠发达地区FDI与经济增长的动态关系研究——以广西数据为例

以广西1986～2009年有关数据为基础,运用协整分析、脉冲响应函数和方差分解分析等方法,对外商直接投资和经济增长之间的动态关系进行实证分析.结果显示:广西的外商直接投资与经济增长之间具有长期均衡关系,而且FDI对GDP增长具有较弱的正效应,短期具有一定的波动性。最后,提出相关的政策措施。     

序列相关的微观结构噪声估计

基于股票有效价格计算的已实现波动率(Realized Variance)可作为股票收益波动率的估计,且在一定条件下,这一估计是无偏的和一致的。然而实际观测到的价格由于受到市场微观结构导致的噪声的干扰,与有效价格并不一致。因此,在高频数据环境下必须考虑如何降低噪声干扰。本文基于Hansen和Lunde给出的在噪声序列存在相关性假设下的一种关于RV的无偏估计,进一步推导出在此情形下估计噪声方差的方法。我们的估计挖掘了不同频率下的股票交易高频数据所反映出的信息,利用传统的在噪声影响下的有偏RV估计与Hansen和Lunde的无偏RV估计之间的差估计噪声。同时,本文也给出了在实践中如何确定这些频率的方法。     

Regulatory reform and market efficiency: The case of Indian agricultural commodity futures markets

We present the results of two efficiency measures that include intraday return predictability measure based on order imbalance and measures of several variance ratio tests on intraday subsamples of nine major Indian agricultural commodity futures (castor seed, cotton oil cake, rape mustard seed, soybean, refined soya oil, crude palm oil, jeera, chana, and turmeric) quoted in the National Commodity and Derivatives Exchange (NCDEX). We perform the efficiency measures on five subsamples with holding periods of 5, 10, 15, 30, and 60 min over two sample periods following the announcement of the merger between the Forward Market Commission (FMC) and Securities Exchange Board of India (SEBI). We compare results of tests of weak-form market efficiency of futures markets between two periods (pre-merger period and post-merger period). Our results confirm that Indian agricultural commodity futures markets continue to remain inefficient in the short-term during both pre-merger and post-merger periods. Based on these findings, it is likely that profitable trading strategies in the short intraday intervals will be available for traders and market participants during post-merger period. Thus, regulators must focus more on policy initiative so as to enhance market quality in order to address such inefficiencies in Indian commodity futures markets.     

Nexus between telecommunication infrastructures,economic growth and development in Africa: Panel vector autoregression (P-VAR) analysis

This study examines the causal-effect relationship between telecommunication infrastructures, economic growth and development in selected African countries. It further estimates the trivariate impacts of telecommunication infrastructures, economic growth and development in the region. The analysis considers a panel of forty-six African countries from 2000 to 2015. To measure economic growth, real gross domestic product serves as the proxy, while economic development is measured by the Human Development Index, and telecommunication infrastructures by a composite index of telecommunication computed from mobile line, fixed line and internet access penetration via principal component analysis (PCA). The empirical results suggest the existence of a bidirectional long-run relationship between telecommunication infrastructures, economic growth and development. The causality tests reveal that there is feedback causality between telecommunication infrastructures, economic growth and development. Telecommunication infrastructures promote economic growth and development in Africa and vice versa. Thus, there is need to promote inclusive and holistic policies that will enhance digital provide, economic growth and development simultaneously in Africa. An increase in telecommunication infrastructures will encourage aggregate output and standard of living to move in the same direction in Africa.     

ARE LONG-HORIZON STOCK RETURNS PREDICTABLE? A BOOTSTRAP ANALYSIS

This paper examines empirical evidence of predictability of long-horizon real and excess stock returns in the UK using univariate as well as multivariate Variance Ratio tests. In order to estimate the sampling distribution of the test statistics, artificial histories ofstock returns are generated from their empirical distribution using the bootstrap method. This allows the construction of significance levels of the test statistic which are free from distributional assumptions. The empirical results indicate that there is no evidence of mean reversion in stock prices even if a wider information set to forecast stock returns is used and that the significance of historical Variance Ratio statistics has been overstated by previous studies.     

Optimal investments in volatility

Volatility has evolved as an attractive new asset class of its own. The most common instruments for trading volatility are variance swaps. Mean returns of DAX and ESX variance swaps over the time period of 1995 to 2004 are strongly negative, and only part of the negative premium can be explained by the negative correlation of variance swap returns with stock market indices. We analyze the implications of this observation for optimal portfolio composition. Mean-variance efficient portfolios are characterized by sizable short positions in variance swaps. Typically, the stock index is also sold short to achieve a better portfolio diversification. To capture heterogeneous preferences for higher moments, we use a variant of the polynomial goal programming method. We assume that investors strive for a high Sharpe ratio, high skewness, and low kurtosis. Our analysis reveals that it is often not possible to achieve a balanced tradeoff between Sharpe ratio and skewness. Investors are advised to hold the extreme portfolios (Sharpe ratio driven, skewness driven, or kurtosis driven) and avoid the middle ground. This “all-or-nothing” characteristic is reflected in jumps of asset weights when certain thresholds of preference parameters are crossed. These empirical findings can explain why many investors are so reluctant to implement option-based short-selling strategies.

Measuring connectedness of euro area sovereign risk

We introduce a method for measuring the default risk connectedness of euro zone sovereign states using credit default swap (CDS) and bond data. The connectedness measure is based on an out-of-sample variance decomposition of model forecast errors. Due to its predictive nature, it can respond to crisis occurrences more quickly than common in-sample techniques. We determine the sovereign default risk connectedness using both CDS and bond data in order to obtain a more comprehensive picture of the system. We find evidence that there are several observable factors that drive the difference between CDS and bonds, but both data sources still contain specific information for connectedness spill-overs. In general, we can identify countries that impose risk on the system and the respective spill-over channels. Our empirical analysis covers the years 2009–2014, such that the recovery paths of countries exiting EU and IMF financial assistance schemes and the responses to the ECB’s unconventional policy measures can be analyzed.     

Measuring the increasing connectedness of Chinese assets with global assets: using a variance decompositions method

This study uses the network topology of variance decompositions to investigate the connectedness of four assets (stocks, bonds, foreign exchange and commodities) across five countries (US, EU, UK, Japan and China). We find that connectedness to and from the Chinese asset markets increased significantly from 2013 to 2018, which reveals that Chinese assets have gradually become integrated into the global economy. We also investigate the volatility connectedness in economically fragile periods and find that the Chinese market acted as a transmitter of volatility in the 2015 Chinese stock crash. This finding is potentially essential to modern risk measurement and management.     

Inferring volatility dynamics and risk premia from the S&P 500 and VIX markets

We estimate a flexible affine model using an unbalanced panel containing S&P 500 and VIX index returns and option prices and analyze the contribution of VIX options to the model’s in- and out-of-sample performance. We find that they contain valuable information on the risk-neutral conditional distributions of volatility at different time horizons, which is not spanned by the S&P 500 market. This information allows enhanced estimation of the variance risk premium. We gain new insights on the term structure of the variance risk premium, present a trading strategy exploiting these insights, and show how to improve S&P 500 return forecasts.