#br# 融资融券加大了沪深股市波动吗*

融资融券设计初衷是通过融资加强市场流动性和通过融券提供投资者规避价格下跌风险的金融工具，改善由供求关系严重失衡导致市场巨幅震荡的局面，实现资本市场长期稳定的目标。实际操作中，融资融券疏通货币市场和资本市场间的资金流动，撬动巨额资金涌入股市；融资规模扩张过快而融券做空力量薄弱，业务结构发展严重失衡，导致两融业务具有“小冲击、大波动”的金融加速效应，放大了外部冲击引起股价上涨和下跌的幅度。协整回归分析表明，两融业务规模的扩张和收缩对上证指数涨跌具有显著的同向影响。TGARCH事件模型结果进一步证实融资融券从稳定股价到加剧波动的功能变化。随着标的股票扩容和业务常规化，两融业务导致股市投机过度，加剧了沪深两市的资产价格异动，没有达到平抑波动的设计预期。     

Comparative randomized inverse sampling

According to previous literature, we define randomized inverse sampling for comparing two treatments with respect to a binary response as the sampling that stops when a total fixed number of successes, irrespective of the treatments, are observed. We have obtained elsewhere the asymptotic distributions for the counting variables involved and have shown them to be equivalent to the corresponding asymptotic distributions for multinomial sampling. In this paper, we start deriving the same basic results using different techniques, and we then show how they give rise to genuinely novel procedures when translated into finite sample approximations. As the main example, a novel confidence interval for the logarithm of the odds ratio of two success probabilities can be constructed in the case of comparative randomized inverse sampling. Some advantages over the standard multinomial sampling in terms of coverage probabilities are visible when no adjustment for cells with zero counts is applied; otherwise, the two sampling schemes appear to be fairly equivalent. This is a reassurance that under certain circumstances, inverse sampling can be safely chosen over more traditional sampling schemes.     

Venture capital trusts and the expiration of IPO lock-up provisions

Venture capital trusts (VCTs) were introduced to provide private equity capital for small expanding companies and to promote innovation. Investors in initial public offerings are rewarded with tax relief on the cost of lock-up provisions to stabilize the market. This paper examines the market reaction and trading activity around the expiration of lock-up provisions of 148 VCTs listed on the London Stock Exchange from 1995 to 2006. Downward-sloping demand curve theory suggests that an increased supply of VCT shares at the expiry date could shift their value to a new equilibrium at a lower price. Supporting this prediction, we document evidence of negative abnormal returns as well as permanent increases in the price discount relative to net asset value and trading volumes at and around the expiries of the required holding periods of VCTs. In addition, less negative abnormal returns, lower abnormal discounts and lower abnormal trading volumes are associated with VCTs that invest in AIM-listed companies due to lower information asymmetry, that experience lower prior performance due to a less pronounced disposition effect, and that are subject to a shorter lock-up horizon or are offering more generous tax benefits.     

DSGE pileups

The sampling distribution of estimators for DSGE structural parameters tends to be non-normal and/or pile up on the boundary of the theoretically admissible parameter space. This calls into question both the reliability of asymptotic approximations and the presumption of correct specification. This paper seeks to develop a conceptual framework for understanding how these phenomena arise, and to provide pragmatic methods for dealing with them in practice. The results are presented in three examples and a medium scale DSGE model.     

The Role of Financial Ratios in the Variance of Stock Trading Volume in Emerging Stock Markets

The study used quarterly panel data of 6 years from 2010 to 2015 of all companies listed on both Vietnamese stock markets including the Ho Chi Minh City Stock Exchange and Ha Noi Stock Exchange, and on three leading industries consisting of insurance-banking, foodstuff, and real estate to explore the relationship among four key financial ratios and stock trading volume. Two models, fixed effects model (FEM) and random effects model (REM), with robust standard errors, were applied for this study. The key findings showed that earnings before tax on sales, debt on owner’s equity, and owner’s equity on total assets significantly influenced trading volume.     

An Empirical Investigation of the Effects of Rounding on the SPF Probabilities of Decline and Output Growth Histograms

I consider the possibility that respondents to the Survey of Professional Forecasters round their probability forecasts of the event that real output will decline in the future, as well as their reported output growth probability distributions. I make various plausible assumptions about respondents’ rounding practices, and show how these impinge upon the apparent mismatch between probability forecasts of a decline in output and the probabilities of this event implied by the annual output growth histograms. I find that rounding accounts for about a quarter of the inconsistent pairs of forecasts.     

LACK OF RIGOUR IN DEFENDING FAIRTRADE: A REJOINDER TO ALISTAIR SMITH

Smith (2010 ) does not deny that he made errors in economic theory, logic and fact, and that he had misused evidence. He says that I misrepresented a large body of theory, that I distorted what he said in four places and that I was wrong in one sentence. These statements are false.     

Cointegration as an explanation for the Meese–Rogoff puzzle

Some economists suggest that the failure of exchange-rate models to outperform the random walk in exchange rate forecasting out of sample can be attributed to failure to take into account cointegration when it is present. We attempt to find out if cointegration matters for forecasting accuracy by examining the relation between the stationarity and size of the forecasting error. Results based on three macroeconomic models of exchange rates do not provide strong support for the proposition that cointegration matters for forecasting accuracy. The simulation results show that while stationary errors tend to be smaller than non-stationary errors, this is not a universal rule. Irrespective of the presence or absence of cointegration, none of the three models can outperform the random walk in out-of-sample forecasting, which means that cointegration cannot solve the Meese–Rogoff puzzle.