Positive feedback trading and long-term volatility links: evidence from real estate markets of USA,Be/Lux and Switzerland

This article investigates the positive feedback trading strategies in the real estate markets of USA, Belgium/Luxembourg (Be/Lux) and Switzerland, linking these strategies with long-term volatility. The results are in favour of a positive feedback trading strategy which negatively influences investors' risk-return position on real estate markets.     

基于遗传算法的中国股市波动性研究

本文介绍了金融市场波动性过程的长期记忆性特征的分整自回归条件异方差模型——FIGARCH（p,d,q）,并介绍了一种建立FIGARCH模型的新方法——遗传算法。对上证综合指数进行实证分析,对其收益率建立自回归模型（AR模型）,由Eviews软件可知模型的残差项具有明显的异方差效应,应用遗传算法的基本步骤进行C语言编程,由此求解FIGARCH模型的各项参数值,从而建立FIGARCH模型,实证结果表明中国股市波动性过程具有明显的长记忆性。     

Impacts of the financial crisis on eurozone sovereign CDS spreads

We study the variation of sovereign credit default swaps (CDSs) of eurozone countries, their persistence and co-movements, with particular attention given to the impact of the financial crisis. Specifically, using a dual fractional integration model, we test the evidence of long memory for CDSs of ten eurozone countries. Our analysis reveals that price discovery processes satisfy the minimum requirements for a weak form of efficiency for sovereign CDS markets, even during the crisis. In contrast, we document the spreading out of persistent CDS uncertainty among the peripheral economies with its outbreak. We provide evidence that CDS uncertainty has implications for the pricing of sovereign risk including that of core countries in the crisis period. Finally, we present the potential spillover effects utilizing a dynamic conditional correlation model and show that, with the collapse of Lehman, the probability of a contagion increased across all countries and became more explicit for peripheral economies as the sovereign crisis took on a new dimension.     

基于FIGARCH模型的中国房地产指数的实证分析

在T分布和正态分布假设下采用GARCH模型和FIGARCH模型对上证地产股指数日收益率序列进行建模分析,结果表明,上证地产股指数日收益率序列的波动具有显著的长记忆性,表明外部冲击对波动有着长期的影响。因此,采用FIGARCH模型建模的效果优于采用GARCH模型建模的效果,并且在T分布假设下拟合模型,其效果优于在正态分布假设下拟合的模型。     

Computing value at risk with high frequency data

We compare the computation of value at risk with daily and with high frequency data for the Deutsche mark–US dollar exchange rate. Among the main points considered in the paper are: (a) the comparison of measures of value at risk on the basis of multi-step volatility forecasts; (b) the computation of the degree of fractional differencing for high frequency data in the context of a Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity (FIGARCH) model; and (c) the comparison between deterministic and stochastic models for the filtering of high frequency returns.     

International nonlinear causality between stock markets

In this paper, we test for linear and nonlinear Granger causality between the French, German, Japanese, UK and US daily stock index returns from 1973 to 2003. We find a strong contemporaneous linear dependence between European countries and a directional linear dependence from the US towards the other markets. Besides, linear causality increases after 1987, a finding consistent with the expected effects of financial liberalization of the 1980s and the 1990s. Above all, we document the presence of bidirectional nonlinear causality between daily returns. To check for spurious nonlinear causality, we filter out heteroskedasticity using a FIGARCH model. The dramatic decrease in the number of significant nonlinear causality lags confirms that heteroskedasticity played a major part in the previous findings. We then check if a few structural breaks can explain the remaining nonlinear causality. We find that a large number of nonlinear relationships vanish when we control for structural breaks, whereas linear causality remains.     

FIGARCH的协同持续性研究

波动持续性是广泛存在于金融事件序列的一类普遍现象,波动持续性建模是从动态的角度研究风险变化的一种有效方法。由于分形理论能够准确描述经济行为本身的非线性结构特点,将分形方法引入了协同持续研究中,引出了FIGARCH模型,考察了FIGARCH的协同持续性。     

Deviations from daily uncovered interest rate parity and the role of intervention

This paper considers the relationship between daily deviations from uncovered interest rate parity and US and German central bank intervention. The study uses daily overnight Eurocurrency deposit rates with a maturity time of 1 day, which exactly matches the sampling interval of the data. The intervention data are the official net daily purchases and sales of dollars vis-à-vis the German mark by the Federal Reserve System and the Bundesbank. The model uses FIGARCH innovations to represent the degree of long-term dependence in the volatility process. Some support is found for the intervention variables affecting the risk premium as predicted by theory. The impact of intervention in the 2 years immediately following the meltdown of the equity markets in October 1987 and Louvre Accord is particularly strong.     

基于波动阶段划分的我国期铜市场长期记忆性实证研究

金融市场通常由于波动结构性突变的存在而出现伪长记忆性现象。运用ICSS算法寻找方差突变点进行阶段划分，运用V／S分析法对我国期铜市场波动阶段前后的长期记忆性进行检测和比较，并利用FIGARCH模型对波动序列的长期记忆性进行建模估计。研究结果表明，我国期铜市场存在全程长期记忆性；阶段划分后序列的长期记忆性显著降低；期铜波动的FIGARCH模型具有更优的拟舍效果和预测能力。     

LONG MEMORY IN SOUTHERN AFRICAN STOCK MARKETS

The paper examines long memory in equity returns and volatility for stock markets in Botswana, South Africa and Zimbabwe using the ARFIMA‐FIGARCH model in order to assess the efficiency of these markets in processing information. The findings are diverse. Significant long memory is demonstrated in the equity returns of Botswana; while, in South Africa this result is not statistically different from zero. For Zimbabwe returns are characterised by an anti‐persistent process. Furthermore, all the markets investigated provide evidence of long memory in volatility with the exception of Botswana where there is no evidence of volatility persistence and hence the return from taking risk in this market cannot be predicted on the basis of previous values.