Hedging and diversification across commodity assets

ABSTRACT

We investigate the conditional cross effects and volatility spillover between equity markets and commodity markets (oil and gold), Fama and French HML and SMB factors, volatility index (VIX) and bonds using different multivariate GARCH specifications considering the potential asymmetry and persistence behaviours. We analyse the dynamic conditional correlation between the US equity market and a set of commodity prices and risk factors to forecast the transmission of shock to the equity market firstly, and to determine and compare the optimal hedge ratios from the different models based on the hedging effectiveness of each model. Our findings suggest that all models confirm the significant returns and volatility spillovers. More importantly, we find that GO-GARCH is the best-fit model for modelling the joint dynamics of different financial variables. The results of the current study have implications for investors: (i) the equity market displays inverted dynamics with the volatility index suggesting strong evidence of diversification benefit; (ii) of the hedging assets gold appears the best hedge for the US equity market as it has a higher hedge effectiveness than oil and bonds over time; and (iii) despite these important results, a better hedge may be obtained by using well-selected firm sized and profitability-based portfolios.     

中国通货膨胀率及其波动关系分析

有关通货膨胀率和通货膨胀率波动影响关系,存在F riedm an-B a ll和Cuk ierm an-M e ltzer两种假说,即存在通货膨胀率及其波动的相互影响关系。使用GARCH和TGARCH模型,选择中国1993~2004年月度通货膨胀率数据,检验结果表明F riedm an-B a ll假说成立,稳健的货币政策对经济发展有积极作用。     

中国通货膨胀及其波动性关系的实证研究

本文利用GARCH模型生成中国通货膨胀波动性的衡量指标,并实证分析1983年1月至2010年4月中国的通货膨胀与通货膨胀波动性之间的关系。结果表明:在中国,通货膨胀率是通货膨胀波动性的Granger原因,通货膨胀对通货膨胀波动性有稳定的正向影响关系,同时相同强度的通货膨胀冲击远远大于通货紧缩冲击对通货膨胀波动性的影响。对中国而言,控制通货膨胀比追求经济增长更重要。     

货币增长不确定性与通货膨胀不确定性——“波动溢出”假说与实证检验

文章基于通货膨胀——通货膨胀不确定性关系的理论研究,提出货币增长不确定性向通货膨胀不确定性波动溢出的计量检验假说,并利用中国数据,运用多元GARCH模型进行实证检验。结果发现,存在货币增长不确定性显著向通货膨胀不确定性波动溢出的效应。这意味着,货币增长不确定性具有提供有关预测通货膨胀不确定性信息的能力。同时也表明,货币增长不确定性是通货膨胀不确定性的重要解释变量,其重要性不应被忽视。实证结论的政策含义是:减少货币增长不确定性是降低通货膨胀不确定性的重要途径,我国20世纪90年代中后期稳健的货币政策所带来的通货膨胀不确定性显著降低的现实支持了这个观点。     

Do domestic bond markets participation help reduce financial dollarization in developing countries?

In this paper, I analyze the effect of domestic sovereign bond market (BM) participation on financial dollarization using a large panel of 114 developing countries over the period 1984–2009. Building on entropy balancing, my results reveal strong evidence that domestic BM participation significantly reduces financial dollarization in domestic BM countries compared to their non-domestic BM peers. Moreover, I find that the favorable impact of domestic BM on financial dollarization (i) is larger for inflation targeting countries compared to non-inflation targeting countries, (ii) is apparent exclusively in a non-pegged exchange rate regime, (iii) and is larger when there are fiscal rules that constrain the discretion of fiscal policy makers. Finally, I show that the induced drop in inflation rate and its variability, nominal exchange rate variability, and seigniorage revenue are potential transmission mechanisms through which the presence of domestic BM reduces financial dollarization in domestic BM countries.     

我国通胀对股票市场条件波动影响研究

将通胀引入标准GARCH模型,分别研究我国通胀率、通胀率变化和移动平均通胀率对股市条件波动的影响。实证结果表明通胀对我国股票市场条件波动几乎不存在影响,从而否定了通胀会使投资者预期经济变坏,更加厌恶风险,以致引起资产价格剧烈波动的假说。     

“Expiration hour effect of futures and options markets on stock market” — A case study on NSE (National Stock Exchange of India)

This paper studies the effect of expiration day of the Index futures and Options on the trading volume, variance and price of the underlying shares. The impact of derivatives trading on the underlying stock market has been widely documented in the Finance literature. In particular, significant differences in the statistical properties of asset returns (for instance, mean and variance) during expiration and non-expiration days have been advanced as an evidence for the destabilization effect (or lack there of) of derivative instruments. The earlier studies have, however, drawn their conclusions without rigorously modelling the underlying stochastic data generation process. Given that the statistical properties mentioned before are merely traits of the asset returns, this approach can lead to spurious results if analyzed in isolation of the underlying process. We propose to address this crucial shortcoming by examining the expiration day effect from a GARCH (Generalized Auto Regressive Conditional Heteroskedastic) framework. We use both daily and high frequency (5 min and 10 min) data on S&P CNX Nifty Index. Our central finding using intra-day data is that while there is no pressure – downward or upward – on index returns, the volatility is indeed significantly affected by the expiration of contracts. This effect, however, doesn’t show up in daily data.     

A nonparametric method for term structure fitting with automatic smoothing

We present a nonparametric method for fitting the term structure of interest rates from bond prices. Our method is a variant of the smoothing spline approach, but within our framework we are able to determine the smoothing coefficient automatically from data using the generalized cross-validation or maximum likelihood estimates. We present an effective numerical algorithm to simultaneously find the term structure and the optimal smoothing coefficient. Finally, we compare the proposed nonparametric fitting method with other parametric and nonparametric methods to find its superior performance. We find that existing term structure fitting methods perform well in liquid markets while illiquid markets present new challenges, which we address in this article.     

Does inflation cause gold market price changes? evidence on the G7 countries from the tests of nonparametric quantile causality in mean and variance

This article utilizes the newly proposed nonparametric causality-in-quantiles test to examine the predictability of mean and variance of changes in gold prices based on inflation for G7 countries. The causality-in-quantiles approach permits us to test for not only causality in mean but also causality in variance. We start our investigation by utilizing tests for nonlinearity. These tests identify nonlinearity, showing that the linear Granger causality tests are subject to misspecification error. Unlike tests of misspecified linear models, our nonparametric causality-in-quantiles tests find causality in mean and variance from inflation to gold market price changes between the 0.20 quantile and the 0.70 quantile, implying that very low- and high-price changes in gold markets are not related to inflation. These changes should be related to other sources, such as financial shocks and exchange market shocks. We find support that gold serves as a hedge against inflation, but only in the mid-quantile ranges, i.e. quantiles from 0.20 to 0.70. Our results show that gold does not serve as a hedge against inflation during periods when gold market price changes are very low or very high, which are respectively quiet and highly volatile periods.