The impact of global economic policy uncertainty on portfolio optimization: A Black–Litterman approach

This paper investigates the asymmetric impact of global economic policy uncertainty (GEPU) on global asset allocation. We employ the Double Asymmetric GARCH-MIDAS (DAGM) model to examine the asymmetric effect of GEPU shocks on long-term volatilities of global equities, bonds, commodities, clean energy and Bitcoin. The GEPU-based volatility is used as a proxy for the uncertainty of the investor’s views in the Black-Litterman (BL) framework. Empirical results show that the BL model with GEPU-based views yields higher out-of-sample risk-adjusted returns than other traditional benchmarks in most cases. The findings suggest that investors should consider the influence of GEPU when making portfolio decisions.     

The relationship between implied and realized volatility: evidence from the Australian stock index option market

This paper examines the relationship between the volatility implied in option prices and the subsequently realized volatility by using the S&P/ASX 200 index options (XJO) traded on the Australian Stock Exchange (ASX) during a period of 5 years. Unlike stock index options such as the S&P 100 index options in the US market, the S&P/ASX 200 index options are traded infrequently and in low volumes, and have a long maturity cycle. Thus an errors-in-variables problem for measurement of implied volatility is more likely to exist. After accounting for this problem by instrumental variable method, it is found that both call and put implied volatilities are superior to historical volatility in forecasting future realized volatility. Moreover, implied call volatility is nearly an unbiased forecast of future volatility.

Does economic policy uncertainty drive the dynamic spillover among traditional currencies and cryptocurrencies? The role of the COVID-19 pandemic

The paper examines the dynamic spillover among traditional currencies and cryptocurrencies before and during the COVID-19 pandemic and investigates whether economic policy uncertainty (EPU) impacts this spillover. Based on the TVP-VAR approach, we find evidence of spillover effects among currencies, which increased widely during the pandemic. In addition, results suggest that almost all cryptocurrencies remain as “safe-haven” tools against market uncertainty during the COVID-19 period. Moreover, comparative analysis shows that the total connectedness for cryptocurrencies is lower than for traditional currencies during the crisis. Further analysis using quantile regression suggests that EPU exerts an impact on the total and the net spillovers with different degrees across currencies and this impact is affected by the health crisis. Our findings have important policy implications for policymakers, investors, and international traders.     

A multivariate nonparametric test for return and volatility timing

This paper develops a novel approach to simultaneously test for market timing in stock index returns and volatility. The tests are based on the estimation of a system of regression equations with indicator variables and provide detailed information about the statistical significance of alternative market timing components.     

不同的政策不确定性对股市波动影响相同吗?

本文基于多因子混频波动率模型,研究经济政策不确定性对股市行业波动的影响,为预防出现结构性断点,将样本分为经济增长和经济平稳两个时期,分别探讨两个时期内经济政策不确定性对股市波动的影响。研究发现,在全样本时期货币政策不确定性会显著增强行业波动,贸易和外汇政策不确定性会抑制行业波动,而财政政策不确定性的影响存在行业差异性;子样本结果显示,贸易政策不确定性对行业波动的影响存在非对称性,在经济增长期存在助推作用,在经济平稳期存在抑制作用;同时行业波动在经济增长期对贸易政策反应敏感,在经济平稳期对财政政策反应敏感。     

Realizing smiles: Options pricing with realized volatility

We develop a discrete-time stochastic volatility option pricing model exploiting the information contained in the Realized Volatility (RV), which is used as a proxy of the unobservable log-return volatility. We model the RV dynamics by a simple and effective long-memory process, whose parameters can be easily estimated using historical data. Assuming an exponentially affine stochastic discount factor, we obtain a fully analytic change of measure. An empirical analysis of Standard and Poor's 500 index options illustrates that our model outperforms competing time-varying and stochastic volatility option pricing models.     

Efficient estimation of drift parameters in stochastic volatility models

We study the parametric problem of estimating the drift coefficient in a stochastic volatility model , where Y is a log price process and V the volatility process. Assuming that one can recover the volatility, precisely enough, from the observation of the price process, we construct an efficient estimator for the drift parameter of the diffusion V. As an application we present the efficient estimation based on the discrete sampling with δ _n →0 and n δ _n →∞. We show that our setup is general enough to cover the case of ‘microstructure noise’ for the price process as well.      

Iterative method for exponentially weighted rolling regression

This note proposes an iterative method for exponentially weighted rolling regression (EWRR), which was proved to be an optimal estimator of volatility by Foster and Nelson [Econometrica 64 (1996)]. The method accelerates the numerical evaluation of EWRR under certain circumstances. An alternative to usual realized volatility is proposed for its application.     

What is the correct meaning of implied volatility?

This paper presents a closed-form solution for the valuation of European options under the assumption that the excess returns of an underlying asset follow a diffusion process. In light of our model, the implied volatility computed from the Black–Scholes formula should be viewed as the volatility of excess returns rather than as the volatility of gross returns. Using the SPX and the OMX options data, we test whether implied volatility obtained from Black-Scholes option price explains the volatilities of excess returns better than gross returns, even though the result is not statistically significant.     

When to go abroad: economic policy uncertainty and Chinese firms’ overseas investment

We study how economic policy uncertainty (EPU) influences firms’ overseas investments for Chinese listed companies. We find a significant negative relationship between EPU and firms’ overseas investments after controlling for firm characteristics and macroeconomic variables. Chinese firms seem to reduce their overseas investments on fixed income securities when facing domestic policy uncertainty. The negative relationship is pronounced for financially constrained firms, firms relying on government subsidies and with low overseas revenues, and SOEs. Firms operating in high marketisation regions can mitigate the negative effect of EPU on firms’ overseas investments. Our results remain significant when considering endogeneity problems.     

Asymmetric volatility in the foreign exchange markets

We examine the presence or absence of asymmetric volatility in the exchange rates of Australian dollar (AUD), Euro (EUR), British pound (GBP) and Japanese yen (JPY), all against US dollar. Our investigation is based on a variant of the heterogeneous autoregressive realized volatility model, using daily realized variance and return series from 1996 to 2004. We find that a depreciation against USD leads to significantly greater volatility than an appreciation for AUD and GBP, whereas the opposite is true for JPY. Relative to volatility on days following a positive one-standard-deviation return, volatility on days following a negative one-standard-deviation return is higher by 6.6% for AUD, 6.1% for GBP, and 21.2% for JPY. The realized volatility of EUR appears to be symmetric. These results are robust to the removal of jump component from realized volatility and the sub-samplings defined by structural-changes. The asymmetry in AUD, GBP and JPY appears to be embedded in the continuous component of realized volatility rather than the jump component.     

What drives U.S. financial sector volatility? A Bayesian model averaging perspective

We investigate the driving forces behind the quarterly stock price volatility of firms in the U.S. financial sector over the period from 1990 to 2017. The driving forces represent a set of 28 economic indicators that are routinely used to detect financial instability and crises and correspond to the development of the financial, monetary, real, trade and fiscal sector as well as to the development of the bond and equity markets. The dimensionality and model choice uncertainty are addressed using Bayesian model averaging, which led to the identification of only seven variables that tend to systematically drive the stock price volatility of financial firms in the U.S.: housing prices, short-term interest rates, net national savings, default yield spread, and three credit market variables. We also confirm that our results are not an artefact of volatility associated with market downturns (for negative semi-volatility), as the results are similar even when market volatility is associated with market upsurge (positive semi-volatility). Given the identified drivers, our results provide supporting empirical evidence that dampening credit cycles might lead to decreased volatility in the financial sector.     

The distribution of realized variances: Marginal behaviors, asymmetric dependence and contagion effects

We examine the unconditional distribution of the realized variance of three European stock market indexes obtained from intraday transaction prices. We find that they share common distributional features: a significant mass close to zero, a sharp decrease afterwards and a significant right tail. Their important differences, however, compel us to model them non-parametrically through lognormal kernel estimators. We then move to the analysis of their dependence structure and find strong evidence of asymmetry. Hence, unlike common practice, we resort to non-exchangeable copula models. Such a characterization also allows us to assess the direction of greater contamination among stock market variances.     

基于“已实现”波动率的ARFIMA模型预测实证研究

本文采用二次移动平均方法平衡影响"已实现"波动率预测精度的测量误差和市场微观结构误差,利用沪深300指数高频数据实证研究,结果表明"已实现"波动率序列的分布是非正态分布且具有长记忆性,对数"已实现"波动率序列接近于正态分布;最后建立ARFIMA模型,并对波动率进行了预测研究。