The Impact of the GFC on Sectoral Market Efficiency: Non‐linear Testing for the Case of Australia

This paper investigates the efficiency of the Australian stock market during the period of volatility and disruption associated with the Global Financial Crises (GFC). Furthermore, the investigation seeks to observe any divergence in market efficiency between industry sectors that demonstrate differing economic performance across the period. Spanning a time period of 2000–2015, the data are split into three periods of distinct economic conditions: a pre‐crisis period of relatively high growth, the GFC period of disruption and contraction, and a post‐GFC period of relatively low growth. Five sector indices listed on the Australian Securities Exchange are analysed to search for evidence of market efficiency (Real Estate, Consumer Discretionary, Financials, Materials, and Metals and Mining). A range of non‐linear tests are applied in order to systematically investigate the structure of the market in each sector. The results highlight the cointegrated nature of non‐linearity across related sectors, and also demonstrate that different industries within the same economy can reveal highly diverse patterns of non‐linearity and market efficiency in response to financial crisis.     

中国股市的世界一体化与区域一体化：行业视角

本文从行业视角出发，研究了我国A股市场的世界一体化与区域一体化的动态进程。研究发现：特定行业因素对工业、原材料和金融行业的冲击超过了外界因素对A股市场整体的影响；与世界因素相比，亚洲区域因素对A股指数及大多数行业的影响占据主导地位；在次贷危机期间，亚洲区域因素对A股市场中金融行业的影响最大，金融行业成为亚洲区域风险向国内市场传递的主要载体。     

Analysing dynamic linkages and hedging strategies between Islamic and conventional sector equity indexes

This study analyses the dynamic spillovers across 10 Dow Jones Islamic and conventional sector index pairs. Using various multivariate GARCH models, the results show significant time-varying conditional correlations for all the pairs. Moreover, there is evidence that the conditional correlations for all the sector pairs, except those of the Telecommunication and Utilities sectors, increase after the onset of the global financial crisis (GFC), suggesting non-subsiding risks, contagion effects and gradual greater financial linkages. The Islamic sectors’ risk exposure can be effectively hedged over time in diversified portfolios containing conventional sector stocks. These results provide several practical implications for portfolio managers and policymakers in regard to optimal asset allocations, portfolio risk management and the diversification benefits among these markets.     

Contagion of the Global Financial Crisis and the real economy: A regional analysis

This paper investigates the contagion effects of the Global Financial Crisis (2007–2009) by examining ten sectors in six developed and emerging regions during different phases of the crisis. The analysis tests different channels of financial contagion across regions and real economy sectors by utilizing dynamic conditional correlation from the multivariate Fractionally Integrated Asymmetric Power ARCH (FIAPARCH) model. Evidence shows that the GFC can be characterized by contagion effects across regional stock markets and regional financial and non-financial sectors.However, Developed Pacific region and some sectors in particular Consumer Goods, Healthcare and Technology across all regions seem to be less affected by the crisis, while the most vulnerable sectors are observed in the emerging Asian and European regions. Further, the analysis on a crisis phase level indicates that the most severe contagion effects exist after the failure of Lehman Brothers limiting the effectiveness of portfolio diversification.     

Volatility spillover and multivariate volatility impulse response analysis of GFC news events

This article applies two measures to assess spillovers across markets: the Diebold and Yilmaz’s (2012) spillover index and the Hafner and Herwartz’s (2006) analysis of multivariate GARCH models using volatility impulse response analysis. We use two sets of data, daily realized volatility (RV) estimates taken from the Oxford-Man RV library, for the S&P500 and the FTSE, plus 10 years of daily returns series for the New York Stock Exchange Index and the FTSE 100 index. Both data sets capture both the global Financial Crisis (GFC) and the subsequent European Sovereign Debt Crisis (ESDC). The spillover index captures the transmission of volatility to and from markets, plus net spillovers. The Volatility Impulse Responses (VIRF) have to be calibrated to conditional volatility estimated at a particular point in time. We explore the impact of three different shocks, the onset of the GFC, the height of the GFC, and the impact of the ESDC. Our modelling includes leverage and asymmetric effects applying a multivariate GARCH model, and further analysis using both BEKK and diagonal BEKK (DBEKK) models. We find the impact of negative shocks is larger, but shorter in duration, in this case a difference between 3 and 6 months.     

Optimal trading strategies for Lévy-driven Ornstein–Uhlenbeck processes

This study derives an optimal pairs trading strategy based on a Lévy-driven Ornstein–Uhlenbeck process and applies it to high-frequency data of the S&P 500 constituents from 1998 to 2015. Our model provides optimal entry and exit signals by maximizing the expected return expressed in terms of the first-passage time of the spread process. An explicit representation of the strategy’s objective function allows for direct optimization without Monte Carlo methods. Categorizing the data sample into 10 economic sectors, we depict both the performance of each sector and the efficiency of the strategy in general. Results from empirical back-testing show strong support for the profitability of the model with returns after transaction costs ranging from 31.90% p.a. for the sector ‘Consumer Staples’ to 278.61% p.a. for the sector ‘Financials’. We find that the remarkable returns across all economic sectors are strongly driven by model parameters and sector size. Jump intensity decreases over time with strong outliers in times of high market turmoil. The value-add of our Lévy-based model is demonstrated by benchmarking it with quantitative strategies based on Brownian motion-driven processes.     

Information Transmission between Mature and Emerging Equity Markets During Normal and Crisis Periods: An Empirical Examination

In this paper, we examine the price discovery and volatility spillovers between eight mature market economies (MMEs) and eight emerging market economies (EMEs) from January 2003 to July 2014, covering three sub-periods—prior to the 2007–09 global financial crisis (GFC), during the crisis, and post-crisis. The results of price discovery indicate that MMEs lead EMEs in the pre-crisis and post-crisis periods. All MMEs are cointegrated with China in the pre-crisis period but not in the post-crisis period. Dynamic cointegration results reconfirm our findings from Johansen’s co-integration test. The asymmetric dynamic conditional correlation (ADCC-GARCH) coefficients suggest a regional pattern among MMEs and EMEs, except in the case of European MMEs with South Africa. Employing BEKK-GARCH model, we find that volatility spillovers of MMEs with China and of Italy with EMEs weakened in the post-crisis period as compared to the pre-crisis period implying that the GFC damaged the information transmission process, particularly for China and Italy. While China is a large economy with strong trade linkages with the rest of the world, Italy is one of the larger European economies which was in relatively greater distress during the EDC. The findings have implications for policy makers and investors.

     

Semi‐Parametric Examination of Industry Risk: The Australian Evidence

This paper examines the time variation form of the systematic risk measurement, beta, in Australian industry sectors. By using a semi‐parametric approach, the systematic risk measurement, beta, is defined as a combination of one stable parametric component and one varying non‐parametric component. Two categories of industries were identified. The Energy, Material, Mining, Industrial and Property Trust industries had a generally increasing beta for most of the sample period, while the Consumer Discretionary, Financials Excluding Property Trust, IT and Telecommunications had a decreasing beta for the same period. The betas of the Health and Utility industries are more stable than others. The variation of industry risk is linked with the market conditions, as well as the change of interest rates.     

Spillover across Eurozone credit market sectors and determinants

We examine spillover and its determinants among Eurozone sector level credit markets using time and frequency domain spillover approaches. Based on network theory and connectedness analysis, we identify the sectors that are major transmitters and receivers of spillover during normal and crisis periods. The rolling window analysis shows that short-run spillover among credit market sectors intensifies during global and Eurozone crisis periods. Further, using Bayesian model averaging, we find that overall financial conditions and stock market volatility are the main drivers of total and sector-level spillover. Our findings have important implications for policymakers and investors interested in Euro-area credit risk at the sector level.     

Volatility spillovers across daytime and overnight information between China and world equity markets

This article explores the transmission of daytime and overnight information in terms of returns and volatility between Chinese and Asian, European and North American main stock markets. We propose a bivariate analysis with China as benchmark. By testing the constancy of the conditional correlations, we use an extended constant or dynamic conditional correlation GARCH model. The empirical findings show that across the daytime information transmissions, the relationships between China and Asian markets are closer than China and non-Asian markets, whereas through the overnight information transmissions these relationships are inverse. The analysis provides, before the crisis, that the overnight volatility spillover effects are from China to the United States and the United Kingdom. During the crisis, China affects the United Kingdom in terms of daytime volatility spillovers, whereas in terms of overnight volatility spillovers China affects the United States and is influenced by Japan. After the crisis, daytime volatility spillovers are from Taiwan to China, whereas the overnight volatility spillover effects are from China to the United States and the United Kingdom.     

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.     

Volatility spillovers to the emerging financial markets during taper talk and actual tapering

On 22 May 2013, Fed chairman, Ben Bernanke surprised markets by indicating to the media that the US Fed may taper its quantitative easing programme. This set out financial volatility across the globe over the next several months that spilled over to the financial markets of emerging market economies (EMEs). It prompted many EME central banks to take varied policy actions. Looking into this widely known event, this article presents formal empirical evidence establishing that (i) conditional volatility during taper talk exceeded that during actual tapering and (ii) volatility spillovers took place ‘contemporaneously’ from the US markets to the key EMEs during this period. The results suggest importance of careful communications by advanced economy central banks and the possibility of establishing ‘rules of the monetary game’. They also suggest that in the absence of international policy coordination to contain spillovers, EME central banks should build adequate buffers and reinforce financial stability ahead of the reversal of the global interest rate cycle.     

Strength of co-movement between sector CDS indexes and relationship with major economic and financial variables over time and during investment horizons

The main purpose of this article is to analyse the co-movement in both time and frequency between financial sector CDS indexes and between these indexes and their main economic and financial control variables for the period 2004–2014. Empirically, we implement the wavelet-squared coherence methodology to analyse the co-movement through time, frequency and power. Our results unveil that the co-movement between the three financial sectors’ CDSs changes through time and investment horizons, stressing the importance of hedging portfolios in real time. Also, we uncover that the changes in co-movement to relatively higher frequencies coincide with the inception of the recent global financial crisis. This result is collaborated with the co-movement between each CDS index and other global risk factors, including crude oil prices, interest rates and equity market volatility. Finally, we compare the wavelet coherence results with those of the DCC-FIAPARCH model and find that the two different approaches provide quite similar conditional correlations over time. Our results are important for investors, debtors, creditors and other decision-makers which are interested in CDS spread co-movements at different frequencies or investment horizons. It would be useful for all market participants to resort to an appropriate frequency domain to have better understanding of the sector CDS interrelationship behaviour in this domain.     

Volatility spillovers between the oil market and the European Union carbon emission market

This paper examines the dynamics of volatility transmission between EU emission allowances (EUA) and oil markets using a range-based volatility measure. We propose a multivariate conditional autoregressive range model with bivariate lognormal distribution to capture volatility dynamics and volatility spillovers between oil and EUA markets. Our findings for Phase II of the European Union Emissions Trading Scheme point to the existence of volatility dynamics and leverage effects and to no significant volatility spillovers between these markets. These results remained robust to other volatility measures and model specifications.     

Dynamic frequency connectedness between oil and natural gas volatilities

The goal of this paper is twofold. First, we study dynamic volatility connectedness between oil and natural gas over the period 1994 to 2018. Second, we examine the frequency dynamics of the transmission mechanism arising from frequency-specific responses to volatility shocks. To do so, we adopt a newly introduced approach that decomposes connectedness measures based on variance decompositions into their components at different frequency ranges. Our results summarize as follows: (a) there is a substantial variation in volatility spillovers over time; (b) the natural gas market was a net transmitter during the central part of our sample period; (c) the magnitude of spillovers was smaller after the financial crisis, but volatilities are not decoupled. (d) The volatility propagation mechanism is frequency dependent. Connectedness is typically created at low-frequencies, with volatility shocks across markets having long-lasting effects. However, during some specific periods, such as after Katrina, volatility was transmitted much faster, with shocks dissipating in the short-run.     

Volatility spillovers of unconventional monetary policy to emerging market economies

Emerging market economies (EMEs) have experienced waves of market volatility since the global financial crisis, with some commentators ascribing this at least partly related to monetary policy decisions in advanced economies. This paper examines volatility spillovers from changes in the size of the balance sheets of the Federal Reserve (FED) and European Central Bank (ECB) to EMEs from 2003 to 2018. We find that volatility spillovers to EME currency markets are greater in magnitude from the FED, while EME stock and bond markets are also vulnerable to volatility spillovers in a similar magnitude from both the ECB and the FED. We find only limited evidence of volatility transmission to the real economy of EMEs following the monetary policy actions of the FED and ECB. Finally, we show that the proportion of the volatility in EMEs that is accounted for by changes in FED and ECB balance sheets shifts over time. Our paper has important policy implications for EMEs, notably in respect of volatility transmission channels.     

Spillover effects of FDI inflows on output growth: An analysis of aggregate and disaggregated FDI inflows of 13 MENA economies

This paper examines the effect of foreign direct investment (FDI) inflows on overall growth, as well as its sector-specific spillovers in the Middle Eastern and North African region during the period from 2000 to 2020. Our major innovation is our ability to disaggregate FDI into primary, secondary and tertiary and examine their individual impact on growth, as well as their sector-specific spillovers by using dynamic panel GMM methodology. We find prima facie evidence that total FDI significantly stimulates growth. However, when we turn to the disaggregated FDI data, primary sector FDI adversely affects the gross domestic product (GDP) growth in the service sector and overall GDP growth. On the other hand, secondary FDI has a ‘double-edged’ effect, benefiting its own sector (the service sector's GDP growth), but not other sectors. In contrast, service sector FDI stimulates GDP growth in mining, manufacturing and service sectors, thereby enhancing overall economic growth. Our findings have important policy implications regarding the incentives provided by governments to encourage FDI, which need to be fine-tuned to attract certain types of FDI (tertiary), with less focus on the primary sector     

Oil Price Shocks and Volatility in Australian Stock Returns

This paper examines the effect of oil shocks on return and volatility in the sectors of Australian stock market and finds significant effects for most sectors. For the overall market index, an increase in oil price return significantly reduces return, and an increase in oil price return volatility significantly reduces volatility. An advantage of looking at sector returns rather than a general index of stock returns is that sectors may well differ markedly in how they respond to oil price shocks. The energy and material sectors (as expected) and the financial sector (surprisingly) are out of step (in different ways) with results for the other sectors and for the overall index. A rise in oil price increases returns in the energy and material sectors and an increase in oil price return volatility increases stock return volatility in the financial sector. Explanation for the negative (positive) association between oil return (oil return volatility) and returns (volatility of returns) in the financial sector must be based on the association via lending to and/or holdings of corporate bonds issued by firms with significant exposure to oil price fluctuations and their speculative positions in oil‐related instruments.     

Volatility Spillovers and Contagion from Mature to Emerging Stock Markets

This paper models volatility spillovers from mature to emerging stock markets, tests for changes in the transmission mechanism during turbulences in mature markets, and examines the implications for conditional correlations between mature and emerging market returns. Tri‐variate GARCH–BEKK models of returns in mature, regional emerging, and local emerging markets are estimated for 41 emerging market economies (EMEs). Wald tests suggest that mature market volatility affects conditional variances in many emerging markets. Moreover, spillover parameters change during turbulent episodes. In the majority of the sample EMEs, conditional correlations between local and mature markets increase during these episodes. While conditional variances in local markets rise as well, volatility in mature markets rises more, and this shift is the main factor behind the increase in conditional correlations. With few exceptions, conditional beta coefficients between mature and emerging markets tend to be unchanged or lower during turbulences.     

Fear connectedness among asset classes

This study investigates the interconnection between five implied volatility indices representative of different financial markets during the period 1 August 2008–29 December 2017. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yilmaz. Second, we make use of a dynamic analysis to evaluate both the net directional connectedness for each market and all net pairwise directional connectedness. Our results suggest that a 38.99%, of the total variance of the forecast errors is explained by shocks across markets, indicating that the remainder 61.01% of the variation is due to idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability. Finally, we also document frequently switch between a net volatility transmitter and a net volatility receiver role in the five markets under study.