Predicting stock market returns and volatility with investor sentiment : evidence from eight developed countries

We test the predictive ability of investor sentiment on the return and volatility at the aggregate market level in the U.S., four largest European countries and three Asia-Pacific countries. We find that in the U.S., France and Italy periods of high consumer confidence levels are followed by low market returns. In Japan both the level and the change in consumer confidence boost the market return in the next month. Further, shifts in sentiment significantly move conditional volatility in most of the countries, and in Italy such impacts lead to an increase in returns by 4.7% in the next month.

Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold

This paper employs a VAR-GARCH model to investigate the return links and volatility transmission between the S&P 500 and commodity price indices for energy, food, gold and beverages over the turbulent period from 2000 to 2011. Understanding the price behavior of commodity prices and the volatility transmission mechanism between these markets and the stock exchanges are crucial for each participant, including governments, traders, portfolio managers, consumers, and producers. For return and volatility spillover, the results show significant transmission among the S&P 500 and commodity markets. The past shocks and volatility of the S&P 500 strongly influenced the oil and gold markets. This study finds that the highest conditional correlations are between the S&P 500 and gold index and the S&P 500 and WTI index. We also analyze the optimal weights and hedge ratios for commodities/S&P 500 portfolio holdings using the estimates for each index. Overall, our findings illustrate several important implications for portfolio hedgers for making optimal portfolio allocations, engaging in risk management and forecasting future volatility in equity and commodity markets. © 2013 Elsevier B.V.

The impacts of exchange rate volatility on vegetable trade flows

Trade flows of commodities are generally affected by the principles of comparative advantage in a free trade. However, trade flows might be enhanced or distorted not only by various government interventions, but also by exchange rate fluctuations among others. This study applies a commodity-specific gravity model to selected vegetable trade flows among Organization for Economic Co-operation and Development (OECD) countries to determine the effects of exchange rate uncertainty on the trade flows. Using the data from 1996 to 2002, the results show that, while the exchange rate uncertainty significantly reduces trade in the majority of commodity flows, there is evidence that both short- and long-term volatility have positive effect on trade flows of specific commodities. This study also tests the regional preferential trade agreements such as the North American Free Trade Agreement (NAFTA), the Asia-Pacific Economic Cooperation (APEC) and the EU, and their different effects on commodities.

Corporate credit risk prediction under stochastic volatility and jumps

This paper examines the impact of allowing for stochastic volatility and jumps (SVJ) in a structural model on corporate credit risk prediction. The results from a simulation study verify the better performance of the SVJ model compared with the commonly used Merton model, and three sources are provided to explain the superiority. The empirical analysis on two real samples further ascertains the importance of recognizing the stochastic volatility and jumps by showing that the SVJ model decreases bias in spread prediction from the Merton model, and better explains the time variation in actual CDS spreads. The improvements are found particularly apparent in small firms or when the market is turbulent such as the recent financial crisis.

Food price volatility and hunger alleviation-can Cannes work

Recent years have seen global food prices rise and become more volatile. Price surges in 2008 and 2011 held devastating consequences for hundreds of millions of people and negatively impacted many more. Today one billion people are hungry. The issue is a high priority for many international agencies and national governments. At the Cannes Summit in November 2011, the G20 leaders agreed to implement five objectives aiming to mitigate food price volatility and protect vulnerable persons. To succeed, the global community must now translate these high level policy objectives into practical actions. In this paper, we describe challenges and unresolved dilemmas before the global community in implementing these five objectives. The paper describes recent food price volatility trends and an evaluation of possible causes. Special attention is given to climate change and water scarcity, which have the potential to impact food prices to a much greater extent in coming decades. We conclude the world needs an improved knowledge base and new analytical capabilities, developed in parallel with the implementation of practical policy actions, to manage food price volatility and reduce hunger and malnutrition. This requires major innovations and paradigm shifts by the global community.

Comparison of intraspecific genetic structure among related chironomids (Diptera) from New Zealand and Patagonia : disparity between potential and realized dispersal

Population genetic studies of freshwater invertebrate taxa in New Zealand and South America are currently few despite the geologically and climatically dynamic histories of these regions. The focus of our study was a comparison of the influence on realized dispersal of 2 closely related nonbiting midges (Chironomidae) of population fragmentation on these separated austral land masses. We used a 734-base pair (bp) fragment of cytochrome c oxidase subunit I (COI) to investigate intraspecific genetic structure in Naonella forsythi Boothroyd in New Zealand and Ferringtonia patagonica Edwards in Patagonia. We proposed hypotheses about their potential dispersal and, hence, expected patterns of genetic structure in these 2 species based on published patterns for the closely related Australian taxon Echinocladius martini Cranston. Genetic structure revealed for both N. forsythi and F. patagonica was characterized by several highly divergent (2.0–10.5%) lineages of late Miocene–Pliocene age within each taxon that were not geographically localized. Many were distributed widely. This pattern differed greatly from population structure in E. martini, which was typified by much greater endemicity of divergent genetic lineages. Nevertheless, diversification of lineages in all 3 taxa appeared to be temporally congruent with the onset of late Miocene glaciations in the southern hemisphere that may have driven fragmentation of suitable habitat, promoting isolation of populations and divergence in allopatry. We argue that differences in realized dispersal post-isolation may be the result of differing availability of suitable habitat in interglacial periods.

Sources and composition of sub-200 nm sea spray aerosol inferred from volatility and hygroscopicity

Enrichment of marine organics in remote marine aerosols can influence their ability to act as cloud condensation nuclei (CCN), which are sites for water vapour to condense into cloud droplets. This project identified the composition and hygroscopicity of sea spray aerosol (SSA) formed at the ocean surface due to bursting of entrained air bubbles. SSA from organically enriched waters in the southwest Pacific and Southern Oceans were investigated. Results indicate that current emission schemes may not adequately predict SSA CCN, influencing the representation of cloud formation in climate modelling.

Modelling CO2 adsorption and separation on experimentally-realized B40 fullerene

Searching for efficient solid sorbents for CO2 adsorption and separation is important for developing emergent carbon reduction and natural gas purification technology. This work, for the first time, has investigated the adsorption of CO2 on newly experimentally realized cage-like B40 fullerene (Zhai et al., 2014) based on density functional theory calculations. We find that the adsorption of CO2 on B40 fullerene involves a relatively large energy barrier (1.21 eV), however this can be greatly decreased to 0.35 eV by introducing an extra electron. A practical way to realize negatively charged B40 fullerene is then proposed by encapsulating a Li atom into the B40 fullerene (Li@B40). Li@B40 is found to be highly stable and can significantly enhance both the thermodynamics and kinetics of CO2 adsorption, while the adsorptions of N2, CH4 and H2 on the Li@B40 fullerene remain weak in comparison. Since B40 fullerene has been successfully synthesized in a most recent experiment, our results highlight a new promising material for CO2 capture and separation for future experimental validation.

Effect of atmospheric aging on volatility and reactive oxygen species of biodiesel exhaust nano-particles

In the prospect of limited energy resources and climate change, effects of alternative biofuels on primary emissions are being extensively studied. Our two recent studies have shown that biodiesel fuel composition has a significant impact on primary particulate matter emissions. It was also shown that particulate matter caused by biodiesels was substantially different from the emissions due to petroleum diesel. Emissions appeared to have higher oxidative potential with the increase in oxygen content and decrease of carbon chain length and unsaturation levels of fuel molecules. Overall, both studies concluded that chemical composition of biodiesel is more important than its physical properties in controlling exhaust particle emissions. This suggests that the atmospheric aging processes, including secondary organic aerosol formation, of emissions from different fuels will be different as well. In this study, measurements were conducted on a modern common-rail diesel engine. To get more information on realistic properties of tested biodiesel particulate matter once they are released into the atmosphere, particulate matter was exposed to atmospheric oxidants, ozone and ultra-violet light; and the change in their properties was monitored for different biodiesel blends. Upon the exposure to oxidative agents, the chemical composition of the exhaust changes. It triggers the cascade of photochemical reactions resulting in the partitioning of semi-volatile compounds between the gas and particulate phase. In most of the cases, aging lead to the increase in volatility and oxidative potential, and the increment of change was mainly dependent on the chemical composition of fuels as the leading cause for the amount and the type of semi-volatile compounds present in the exhaust.

Volatility transmission in global financial markets

As financial markets have become increasingly integrated internationally, the topic of volatility transmission across these markets has become more important. This thesis investigates how the volatility patterns of the world's main financial centres differ across foreign exchange, equity, and bond markets.

Giving in Australia: Philanthropic Potential Beginning To Be Realized

Australia in a sense has two histories: that of its indigenous Aboriginal and Torres Strait Islander people based on a traditional culture of mutual dependence and reciprocal altruism (Turner, 1981) and the other from its eighteenth century colonization as a British penal outpost. These colonial overtones have proved an abiding cultural force. A dominant government presence, British legal platform, and ongoing sense that ‘the government will provide’ remain today (Liffman, 2008; McDonald & Scaife, 2011).

Volatility transmission in global financial markets

This paper considers the transmission of volatility in global foreign exchange, equity and bond markets. Using a multivariate GARCH framework which includes measures of realised volatility as explanatory variables, significant volatility and news spillovers are found to occur on the same trading day between Japan, Europe, and the United States. All markets exhibit significant degrees of asymmetry in terms of the transmission of volatility associated with good and bad news. There are also strong links between diffusive volatilities in all three markets, whereas jumpactivity is only importantwithin the equitymarkets. The results of this paper deepen our understanding of how news and volatility are propagated through global financial markets.

Estimating the parameters of stochastic volatility models using option price data

This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.

A heterogeneous computing approach to simulation of the Heston Stochastic Volatility Model

Stochastic volatility models are of fundamental importance to the pricing of derivatives. One of the most commonly used models of stochastic volatility is the Heston Model in which the price and volatility of an asset evolve as a pair of coupled stochastic differential equations. The computation of asset prices and volatilities involves the simulation of many sample trajectories with conditioning. The problem is treated using the method of particle filtering. While the simulation of a shower of particles is computationally expensive, each particle behaves independently making such simulations ideal for massively parallel heterogeneous computing platforms. In this paper, we present our portable Opencl implementation of the Heston model and discuss its performance and efficiency characteristics on a range of architectures including Intel cpus, Nvidia gpus, and Intel Many-Integrated-Core (mic) accelerators.

Elements of Volatility at High Frequency

Volatility is central in options pricing and risk management. It reflects the uncertainty of investors and the inherent instability of the economy. Time series methods are among the most widely applied scientific methods to analyze and predict volatility. Very frequently sampled data contain much valuable information about the different elements of volatility and may ultimately reveal the reasons for time varying volatility. The use of such ultra-high-frequency data is common to all three essays of the dissertation. The dissertation belongs to the field of financial econometrics. The first essay uses wavelet methods to study the time-varying behavior of scaling laws and long-memory in the five-minute volatility series of Nokia on the Helsinki Stock Exchange around the burst of the IT-bubble. The essay is motivated by earlier findings which suggest that different scaling laws may apply to intraday time-scales and to larger time-scales, implying that the so-called annualized volatility depends on the data sampling frequency. The empirical results confirm the appearance of time varying long-memory and different scaling laws that, for a significant part, can be attributed to investor irrationality and to an intraday volatility periodicity called the New York effect. The findings have potentially important consequences for options pricing and risk management that commonly assume constant memory and scaling. The second essay investigates modelling the duration between trades in stock markets. Durations convoy information about investor intentions and provide an alternative view at volatility. Generalizations of standard autoregressive conditional duration (ACD) models are developed to meet needs observed in previous applications of the standard models. According to the empirical results based on data of actively traded stocks on the New York Stock Exchange and the Helsinki Stock Exchange the proposed generalization clearly outperforms the standard models and also performs well in comparison to another recently proposed alternative to the standard models. The distribution used to derive the generalization may also prove valuable in other areas of risk management. The third essay studies empirically the effect of decimalization on volatility and market microstructure noise. Decimalization refers to the change from fractional pricing to decimal pricing and it was carried out on the New York Stock Exchange in January, 2001. The methods used here are more accurate than in the earlier studies and put more weight on market microstructure. The main result is that decimalization decreased observed volatility by reducing noise variance especially for the highly active stocks. The results help risk management and market mechanism designing.