Financialization, crisis and commodity correlation dynamics

Stronger investor interest in commodities may create closer integration with conventional asset markets. We estimate sudden and gradual changes in correlation between stocks, bonds and commodity futures returns driven by observable financial variables and time, using double smooth transition conditional correlation (DSTCC–GARCH) models. Most correlations begin the 1990s near zero but closer integration emerges around the early 2000s and reaches peaks during the recent crisis. Diversification benefits to investors across equity, bond and stock markets were significantly reduced. Increases in VIX and financial traders’ short open interest raise futures returns volatility for many commodities. Higher VIX also increases commodity returns correlation with equity returns for about half the pairs, indicating closer integration.

International stock market linkages : are overnight returns on the U.S. Market informative?

Based on the theory of international stock market co-movements, this study shows that a profitable trading strategy can be developed. The U.S. market return is considered as overnight information by ordinary investors in the Asian and the European stock markets, and opening prices in local markets reflect the U.S. overnight return. However, smart traders would either judge the impact of overnight information more correctly, or predict unreleased information. Thus, the difference between expected opening prices based on the U.S. return and actual opening prices is counted as smart traders’ prediction power, which is either a buy or a sell signal. Using index futures price data from 12 countries from 2000 to 2011, cumulative returns on the trading strategy are calculated with taking into account transaction costs. The empirical results show that the proposed trading strategy generates higher riskadjusted returns than that of the benchmarks in 12 sample countries. The trading performances for the Asian markets surpass those for the European markets because the U.S. return is the only overnight information for the Asian markets whereas the Asian markets returns are additional information to the European investors.

Decoupling 2 : technologies, opportunities and policy options

This report was produced by the Decoupling Working Group of the International Resource Panel. It explores technological possibilities and opportunities for both developing and developed countries to accelerate decoupling and reap the environmental and economic benefits of increased resource productivity. It also examines several policy options that have proved to be successful in helping different countries to improve resource productivity in various sectors of their economy, avoiding negative impacts on the environment. It does not seem possible for a global economy based on the current unsustainable patterns of resource use to continue into the future. The economic consequences of these patterns are already apparent in three areas: increases in resource prices, increased price volatility and disruption of environmental systems. The environment impacts of resource use are also leading to potentially irreversible changes to the world’s ecosystems, often with direct effects on people and the economy – for example through damage to health, water shortages, loss of fish stocks or increased storm damage. But there are alternatives to these scary patterns. Many decoupling technologies and techniques that deliver resource productivity increases as high as 5 to 10-fold are already available, allowing countries to pursue their development strategies while significantly reducing their resource footprint and negative impacts on the environment. This report shows that much of the policy design “know-how” needed to achieve decoupling is present in terms of legislation, incentive systems, and institutional reform. Many countries have tried these out with tangible results, encouraging others to study and where appropriate replicate and scale up such practices and successes.

Long Term Dynamics in CO2 Allowance Prices and Carbon Capture Investments

In this paper we analyse the behaviour of the EU market for CO2 emission allowances; specifically, we focus on the contracts maturing in the Kyoto Protocol's second period of application (2008 to 2012). We calibrate the underlying parameters for the allowance price in the long run and we also calibrate those from the Spanish wholesale electricity market. This information is then used to assess the option to install a carbon capture and storage (CCS) unit in a coal-fired power plant. We use a two-dimensional binomial lattice where costs and profits are valued and the optimal investment time is determined. In other words, we study the trigger allowance prices above which it is optimal to install the capture unit immediately. We further analyse the impact of several variables on the critical prices, among them allowance price volatility and a hypothetical government subsidy. We conclude that, at current permit prices, from a financial point of view, immediate installation does not seem justified. This need not be the case, though, if carbon market parameters change dramatically and/or a specific policy to promote these units is adopted.

Essays in Behavioral Decision Theory

This thesis studies decision making under uncertainty and how economic agents respond to information. The classic model of subjective expected utility and Bayesian updating is often at odds with empirical and experimental results; people exhibit systematic biases in information processing and often exhibit aversion to ambiguity. The aim of this work is to develop simple models that capture observed biases and study their economic implications.

In the first chapter I present an axiomatic model of cognitive dissonance, in which an agent's response to information explicitly depends upon past actions. I introduce novel behavioral axioms and derive a representation in which beliefs are directionally updated. The agent twists the information and overweights states in which his past actions provide a higher payoff. I then characterize two special cases of the representation. In the first case, the agent distorts the likelihood ratio of two states by a function of the utility values of the previous action in those states. In the second case, the agent's posterior beliefs are a convex combination of the Bayesian belief and the one which maximizes the conditional value of the previous action. Within the second case a unique parameter captures the agent's sensitivity to dissonance, and I characterize a way to compare sensitivity to dissonance between individuals. Lastly, I develop several simple applications and show that cognitive dissonance contributes to the equity premium and price volatility, asymmetric reaction to news, and belief polarization.

The second chapter characterizes a decision maker with sticky beliefs. That is, a decision maker who does not update enough in response to information, where enough means as a Bayesian decision maker would. This chapter provides axiomatic foundations for sticky beliefs by weakening the standard axioms of dynamic consistency and consequentialism. I derive a representation in which updated beliefs are a convex combination of the prior and the Bayesian posterior. A unique parameter captures the weight on the prior and is interpreted as the agent's measure of belief stickiness or conservatism bias. This parameter is endogenously identified from preferences and is easily elicited from experimental data.

The third chapter deals with updating in the face of ambiguity, using the framework of Gilboa and Schmeidler. There is no consensus on the correct way way to update a set of priors. Current methods either do not allow a decision maker to make an inference about her priors or require an extreme level of inference. In this chapter I propose and axiomatize a general model of updating a set of priors. A decision maker who updates her beliefs in accordance with the model can be thought of as one that chooses a threshold that is used to determine whether a prior is plausible, given some observation. She retains the plausible priors and applies Bayes' rule. This model includes generalized Bayesian updating and maximum likelihood updating as special cases.

Prices versus quantities versus bankable quantities

Quantity-based regulation with banking allows regulated firms to shift obligations across time in response to periods of unexpectedly high or low marginal costs. Despite its wide prevalence in existing and proposed emission trading programs, banking has received limited attention in past welfare analyses of policy choice under uncertainty. We address this gap with a model of banking behavior that captures two key constraints: uncertainty about the future from the firm's perspective and a limit on negative bank values (e.g. borrowing). We show conditions where banking provisions reduce price volatility and lower expected costs compared to quantity policies without banking. For plausible parameter values related to U.S. climate change policy, we find that bankable quantities produce behavior quite similar to price policies for about two decades and, during this period, improve welfare by about a $1 billion per year over fixed quantities. © 2012 Elsevier B.V.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

Analysis of Electricity Market Prices Using Multidimensional Scaling

This paper studies the impact of the energy upon electricity markets using Multidimensional Scaling (MDS). Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, the results help electricity markets agents hedging against Market Clearing Price (MCP) volatility.

Tracking error of exchange-traded funds: Evidence from the UK

This paper is mainly concerned with the tracking accuracy of Exchange Traded Funds (ETFs) listed on the London Stock Exchange (LSE) but also evaluates their performance and pricing efficiency. The findings show that ETFs offer virtually the same return but exhibit higher volatility than their benchmark. It seems that the pricing efficiency, which should come from the creation and redemption process, does not fully hold as equity ETFs show consistent price premiums. The tracking error of the funds is generally small and is decreasing over time. The risk of the ETF, daily price volatility and the total expense ratio explain a large part of the tracking error. Trading volume, fund size, bid-ask spread and average price premium or discount did not have an impact on the tracking error. Finally, it is concluded that market volatility and the tracking error are positively correlated.

Closed form approximations for spread options

This article expresses the price of a spread option as the sum of the prices of two compound options. One compound option is to exchange vanilla call options on the two underlying assets and the other is to exchange the corresponding put options. This way we derive a new closed form approximation for the price of a European spread option and a corresponding approximation for each of its price, volatility and correlation hedge ratios. Our approach has many advantages over existing analytical approximations, which have limited validity and an indeterminacy that renders them of little practical use. The compound exchange option approximation for European spread options is then extended to American spread options on assets that pay dividends or incur costs. Simulations quantify the accuracy of our approach; we also present an empirical application to the American crack spread options that are traded on NYMEX. For illustration, we compare our results with those obtained using the approximation attributed to Kirk (1996, Correlation in energy markets. In: V. Kaminski (Ed.), Managing Energy Price Risk, pp. 71–78 (London: Risk Publications)), which is commonly used by traders.

The effect of asymmetries on optimal hedge ratios

There is widespread evidence that the volatility of stock returns displays an asymmetric response to good and bad news. This article considers the impact of asymmetry on time-varying hedges for financial futures. An asymmetric model that allows forecasts of cash and futures return volatility to respond differently to positive and negative return innovations gives superior in-sample hedging performance. However, the simpler symmetric model is not inferior in a hold-out sample. A method for evaluating the models in a modern risk-management framework is presented, highlighting the importance of allowing optimal hedge ratios to be both time-varying and asymmetric.

A-REIT rights issues

Purpose – This is the first REIT paper to seek to empirically examine potential influencing factors on the discounts and underwriting fees of Australian REIT rights issues.

Design/methodology/approach – Using a methodology similar to Owen and Suchard, and Armitage, a sample of 62 A-REIT rights issues during 2001-2009 is analyzed. A variety of potential factors influencing discounts and underwriting fees are explored.

Findings – Over A$20 billion was raised by A-REIT rights issues during 2001-2009 (this around three times that raised through A-REIT initial public offerings during the same period). The mean offer price was discounted around 9.5 percent from the current market price and underwriting fees averaged 2.9 percent of gross proceeds raised – both substantially less than for industrial rights issues. The standard deviation of daily returns for the past year appears to influence the percentage discount offered to subscribers. This volatility was particularly noticeable in 2008 and 2009, during the global financial crisis, where new issues were discounted substantially so as to raise equity to repay debt. This historical risk variable appears paramount in determining the discounts to subscribers and fees to underwriters.

Practical implications – A-REITs seeking to minimize the discounts offered to subscribers and to minimize their underwriting costs with rights issue equity capital raisings must first minimize their share price volatility.

Originality/value – This paper adds to the international costs of capital raising literature of REITs by examining such costs with A-REIT rights issues and is the first paper to examine factors influencing these costs.

New empirical evidence on the bid-ask spread

In this article, we model the determinants of spread for 734 firms listed on the NYSE over the period 1 January 1998 to 31 December 2008. We propose a panel data model of the determinants of spread. There are four main messages emerging from our work. We find a statistically significant effect of volume on spread inconsistent with the work of Johnson (2008). On price, we find mixed results, consistent with the literature. On the effect of price volatility on spread, our results are completely the opposite of the cross-sectional literature but sides with the relatively recent work of Chordia et al. (2001). We allow for persistence of spread as a determinant of spread and find significant evidence of spread persistence across all 16 sectors. Finally, we examine size effects and find statistically strong evidence of size effects based on the relationship between price and spread, persistence and spread, and volatility and spread.

Call auction transparency and market liquidity: Evidence from China

This paper uses the natural experiment offered by the Shanghai Stock Exchange to investigate the impact of opening call auction transparency on market liquidity. We find that the dissemination of indicative trade information during the pre-open call auction session leads to an overall improvement in stock liquidity in the continuous trading session. Bid-ask spreads narrow in the first trading hour because adverse selection risk fell significantly and there is less price volatility in the continuous market. This effect is greater for actively traded securities than illiquid securities. Our findings are robust for different lengths of sample period, different lengths of trading hours after market open, and stocks that had (and had not) reformed the share split structure during our research period.