The structure and resilience of financial market networks

Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience. (C) 2012 American Institute of Physics. [doi:10.1063/1.3683467]

Food-Retail Development and the Myth of Everyday Low Prices: The Case of Brazil

This article analyses the changes in Brazilian food retailing by investigating the co-existence of, and the pricing variation across, large supermarket chains and small independent supermarkets. It uses cointegration tests to show that, despite the widespread belief that small supermarkets are inefficient and charge higher prices, they in fact charge lower prices. Accordingly, in contrast to the prevailing literature on food-retail development, competition in food retail is complex and cannot be described as a simple Darwinian process of market concentration. The article explores the survival of small retail and its consequences for the current discussion on modern food retail in developing countries.

Agricultural commodities pricing model applied to the Brazilian sugar market

This article suggests a pricing model for commodities used to produce biofuel. The model is based on the concept that the deterministic component of the Wiener process is not constant and depends on time and exogenous variables. The model, which incorporates theory of storage, the convenience yield and the seasonality of harvests, was applied in the Brazilian sugar market. After predictions were made with the Kalman filter, the model produced results that were statistically more accurate than those returned by the two-factor model available in the literature.

A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

Essays On CEO Compensation: New Evidence On The Managerial-Power Vs. Optimal Contracting Debate

This dissertation analyzes the effect of market analysts’ expectations of share prices (price targets) on executive compensation. It examines how well the estimated effects of price targets on compensation fit with two competing views on determining executive compensation: the arm’s length bargaining model, which assumes that a board seeks to maximize shareholders’ interests, and the managerial power model, which assumes that a board seeks to maximize managers’ compensation (Bebchuk et al. 2005). The first chapter documents the pattern of CEO pay from fiscal year 1996 to 2010. The second chapter analyzes the Institutional Broker Estimate System Detail History Price Target data file, which that reports analysts’ price targets for firms. I show that the number of price target announcements is positively associated with company share price’s volatility, that price targets are predictive of changes in the value of stocks, and that when analysts announce positive (negative) expectations of future stock price, share prices change in the same direction in the short run. The third chapter analyzes the effect of price targets on executive compensation. I find that analysts' price targets alter the composition of executive pay between cash-based compensation and stock-based compensation. When analysts forecast a rise (fall) in the share price for a firm, the compensation package tilts toward stock-based (cash-based) compensation. The substitution effect is stronger in companies that have weaker corporate governance. The fourth chapter explores the effect of the introduction of the Sarbanes-Oxley Act (SOX) in 2002 and its reinforcement in 2006 on the options granting process. I show that the introduction of SOX and its reinforcement eliminated the practice of backdating options but increased “spring-loading” of option grants around price targets announcements. Overall, the dissertation shows that price targets provide insights into the determinants of executive pay in favor of the managerial power model.

Scenari finanziari e portafogli ottimi: modelli di previsione e strategie per l'asset allocation tattica

Le scelte di asset allocation costituiscono un problema ricorrente per ogni investitore. Quest’ultimo è continuamente impegnato a combinare diverse asset class per giungere ad un investimento coerente con le proprie preferenze. L’esigenza di supportare gli asset manager nello svolgimento delle proprie mansioni ha alimentato nel tempo una vasta letteratura che ha proposto numerose strategie e modelli di portfolio construction. Questa tesi tenta di fornire una rassegna di alcuni modelli innovativi di previsione e di alcune strategie nell’ambito dell’asset allocation tattica, per poi valutarne i risvolti pratici. In primis verificheremo la sussistenza di eventuali relazioni tra la dinamica di alcune variabili macroeconomiche ed i mercati finanziari. Lo scopo è quello di individuare un modello econometrico capace di orientare le strategie dei gestori nella costruzione dei propri portafogli di investimento. L’analisi prende in considerazione il mercato americano, durante un periodo caratterizzato da rapide trasformazioni economiche e da un’elevata volatilità dei prezzi azionari. In secondo luogo verrà esaminata la validità delle strategie di trading momentum e contrarian nei mercati futures, in particolare quelli dell’Eurozona, che ben si prestano all’implementazione delle stesse, grazie all’assenza di vincoli sulle operazioni di shorting ed ai ridotti costi di transazione. Dall’indagine emerge che entrambe le anomalie si presentano con carattere di stabilità. I rendimenti anomali permangono anche qualora vengano utilizzati i tradizionali modelli di asset pricing, quali il CAPM, il modello di Fama e French e quello di Carhart. Infine, utilizzando l’approccio EGARCH-M, verranno formulate previsioni sulla volatilità dei rendimenti dei titoli appartenenti al Dow Jones. Quest’ultime saranno poi utilizzate come input per determinare le views da inserire nel modello di Black e Litterman. I risultati ottenuti, evidenziano, per diversi valori dello scalare tau, extra rendimenti medi del new combined vector superiori al vettore degli extra rendimenti di equilibrio di mercato, seppur con livelli più elevati di rischio.

The market manipulation regime in the European Union

Market manipulation is an illegal practice that enables a person can profit from practices that artificially raise or lower the prices of an instrument in the financial markets. Its prohibition is based on the 2003 Market Abuse Directive in the EU. The current market manipulation regime was broadly considered as a big success except for enforcement and supervisory inconsistencies in the Member States at the initial. A review of the market manipulation regime began at the end of 2007, which became quickly incorporated into the wider EU crisis-era reform program. A number of weaknesses of current regime have been identified, which include regulatory gaps caused by the development of trading venues and financial products, regulatory gaps concerning cross-border and cross-markets manipulation (particular commodity markets), legal uncertainty as a result of various implementation, and inefficient supervision and enforcement. On 12 June 2014, a new regulatory package of market abuse, Market Abuse Regulation and Directive on criminal sanctions for market abuse, has been adopted. And several changes will be made concerning the EU market manipulation regime. A wider scope of the regime and a new prohibition of attempted market manipulation will ensure the prevention of market manipulation at large. The AMPs will be subject to strict scrutiny of ESMA to reduce divergences in implementation. In order to enhance efficiency of supervision and enforcement, powers of national competent authorities will be strengthened, ESMA is imposed more power to settle disagreement between national regulators, and the administrative and criminal sanctioning regimes are both further harmonized. In addition, the protection of fundamental rights is stressed by the new market manipulation regime, and some measures are provided to guarantee its realization. Further, the success EU market manipulation regime could be of significant reference to China, helping China to refine its immature regime.

The Choice of Expedient Regulatory Controls on Housing Market Using Short-Term Equilibria Model

Khutoretsky dealt with the problem of maximising a linear utility function (MUF) over the set of short-term equilibria in a housing market by reducing it to a linear programming problem, and suggested a combinatorial algorithm for this problem. Two approaches to the market adjustment were considered: the funding of housing construction and the granting of housing allowances. In both cases, locally optimal regulatory measures can be developed using the corresponding dual prices. The optimal effects (with the regulation expenditures restricted by an amount K) can be found using specialised models based on MUF: a model M1 for choice of the optimum structure of investment in housing construction, and a model M2 for optimum distribution of housing allowances. The linear integer optimisation problems corresponding to these models are initially difficult but can be solved after slight modifications of the parameters. In particular, the necessary modification of K does not exceed the maximum construction cost of one dwelling (for M1) or the maximum size of one housing allowance (for M2). The result is particularly useful since slight modification of K is not essential in practice.

Managing server energy and reducing operational cost for online service providers

The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.

Minimizing residential distribution system operating costs through intelligently scheduled plug-in hybrid electric vehicle charging

Rising fuel prices and environmental concerns are threatening the stability of current electrical grid systems. These factors are pushing the automobile industry towards more effcient, hybrid vehicles. Current trends show petroleum is being edged out in favor of electricity as the main vehicular motive force. The proposed methods create an optimized charging control schedule for all participating Plug-in Hybrid Electric Vehicles in a distribution grid. The optimization will minimize daily operating costs, reduce system losses, and improve power quality. This requires participation from Vehicle-to-Grid capable vehicles, load forecasting, and Locational Marginal Pricing market predictions. Vehicles equipped with bidirectional chargers further improve the optimization results by lowering peak demand and improving power quality.

IS THE U.S. SHALE GAS BOOM HAVING AN EFFECT ON THE EUROPEAN GAS MARKET?

This thesis focuses on the impact of the American shale gas boom on the European natural gas market. The study presents different tests in order to analyze the dynamics of natural gas prices in the U.S., U.K. and German natural gas market. The question of cointegration between these different markets are analyzed using several tests. More specifically, the ADF tests for the presence of a unit root. The error correction model test and the Johansen cointegration procedure are applied in order to accept or reject the hypothesis of an integrated market. The results suggest no evidence of cointegration between these markets. There currently is no evidence of an impact of the U.S. shale gas boom on the European market.

ELECTRICITY GENERATION MODELING AND PHOTOVOLTAIC FORECASTS IN CHINA

With the economic development of China, the demand for electricity generation is rapidly increasing. To explain electricity generation, we use gross GDP, the ratio of urban population to rural population, the average per capita income of urban residents, the electricity price for industry in Beijing, and the policy shift that took place in China. Ordinary least squares (OLS) is used to develop a model for the 1979-2009 period. During the process of designing the model, econometric methods are used to test and develop the model. The final model is used to forecast total electricity generation and assess the possible role of photovoltaic generation. Due to the high demand for resources and serious environmental problems, China is pushing to develop the photovoltaic industry. The system price of PV is falling; therefore, photovoltaics may be competitive in the future.

CAN CHINA USE ALTERNATIVE ENERGIES INSTEAD OF COAL TO PROVIDE MORE ELECTRICITY BY 2030?

Following the rapid growth of China's economy, energy consumption, especially electricity consumption of China, has made a huge increase in the past 30 years. Since China has been using coal as the major energy source to produce electricity during these years, environmental problems have become more and more serious. The research question for this paper is: "Can China use alternative energies instead of coal to produce more electricity in 2030?" Hydro power, nuclear power, natural gas, wind power and solar power are considered as the possible and most popular alternative energies for the current situation of China. To answer the research question above, there are two things to know: How much is the total electricity consumption in China by 2030? And how much electricity can the alternative energies provide in China by 2030? For a more reliable forecast, an econometric model using the Ordinary Least Squares Method is established on this paper to predict the total electricity consumption by 2030. The predicted electricity coming from alternative energy sources by 2030 in China can be calculated from the existing literature. The research results of this paper are analyzed under a reference scenario and a max tech scenario. In the reference scenario, the combination of the alternative energies can provide 47.71% of the total electricity consumption by 2030. In the max tech scenario, it provides 57.96% of the total electricity consumption by 2030. These results are important not only because they indicate the government's long term goal is reachable, but also implies that the natural environment of China could have an inspiring future.

Three essays on prices and selection

Competitive Market Segmentation Abstract In a two-firm model where each firm sells a high-quality and a low-quality version of a product, customers differ with respect to their brand preferences and their attitudes towards quality. We show that the standard result of quality-independent markups crucially depends on the assumption that the customers' valuation of quality is identical across firms. Once we relax this assumption, competition across qualities leads to second-degree price discrimination. We find that markups on low-quality products are higher if consuming a low-quality product involves a firm-specific disutility. Likewise, markups on high-quality products are higher if consuming a high-quality product creates a firm-specific surplus. Selection upon Wage Posting Abstract We discuss a model of a job market where firms announce salaries. Thereupon, they decide through the evaluation of a productivity test whether to hire applicants. Candidates for a job are locked in once they have applied at a given employer. Hence, such a market exhibits a specific form of the bargain-then-ripoff principle. With a single firm, the outcome is efficient. Under competition, what might be called "positive selection" leads to market failure. Thus our model provides a rationale for very small employment probabilities in some sectors. Exclusivity Clauses: Enhancing Competition, Raising Prices Abstract In a setting where retailers and suppliers compete for each other by offering binding contracts, exclusivity clauses serve as a competitive device. As a result of these clauses, firms addressed by contracts only accept the most favorable deal. Thus the contract-issuing parties have to squeeze their final customers and transfer the surplus within the vertical supply chain. We elaborate to what extent the resulting allocation depends on the sequence of play and discuss the implications of a ban on exclusivity clauses.

Strategic Behavior in Day-Ahead and Real-Time Markets for Electricity: Offer Cost or Payment Cost Minimization?

This study compares the procurement cost-minimizing and productive efficiency performance of the auction mechanism used by independent system operators (ISOs) in wholesale electricity auction markets in the U.S. with that of a proposed alternative. The current practice allocates energy contracts as if the auction featured a discriminatory final payment method when, in fact, the markets are uniform price auctions. The proposed alternative explicitly accounts for the market clearing price during the allocation phase. We find that the proposed alternative largely outperforms the current practice on the basis of procurement costs in the context of simple auction markets featuring both day-ahead and real-time auctions and that the procurement cost advantage of the alternative is complete when we simulate the effects of increased competition. We also find that a trade-off between the objectives of procurement cost minimization and productive efficiency emerges in our simple auction markets and persists in the face of increased competition.