Dissertations / Theses on the topic 'Electrical market'
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1
Das, Sanmay. "Intelligent Market-Making in Artificial Financial Markets." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/5570.
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This thesis describes and evaluates a market-making algorithm for setting prices in financial markets with asymmetric information, and analyzes the properties of artificial markets in which the algorithm is used. The core of our algorithm is a technique for maintaining an online probability density estimate of the underlying value of a stock. Previous theoretical work on market-making has led to price-setting equations for which solutions cannot be achieved in practice, whereas empirical work on algorithms for market-making has focused on sets of heuristics and rules that lack theoretical justification. The algorithm presented in this thesis is theoretically justified by results in finance, and at the same time flexible enough to be easily extended by incorporating modules for dealing with considerations like portfolio risk and competition from other market-makers. We analyze the performance of our algorithm experimentally in artificial markets with different parameter settings and find that many reasonable real-world properties emerge. For example, the spread increases in response to uncertainty about the true value of a stock, average spreads tend to be higher in more volatile markets, and market-makers with lower average spreads perform better in environments with multiple competitive market-makers. In addition, the time series data generated by simple markets populated with market-makers using our algorithm replicate properties of real-world financial time series, such as volatility clustering and the fat-tailed nature of return distributions, without the need to specify explicit models for opinion propagation and herd behavior in the trading crowd.
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SZCZERBACKI, CAROLINA FERREIRA. "ELECTRICAL ENERGY PRICE STRUCTURING FOR THE BRAZILIAN MARKET." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2007. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=10656@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOOs preços de energia elétrica, insumo básico para todo o Modelo Setorial, constituem uma das maiores incertezas do setor. Estas incertezas abrangem todos os elementos formadores de preços: a oferta, a demanda e as regras de mercado, tornando muitas vezes difícil ao agente a avaliação concreta e precisa do processo da formação de preços e do impacto que a variação de um dos elementos do processo produz no resultado final. O objetivo deste trabalho é apresentar a estrutura de formação de preços no mercado energético brasileiro de forma sistematizada, avaliando a composição das variáveis que afetam esta estrutura: a demanda por consumo, a expansão do sistema e as disponibilidades energéticas. O mercado é modelado em todos os seus detalhes físicos, e o cálculo é realizado a partir de todo o arcabouço regulatório, incluindo a reprodução do modelo de operação ótima responsável pelos preços de energia. Descreve-se inicialmente um modelo de previsão de demanda por subsistema, utilizando-se técnicas de Teoria de Análise Funcional. Focaliza-se em seguida o suprimento futuro de energia no país a partir da expansão da oferta. Finalmente, utiliza-se uma simulação da operação ótima do sistema a partir da reprodução dos resultados do modelo utilizado no setor - o Newave - a partir de uma implementação própria desenvolvida especialmente no escopo deste trabalho. De posse dos possíveis cenários futuros, pode-se mensurar o impacto que a variação de cada elemento formador (demanda, expansão e afluências) tem sobre os custos de energia. É possível observar que as incertezas nestas variáveis podem gerar grandes impactos nos custos marginais e, conseqüentemente, nos custos futuros de energia elétrica.
Energy Prices, essential input for the Sectorial Model, consist on the biggest uncertainties of the Electric Sector. These uncertainties enclose all price elements: the supply, the demand and the market rules, making sometimes difficult for the agents to evaluate the price process and the impact that the variation of each process element can produce on the result. The objective is to present Brazilian price process in a structuralized way, evaluating the variables composition that affects this structure: the demand, the electric system expansion and the energy supply availability. The market is modeled in all its physical details, and the calculation is done into the regulatory environment, including a reproduction of the optimal operation model responsible for energy prices. First, a demand forecast model is described, based on Functional Analysis Theory. Then, the focus is on the energy future supply, analyzing the supply expansion in Brazil. Finally, an optimal operation system is simulated, reproducing the sector model (Newave) results from an implementation developed in this work. From these possible future settings, each element (demand, expansion and energy supply availability) variation impact on energy prices can be measured. The simulations show that uncertainties about these variables can have big impacts on marginal costs and, consequently, on the energy future prices.
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Aloysius, Romila Mariette. "Market Analysis of Cardiac Electrical Mapping Platform in the Cardiac Resynchronization Therapy Market." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1363099595.
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Turan, Ali. "The Turan Electric Company - the leader of the turkish market of energy and electrical products." Thesis, Київський національний університет технологій та дизайну, 2017. https://er.knutd.edu.ua/handle/123456789/6676.
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Ning, Zihan. "ELECTRICITY MARKET SIMULATOR." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1480695981422754.
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Bouffard, François. "Electricity market-clearing with stochastic security." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=100326.
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In this dissertation we formulate a short-term electricity market-clearing problem with stochastic security criteria. The proposed stochastic security criteria, snake use of probabilistic measures of the expected bald not served or of the loss-of-load probability associated with the random failures of pre-selected sets of generators, lines as well as load disturbances. We snow that by economically penalizing the operation of the market through the associated demand-side costs of involuntary load shedding, the reserve service requirements are determined implicity, thus removing the needs for specifing any a priori reserve requirements. Under this approach, the market-clearing problem gains in flexibility as it can balance file respective expected costs of: (i) the pre-contingency preventive security control actions that include unit commitment, generation and load dispatch as well as reserve scheduling; (ii) the post-contingency corrective actions that deploy reserves through further unit, commitment decisions and load and generation re-dispatch; and, (iii) any post-contingency involuntary load shedding decisions. Case studies illustrate that electricity market-clearing with stochastic security leads to non-negligible economic savings for society; while it can still ensure that consumers benefit from a secure supply of electricity given how they value load shedding.We derive theoretical results pertaining to the prices of energy and security corresponding to the optimal schedules of the market-clearing process. The key result of this analysis establishes that involuntary load shedding is used after a contingency if and only if the expected marginal costs of scheduling reserves and deploying them are greater than the expected marginal costs of load shedding.
We then extend the model of electricity market-clearing with stochastic security by proposing a short-term electricity market-clearing formulation capable of accounting for non-dispatchable and intermittent power generation sources like wind power. We show how the electricity market-clearing model can take into account uncertainties in the next day/hours wind power generation predictions as well as those of the demand. Also, We demonstrate how the market-clearing formulation can integrate the scheduling of a large-scale centralized energy storage infrastructure.
Finally we define rigorously the concept of the set of umbrella, contingencies for security-constrained optimal power flow problems, a class of power system scheduling problems to which market-clearing with stochastic: security belongs. We propose an identification method to identify the members of this set by making use of the vector norms of the Lagrange multipliers associated with the post-contingency power balance relations. We suggest a heuristic contingency ranking rule based on those vector norms, and we argue that, the proposed identification rule and ranking method can be of use to system operators when specifying reduced sets of contingencies for security-constrained market-clearing problems.
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Peng, Tengshun. "Bidding strategy and empirical analysis of bidding in electrical power market." Online access for everyone, 2006. http://www.dissertations.wsu.edu/Dissertations/Spring2006/t%5Fpeng%5F011406.pdf.
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Westerström, Erik. "Barriers to blockchain adoption in the public electrical vehicle charging market." Thesis, Blekinge Tekniska Högskola, Institutionen för industriell ekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20139.
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The adoption of blockchain in the public electrical vehicle charging market has yet to be realized to its full potential, despite existing proof-of-concept. A positive outlook for blockchain is suggested by contemporary research, as well as the need for empirical studies to fully identify blockchain’s barriers to adoption. Through qualitative methods, a focused literature review, and in-depth interviews with subject matter experts, this thesis investigated which barriers to blockchain adoption exist in the public electrical vehicle charging market. The results indicated that the main barrier to blockchain adoption was the structure of the public electrical vehicle charging market itself, since it is an immature market experiencing constant change. This was followed by: coordination, norms and cultures, business process, incumbent technological solutions, regulations and legislations, shared infrastructure, and distributed ledger technology. These barriers were not shown individually, but were affected by each other. It is concluded that blockchain technology is not needed by the market in its current state, as its key defining attributes of privacy, security and decentralization are not deemed worth the cost of its own implementation. This research contributes to, and updates, the knowledge of blockchain utilization for the public electrical vehicle charging market. The results can be used by private and public organizations and scholars as reference material with regards to blockchain adoption for public electrical vehicle charging.
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Feijer, Diego (Diego Francisco Feijer Rovira). "Financial market failures and systemic crises." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101570.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 97-103).
This thesis contributes to the theoretical literature that studies the macroeconomic implications of financial frictions. It develops frameworks to address different financial market failures, and evaluate preventive policies to mitigate the vulnerability of the economy to costly systemic crises. First, it identifies a credit risk (fire sale) externality that justifies the macroprudential regulation of short-term debt to mitigate the probability of systemic bank runs. Without regulation, banks do not internalize how their funding decisions affects the terms at which other market participants can obtain credit. The formal welfare study conducted, provides a general equilibrium notion of systemic risk that captures both fundamental insolvency and illiquidity risk. It also connects this measure with the optimal Pigouvian (corrective) tax. Second, it shows that liquidity crises may arise as the result of endogenous information panics. It finds that collective ignorance is welfare maximizing but it is fragile, susceptible to self-fulfilling fears about asymmetric information. Adverse selection may thus obtain in equilibrium, sustained by negative aggregate expectations. The mechanism that gives rise to multiple equilibria is robust to the introduction of noisy private signals, and warrants the regulation of information acquisition for rent-seeking (speculative) motives. Finally, it demonstrates the limitations of unconventional credit easing policies to stimulate lending during market-freezes. With inter-temporal investment complementarities, credit to non-financial firms may be curtailed as the result of dynamic coordination failures. Interest rate cuts mitigate coordination risk, but increase the average duration of credit market freezes when the productivity of capital is high. Capital injections in the banking sector, or direct lending to non-financial firms, are completely ineffective, because reductions in deposits from households crowd out government spending. In contrast, government guarantees improve welfare by reducing strategic uncertainty.
by Diego Feijer.
Ph. D.
10
Meng, Xianglin S. M. Massachusetts Institute of Technology. "Systemic risk in the interbank lending market." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117814.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 77-81).
Our goal is to understand the functioning of the interbank lending market in times of market stress. Working towards this goal, we conduct theoretical analysis and simulation to study the effects of network structure and shock scenarios on systemic risk in the market. We consider shocks of various sizes at both global and local scales. In terms of risk measures, we study relative systemic loss and the default rate, separating the latter quantity into fundamental default and contagion. Our simulations suggest that all systemic risk measures are similar on the well-studied directed Erdős-Rényi model and the more complex fitness model if we match the mean density and the mean edge weight of these two models. We show through both derivations and simulations that the network size has little effect on systemic risk when the network is sufficiently large. Moreover, as the mean degree grows, the different default rates considered all increase, while relative systemic loss decreases. Furthermore, simulations suggest that local shocks tend to cause more harm than global shocks of the same total size. We also derive upper and lower bounds on a bank's probability of default, only using its neighbors' information. For implementation, we build a method for real-time, automatic, interpretable assessment of financial systemic risk, which only requires temporal snapshots of observable data. Our algorithm takes in partial data, inferring a random graph model, and then generates empirical distributions for risk measures. The first part relies on inferring a fitness model that is compatible with observed information. For the second part, we use simulations to obtain empirical distributions for systemic risk that arises from interbank clearing. We test our method on synthetic data and apply it to the federal funds market using empirical data. Our method is fast enough to be incorporated into algorithms that produce intraday time trajectories of risk prediction. The data requirement is practical for investors as well as regulators, policy-makers, and financial institutions.
by Xianglin Meng.
S.M.
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Wang, David Yi 1971. "Market Maker : an agent-mediated marketplace infrastructure." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80134.
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Raykin, Boris 1976. "System dynamics of market making and liquidity." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/47621.
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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (leaves 47-49).
by Boris Raykin.
S.B.and M.Eng.
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Li, Fu Jian. "Internet use of manufacturers in low-voltage electrical product market in China." Thesis, University of Macau, 2001. http://umaclib3.umac.mo/record=b1636658.
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Wei, Ermin. "Distributed optimization and market analysis of networked systems." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/92968.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 173-179).
In the interconnected world of today, large-scale multi-agent networked systems are ubiquitous. This thesis studies two classes of multi-agent systems, where each agent has local information and a local objective function. In the first class of systems, the agents are collaborative and the overall objective is to optimize the sum of local objective functions. This setup represents a general family of separable problems in large-scale multi-agent convex optimization systems, which includes the LASSO (Least-Absolute Shrinkage and Selection Operator) and many other important machine learning problems. We propose fast fully distributed both synchronous and asynchronous ADMM (Alternating Direction Method of Multipliers) based methods. Both of the proposed algorithms achieve the best known rate of convergence for this class of problems, O(1/k), where k is the number of iterations. This rate is the first rate of convergence guarantee for asynchronous distributed methods solving separable convex problems. For the synchronous algorithm, we also relate the rate of convergence to the underlying network topology. The second part of the thesis focuses on the class of systems where the agents are only interested in their local objectives. In particular, we study the market interaction in the electricity market. Instead of the traditional supply-follow-demand approach, we propose and analyze a systematic multi-period market framework, where both (price-taking) consumers and generators locally respond to price. We show that this new market interaction at competitive equilibrium is efficient and the improvement in social welfare over the traditional market can be unbounded. The resulting system, however, may feature undesirable price and generation fluctuations, which imposes significant challenges in maintaining reliability of the electricity grid. We first establish that the two fluctuations are positively correlated. Then in order to reduce both fluctuations, we introduce an explicit penalty on the price fluctuation. The penalized problem is shown to be equivalent to the existing system with storage and can be implemented in a distributed way, where each agent locally responds to price. We analyze the connection between the size of storage, consumer utility function properties and generation fluctuation in two scenarios: when demand is inelastic, we can explicitly characterize the optimal storage access policy and the generation fluctuation; when demand is elastic, the relationship between concavity and generation fluctuation is studied.
by Ermin Wei.
Ph. D.
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Rayanakorn, Surapap. "Financial market imperfections and their asset pricing implications." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/75646.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 119-123).
This thesis consists of two studies on financial market imperfections. The first study (Chapters 2 and 3) investigates illiquidity, which is a reflection of different imperfections, and its pricing implications in the corporate bond market. The second study (Chapter 4) evaluates the impact of a short-sale ban, which is a form of financial constraints, on the equity and derivatives markets. In Chapter 2, we propose illiquidity measures that outperform existing ones statistically and economically. We estimate various illiquidity measures in the corporate bond market, using transaction-level data from 2002 to 2010. In the cross-section, we find illiquidity measures to be related to bond characteristics often used as illiquidity proxies. In the time-series, we show commonality in the aggregate illiquidity measures, increasing during the sub-prime crisis and peaking in October 2008. We then identify that time variation in aggregate illiquidity measures is linked with market variables such as the VIX index. In Chapter 3, we examine pricing implications of the illiquidity measures. We find that illiquidity level is priced both at the aggregate level and at the bond level throughout the sample period. However, the role of illiquidity risk in pricing bond yield spreads is weaker, and is driven by the 2008 financial crisis. In Chapter 4, we study the 2008 short-sale ban. We find that the banned stocks have positive cumulative abnormal returns and become more volatile when the ban is imposed. We document greater demand and abnormalities in the futures market and option market under the short-sale ban. This evidence suggests that a short-sale ban may not stabilize a financial market in crisis.
by Surapap Rayanakorn.
Ph.D.
16
Johari, Ramesh 1976. "Efficiency loss in market mechanisms for resource allocation." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/16694.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (p. 237-249).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
This thesis addresses a problem at the nexus of engineering, computer science, and economics: in large scale, decentralized systems, how can we efficiently allocate scarce resources among competing interests? On one hand, constraints are imposed on the system designer by the inherent architecture of any large scale system. These constraints are counterbalanced by the need to design mechanisms that efficiently allocate resources, even when the system is being used by participants who have only their own best interests at stake. We consider the design of resource allocation mechanisms in such environments. The analytic approach we pursue is characterized by four salient features. First, the monetary value of resource allocation is measured by the aggregate surplus (aggregate utility less aggregate cost) achieved at a given allocation. An efficient allocation is one which maximizes aggregate surplus. Second, we focus on market-clearing mechanisms, which set a single price to ensure demand equals supply. Third, all the mechanisms we consider ensure a fully efficient allocation if market participants do not anticipate the effects of their actions on market-clearing prices. Finally, when market participants are price anticipating, full efficiency is generally not achieved, and we quantify the efficiency loss. We make two main contributions. First, for three economic environments, we consider specific market mechanisms and exactly quantify the efficiency loss in these environments when market participants are price anticipating. The first two environments address settings where multiple consumers compete to acquire a share of a resource in either fixed or elastic supply; these models are motivated by resource allocation in communication
(cont.) networks. The third environment addresses competition between multiple producers to satisfy an inelastic demand; this model is motivated by market design in power systems. Our second contribution is to establish that, under reasonable conditions, the mechanisms we consider minimize efficiency loss when market participants anticipate the effects of their actions on market-clearing prices. Formally, we show that in a class of market-clearing mechanisms satisfying certain simple mathematical assumptions and for which there exist fully efficient competitive equilibria, the mechanisms we consider uniquely minimize efficiency loss when market participants are price anticipating.
by Ramesh Johari.
Ph.D.
17
Visudhiphan, Poonsaeng 1973. "A dynamic model of the electricity generation market." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/47726.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (leaves 105-107).
This thesis proposes that the bidding process that occurs daily in the competitive short-run power market can be modeled as a dynamic system, or a dynamic game played by electricity generators. Such a game is a finitely repeated one of complete but imperfect information. In this thesis, a dynamic model representing a small shortrun power market is formulated as a repeated game. Daily price competition provides sufficient information for the generators to estimate their bids. The next bids of each generator are proposed as functions of the previous and current bids. Results from the dynamic model show that the generators' bidding strategy affects the dynamics of the modeled power market. Different strategies yield different market clearing price patterns. Moreover, a step-supply function bid, in which an offer price relates to an offer quantity by a marginal-cost function, and the maximum available capacity of each generator, can cause inefficient prices in some scheduling periods and/or might result in inefficient dispatches in each scheduling day. In addition, depending on the bidding strategy that is uniformly applied to the model, although there is certainty of inelastic anticipated demand in the model, the repeated bidding processes tends to allow the generators to "learn" from the market so that they can tacitly collude to create demand deficiency. It is further suggested here that when demand deficiency unexpectedly occurs in peak-load periods, a real-time market (i.e., an hour-ahead market) might be needed so that supply always meets demand.
by Poonsaeng Visudhiphan.
S.M.
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McCord, Anna Gabriele. "Public works as a response to labour market failure in South Africa." Master's thesis, University of Cape Town, 2002. http://hdl.handle.net/11427/6953.
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Bibliography : leaves 112-120.Unemployment has been rising in South Africa for the last three decades, leading to official unemployment rates of 26.4% (37% if the broad definition is used). This implies a jobless total of 7 million, with more than 40% of the rural population unemployed, and the development of a growing pool of workers who are excluded from the labour market. The South African economy is facing labour market failure, with labour supply increasingly outstripping demand. If the economy continues on its current growth path this problem of labour market failure will intensify and the employment situation will continue to deteriorate. The severe levels of unemployment resulting from this market failure are a particular problem in South Africa given the role unemployment plays in exacerbating poverty and inequality in an already highly unequal and segmented society, and the uneven incidence of unemployment among racial groups. Public works programming offers a response to both poverty and unemployment, while also addressing the linked national priority issue of asset creation. This paper discusses the option of state intervention through public works, reviewing the South African response in the context of global public works experience. The paper examines both project based public works programming, which forms the dominant policy response in South Africa, and the option of large-scale labour intensification of state expenditure, and examines the employment creation and cost implications of each, drawing on a case study from KwaZulu Natal. The paper concludes that public works interventions in South Africa to date have been relatively limited in scope and impact, and that the potential exists for far greater job creation and poverty alleviation through both the labour intensification of public spending, and the rationalization of the project based approach.
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Jerndal, Rasmus, and Ossian Krödel. "Portfolio Optimization with Market State Analysis." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239361.
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This bachelor thesis examines if portfolio allocation models can be reversed to find the investor’s perceived probabilities of different market states. This is achieved through a method which optimizes an inverted convex program with respect to market states from an assumed optimized portfolio of n securities. The concept the authors wished to explore was whether the actions of a known portfolio could be correlated to a set of factors in the market and further predict the portfolio management’s actions. This paper shows that such correlations are possible for simulated portfolios but does not dive deeper into the classification of markets, stocks and factors to solve the problem for a real portfolio.
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Chiu, Kenneth. "Generalized Gaussian covariance analysis in multi-market risk assessment." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/35449.
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Loflin, Jonathan Paul 1976. "A distributed online financial market : design, implementation, and experiments." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80542.
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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (p. 109-110).
by Jonathan Paul Loflin.
M.Eng.
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Liu, Clare H. "Applications of twitter emotion detection for stock market prediction." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113131.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 71-76).
Currently, most applications of sentiment analysis focus on detecting sentiment polarity, which is whether a piece of text can be classified as positive or negative. However, it can sometimes be important to be able to distinguish between distinct emotions as opposed to just the polarity. In this thesis, we use a supervised learning approach to develop an emotion classifier for the six Ekman emotions: joy, fear, sadness, disgust, surprise, and anger. Then we apply our emotion classifier to tweets from the 2016 presidential election and financial tweets labeled with Twitter cashtags and evaluate the effectiveness of using finer-grained emotion categorization to predict future stock market performance.
by Clare H. Liu.
M. Eng.
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Eidson, Donald Brian. "Estimation and hierarchical control of market-driven electric power systems." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11068.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (leaves 328-337).
by Donald Brian Eidson.
Ph.D.
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Skantze, Petter L. 1973. "Closed-loop market dynamics for a deregulated electric power industry." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/46248.
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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (leaves 78-79).
The deregulation of the electric power industry in the United States has put pressure on system operators to maintain security and performance levels under increasingly uncertain market conditions. The debate over which market structure is best suited to facilitate provision of power on a competitive basis is still ongoing. In this thesis, a summary is provided first of the effects of deregulation in the U.K. and Scandinavian markets. Based on this summary, a new market structure for trading electrical power is proposed. The trading process is separated into three markets: the long-term, spot and controls markets, distinguished by time frames as well as their functionality. Extensive modeling of the technical behavior of the system as well as the economic decision process of industry participants is introduced. A simulation of the market, driven by stochastic disturbances, shows how entirely profit-based generators adapt themselves to optimize overall social welfare. The second contribution from this thesis is the development of a new concept for market-based frequency controls. By requiring information about load volatility to be included in bilateral contracts, system operators will be able to provide individualized incentives for generators and loads to reduce the overall need for system control. In addition, a modification to the existing criteria for frequency regulation is proposed. It is shown how by relying solely on system frequency as a control variable, an inter-area market for controls can be created. In addition to improving efficiency and taking advantage of inter-area price differentials, the new criterion also eliminates the need for real time coordination of generators participating in frequency control.
by Petter L. Skantze.
M.Eng.
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Chua, Cheong Wei 1975. "A stochastic pool-based electricity market simulator /." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=31045.
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In Part I, two pool-based electricity market models are compared in terms of their economic impact on the market participants, the Lossless Economic Dispatch (LED) and the Optimal Power Flow (OPF). The OPF is shown to be economically more efficient, more accurate and more equitable to the participants.In Part II, a stochastic electricity market simulator (SEMS) is designed using elements of Monte Carlo methods and game theory. Each generator is assumed to operate in a stochastic manner, according to a bid strategy composed of a set of pre-established bid instances and a corresponding set of bid probabilities. The Pool dispatches power and defines prices according to either the LED or OPF models from Part I. Generators can update their bidding strategies according to a profit performance index reflecting their degree of risk tolerance, Chicken (risk averse), Average, and Cowboy (risk taker). SEMS can predict issues such as unintended collusion, as well as to evaluate bidding strategies.
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Kizilkale, Arman. "Stochastic and mean field theory of adaptive and power market systems." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114234.
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This thesis investigates control and optimization in large population games, particularly continuous time power markets. The first part of the thesis is mostly theoretical, whereas the second part of the thesis is more application oriented. The last chapter employs the techniques presented in the first part of the thesis in the formulation and analysis of continuous time power markets. The mean field (MF) methodology provides decentralized strategies which yield Nash equilibria for large population games in the asymptotic limit of an infinite (mass) population. The MF best response laws use only the local information of each agent, while the mass effect is calculated offline using statistical information on population parameters. These laws yield approximate equilibria when applied in the finite population. In the first part of the thesis we investigate the stability and equilibrium properties of the overall population in a mean field formulation for three scenarios. First, we consider the problem when the a priori information of each individual, i.e. local information and mass statistics, is absent, and each agent is only allowed to observe a decaying fraction of agents in the population. Each agent estimates its local parameters via the recursive weighted least squares (RWLS) algorithm and the distribution of the mass parameters via maximum likelihood estimation (MLE). Secondly, we consider the problem in the presence of a major agent where in addition to a large population of individual cost minimizer agents, a fraction of the agents are social cost minimizers. Lastly, we investigate coalition formations in the mean field context.The second part of the thesis is devoted to an efficiency analysis of power markets in optimal control and dynamic game frameworks. We begin the analysis of efficiency by modelling the market as a dynamical system with demand and supply processes both in a centralized framework and in a multi-agent setup and we investigate the efficiency and the equilibrium of the market. We provide an efficiency non-volatility no-free-lunch trade-off theorem. We extend the model by adding an intermittent supplier and show that for a sufficiently high intermittent supply volatility, the intermittent supplier might negatively impact the social efficiency. We introduce a novel market mechanism for power markets: we define one price process for supply subject to friction and another invisible price for frictionless ancillary supply and show that (i) the negative efficiency impact of the intermittent supplier due to stochasticity and uncontrollability can be offset, and (ii) the volatility of the price can be decreased with the new double price mechanism.Lastly, we model the power market as a large population dynamic game where suppliers and consumers submit their bids in real-time. The agents are coupled in their dynamics and cost functions through the price process. The control action computation complexity and information exchange requirements for each agent increase as the number of agents in the system increases, and this naturally leads to computational intractability. We apply the mean field methodology to study the limit behaviour of a large population of consumers and suppliers, and present a decentralized algorithm where agents submit their bids solely following the price signal and using statistical information that is measured from the entire population. We show that under some restrictions on the population parameter distributions the proposed algorithm gives rise to a situation where (i) all agent systems are stable, and (ii) the set of controls yields an equilibrium.Cette thèse s'intéresse au contrôle et à l'optimisation dans des jeux à population importante, et plus particulièrement les marchés énergétiques à temps continu. La première partie de la thèse est essentiellement théorique alors que la seconde s'attache davantage à des applications. Le dernier chapitre applique les techniques développées dans la première partie à la formulation et à l'analyse de marchés énergétiques à temps continu.La méthodologie des jeux à champ moyen donne des stratégies décentralisées qui mènent à des équilibres de Nash pour des jeux avec d'importantes populations approchant une masse infinie. Dans cette méthodologie, les lois ayant les meilleures réponses utilisent uniquement une information locale pour chaque agent, alors que l'effet de masse est calculé indépendamment en utilisant des informations statistiques sur les paramètres de population. Ces lois mènent à des équilibres approchés lorsqu'elles sont utilisées sur des populations finies.Dans la première partie de la thèse, nous nous intéressons aux propriétés de stabilité et d'équilibre de la population totale dans trois scénarios de jeux à champ moyen. D'abord, nous considérons le problème où l'information a priori de chaque individu, c'est-à-dire l'information locale et la statistique de masse, est absente et chaque agent est uniquement autorisé à observer une fraction décroissante de la population. Chaque agent estime ses paramètres locaux en utilisant l'algorithme de moindres carrés pondérés récursifs ainsi que la distribution des paramétres de masse par estimation du maximum de vraisemblance.Ensuite, nous considérons le problème sous contrainte d'existence d'un agent majeur où en plus d'une grande population d'agents minimisant leurs coûts individuels, une fraction des agents minimisent le coût social. Enfin, nous explorons la possibilité de coalitions dans le contexte des jeux à champ moyen.Le deuxième partie de la thèse s'attache à l'analyse d'efficacité des marchés énergétiques avec un contrôle optimal et dans le cadre des jeux dynamiques. Nous débutons cette analyse d'efficacité en modélisant le marché en système dynamique avec offres et demandes groupées dans un même cadre et dans une installation multi-agents, et nous analysons l'efficacité et l'équilibre du marché. Nous introduisons un théorème surprenant de compromis "rien n'est gratuit" efficacité-volatilité. Nous élargissons ensuite le modèle en ajoutant un fournisseur intermittent, et nous montrons que pour une volatilité suffisamment importante de ses approvisionnements, il peut avoir un impact négatif sur l'efficacité sociale.Enfin, nous modélisons les marchés énergétiques comme un jeu dynamique de population d'importance où les fournisseurs et les consommateurs soumettent leur offres en temps réel. La dynamique et les fonctions de coûts des agents sont liées par le processus de prix.La complexité de calcul et les exigences de contrôle des mesures d'échange d'informations pour chaque agent augmente en fonction de la croissance du nombre d'agents dans le système, ce qui conduit naturellement à l'insolubilité de calcul. Nous appliquons la méthodologie du champ moyen pour étudier le comportement limite d'une importante population de consommateurs et de fournisseurs, et présentons un algorithme décentralisé où les agents présentent leurs offres uniquement en suivant le signal de prix et en utilisant l'information statistique qui est mesurée à partir de la population entière. Nous montrons que sous certaines restrictions sur les distributions des paramètres de la population, l'algorithme proposé donne lieu à une situation où (i) tous les systèmes d'agents sont stables, et (ii) l'ensemble des contrôles donne lieu à un équilibre.
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Sun, Karl 1970. "Micropayments as a form of market-based intellectual property protection." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/42754.
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Neumayer, Sebastian James. "Efficiency loss in a class of two-sided market mechanisms." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/38666.
Full textAbstract:
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 57).
This thesis addresses the question of how to efficiently allocate resources among competing players in convex environments. We will analyze the efficiency loss of certain two-sided market mechanisms involving both consumers and suppliers that are natural extensions of Johari's thesis. After gaining intuition about the mechanisms, we show that their worst case efficiency loss approaches 100%. We then introduce some supply-side market mechanisms in a network setting. In the market mechanisms we study, every player submits a bid which specifies a demand or supply function from a parameterized family. Then, the mechanism allocates resources so that supply meets demand.
by Sebastian James Neumayer.
S.M.
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Ileri, Fırat. "Optimal dynamic pricing for clearance sales on the spot market." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/53127.
Full textAbstract:
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (p. 79).
In this thesis, we develop an optimal dynamic pricing strategy for clearance sales of a textile manufacturing company which allows last-minute cancellations of orders without penalty. This company faces the difficult task of determining the optimal prices to clear the unsold products which result from last-minute order cancellations of its customers. The presented results in this thesis provide the company with a mathematical tool which can be used to optimally and dynamically set prices to maximize the profits in the clearance sales. We assume that buyers are myopic, demand multiple units of products and have independent demand. We also assume that the company has limited information on the valuation of buyers. Using these assumptions, an analytical model and estimations from the historical data are developed and dynamic programming is used to devise an optimal dynamic pricing strategy for the clearance sales of the company.
by Fırat Ileri.
M.Eng.
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Luo, Yiyang M. Eng Massachusetts Institute of Technology. "A study of stock market liquidity from 1973 to 2015." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105979.
Full textAbstract:
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 63-66).
In this thesis we analyze US stock market liquidity in the period of 1973 to 2015 from three perspectives: price impact, turnover ratio, and trading frequency. We use the Center for Research in Security Prices (CRSP) and Trade and Quotes (TAQ) databases to acquire stock data across different time spans to perform analysis across different time horizons, including stock listing and de-listing analysis using monthly trades data, price impact and turnover ratio analysis using daily trades data, and intraday trading frequency case studies using intraday trades data. We first analyze price impact of all common stocks in the US stock market from 1973 to 2015 using linear regression between the a stock's holding period return and the natural log of its dollar trading volume to estimate the price impact. We then perform frequency decomposition of price impact time series and reconstruct price impact time series using Inverse Discrete Fourier Transform. We find market liquidity cycles of 8.6 years and 4.3 years and analyze the implications of these liquidity cycles in the context of economic cycles. Next we analyze turnover ratio of all common stocks in the US stock market from 1973 to 2015. We find evidence for the turnover ratio increasing more for illiquid stocks than liquid stocks in response to market events. Through an analysis of the trailing 2 year correlation between turnover ratio and price impact, we show that this correlation in liquid stocks steadily increases starting from the early 1990s, possibly due to the proliferation of day traders. Finally we perform intraday cases studies for the 2007 Quant Meltdown, first day of the 2008 Financial Crisis' worst week, and the 2010 Flash Crash respectively. We use the number of trades within one minute as a proxy for trading frequency. We find evidence for most trades happening around 10am and towards the end of the trading day around 3:30pm; hence the market liquidity are most abundant during these peak time. We also provide a method to investigate irregular market behavior and intraday liquidity shocks from unusual increases and decreases in trading frequency during the day.
by Yiyang Luo.
M. Eng.
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DAVID, PEDRO AMERICO MORETZ-SOHN. "SPOT PRICE REGULATION, INVESTMENT ATTRACTION AND RISK MANAGEMENT IN THE BRAZILIAN ELECTRICAL ENERGY MARKET." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2004. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=5216@1.
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FURNAS CENTRAIS ELÉTRICAS S.AO mercado brasileiro de energia elétrica ainda não encontrou um modelo de mercado e de formação de preço que garanta a expansão auto-sustentada da oferta. Investigando em detalhe o modelo atual de despacho da geração e formação do preço, demonstramos a sua pouca eficácia na atração de investimentos, e identificamos a causa dessa falha como sendo a miopia do modelo de despacho, uma vez os estados críticos do sistema só aprecem de forma significativa quando o sistema já estiver degradado. São estudados três modelos alternativos que modificam a função-objetivo ou a regra de formação do preço, ajustados de modo a viabilizar e tornar suficientemente atrativos os investimentos na expansão da oferta. Finalmente, estes modelos são então comparados entre si e com o modelo atual, quanto ao valor para o investidor e quanto ao custo para o sistema e para o consumidor. Um mercado é dito completo se permite aos agentes alocar livremente seus recursos e demandas quando estiverem disponíveis e/ou forem necessários e permite que os agentes condicionem estes recursos / demandas ao estado (preço) do mercado. Estas funcionalidades são implementadas através dos derivativos financeiros, negociados no mercado futuro. Neste trabalho fazemos uma análise conceitual do mercado futuro de energia elétrica, indicando a diferença em relação ao de outras commodities e apresentando um modelo da oferta e demanda por contratos futuros de energia elétrica.
The Brazilian Market of Electrical Energy has not yet found a stable market and price model that ensues the feasibility and makes attractive a self-sustained investment for the expansion of electrical energy generation. Researching the current generation dispatch and spot price model, we show that it is ineffective to attract investments because the model is myopic, since the range of critical system states that is foreseen at the current state is not significant until the system is already too degraded. Stemming from this conclusion, we develop three alternative models, modifying the dispatch model objective and the price formation rule. These alternative models are tuned to make the investments in generation expansion feasible and attractive. The models are compared regarding their value to the investor and the cost to the system and to the consumer. A complete market allows the economic agents to freely allocate their resources and requirements whenever they are available and/or required. A complete market also allows conditional settlement, i.e., to condition the resource availability and/or requirement to a particular market state (price). These features are realized by financial derivatives, in the, so called, futures market. We present a conceptual analysis of the electrical energy s future market, pointing the differences to other commodities future markets that are due to economical unfeasibility of storing electricity. We also present an equilibrium model for the forward electrical energy contracts.
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Rodrigo, Deepal. "Optimal operational strategies for a day-ahead electricity market in the presence of market power using multi-objective evolutionary algorithm." Diss., Manhattan, Kan. : Kansas State University, 2007. http://hdl.handle.net/2097/389.
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Riordan, John Edward. "A neural network based distributed system for forecasting the stock market." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/12953.
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Thesis (B.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1991.Includes bibliographical references (leaves 58-60).
by John Edward Riordan.
B.S.
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Chaudhuri, Shomesh Ernesto. "Financial signal processing : applications to asset-market dynamics and healthcare finance." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117839.
Full textAbstract:
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 139-144).
The seemingly random fluctuations of price and value produced by information flow and complex interactions across a diverse population of stakeholders has motivated the extensive use of stochastic processes to analyze both capital markets and the regulatory approval process in healthcare. This thesis approaches the statistical analysis of such processes through the lens of signal processing, with a particular emphasis on studying how dynamics evolve over time. We begin with a brief introduction to financial signal processing in Part I, before turning to specific applications in the main body of the thesis. In Part II, we apply spectral analysis to understand and quantify the relationship between asset-market dynamics across multiple time horizons, and show how this framework can be used to improve portfolio and risk management. Using the Fourier transform, we decompose asset-return alphas, betas and covariances into distinct frequency components, allowing us to identify the relative importance of specific time horizons in determining each of these quantities. Our approach can be applied to any portfolio, and is particularly useful for comparing the forecast power of multiple investment strategies. Part III addresses the growing interest from the healthcare industry, regulators and patients to include Bayesian adaptive methods in the regulatory approval process of new therapies. By applying sequential likelihood ratio tests to a Bayesian decision analysis framework that assigns asymmetric weights to false approvals and false rejections, we are able to design adaptive clinical trials that maximize the value to current and future patients and consequently, public health. We also consider the possibility that as the process unfolds, drug sponsors might stop a trial early if new information suggests market prospects are not as favorable as originally forecasted. We show that clinical trials that can be modified as data are observed are more valuable than trials without this flexibility.
by Shomesh Ernesto Chaudhuri.
Ph. D.
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Gregorovic, Dennis (Dennis George) 1977. "HereToThere : market-based mechanisms for allocating agents to location-based tasks." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86466.
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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references.
by Dennis Gregorovic.
S.B.and M.Eng.
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Das, Sanmay 1979. "Dealers, insiders and bandits : learning and its effects on market outcomes." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/37916.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 145-149).
This thesis seeks to contribute to the understanding of markets populated by boundedly rational agents who learn from experience. Bounded rationality and learning have both been the focus of much research in computer science, economics and finance theory. However, we are at a critical stage in defining the direction of future research in these areas. It is now clear that realistic learning problems faced by agents in market environments are often too hard to solve in a classically rational fashion. At the same time, the greatly increased computational power available today allows us to develop and analyze richer market models and to evaluate different learning procedures and algorithms within these models. The danger is that the ease with which complex markets can be simulated could lead to a plethora of models that attempt to explain every known fact about different markets. The first two chapters of this thesis define a principled approach to studying learning in rich models of market environments, and the rest of the thesis provides a proof of concept by demonstrating the applicability of this approach in modeling settings drawn from two different broad domains, financial market microstructure and search theory. In the domain of market microstructure, this thesis extends two important models from the theoretical finance literature.
(cont.) The third chapter introduces an algorithm for setting prices in dealer markets based on the model of Glosten and Milgrom (1985), and produces predictions about the behavior of prices in securities markets. In some cases, these results confirm economic intuitions in a significantly more complex setting (like the existence of a local profit maximum for a monopolistic market-maker) and in others they can be used to provide quantitative guesses for variables such as rates of convergence to efficient market conditions following price jumps that provide insider information. The fourth chapter studies the problem faced by a trader with insider information in Kyle's (1985) model. I show how the insider trading problem can be usefully analyzed from the perspective of reinforcement learning when some important market parameters are unknown, and that the equilibrium behavior of an insider who knows these parameters can be learned by one who does not, but also that the time scale of convergence to the equilibrium behavior may be impractical, and agents with limited time horizons may be better off using approximate algorithms that do not converge to equilibrium behavior. The fifth and sixth chapters relate to search problems. Chapter 5 introduces models for a class of problems in which there is a search "season" prior to hiring or matching, like academic job markets.
(cont.) It solves for expected values in many cases, and studies the difference between a "high information" process where applicants are immediately told when they have been rejected and a "low information" process where employers do not send any signal when they reject an applicant. The most important intuition to emerge from the results is that the relative benefit of the high information process is much greater when applicants do not know their own "attractiveness," which implies that search markets might be able to eliminate inefficiencies effectively by providing good information, and we do not always have to think about redesigning markets as a whole. Chapter 6 studies two-sided search explicitly and introduces a new class of multi-agent learning problems, two-sided bandit problems, that capture the learning and decision problems of agents in matching markets in which agents must learn their preferences. It also empirically studies outcomes under different periodwise matching mechanisms and shows that some basic intuitions about the asymptotic stability of matchings are preserved in the model. For example, when agents are matched in each period using the Gale-Shapley algorithm, asymptotic outcomes are always stable, while a matching mechanism that induces a stopping problem for some agents leads to the lowest probabilities of stability.
(cont.) By contributing to the state of the art in modeling different domains using computational techniques, this thesis demonstrates the success of the approach to modeling complex economic and social systems that is prescribed in the first two chapters.
by Sanmay Das.
Ph.D.
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Bautista, Alderete Guillermo. "Alternative Models to Analyze Market Power and Financial Transmission Rights in Electricity Markets." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/825.
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One of the main concerns with the introduction of competition in the power sector is the strategic behaviour of market participants. Computable models of strategic behaviour are becoming increasingly important to understand the complexities of competition. Such models can help analyze market designs and regulatory policies. In this thesis, further developments on the modelling and analysis of strategic behaviour in electricity markets are presented. This thesis work has been conducted along three research lines. In the first research line, an oligopolistic model of a joint energy and spinning reserve market is formulated to analyze imperfect competition. Strategic behaviour is introduced by means of conjectured functions. With this integrated formulation for imperfect competition, the opportunity cost between generation and spinning reserve has been analytically derived. Besides, inter-temporal and energy constraints, and financial transmission rights are taken into account. Under such considerations, competition in electricity markets is modelled with more realism. The oligopolistic model is formulated as an equilibrium problem in terms of complementarity conditions.
In the second research line, a methodology to screen and mitigate the potential exacerbation of market power due to the ownership of financial transmission rights is presented. Hedging position ratios are computed to quantify the hedging level of financial transmission rights. They are based on the actual impact that each participant has in the energy market, and on the potential impact that it would have with the ownership of financial transmission rights. Thus, hedging position ratios are used to identify the potential gambling positions from the transmission rights bidders, and, therefore, used to prioritize critical positions in the auction for transmission rights.
In the last research line, alternative equilibrium models of markets for financial transmission rights are formulated. The proposed equilibrium framework is more natural and flexible for modelling markets than the classic cost-minimization markets. Different markets for financial transmission rights are modelled, namely: i) forwards, ii) options, and iii) joint forwards and options. Moreover, one-period, multi-period and multi-round markets for forwards are derived. These equilibrium models are proposed to analyze the bidding strategies of market participants. The potential impact of bidders on congestion prices is modelled by means of conjectured transmission price functions.
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Tai, Li-Te David 1966. "Modeling the market dynamics of workstation platform adoption." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80010.
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Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (p. 79).
by Li-Te David Tai.
S.M.
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Duran, Alexander Michael St Clair 1976. "Analysis of online algorithms for resource allocation applied to the stock market." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80061.
Full textAbstract:
Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (p. 84).
by Alexander Michael St. Clair Duran.
S.B.and M.Eng.
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Jinting, Li, Han Jie, and Qiu Zhaofeng. "An Empirical Study on Greenwashing and Consumers' Green Purchase Intention in Chinese Electrical Appliance Market." Thesis, Jönköping University, IHH, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-52815.
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Purpose: This study aims to inform readers whether greenwashing in the Chinese electrical appliance market impacts consumers' green purchase intention. Methods: This study uses theory of planned behaviour as the theoretical basis to construct a structural equation model. An online questionnaire survey was conducted on 521 participants. Results: Our analysis shows that greenwashing has indirectly positively correlated with green purchase intention; green attitude and green perceived value play an intermediary role between greenwashing and green purchase intention. Conclusion: This study concluded that in the Chinese electrical appliance market, greenwashing has positively affected green attitudes and green perceived value, then green attitudes and green perceived value positively affected green purchase intention, and green attitudes positively affected green perceived value. Structure: In this study, after the introduction, the model and related proprietary definitions involved in the research are explained, and hypotheses are proposed. Next are the research methods and research results, and then the discussion of the research results. Finally, the possible directions of future research are discussed.
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Yan, Jun. "Investigation of the impact of demand elasticity and system constraints on electricity market using extended Cournot approach." Doctoral thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/16774.
Full textAbstract:
Includes bibliographical referencesIn today's electricity supply industry, demand side participation is considered an important factor that can influence the market performance and output effectively. Demand elasticity shows the sensitivity of demand side to the market price, and thus can provide potential adjustment of demand in the market. The purpose of this research is to study the impact of demand elasticity on power producers 'market competition output. An analytical model, called "Extended Cournot model" is developed in this thesis based on the classical Cournot model. Through the integration with conjectural variation model, in which power producers consider both the generation and price level, the extended Cournot model can analyze electricity market results under the conditions of different constraints. In the classical Nash Cournot model, capacity withdrawal exists in most cases especially when transmission constraint occurs. In contrast, the newly developed analytical model ensures that demand is always satisfied at all time. Demand elasticity is incorporated directly into the market results calculation instead of using the market clearing price. This approach enables the load demand to directly obtain the market results by tuning its demand elasticity. The intention is to show that demand side should be more encouraged to participate in the market competition. In the classical economic dispatch, the load demand is highly inelastic. From the load curve, there is only a change of physical volume of demand. The demand responsiveness, which is represented by demand elasticity, has been understated. In this thesis, the hypothesis is that demand elasticity and system constraint have critical influence on the power producers' competition results in terms of market clearing price, individual output and profit. Load demand can make use of demand elasticity to affect its final payment to the market. Such ability is expected to be limited in the case where system constraints, i.e. generation limits and transmission limits, exist. For simplicity, a small network and number of power producers are used in this thesis to investigate the effectiveness of the Extended Cournot model. However, this model can be applied to more complex networks with different market environments.
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Frem, Bassam. "The effects of demand uncertainty on strategic gaming in the merit-order electricity pool market." Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=86969.
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In a merit-order electricity pool market, generating companies (Gencos) game with their offered incremental cost to meet the electricity demand and earn bigger market shares and higher profits. However when the demand is treated as a random variable instead of as a known constant, these Genco gaming strategies become more complex.After a brief introduction of electricity markets and gaming, the effects of demand uncertainty on strategic gaming are studied in two parts: (1) Demand modelled as a discrete random variable (2) Demand modelled as a continuous random variable.
In the first part, we proposed an algorithm, the discrete stochastic strategy (DSS) algorithm that generates a strategic set of offers from the perspective of the Gencos' profits. The DSS offers were tested and compared to the deterministic Nash equilibrium (NE) offers based on the predicted demand. This comparison, based on the expected Genco profits, showed the DSS to be a better strategy in a probabilistic sense than the deterministic NE.
In the second part, we presented three gaming strategies: (1) Deterministic NE (2) No-Risk (3) Risk-Taking. The strategies were then tested and their profit performances were compared using two assessment tools: (a) Expected value and standard deviation (b) Inverse cumulative distribution. We concluded that despite yielding higher profit performance under the right conjectures, Risk-Taking strategies are very sensitive to incorrect conjectures on the competitors' gaming decisions. As such, despite its lower profit performance, the No-Risk strategy was deemed preferable.
Dans le marché d'électricité mutuel, gouverné par l'ordre de mérite, les compagnies de production (Gencos) jouent avec leurs coûts différentiels offerts pour gagner une plus grande part du marché ainsi qu'un profit plus élevé, tout en satisfaisant la demande des consommateurs. Toutefois, lorsque la demande est considérée comme une variable aléatoire au lieu d'une constante définie, les stratégies de jeu des Gencos deviennent beaucoup plus difficiles à gérer.
Après une introduction sur les marchés d'électricité et la théorie des jeux, nous étudions les effets de l'incertitude de la demande sur les stratégies de jeu en deux parties : (1) la demande est traitée comme une variable aléatoire discrète (2) la demande est traitée comme une variable aléatoire continue.
Dans la première partie nous proposons un algorithme, l'algorithme de la stratégie stochastique discrète (DSS) qui nous donne un ensemble d'offres stratégiques visant de meilleurs profits pour les Gencos. Les offres calculées par l'algorithme DSS ont été testées et comparées aux offres de l'algorithme d'équilibre Nash (NE) non-stochastique, basé sur la demande prévue. Utilisant les résultats de cette comparaison où on évalue l'espérance mathématique des profits des Gencos, nous avons conclu que la stratégie DSS donne un meilleur rendement stochastique que celle du NE non-stochastique
Dans la deuxième partie de l'étude nous avons présenté trois stratégies de jeu : (1) Le NE non-stochastique (2) Sans-Risque (3) Avec-Risque. Les stratégies ont été testées et leurs performances vis-à-vis des profits des Gencos furent comparées utilisant deux outils d'évaluation : (a) Espérance mathématique et écart-type (b) Fonction de répartition inverse. Nous avons conclus que, malgré leurs performances plus élevées vis-à-vis des profits aves les conjectures correctes, les stratégies Avec-Risque sont très sensibles aux erreurs dans les conjectures à propos des décisions de jeu des concurrents. De ce fait, même avec une performance moins favorable, la stratégie Sans-Risque fut considérée préférable.
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Mak, Chi-hang. "The role of market competition in the performance of the Electrical and Mechanical Services trading fund." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36451411.
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Mak, Chi-hang, and 麥智恆. "The role of market competition in the performance of the Electrical and Mechanical Services trading fund." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B36451411.
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Cardell, Judith Bernitt. "Integrating small scale distributed generation into a deregulated market : control strategies and price feedback." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/10198.
Full textAbstract:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (p. [223]-231.
by Judith Bernitt Cardell.
Ph.D.
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Guery, Edvin. "Designing a plug-and-go solution to expand the electric vehicle market." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-284326.
Full textAbstract:
The transport sector stands for almost a quarter of the carbon emissions released into the atmosphereand is a sector where a lot of work remains to be done to mitigate climate change. To make a changequickly, the vehicles currently traveling the roads will need to be converted from internal combustionengine (ICE) driven vehicle to battery electric vehicles (BEV). The reduction in the use of fossil fuelswill then have an immediately effect, which production of a new BEV does not, as otherwise the oldICE still stays on the road up until taken out of service. With a growth of economy in developingcountries, such as Kenya, comes an expansion of the transport sector. It is very important to limit thenegative environmental effect this may cause. One way to do this is to introduce electric vehicles.Therefore, a field study was held in order to recognise the different demands put on a vehicle in theKenyan national parks, a Toyota Land Cruiser in use of the safari business. From this, a drive draindesign was established. To have a broader span of applicability, it was made with the thought offlexibility to expand production to other models and set a standard to work in the future. To achievethis flexibility, the drive train components were divided into different compartments. Thesecompartments should fit together, forming the entire drive train. When converting different vehicles,different types of compartments can be fitted together to answer its specific needs. Thesecompartments allow for a more modular product and can be easily adaptable when need be. The hopeis that this way of installation can offer services to a wide range of vehicle models without having tomake specific designs for every single one. With a growing number of electric vehicles on the roads,coupled with the high capacity of renewable energy sources found in Kenya, it has the potential tomore become more self-reliant.Transportsektorn står för nästan en fjärdedel av de koldioxidutsläpp som släpps ut i atmosfären ochär en sektor där mycket återstår att göra för att sakta ner klimatförändringarna. För att snabbt kunnase en effekt så måste fordon som för närvarande reser på vägarna omvandlas från förbränningsdrivnatill batteridrivna fordon. Detta skulle ge en omedelbar minskning utav fossila bränslen, vilkenproduktion utav nya eldrivna fordon inte gör, då de fossildrivna fordonen I sådana fall skulle fortsättasatt köras fram till dess att de tas ur funktion. Med den ekonomiska tillväxten som sker I ett flertalutvecklingsländer, likt Kenya, så tillkommer också en expansion utav transportsektorn. Det är viktigtatt minimera de negativa effekterna som detta har på klimatet. Ett sätt att göra detta är medanvändning utav eldrivna fordon. Därför har en fältstudie genomfördes för att identifiera de olikakraven som ställs på ett fordon i de kenyanska nationalparkerna, en Toyota Land Cruiser I detta fall,som används inom safariindustrin. Från detta så designades en elektrisk drivlina. Men för att ha ettstörre tillämpningsområde så ansågs flexibilitet vara viktigt för att kunna utvidga produktionen tillandra modeller och sätta en standard för framtida produktion. För att uppnå denna flexibilitet deladesdrivlinans olika komponenterna upp i olika moduler. Dessa moduler passar samman och bildartillsammans hela drivlinan. Vid ombyggnad av olika fordon kan olika typer av moduler monteras ihopför att tillgodose dess specifika behov. Dessa moduler möjliggör en mer modulär produkt och kan lättanpassas vid behov. Förhoppningen är att detta sätt att installera kan erbjuda tjänster till ett brettutbud av fordonsmodeller utan att behöva göra en specifik lösning för varje enskild modell. Men enökning utav eldrivna fordon på vägarna och med en stor källa utav förnybara resurser så ser Kenya utatt ha vad som krävs att bli självförsörjande.
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Olsson, Magnus. "Optimal regulating power market bidding strategies in hydropower systems." Licentiate thesis, Stockholm :, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-596.
Full text
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Maida, Elisabeth M. (Elisabeth Marigo). "The regulation of internet interconnection : assessing network market power." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/79345.
Full textAbstract:
Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 59-64).
Interconnection agreements in the telecommunications industry have always been constrained by regulation. Internet interconnection has not received the same level of scrutiny. Recent debates regarding proposed mergers, network neutrality, Internet peering, and last mile competition have generated much discussion about whether Internet interconnection regulation is warranted. In order to determine whether such regulation is necessary, policymakers need appropriate metrics to help gauge a network provider's market power. Since Internet interconnection agreements are typically not published publicly, policymakers must instead rely on proxy metrics and inferred interconnection relationships. Alessio D'Ignazio and Emanuele Giovannetti have attempted to address this challenge by proposing a standard set of metrics that are based on and assessed using network topology data. They suggest two metrics, referred to as customer cone and betweenness, as proxies for market size and market power. This thesis focuses on the efficacy of the proposed customer cone and betweenness metrics as proxies for network market size and market power.
by Elisabeth M. Maida.
S.M.
S.M.in Technology and Policy
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Fu, Hao. "Market-oriented micro virtual power prosumers operations in distribution system operator framework." Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7516/.
Full textAbstract:
As the European Union is on track to meet its 2020 energy targets on raising the share of renewable energy and increasing the efficiency in the energy consumption, considerable attention has been given to the integration of distributed energy resources (DERs) into the restructured distribution system. This thesis proposes market-oriented operations of micro virtual power prosumers (J.lVPPs) in the distribution system operator framework, in which the J.lVPPs evolve from home-oriented energy management systems to price-taking prosumers and to price-making prosumers. Considering the diversity of the DERs installed in the residential sector, a configurable J.l VPP is proposed first to deliver multiple energy services using a fuzzy logic-based generic algorithm. By responding to the retail price dynamics and applying load control, the J.lVPP achieves considerable electricity bill savings, active utilisation of energy storage system and fast return on investment. As the J.lVPPs enter the distribution system market, they are modelled as price-takers in a two-settlement market first and a chance-constrained formulation is proposed to derive the bidding strategies. The obtained strategy demonstrates its ability to bring the J.l VPP maximum profit based on different composition of DERs and to maintain adequate supply capacity to meet the demand considering the volatile renewable generation and load forecast. Given the non-cooperative nature of the actual market, the J.l VPPs are transformed into price-makers and their market behaviours are studied in the context of electricity market equilibrium models. The resulted equilibrium problems with equilibrium constraints (EPEC) are presented and solved using a novel application of coevolutionary approach. Compared with the roles of home-oriented energy management systems and price-taking prosumers, the J.lVPPs as price making prosumers have an improved utilisation rate of the installed DER capacity and a guaranteed profit from participating in the distribution system market.
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Caley, Jeffrey Allan. "A Survey of Systems for Predicting Stock Market Movements, Combining Market Indicators and Machine Learning Classifiers." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/2001.
Full textAbstract:
In this work, we propose and investigate a series of methods to predict stock market movements. These methods use stock market technical and macroeconomic indicators as inputs into different machine learning classifiers. The objective is to survey existing domain knowledge, and combine multiple techniques into one method to predict daily market movements for stocks. Approaches using nearest neighbor classification, support vector machine classification, K-means classification, principal component analysis and genetic algorithms for feature reduction and redefining the classification rule were explored. Ten stocks, 9 companies and 1 index, were used to evaluate each iteration of the trading method. The classification rate, modified Sharpe ratio and profit gained over the test period is used to evaluate each strategy. The findings showed nearest neighbor classification using genetic algorithm input feature reduction produced the best results, achieving higher profits than buy-and-hold for a majority of the companies.