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31	能源與貴金屬連結及利率連結之結構型商品評價與分析─以中國銀行結構性存款為例 / The Pricing and Analysis of Commodities-Linked and Interest Rate-Linked Structured Products: The Case Study of Structured Deposits Launched by Bank of China 蔡昌甫, Tsai,Chang Fu Unknown Date (has links) 在過去二到三年之中，能源、金屬、軟性商品等原物料價格漲勢強勁，成為市場上最炙手可熱的商品。然而，原物料價格漲升為全球帶來了通膨隱憂，世界各國紛紛採用各種貨幣政策和財政政策試圖緩解通膨壓力。其中，利率政策即是相當重要的一環。在這樣的背景之下，是否對於能源、貴金屬和利率衍生性商品的設計和定價上產生影響，值得進一步檢視。因此，本論文選擇以中國大陸的原油與黃金連結複合式選擇權，以及利率（HIBOR）連結可贖回每日區間計息等兩種結構性存款作為研究個案，以財務工程的理論模型為中國銀行的金融創新產品作評價與分析。在原油與黃金連結複合式選擇權部分，分別假設金價和油價服從幾何布朗運動（Geometric Brownian Motion）推導出封閉解，以及Schwartz的一因子均數回歸模型，採蒙地卡羅模擬法模擬標的資產之價格路徑並以之估算商品理論價值和發行機構利潤，之後則就避險參數和商品預期收益率作分析。在利率連結可贖回每日區間計息結構性存款部分，由於具有發行機構可提前贖回的特性，本論文採用LIBOR市場模型（BGM Model）為評價基礎，先利用市場報價資訊計算期初遠期利率及進行參數校準，再以蒙地卡羅模擬法模擬遠期利率路徑，最後以Longstaff and Schwartz（2001）提出的最小平方蒙地卡羅法（LSM）計算商品理論價值和發行機構利潤。除估算商品理論價值以檢視中國銀行的商品定價合理性之外，本文也針對中國大陸的外匯和利率政策對金融機構在商品設計方面的影響作分析，最後則分別就財務工程與金融創新以及總體政策與金融市場兩方面提出結論與建議，以供各界參酌。 / The prices of physical commodities have risen a lot and led to pressure of inflation for several years. Many countries over the world have tried hard to tackle inflation threat with monetary and fiscal policies. Under this circumstance, the design and pricing of structured products should be affected. Therefore, the oil and gold-linked and interest rate-linked structured deposits launched by Bank of China are selected to be the case study in this thesis. Prices of the underlying assets are assumed to follow Geometric Brownian Motion, and the close-form solution of the oil and gold-linked structured deposit embedded with compound options is derived. Moreover, Schwartz’s One-Factor Mean Reversion Model is adopted to derive the fair value by simulation. In addition to the fair value and issuer’s profit, the expected rate of return, hedge parameters (Greeks) and model difference are presented in this thesis. As for the interest rate-linked Callable Daily Range Accrual Deposit, the thesis presents the steps of pricing by simulation. LIBOR Market Model (BGM Model) is adopted to derive the fair value of Callable Range Deposit with Least Squares Monte Carlo approach. Besides, the design and pricing of structured products are actually influenced by those policies in relation to interest rates and currencies adopted by government of Mainland China. The influence is discussed in the thesis as well. Eventually, the conclusions and suggestions are made with respect to macroeconomic policy and financial market as well as financial innovation. 複合式選擇權每日區間計息結構性存款幾何布朗運動均數回歸 LIBOR市場模型最小平方蒙地卡羅法 compound option range accrual deposit BGM Model Geometric Brownian Motion Mean Reversion LIBOR Market Model Least Squares Monte Carlo
32	[en] RISK ANALYSIS IN A PORTFOLIO OF COMMODITIES: A CASE STUDY / [pt] ANÁLISE DE RISCOS NUM PORTFÓLIO DE COMMODITIES: UM ESTUDO DE CASO LUCIANA SCHMID BLATTER MOREIRA 23 March 2015 (has links) [pt] Um dos principais desafios no mercado financeiro é simular preços mantendo a estrutura de correlação entre os inúmeros ativos de um portfólio. Análise de Componentes Principais emerge como uma solução para este último problema. Além disso, dada a incerteza presente nos mercados de commodities de derivados de petróleo, o investidor quer proteger seus ativos de perdas potenciais. Como uma alternativa a esse problema, a otimização de várias medidas de risco, como Value-at-risk, Conditional Value-at-risk e medida Ômega, são ferramentas financeiras importantes. Além disso, o backtest é amplamente utilizado para validar e analisar o desempenho do método proposto. Nesta dissertação, trabalharemos com um portfólio de commodities de petróleo. Vamos unir diferentes técnicas e propor uma nova metodologia que consiste na diminuição da dimensão do portfólio proposto. O passo seguinte é simular os preços dos ativos na carteira e, em seguida, otimizar a alocação do portfólio de commodities de derivados do petróleo. Finalmente, vamos usar técnicas de backtest, a fim de validar nosso método. / [en] One of the main challenges in the financial market is to simulate prices keeping the correlation structure among numerous assets. Principal Component Analysis emerges as solution to the latter problem. Also, given the uncertainty present in commodities markets, an investor wants to protect his/her assets from potential losses, so as an alternative, the optimization of various risk measures, such as Value-at-risk, Conditional Value-at-risk and Omega Ratio, are important financial tools. Additionally, the backtest is widely used to validate and analyze the performance of the proposed methodology. In this dissertation, we will work with a portfolio of oil commodities. We will put together different techniques and propose a new methodology that consists in the (potentially) decrease the dimension of the proposed portfolio. The following step is to simulate the prices of the assets in the portfolio and then optimize the allocation of the portfolio of oil commodities. Finally, we will use backtest techniques in order to validate our method. [pt] OTIMIZACAO [en] OPTIMIZATION [pt] GARCH [en] GARCH [pt] VALUE-AT-RISK - VAR [en] VALUE-AT-RISK - VAR [pt] MOVIMENTO GEOMETRICO BROWNIANO [en] GEOMETRIC BROWNIAN MOTION [pt] ANALISE DE COMPONENTES PRINCIPAIS [en] PRINCIPAL COMPONENT ANALYSIS [pt] CONDITIONAL VALUE-AT-RISK - CVAR [en] CONDITIONAL VALUE-AT-RISK - CVAR [pt] MEDIDA OMEGA [en] OMEGA THEORY [pt] BACKTESTING TECHNIQUES [en] BACKTESTING TECHNIQUES
33	Optimization of production allocation under price uncertainty : relating price model assumptions to decisions Bukhari, Abdulwahab Abdullatif 05 October 2011 (has links) Allocating production volumes across a portfolio of producing assets is a complex optimization problem. Each producing asset possesses different technical attributes (e.g. crude type), facility constraints, and costs. In addition, there are corporate objectives and constraints (e.g. contract delivery requirements). While complex, such a problem can be specified and solved using conventional deterministic optimization methods. However, there is often uncertainty in many of the inputs, and in these cases the appropriate approach is neither obvious nor straightforward. One of the major uncertainties in the oil and gas industry is the commodity price assumption(s). This paper investigates this problem in three major sections: (1) We specify an integrated stochastic optimization model that solves for the optimal production allocation for a portfolio of producing assets when there is uncertainty in commodity prices, (2) We then compare the solutions that result when different price models are used, and (3) We perform a value of information analysis to estimate the value of more accurate price models. The results show that the optimum production allocation is a function of the price model assumptions. However, the differences between models are minor, and thus the value of choosing the “correct” price model, or similarly of estimating a more accurate model, is small. This work falls in the emerging research area of decision-oriented assessments of information value. / text Oil price model Geometric Brownian Motion Mean Reversion with jumps Stochastic process Decision analysis Risk analysis Value of information VOI Optimization Uncertainty Portfolio optimization Crude type Optimization under uncertainty Risk solver platform Gams Linear programming Non-linear programming Operations research Risk Oil industry Petroleum management
34	Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement El-Khatib, Mayar January 2010 (has links) While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond. highway development decision making under uncertainty real options jump processes infinitely divisible distributions Lévy processes measure theory characteristic function characteristic exponent Lévy jump measure probability measure cádlág stochastic process Wiener process Poisson process compound Poisson process finite activity models jump diffusion models Merton model Gaussian jump process Kou model double exponential jump process leptokurtic volatility smile infinite activity models pure jumps process generalized hyperbolic model modified Bessel function negative inverse Gaussian model geometric Brownian motion model log-normal distribution model normality assumption heavy-tailed distribution asymmetric distribution quantile-quantile plot Rydberg algorithm parameter calibration moments cummulants sum of squares Monte Carlo simulation least-squares regression backward dynamic programming discrete-time Markov chain land price traffic demand highway service quality index data collection traffic volume Annual Average Daily Traffic Ontario Ministry of Transportation Land Registry Office Freedom of Information Act seasonality value of transportation types of transportation systems importance of highway systems cost of wrong decisions monetary cost private sector cost human cost land expropriation environmental cost irreversibility cost factor time cost factor political cost factor opportunity cost opportunity cost of wrong decisions economic cost of wrong decisions economic cost of mis-estimation economic profit of wrong decisions cost of inaction price of making right decisions scope of decisions rehabilitation decision land acquisition decision expansion decision uncertainty modeling land acquisition cost expropriation cost construction cost material cost Montréal-Mirabel International Airport Pickering Airport 407 Express Toll Route Highway 407 Statistics
35	Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement El-Khatib, Mayar January 2010 (has links) While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond. highway development decision making under uncertainty real options jump processes infinitely divisible distributions Lévy processes measure theory characteristic function characteristic exponent Lévy jump measure probability measure cádlág stochastic process Wiener process Poisson process compound Poisson process finite activity models jump diffusion models Merton model Gaussian jump process Kou model double exponential jump process leptokurtic volatility smile infinite activity models pure jumps process generalized hyperbolic model modified Bessel function negative inverse Gaussian model geometric Brownian motion model log-normal distribution model normality assumption heavy-tailed distribution asymmetric distribution quantile-quantile plot Rydberg algorithm parameter calibration moments cummulants sum of squares Monte Carlo simulation least-squares regression backward dynamic programming discrete-time Markov chain land price traffic demand highway service quality index data collection traffic volume Annual Average Daily Traffic Ontario Ministry of Transportation Land Registry Office Freedom of Information Act seasonality value of transportation types of transportation systems importance of highway systems cost of wrong decisions monetary cost private sector cost human cost land expropriation environmental cost irreversibility cost factor time cost factor political cost factor opportunity cost opportunity cost of wrong decisions economic cost of wrong decisions economic cost of mis-estimation economic profit of wrong decisions cost of inaction price of making right decisions scope of decisions rehabilitation decision land acquisition decision expansion decision uncertainty modeling land acquisition cost expropriation cost construction cost material cost Montréal-Mirabel International Airport Pickering Airport 407 Express Toll Route Highway 407 Statistics

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