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"The monograph addresses a problem of stochastic analysis based on the uncertainty assessment by simulation and application of this method in ecology and steel industry under uncertainty. "

"This is the expanded second edition of a successful textbook that provides a broad introduction to important areas of stochastic modelling. The original text was developed from lecture notes for a one-semester course for third-year science and actuarial students at the University of Melbourne. It reviewed the basics of probability theory and then covered the following topics: Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory, basic renewal theory, elements of time series and simulation. The present edition adds new chapters on elements of stochastic calculus and introductory mathematical finance that logically complement the topics chosen for the first edition. This makes the book suitable for a larger variety of university courses presenting the fundamentals of modern stochastic modelling. Instead of rigorous proofs we often give only sketches of the arguments, with indications as to why a particular result holds and also how it is related to other results, and illustrate them by examples. Wherever possible, the book includes references to more specialised texts on respective topics that contain both proofs and more advanced material.Readership: Advanced undergraduates, graduate students, lecturers and researchers in mathematics, statistics, actuarial sciences and economics."

"[Stochastic Optimal Control (SOC), a mathematical theory concerned with minimizing a cost (or maximizing a payout) pertaining to a controlled dynamic process under uncertainty—has proven incredibly helpful to understanding and predicting debt crises and evaluating proposed financial regulation and risk management. Stochastic Optimal Control and the U.S. Financial Debt Crisis analyzes SOC in relation to the 2008 U.S. financial crisis, and offers a detailed framework depicting why such a methodology is best suited for reducing financial risk and addressing key regulatory issues. Topics discussed include the inadequacies of the current approaches underlying financial regulations, the use of SOC to explain debt crises and superiority over existing approaches to regulation, and the domestic and international applications of SOC to financial crises. , Stochastic Optimal Control (SOC), a mathematical theory concerned with minimizing a cost (or maximizing a payout) pertaining to a controlled dynamic process under uncertainty—has proven incredibly helpful to understanding and predicting debt crises and evaluating proposed financial regulation and risk management. Stochastic Optimal Control and the U.S. Financial Debt Crisis analyzes SOC in relation to the 2008 U.S. financial crisis, and offers a detailed framework depicting why such a methodology is best suited for reducing financial risk and addressing key regulatory issues. Topics discussed include the inadequacies of the current approaches underlying financial regulations, the use of SOC to explain debt crises and superiority over existing approaches to regulation, and the domestic and international applications of SOC to financial crises. ]"

"Penentuan harga opsi (option pricing) memegang peranan penting pada perdagangan saham agar dapat membuat keputusan yang dapat memperoleh keuntungan yang optimal baik untuk pembeli maupun penjual opsi. Salah satu model pasar yang dapat digunakan pada option pricing ini adalah model Black-Scholes dengan volatilitas stokastik dari harga saham yang berdasarkan proses Ornstein-Uhlenbeck. Model ini digunakan agar dapat menggambarkan sifat dari volatilitas yang ada pada pasar saham sesungguhnya. Untuk mengaproksimasi harga opsi call Eropa berdasarkan model tersebut, digunakan metode Euler-Maruyama. Diteliti juga laju konvergensi dari aproksimasi tersebut. Kemudian, dilakukan analisis terhadap hasil simulasi harga opsi menggunakan beberapa fungsi volatilitas harga saham yang berdasarkan proses Ornstein-Uhlenbeck. Hasil simulasi menunjukkan bahwa pemilihan fungsi volatilitas pada model pasar perlu dipertimbangkan lebih lanjut karena berkaitan dengan konsep mean-reversion yang diharapkan dari volatilitas pasar saham di dunia nyata.

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Option pricing holds a crucial role in trading to make decision that would lead to the best benefit for both the option buyer and seller. The market model that could be used for option pricing is Black-Scholes model with stochastic stock prices volatility driven by Ornstein-Uhlenbeck process. This model is used in order to reflect the properties of the volatility in the real market. In this short thesis, Euler-Maruyama method is used to approximate the price of the European call option based on that model. The rate of convergence of the approximation is also determined. The simulation of the option price approximation is performed with some Ornstein-Uhlenbeck-driven volatility functions for the stock price model. The result of the simulation shows that the choice of the volatility function for the stock price model needs to be scrutinized since it is related to the mean-reversion concept that is expected from the stock prices volatility in real market."

"Mathematical finance requires the use of advanced mathematical techniques drawn from the theory of probability, stochastic processes and stochastic differential equations. These areas are generally introduced and developed at an abstract level, making it problematic when applying these techniques to practical issues in finance"

"Tesis ini melakukan pengukuran efisiensi Unit Usaha Syariah Bank Umum Pemerintah Nasional dan Bank Umum Swasta Nasional diperoleh dengan mengestimasi fungsi profit perbankan dan menghitung rasio BOPO. Secara teoritis, dengan mengestimasi fungsi profit, dapat diukur profit maksimum yang seharusnya diperoleh dari hasil input dan output yang digunakan. Dari hasil estimasi fungsi profit tersebut, kemudian dihitung error term dari fungsi tersebut dengan menggunakan metode Stochastic Frontier Analysis (SFA). Kemudian hasil tersebut dapat menggambarkan kondisi Unit Usaha Syariah Bank Umum Pemerintah Nasional dan Bank Umum Swasta Nasional. Hasil penelitian menunjukkan bahwa rata-rata efisiensi Unit Usaha Syariah dari Bank Umum Pemerintah Nasional dan Bank Umum Swasta Nasional yang diukur dari metode SFA maupun BOPO untuk periode 2005 sampai 2007 tidak berbeda secara signifikan.

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This research performs efficiency measurement of Islamic Banking Units (Unit Usaha Syariah) of National Public Commercial Banks and National Private Commercial Banks by estimating banking profit function and Operating Expenses to Operating Income Ratio (BOPO). Theoretically, the maximum profit, which is essentially obtained from the input and output employed, can be measured by estimating the profit function. After getting the result of the profit function estimation, its error terms are calculated by using Stochastic Frontier Analysis (SFA). The outcome will then be able to describe the condition of Islamic Banking Units of National Public Commercial Banks and National Private Commercial Banks. The result of this research shows that the efficiency average of Islamic Banking Units of National Public Commercial Banks and National Private Commercial Banks measured by using SFA method and Operating Expenses to Operating Income Ratio taken from 2005 to 2007 is not significantly different."

"This volume sharpens our picture of the applications of conformal invariance, introducing non-local observables such as loops and interfaces before explaining how they arise in specific physical contexts. It then shows how to use conformal invariance to determine their properties. Moving on to cover key conceptual developments in conformal invariance, the book devotes much of its space to stochastic Loewner evolution (SLE), detailing SLE’s conceptual foundations as well as extensive numerical tests. The chapters then elucidate SLE’s use in geometric phase transitions such as percolation or polymer systems, paying particular attention to surface effects. "

"Mathematical methods based on the theory of stochastic processes have long been used effectively in telephone traffic modeling. Today's modern network traffic, which is distinctly different from traditional voice traffic, generates challenging mathematical and statistical problems. Stochastic Modeling in Broadband Communications Systems provides a concise overview of stochastic models and mathematical techniques for solving these problems and enhances readers' overall understanding of communication systems. The book also presents an excellent introduction, particularly for students and professionals in probability and applied mathematics, to a huge area of interesting problems and models arising from modern developments in broadband channel transmission systems. The author's clear presentation is based on sound mathematical reasoning, and he has taken special care to make the material easily accessible to readers unable to devote hours of time on rigorous mathematical detail and generality. Topics include models ranging over different time scales of calls, bursts, and cells; different protocol layers for transport, control, and applications; mechanisms for queuing, collisions, delay, and loss; and the effects of buffering, retransmission, multiplexing, and traffic control. Comprehensive exercises are provided at the end of each chapter."