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Artificial Neural Networks in Option Pricing
Vach, Dominik ; Gapko, Petr (advisor) ; Červinka, Michal (referee)
This thesis examines the application of neural networks in the context of option pricing. Throughout the thesis, different architecture choices and prediction parameters are tested and compared in order to achieve better performance and higher accuracy in option valuation. Two different volatility forecast mechanisms are used to compare neural networks performance with Black Scholes parametric model. Moreover, the performance of a neural network is compared also to more advanced modular neural networks. A new technique of adding rational prediction assumptions to neural network prediction is tested and the thesis shows the importance of adding virtual options fulfilling these assumptions in order to achieve better training of the neural network. This method comes out to increase the prediction power of the network significantly. The thesis also shows the neural network prediction outperforms the traditional parametric methods. The size and number of hidden layers in a neural network is tested with an emphasis to provide a benchmark and a structured way how to choose neural network parameters for future applications in option pricing. JEL Classification C13, C14, G13 Keywords Option pricing, Neural networks, Modular neu- ral networks, S&P500 index options Author's e-mail vach.dominik@gmail.com...
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Analysis of Term Structures in High Frequencies
Nedvěd, Adam ; Baruník, Jozef (advisor) ; Červinka, Michal (referee)
This thesis represents an in-depth empirical study of the dependence structures within the term structure of interest rates. Firstly, a comprehensive overview of term structure modelling literature and methods is provided together with a summary of theoretical notions regarding the use of high-frequency data and spectral analysis. Contrary to most studies, the frequency-domain approach is employed, with a special focus on dependency across various quantiles of the joint distribution of the term structure. The main results are obtained using the quantile cross-spectral analysis, a new robust and non-parametric method allowing to uncover dependence structures in quantiles of the joint distribution of multivariate time series. The results are estimated using a dataset consisting of 15 years worth of high-frequency tick-by-tick time series of US Treasury futures. Complex dependence structures are revealed showing signs of both cyclicity and dependence in various parts of the joint distribution of the term structure in the frequency domain. JEL Classification C49, C55, C58, E43, G12, G13 Keywords term structure of interest rates, yield curves, high-frequency analysis, spectral analysis, inter- est rate futures Author's e-mail adam.nedved@fsv.cuni.cz Supervisor's e-mail barunik@fsv.cuni.cz
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The Facility Location Problem for an Alternative Delivery Service
Vaněk, Petr ; Červinka, Michal (advisor) ; Habibi, Arash (referee)
The main intention of the bachelor thesis is to introduce all necessary theory to under- stand and apply the facility location problem for an alternative delivery service. Solving the facility location problem we are able to find optimal warehouse locations to minimize transportation costs from a firm to customers. Our attention is focused on an alternative delivery service which is slowly becoming to be taken seriously in logistic disciplines be- cause many companies are trying to apply drones or robots for shipping goods. The first part of this thesis deals with an important theoretical background needed to understand the facility location problem. Microeconomic view of the problem is presented, basic knowledge of mathematical programming with algorithms is explained and the facility location problem itself is defined. Moreover, each step of the branch & bound algorithm for the facility location problem is explained on an example from Prague. In the practical part of the thesis, we solve a real problem for the Czech company which would like to im- plement a drone delivery service in Prague. Finally, we discuss future technical progress and its impacts on autonomous delivery service, legislative and privacy problems with a drone delivery system in Prague and other possible usage of autonomous vehicles in...
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The Effect of Litigation Risk on Earnings Management in the Proximity to Debt Covenant Violation
Britskiy, Andrey ; Novák, Jiří (advisor) ; Červinka, Michal (referee)
This bachelor thesis aims to establish a relationship between earnings management in proximity to debt covenant violation and the presence of litigation risk. Central testable concept is Watts and Zimmerman (1990) debt covenant hypothesis according to which managers tend to manipulate earnings to reduce the possibility of violation of their company's debt agreement. This setting allows investigating whether the risk of litigation is an effective regulatory mechanism which improves the contracting usefulness of accounting numbers and better align the interests between creditors and company managers, thus making debt covenants more reliable as monitoring mechanisms. Due to inconclusive results, this thesis was unable to establish whether the threat of litigation can discipline managerial reporting practices and deter misreporting for the companies with substantial debt covenant incentives.
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Comparison of continuous and frequent batch auctions
Gottlieb, Oskar ; Šmíd, Martin (advisor) ; Červinka, Michal (referee)
We simulate a fragmented market and study three types of agents and their interactions in continuous trading and frequent-batch auctions. We model the markets using the agent-based modeling approach. There are two exchanges on which one asset is being traded by zero-intelligence (ZI) traders, market makers and a latency arbitrageur. The former two agents are marked as slow traders, the arbitrageur is a fast trader - fast trader has perfect information about the market, slow traders are dependent on the (possibly lagged) NBBO information provided by the regulator. Our main metric is the surplus of ZI traders, we also measure other market's characteristics. We then simulate the market for different delays of the NBBO delay and we find that under certain conditions and until certain length, the batch auctions are beneficial to ZI traders, as they reduce the advantage and therefore the profit of the fast trader.
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Efficiency of Prague Stock Exchange Market using Markov Chains
Kratochvíl, Jonáš ; Červinka, Michal (advisor) ; Hausenblas, Václav (referee)
The main intention of this thesis is to analyze the weak form efficiency of Prague Stock Exchange. We conduct our empirical analysis on daily, weekly and monthly return data of the PX index collected in time period 1994-2017. The theory of Markov chains is employed to decide whether the index returns follow a random walk, the evidence of weak form efficiency. Bayesian Informa- tion Criterion is used to establish the optimal order of the Markov chain, which is in turn tested against the order 0 by Likelihood ratio criterion. The model assumptions of time homogeneity, irreducibility and aperiodicity of transition probability matrix are validated. We reject the weak form efficiency for daily index returns and establish its optimal Markov chain order to be 1. The weak form efficiency is not rejected for weekly and monthly index returns so is the as- sumption of time homogeneity for the whole time period 1994-2017. We propose further analysis of daily returns for time period 2006-2017, which exploits the fact of the weak form inefficiency. Discussion of results and related literature is provided as well as the presentation of all contemplated methods. 1
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Optimization of oil production by OPEC countries
Pilátová, Markéta ; Červinka, Michal (advisor) ; Rečka, Lukáš (referee)
Almost 4 years of low oil prices and excess supply call the relevance of OPEC for current oil market into question. Therefore to investigate its role, this thesis examines the optimum oil production of individual OPEC countries accenting the consequent profit. Firstly, Cournot's model is employed to find equilibrium price and output on the oligopolistic market. Secondly, model considering OPEC and Russia as the Stackelberg leader with competitors forming oligopolistic fringe helps to uncover the potential of the recent car- tel of OPEC and Russia. In both models, data from the year 2016 with different levels of elasticity ranging from -0.1 to -0.2 are utilized. Our re- search suggests that all OPEC members could have increased their profits by forming a non-cooperative oligopolistic market, where prices would reach up to 81.7 USD/bbl. Moreover, as a part of the cartel with Russia, OPEC could increase its joint profits by almost 27 % compared to the oligopolistic market, benefiting from coordinated output cuts followed by a steep growth in price. Thus we can conclude that either OPEC lost its power over the oil market or attempted to maintain its market share and drive higher-cost producers out of the market.
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News Feed Classifications to Improve Volatility Predictions
Pogodina, Ksenia ; Šopov, Boril (advisor) ; Červinka, Michal (referee)
This thesis analyzes various text classification techniques in order to assess whether the knowledge of published news articles about selected companies can improve its' stock return volatility modelling and forecasting. We examine the content of the textual news releases and derive the news sentiment (po larity and strength) employing three different approaches: supervised machine learning Naive Bayes algorithm, lexicon-based as a representative of linguistic approach and hybrid Naive Bayes. In hybrid Naive Bayes we consider only the words contained in the specific lexicon rather than whole set of words from the article. For the lexicon-based approach we used independently two lexicons one with binary another with multiclass labels. The training set for the Naive Bayes was labeled by the author. When comparing the classifiers from the machine learning approach we can conclude that all of them performed similarly with a slight advantage of the hybrid Naive Bayes combined with multiclass lexicon. The resulting quantitative data in form of sentiment scores will be then incorpo rated into GARCH volatility modelling. The findings suggest that information contained in news feeds does bring an additional explanatory power to tradi tional GARCH model and is able to improve it's forecast. On the...
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Alternative Formulation of Pay-as-clear Auction in Electricity Markets
Aussel, D. ; Červinka, Michal ; Henrion, R. ; Pištěk, Miroslav
In widely used formulation of pay-as-clear electricity market the clearing price is given by the Lagrange multiplier of the demand sat- isfaction constraint in the problem of the Independent System Operator (ISO). Following this idea, one may usually calculate the market clearing\nprice analytically even for problems of higher dimensions. However, the economic interpretation of such a market setting is in question, since the minimized criterion does not correspond neither to the cost of production nor to the overall payment of consumers. This observation motivated us\nto propose an alternative clearing mechanism where the total payment of consumers is explicitly minimized. We show existence and uniqueness of the clearing price in such a setting.
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Game Theory Approach to Hostile Takeovers
Tuček, Lukáš ; Červinka, Michal (advisor) ; Čornanič, Aleš (referee)
This bachelor thesis investigates the field of hostile takeovers predominantly from the perspective of the management of the target company. Particular emphasis is placed on review of the defense strategies against hostile takeovers and ways in which they might be abused by the management. This thesis attempts to formulate a game-theoretic model describing the process of a hostile takeover as an extensive-form game with perfect in- formation. Payoff functions for the game further in the thesis computed as Nash equilibria of bargaining problem with the current state of the game as a base for the utility gains. We then briefly discuss the implied relationship among the raider, management and the shareholders. JEL Classification C7; C72; G34 Keywords hostile takeover; game in extensive form; defense strategy
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