Essays about: "pricing algorithms"
Showing result 11 - 15 of 31 essays containing the words pricing algorithms.
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11. Risk Measurement and Performance Attribution for IRS Portfolios Using a Generalized Optimization Method for Term Structure Estimation
University essay from Linköpings universitet/ProduktionsekonomiAbstract : With the substantial size of the interest rate markets, the importance of accurate pricing, risk measurement and performance attribution can not be understated. However, the models used on the markets often have underlying issues with capturing the market's fundamental behavior. READ MORE
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12. Option Pricing using Artificial Neural Networks
University essay from Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisationAbstract : Neural networks have an increasingly important role in the financial market, by offering a solution to stationarity and non-linearity whilst also providing robustness and predictive power. Options and option pricing are a fundamental area of interest in the daily activities of investment banks, hedge funds and trading firms in the financial market. READ MORE
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13. Feature-Based Dynamic Pricing of Airline Ancillaries
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Airline ancillary revenue has increased substantially over the past years. Despite the increasing attention, its pricing models have mostly progressed slowly and remained simple. In this work we apply dynamic pricing models for the purpose of maximizing airline ancillary revenue. Our contributions in this thesis are threefold. READ MORE
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14. Commodity Futures Pricing Via Machine Learning: An Empirical Approach
University essay from Handelshögskolan i Stockholm/Institutionen för finansiell ekonomiAbstract : The goal of this thesis is to use established methodologies in the field of machine learning in finance to extend the list of current applications to commodity futures, reviewing and refining the established empirical approaches to return forecasting and hyperparameter optimization. We thus investigate the out of sample predictive accuracy of tree-based machine learning (ML) techniques and neural networks applied to monthly commodity futures returns, relying on conventional regression and classification accuracy metrics. READ MORE
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15. Tacit collusion with deep multi-agent reinforcement learning
University essay from Handelshögskolan i Stockholm/Institutionen för nationalekonomiAbstract : Automatic pricing now attracts the attention of competition authorities following recent machine learning developments. In particular, previous research shows that the Q-learning algorithm can reach collusive outcomes despite receiving only minimal human intervention. READ MORE
