Essays about: "derivative pricing"
Showing result 1 - 5 of 37 essays containing the words derivative pricing.
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1. Deep learning exotic derivatives
University essay from Uppsala universitet/Avdelningen för systemteknikAbstract : Monte Carlo methods in derivative pricing are computationally expensive, in particular for evaluating models partial derivatives with regard to inputs. This research proposes the use of deep learning to approximate such valuation models for highly exotic derivatives, using automatic differentiation to evaluate input sensitivities. READ MORE
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2. Deep Learning and the Heston Model:Calibration & Hedging
University essay from Göteborgs universitet/Institutionen för nationalekonomi med statistikAbstract : The computational speedup of computers has been one of the de ning characteristicsof the 21st century. This has enabled very complex numerical methods for solving existingproblems. As a result, one area that has seen an extraordinary rise in popularity over the lastdecade is what is called deep learning. READ MORE
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3. Valuation of Additional Tier-1 Contingent Convertible Bonds (AT1 CoCo) : Modelling trigger risk in a practical investment setting
University essay from KTH/Matematisk statistikAbstract : Contingent convertible bonds (often referred to as CoCo bonds, or simply CoCos) are a relatively new financial instrument designed to absorb unexpected losses. This instrument became increasingly more common after the financial crisis of 2008, as a way to decrease the risk of insolvency among banks and other financial institutions. READ MORE
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4. Valuation of Additional Tier-1 Contingent Convertible Bonds (AT1 CoCo) : Accounting for Extension Risk
University essay from KTH/Matematisk statistikAbstract : The investment and financing instrument AT1, or Contingent Convertible bond, has become popular in the post-crisis capital markets, prompting interest and research in the academic world. The instrument's debt definition but equity boosting properties makes it rather extraordinary, and its stochastic features makes multiple mathematical valuation methodologies relevant, especially with regard to the risk of extending the call date of the instrument. READ MORE
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5. Numerical solution for derivative models using finite difference methods and how this can be used with Monte Carlo simulation
University essay from Lunds universitet/Matematisk statistikAbstract : Derivative models often come in the form of stochastic differential equations. From these equations a partial differential equation (PDE) can be derived. By discretizing the PDE the numerical solution is obtained on a form where the value of the derivative can be seen as a probabilistic weighting of future values. READ MORE
