Concept

Discounting

Related publications (32)

Stripping the Swiss discount curve using kernel ridge regression

We analyze and implement the kernel ridge regression (KR) method developed in Filipovic et al. (Stripping the discount curve-a robust machine learning approach. Swiss Finance Institute Research Paper No. 22-24. SSRN. https://ssrn.com/abstract=4058150, 2022 ...

Springer Heidelberg2024

Discount models

Damir Filipovic

Discount is the difference between the face value of a bond and its present value. We propose an arbitrage-free dynamic framework for discount models, which provides an alternative to the Heath-Jarrow-Morton framework for forward rates. We derive general c ...

Heidelberg2023

International Portfolio Choice with Frictions: Evidence from Mutual Funds

Simon Tièche

Using data on international equity portfolio allocations by U.S. mutual funds, we estimate a portfolio expression derived from a standard mean-variance portfolio model extended with portfolio frictions. The optimal portfolio depends on the previous month a ...

OXFORD UNIV PRESS INC2023

Technical and economic feasibility study of high-current HTS bus bars for fusion reactors

Kamil Sedlák, Rainer Wesche, Roberto Guarino

In this study, we present a technical and economic assessment of high-current HTS bus bars for primary use in fusion reactors. Our objective is to verify the technical feasibility of such conductors and, for this purpose, we carry out a conceptual design o ...

ELSEVIER2022

Ride-sourcing fleet rebalancing with proactive and targeted pricing

Nikolaos Geroliminis, Min Ru Wang

This work studies the role of proactive and targeted ride-splitting incentives on the service level and total revenue of a ride-sourcing platform, which is built as a discrete event simulator that incorporates simulated taxi data within a congestible road ...

2022

Identifiability and Generalizability from Multiple Experts in Inverse Reinforcement Learning

Volkan Cevher, Paul Thierry Yves Rolland, Luca Viano, Boris Nikolov

While Reinforcement Learning (RL) aims to train an agent from a reward function in a given environment, Inverse Reinforcement Learning (IRL) seeks to recover the reward function from observing an expert’s behavior. It is well known that, in general, variou ...

2022

Impersonating Chatbots in a Code Review Exercise to Teach Software Engineering Best Practices

Denis Gillet, Maria Jesus Rodriguez Triana, Juan Carlos Farah, Sandy Ingram, Vandit Sharma

Over the past decade, the use of chatbots for educational purposes has gained considerable traction. A similar trend has been observed in social coding platforms, where automated agents support software developers with tasks such as performing code reviews ...

IEEE2022

Global Climate Change Mitigation: Strategic Incentives

Sigit Pria Perdana

Central to global agreement on carbon emissions are strategic interactions amongst regions over abatement policy and the benefits to be shared. These are re-examined in this paper, in which benefits from mitigation stem from a meta-analysis that links carb ...

2020

The triangular value of patents

Albina Khairullina

This thesis addresses the question of a patent value from three different angles. It comprises three papers on the patent valuation methods. The patent valuation issues are well-known to the world of research and practice. However, the debates over what th ...

EPFL2020

Dynamic Credit-Collections Optimization

Thomas Alois Weber

Based on a dynamic model of the stochastic repayment behavior exhibited by delinquent credit-card accounts as a self-exciting point process, a bank can control the arrival intensity of repayments using costly account-treatment actions. A semi-analytic solu ...

2019

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