Financial Option Valuation by Unsupervised Learning with Artificial Neural Networks

[Abstract] Artificial neural networks (ANNs) have recently also been applied to solve partial differential equations (PDEs). The classical problem of pricing European and American financial options, based on the corresponding PDE formulations, is studied here. Instead of using numerical techniques based on finite element or difference methods, we address the problem using ANNs in the context of unsupervised learning. As a result, the ANN learns the option values for all possible underlying stock values at future time points, based on the minimization of a suitable loss function. For the European option, we solve the linear Black–Scholes equation, whereas for the American option we solve the linear complementarity problem formulation. Two-asset exotic option values are also computed, since ANNs enable the accurate valuation of high-dimensional options. The resulting errors of the ANN approach are assessed by comparing to the analytic option values or to numerical reference solutions (for American options, computed by finite elements). In the short note, previously published, a brief introduction to this work was given, where some ideas to price vanilla options by ANNs were presented, and only European options were addressed. In the current work, the methodology is introduced in much more detail

European and American Options Valuation by Unsupervised Learning with Artificial Neural Networks

[Abstract] Artificial neural networks (ANNs) have recently also been applied to solve partial differential equations (PDEs). In this work, the classical problem of pricing European and American financial options, based on the corresponding PDE formulations, is studied. Instead of using numerical techniques based on finite element or difference methods, we address the problem using ANNs in the context of unsupervised learning. As a result, the ANN learns the option values for all possible underlying stock values at future time points, based on the minimization of a suitable loss function. For the European option, we solve the linear Black–Scholes equation, whereas for the American option, we solve the linear complementarity problem formulation

Financial option valuation by unsupervised learning with artificial neural networks

Artificial neural networks (ANNs) have recently also been applied to solve partial differential equations (PDEs). The classical problem of pricing European and American financial options, based on the corresponding PDE formulations, is studied here. Instead of using numerical techniques based on finite element or difference methods, we address the problem using ANNs in the context of unsupervised learning. As a result, the ANN learns the option values for all possible underlying stock values at future time points, based on the minimization of a suitable loss function. For the European option, we solve the linear Black–Scholes equation, whereas for the American option we solve the linear complementarity problem formulation. Two-asset exotic option values are also computed, since ANNs enable the accurate valuation of high-dimensional options. The resulting errors of the ANN approach are assessed by comparing to the analytic option values or to numerical reference solutions (for American options, computed by finite elements). In the short note, previously published, a brief introduction to this work was given, where some ideas to price vanilla options by ANNs were presented, and only European options were addressed. In the current work, the methodology is introduced in much more detail

PERANAN WEBSITE DALAM AKTIVITAS PUBLIC RELATIONS SEBAGAI MEDIA PENGHUBUNG ANTARA MASYARAKAT DAN PEMERINTAH DI DISHUBKOMINFO KARANGANYAR

SUMMARY Ni Nyoman Ayu A.W, D1613067, Public Relations, Utilization Website Functions in Public Relations Activities as Media Communicator between the Community and the Government in Dishubkominfo Karanganyar, 2016. Kuliah Kerja Media (KKM) or we called Job Training do it by the author in Dishubkominfo Karanganyar. The reason why the author chose Dishubkominfo Karanganyar as a job training (KKM) in the field of communication and information technology, especially because it looks a lot of public relations activities or practice public speaking especially between government Karanganyar Regent and his Deputy with a lot of community. Here Public Relations is a communication method that is where the various forms of communication. Which in Punlic Relations that there is an attempt to realize the harmonious relationship between an organization and its publics. Public Relations is a deliberate effort, planned on an on going basis to create mutual understanding between an institution / organization with the public. Public Relations can also be regarded as an art as well as social science of analyzing trends, predicting their consequences, briefed the leaders of the institution / organization and implementing planned programs to meet the interests of both the institution / organization and the people involved. At the time of the job training writers do a lot of practice public relations or public relations starting from routine activities for official that morning assembly, socializing with office workers, mutual coordination with staff-related staff, and lobbied with related parties participating in activities , documenting coverage and must maintain good relations between the internal and external Dishubkominfo Karanganyar District. Even job training is very useful for writing because it can prepare for the world of work that requires professional workers and authors directly to gain knowledge related to the field of public relations in order practices. Based on reports from the job training the institution Dishubkominfo Karangayar District, the authors conclude that public relations activities are vital to maintaining good relations between the internal and external Dishubkominfo Karanganyar District

A randomized controlled trial of eplerenone in asymptomatic phospholamban p.Arg14del carriers

INTRODUCTION Phospholamban (PLN; p.Arg14del) cardiomyopathy is an inherited disease caused by the pathogenic p.Arg14del variant in the PLN gene. Clinically, it is characterized by malignant ventricular arrhythmias and progressive heart failure.1,2 Cardiac fibrotic tissue remodelling occurs early on in PLN p.Arg14del carriers.3,4 Eplerenone was deemed a treatment candidate because of its beneficial effects on ventricular remodelling and antifibrotic properties.5,6 We conducted the multicentre randomized trial ‘intervention in PHOspholamban RElated CArdiomyopathy STudy’ (i-PHORECAST) to assess whether treatment with eplerenone of asymptomatic PLN p.Arg14del carriers attenuates disease onset and progression

A randomized controlled trial of eplerenone in asymptomatic phospholamban p.Arg14del carriers

Phospholamban (PLN; p.Arg14del) cardiomyopathy is an inherited disease caused by the pathogenic p.Arg14del variant in the PLN gene. Clinically, it is characterized by malignant ventricular arrhythmias and progressive heart failure.1,2 Cardiac fibrotic tissue remodelling occurs early on in PLN p.Arg14del carriers.3,4 Eplerenone was deemed a treatment candidate because of its beneficial effects on ventricular remodelling and antifibrotic properties.5,6 We conducted the multicentre randomized trial ‘intervention in PHOspholamban RElated CArdiomyopathy STudy’ (i-PHORECAST) to assess whether treatment with eplerenone of asymptomatic PLN p.Arg14del carriers attenuates disease onset and progression

Antisense Therapy Attenuates Phospholamban p.(Arg14del) Cardiomyopathy in Mice and Reverses Protein Aggregation

Inherited cardiomyopathy caused by the p.(Arg14del) pathogenic variant of the phospholamban (PLN) gene is characterized by intracardiomyocyte PLN aggregation and can lead to severe dilated cardiomyopathy. We recently reported that pre-emptive depletion of PLN attenuated heart failure (HF) in several cardiomyopathy models. Here, we investigated if administration of a Pln-targeting antisense oligonucleotide (ASO) could halt or reverse disease progression in mice with advanced PLN-R14del cardiomyopathy. To this aim, homozygous PLN-R14del (PLN-R14 (Δ/Δ)) mice received PLN-ASO injections starting at 5 or 6 weeks of age, in the presence of moderate or severe HF, respectively. Mice were monitored for another 4 months with echocardiographic analyses at several timepoints, after which cardiac tissues were examined for pathological remodeling. We found that vehicle-treated PLN-R14 (Δ/Δ) mice continued to develop severe HF, and reached a humane endpoint at 8.1 ± 0.5 weeks of age. Both early and late PLN-ASO administration halted further cardiac remodeling and dysfunction shortly after treatment start, resulting in a life span extension to at least 22 weeks of age. Earlier treatment initiation halted disease development sooner, resulting in better heart function and less remodeling at the study endpoint. PLN-ASO treatment almost completely eliminated PLN aggregates, and normalized levels of autophagic proteins. In conclusion, these findings indicate that PLN-ASO therapy may have beneficial outcomes in PLN-R14del cardiomyopathy when administered after disease onset. Although existing tissue damage was not reversed, further cardiomyopathy progression was stopped, and PLN aggregates were resolved