Stefano M. Iacus's Books

Option Pricing and Estimation of Financial Models with R

By: Stefano M. Iacus

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Option Pricing and Estimation of Financial Models with R

By: Stefano M. Iacus

Presents inference and simulation of stochastic process in the field of model calibration for financial times series modelled by continuous time processes and numerical option pricing. Introduces the bases of probability theory and goes on to explain how to model financial times series with continuous models, how to calibrate them from discrete data and further covers option pricing with one or more underlying assets based on these models. Analysis and implementation of models goes beyond the standard Black and Scholes framework and includes Markov switching models, Lévy models and other models with jumps (e.g. the telegraph process); Topics other than option pricing include: volatility and covariation estimation, change point analysis, asymptotic expansion and classification of financial time series from a statistical viewpoint. The book features problems with solutions and examples. All the examples and R code are available as an additional R package, therefore all the examples can be reproduced.

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Page Count

402

Publisher

John Wiley & Sons

Published Date

ISBN 10

1119990203

ISBN 13

9781119990208

Simulation and Inference for Stochastic Differential Equations

With R Examples

By: Stefano M. Iacus

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Simulation and Inference for Stochastic Differential Equations

With R Examples

By: Stefano M. Iacus

This book covers a highly relevant and timely topic that is of wide interest, especially in finance, engineering and computational biology. The introductory material on simulation and stochastic differential equation is very accessible and will prove popular with many readers. While there are several recent texts available that cover stochastic differential equations, the concentration here on inference makes this book stand out. No other direct competitors are known to date. With an emphasis on the practical implementation of the simulation and estimation methods presented, the text will be useful to practitioners and students with minimal mathematical background. What’s more, because of the many R programs, the information here is appropriate for many mathematically well educated practitioners, too.

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Page Count

298

Publisher

Springer Science & Business Media

Published Date

ISBN 10

0387758399

ISBN 13

9780387758398

Simulation and Inference for Stochastic Processes with YUIMA

A Comprehensive R Framework for SDEs and Other Stochastic Processes

By: Stefano M. Iacus,Nakahiro Yoshida

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Simulation and Inference for Stochastic Processes with YUIMA

A Comprehensive R Framework for SDEs and Other Stochastic Processes

By: Stefano M. Iacus,Nakahiro Yoshida

The YUIMA package is the first comprehensive R framework based on S4 classes and methods which allows for the simulation of stochastic differential equations driven by Wiener process, Lévy processes or fractional Brownian motion, as well as CARMA, COGARCH, and Point processes. The package performs various central statistical analyses such as quasi maximum likelihood estimation, adaptive Bayes estimation, structural change point analysis, hypotheses testing, asynchronous covariance estimation, lead-lag estimation, LASSO model selection, and so on. YUIMA also supports stochastic numerical analysis by fast computation of the expected value of functionals of stochastic processes through automatic asymptotic expansion by means of the Malliavin calculus. All models can be multidimensional, multiparametric or non parametric.The book explains briefly the underlying theory for simulation and inference of several classes of stochastic processes and then presents both simulation experiments and applications to real data. Although these processes have been originally proposed in physics and more recently in finance, they are becoming popular also in biology due to the fact the time course experimental data are now available. The YUIMA package, available on CRAN, can be freely downloaded and this companion book will make the user able to start his or her analysis from the first page.

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Page Count

277

Publisher

Springer

Published Date

ISBN 10

3319555693

ISBN 13

9783319555690

Subjective Well-Being and Social Media

By: Stefano M. Iacus,Giuseppe Porro

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Subjective Well-Being and Social Media

By: Stefano M. Iacus,Giuseppe Porro

Subjective Well-Being and Social Media shows how, by exploiting the unprecedented amount of information provided by the social networking sites, it is possible to build new composite indicators of subjective well-being. These new social media indicators are complementary to official statistics and surveys, whose data are collected at very low temporary and geographical resolution. The book also explains in full details how to solve the problem of selection bias coming from social media data. Mixing textual analysis, machine learning and time series analysis, the book also shows how to extract both the structural and the temporary components of subjective well-being. Cross-country analysis confirms that well-being is a complex phenomenon that is governed by macroeconomic and health factors, ageing, temporary shocks and cultural and psychological aspects. As an example, the last part of the book focuses on the impact of the prolonged stress due to the COVID-19 pandemic on subjective well-being in both Japan and Italy. Through a data science approach, the results show that a consistent and persistent drop occurred throughout 2020 in the overall level of well-being in both countries. The methodology presented in this book: enables social scientists and policy makers to know what people think about the quality of their own life, minimizing the bias induced by the interaction between the researcher and the observed individuals; being language-free, it allows for comparing the well-being perceived in different linguistic and socio-cultural contexts, disentangling differences due to objective events and life conditions from dissimilarities related to social norms or language specificities; provides a solution to the problem of selection bias in social media data through a systematic approach based on time-space small area estimation models. The book comes also with replication R scripts and data. Stefano M. Iacus is full professor of Statistics at the University of Milan, on leave at the Joint Research Centre of the European Commission. Former R-core member (1999-2017) and R Foundation Member. Giuseppe Porro is full professor of Economic Policy at the University of Insubria. An earlier version of this project was awarded the Italian Institute of Statistics-Google prize for "official statistics and big data".

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Page Count

218

Publisher

CRC Press

Published Date

ISBN 10

0429685831

ISBN 13

9780429685835

Politics and Big Data

Nowcasting and Forecasting Elections with Social Media

By: Andrea Ceron,Luigi Curini,Stefano Maria Iacus

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Politics and Big Data

Nowcasting and Forecasting Elections with Social Media

By: Andrea Ceron,Luigi Curini,Stefano Maria Iacus

The importance of social media as a way to monitor an electoral campaign is well established. Day-by-day, hour-by-hour evaluation of the evolution of online ideas and opinion allows observers and scholars to monitor trends and momentum in public opinion well before traditional polls. However, there are difficulties in recording and analyzing often brief, unverified comments while the unequal age, gender, social and racial representation among social media users can produce inaccurate forecasts of final polls. Reviewing the different techniques employed using social media to nowcast and forecast elections, this book assesses its achievements and limitations while presenting a new technique of "sentiment analysis" to improve upon them. The authors carry out a meta-analysis of the existing literature to show the conditions under which social media-based electoral forecasts prove most accurate while new case studies from France, the United States and Italy demonstrate how much more accurate "sentiment analysis" can prove.

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Page Count

196

Publisher

Routledge

Published Date

ISBN 10

1317134133

ISBN 13

9781317134138

Simulation and Inference for Stochastic Processes with YUIMA

A Comprehensive R Framework for SDEs and Other Stochastic Processes

By: Stefano M. Iacus,Nakahiro Yoshida

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Simulation and Inference for Stochastic Processes with YUIMA

A Comprehensive R Framework for SDEs and Other Stochastic Processes

By: Stefano M. Iacus,Nakahiro Yoshida

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Solve jigsaw puzzle

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Page Count

277

Publisher

Springer

Published Date

ISBN 10

3319555693

ISBN 13

9783319555690

Option Pricing and Estimation of Financial Models with R

By: Stefano M. Iacus

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Option Pricing and Estimation of Financial Models with R

By: Stefano M. Iacus

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Solve jigsaw puzzle

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Page Count

402

Publisher

John Wiley & Sons

Published Date

ISBN 10

1119990203

ISBN 13

9781119990208

Subjective Well-Being and Social Media

By: Stefano M. Iacus,Giuseppe Porro

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Subjective Well-Being and Social Media

By: Stefano M. Iacus,Giuseppe Porro

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N/A

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Solve jigsaw puzzle

Age

Page Count

218

Publisher

CRC Press

Published Date

ISBN 10

0429685831

ISBN 13

9780429685835

Book's by Stefano M. Iacus

Option Pricing and Estimation of Financial Models with R

Option Pricing and Estimation of Financial Models with R

Simulation and Inference for Stochastic Differential Equations

Simulation and Inference for Stochastic Differential Equations

Simulation and Inference for Stochastic Processes with YUIMA

Simulation and Inference for Stochastic Processes with YUIMA

Subjective Well-Being and Social Media

Subjective Well-Being and Social Media

Politics and Big Data

Politics and Big Data

Simulation and Inference for Stochastic Processes with YUIMA

Simulation and Inference for Stochastic Processes with YUIMA

Option Pricing and Estimation of Financial Models with R

Option Pricing and Estimation of Financial Models with R

Subjective Well-Being and Social Media

Subjective Well-Being and Social Media

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