"1. Knowledge and understanding of the financial statement analysis methodologies applied to management control in companies;
2. Knowledge and understanding of the techniques specific to financial statement analysis as tools for management control and functional to the construction of business plans;
3. Autonomy of judgment regarding the reliability of the information derived from the financial statement analysis and those used for the preparation of business plans;
4. Communication skills in the main terms and techniques of management control, particularly referring to the preparation and reading of business plans;
5. Ability to learn financial statement analysis techniques also supporting the preparation of business plans."
The course aims to teach and provide an understanding of the current state of positive law in Italy and Europe—specifically of criminal relevance—covering the fundamental themes of commercial and corporate criminal law, the study of Supervisory Authorities, and Market Protection, while also addressing the topic of “Corporate Liability” related to Legislative Decree 231/01 in all its aspects.
2. Applying knowledge and understanding:
The dynamic and practical case-law approach addresses the cases of each topic covered with a view to the applied understanding of the law in relation to different factual realities that require interpretation by the jurist in all their roles.
3. Making judgments:
The exegesis-based analysis of the legal texts enables the development of critical autonomy from an interpretive perspective, which the “jurist” student develops in understanding the practical dynamics of the legal institutions being taught.
4. Communication skills:
Communication will also involve “real” seminars with live connections to financial markets to enhance applied knowledge and refine critical interpretation.
5. Learning skills:
Learning will be based on “facts,” an essential starting point in criminal matters, so that the subsumption of facts under the relevant legal provisions is comprehensive, taking into account applied dogmatics together with case law, including that provided at the European level."
I IL D.LGS. 231/01: LA RESPONSABILITÀ “PENALE” DELLE SOCIETÀ
1. Natura della responsabilità
2. Ambito di applicazione
3. Criteri di attribuzione della responsabilità dell’ente
4. Le sanzioni
5. Le misure cautelari
6. Le vicende modificative dell’ente
II ELEMENTI DI DIRITTO PENALE
III LE FATTISPECIE DI REATO
a. i reati contro la pubblica amministrazione
- Nuove regole per la prevenzione e la repressione della corruzione e della illegalità nella pubblica amministrazione: la L. 190/2012, il Piano Nazionale Anticorruzione, la delibera ANAC 8 giugno 2015, white list e rating di legalità, la norma iso 37001
f. i principali reati societari
k. i reati in materia di sicurezza sul lavoro
1. Art. 25 septies del D.L.vo 231/01
2. I principali soggetti responsabili in materia di Sicurezza sul Lavoro
a. il datore di lavoro
b. il dirigente
c. il preposto
d. i lavoratori
3. Modelli di Organizzazione e Gestione ex art. 30 D.L.vo 81/2008
4. Le prime sentenze 231 in materia di Sicurezza sul Lavoro
l. Focus: i reati in materia di riciclaggio
o.: i reati ambientali
r. reati tributari
IV MODELLI DI ORGANIZZAZIONE GESTIONE E CONTROLLO
1. Attuazione del Modello Organizzativo
2. Rilevanza Processuale del Modello
3. Componenti del Modello
3.1 Modello Parte Generale
3.2 Modello Parte Speciale
3.3 Codice Etico
3.4 Organismo di Vigilanza
a. requisiti
b. poteri
c. composizione
d. Attività dell’OdV
e. Il ruolo dell’OdV in materia di riciclaggio
4. Formalizzazione del Modello Organizzativo
5. Manutenzione del Modello Organizzativo
6. Diffusione del Modello Organizzativo
7. Formazione del Personale
V LA RESPONSABILITÀ “PENALE” DELLE SOCIETÀ NEI GRUPPI
VI LA RESPONSABILITÀ “PENALE” DELLE PERSONE GIURIDICHE NEI PAESI DI COMMON LAW E NEI PRINCIPALI ORDINAMENTI EUROPEI
examMode
The final examination consists of an oral test, in which the student will have to demonstrate awareness of the topics covered in the course.
books
the teaching material consists of the handouts distributed by the professor and available on Moodle portal.
The student will be provided with a copy of the GUIDELINES FOR THE CONSTRUCTION OF THE MODELS OF ORGANIZATION, MANAGEMENT AND CONTROL ACCORDING TO LEGISLATIVE DECREE 8 JUNE 2001, N. 231 issued by Confisdustria also in order to analyze the practical case studies contained therein. Practical cases will be analyzed, the orientations of jurisprudence on the subject and national and international best practices will be analyzed
classRoomMode
frequency is not obligatory
bibliography
see textbooks
CORPORATE TAX LAW
Second Semester
8
IUS/12
Learning objectives
"The course aims to achieve the following objectives:
Knowledge and understanding: Acquire in-depth knowledge of corporate tax law, including national and international tax regulations.
Applied knowledge and understanding: Use theoretical knowledge to analyze and resolve practical tax issues faced by businesses.
Autonomy of judgment: Critically evaluate and formulate independent judgments on tax strategies and tax decisions within a business context.
Communication skills: Effectively communicate tax issues, explaining the fiscal implications of business decisions to colleagues, clients, and consultants.
Learning ability: Develop a proactive approach to continuous learning in the field of tax law, enhancing understanding of tax laws and their practical application in a business context."
119992 - LAW OF EXTRAORDINARY TRANSACTIONS
ERMANNO LA MARCA
First Semester
8
IUS/04
Learning objectives
"The course aims to achieve the following objectives:
Knowledge and understanding: Acquire in-depth knowledge of the law related to extraordinary operations, such as mergers, acquisitions, and corporate restructurings.
Applied knowledge and understanding: Use theoretical knowledge to analyze and solve practical cases in the context of extraordinary operations.
Autonomy of judgment: Critically evaluate the legal and strategic implications of extraordinary operations and formulate independent judgments.
Communication skills: Effectively communicate legal strategies and details of extraordinary operations to clients, colleagues, and other stakeholders.
Learning ability: Develop a proactive approach to continuous learning and deepening of legal issues related to extraordinary operations."
The course in Statistical Methods for Business provides students with theoretical and applied skills for data analysis in business contexts, with specific reference to marketing, customer satisfaction, segmentation and user profile analysis. The course combines statistical methods and programming tools in R, with the aim of developing students’ ability to analyse and interpret data and to support data-driven business decisions.
At the end of the course, students will have acquired:
Knowledge and understanding: fundamental knowledge of the main statistical methods for data analysis in business contexts, with specific attention to applications in marketing, customer satisfaction, and the analysis of user behaviour and profiles. Students will also acquire practical knowledge of programming and data analysis tools in R needed to implement the techniques presented during the course.
Applying knowledge and understanding: ability to apply statistical techniques and programming tools in R to real business data and problems, selecting the most appropriate methods according to the objectives of the analysis. Students will be able to use empirical results to support operational and strategic decisions and to propose data-driven solutions in business contexts.
Making judgements: ability to critically assess data quality, the suitability of the statistical techniques used, the reliability of the results obtained and their relevance to the business problem under analysis. Students will also be able to compare alternative methodological approaches and to interpret results while taking into account the limitations of the analyses performed.
Communication skills: ability to present and discuss the results of statistical analyses conducted on business data in a clear, structured and technically appropriate way. Through the preparation and discussion of the final project, students will develop skills in communicating the methods used, the outputs produced and the main operational implications arising from the analysis.
Learning skills: ability to autonomously deepen their knowledge of methods and tools for business data analysis, also through the critical comparison of different methodological solutions. Students will be able to update their statistical and computing skills and adapt them to new problems, datasets and applied contexts in the business field.
16428 - THESIS
Second Semester
12
GRUPPO OPZIONALE AFFINI AMBITO AZIENDALE 24-25 CURR. AC
-
-
-
-
MANAGEMNT OF INFORMATION SYSTEMS
MARCO SMACCHIA
Second Semester
8
SECS-P/10
Learning objectives
The course addresses the topic of digital transformation of organisations, and the consequent impacts on the way modern organisations work and operate. The course invites students to reflect on the changes, opportunities, risks, and consequences on the use of digital technologies in organisational design and change processes, and on the implications for organisational decision making and operational processes.
The course aims at transferring to the students theoretical knowledge and practical skills on the role of digital technologies in organisations, and on the competences and the processes necessary by individuals and organisations to govern this process.
During the course the students will be engaged in learning activities, both theoretical and practical ones, as individuals and in groups. The participation to the course will stimulate in students the development of the following capabilities.
Knowledge and comprehension
Understand the nature and impact of organisational change produced by the introduction of digital technologies in individual and groups behaviour.
Know the main information systems used in organisations.
Know the tools to analyse processes and guide the transformation processes through digital technologies.
Know the tools and the processes for analysing the information needs and for the design of or data analysis and presentation.
Applied knowledge
Being able to identify potential areas of application of digital technologies to solve organisational problems.
Being able to understand and govern the analysis of business processes and their re-engineering in the digital transformation.
Know how to identify and analyse the information needs of an organisation and how to design data analytics tools to satisfy such needs.
Know how to manage a digital transformation process through planning activities and estimating the effort, and know how to control the process using project management tools and techniques
Judgement capabilities
Know the main variables influencing the digital transformation process, know how to analyse them, and be able to judge if and when digital technologies can be used for organisational innovation and change.
Communication capabilities
During the course the students will practice the capabilities of presenting and discussing their ideas on the role of digital technologies in the transformation process of organisations.
Know how to learn
Being able to learn in an autonomous and self-management way.
Learning Objectives
The course aims to provide students with an advanced and systematic understanding of the regulation of financial markets, with particular reference to securities markets, capital raising from the public, financial instruments, and the functioning of listed companies, within the broader framework of national and European commercial law.
Knowledge and understanding
By the end of the course, students will have acquired an in-depth knowledge of the principles and rules governing financial markets, including the regulation of public offerings, investment services and activities, regulated markets, and market abuse, as well as the structure and functioning of listed companies and their ownership and governance arrangements.
Applying knowledge and understanding
Students will be able to apply the knowledge acquired to the analysis of practical cases relating to operations in financial markets, interpreting the relevant legal framework and assessing the legal implications of transactions such as public takeover bids, corporate actions involving listed companies, and other market-relevant phenomena.
Making judgements
Students will develop the ability to critically assess regulatory choices and market dynamics, understanding the interplay between legal rules, investor protection, market integrity, and the protection of minority shareholders.
Communication skills
Students will be able to present legal issues related to financial markets clearly and rigorously, using appropriate technical language and engaging effectively with both specialist and non-specialist audiences.
Learning skills
Students will acquire the methodological tools required to independently update and deepen their knowledge, particularly in light of the continuous evolution of national and European regulation and supervisory practice.
121636 - SUSTAINABILITY AND DIGITAL INNOVATION IN FINANCIAL MARKETS
First Semester
8
ECON-09/B
Learning objectives
The course examines the evolution of financial markets in the context of sustainability and digital innovation. The first part focuses on sustainable finance instruments, including green bonds, green mortgages, and ESG investment funds, analyzing socially responsible investment (SRI) strategies, ESG rating systems, greenwashing practices, and their reputational implications. The course also addresses the pricing of sustainable financial instruments and the use of derivatives for hedging energy-related risks.
The second part is dedicated to the digital transformation of financial intermediation, with a focus on blockchain and decentralized finance (DeFi), digital payments, loan origination and monitoring processes, and the European regulatory framework, including PSD3 and MiCA. The course includes a practical laboratory using STATA for the empirical analysis of financial and ESG data, enabling students to develop operational skills in the evaluation and management of complex financial scenarios.
Upon successful completion of the course, students will have acquired:
a) advanced knowledge of sustainable finance, ESG instruments, and digital innovation processes in financial markets and financial institutions (knowledge and understanding);
b) the ability to analyze sustainable financial instruments, assess ESG-related risks and opportunities, and apply quantitative tools to financial and ESG data analysis (applying knowledge and understanding);
c) the ability to critically evaluate sustainability strategies, digital innovations, and their economic, financial, and regulatory implications (making judgements);
d) the ability to effectively communicate analyses and evaluations related to sustainable finance and financial innovation using appropriate technical terminology (communication skills);
e) the ability to independently explore emerging issues related to sustainability, digitalization, and the evolution of financial markets (learning skills).
119246 - TIME SERIES ANALYSIS
PIERDOMENICO DUTTILO
First Semester
8
STAT-02/A
Learning objectives
The course provides theoretical and applied skills for the statistical analysis of time series, with specific attention to the decomposition of trend and seasonal components, stationary ARMA models, the Box-Jenkins methodology, forecasting, the assessment of forecast accuracy, and ARCH and GARCH models, also through the use of the statistical software R.
At the end of the course, students will have acquired:
Knowledge and understanding: acquisition of the fundamental knowledge related to the structure of time series, their main components, decomposition methods, stationary linear ARMA models, the Box-Jenkins methodology, and models for conditional heteroskedasticity, with specific reference to applications in economics and statistics.
Applied knowledge and understanding: ability to correctly apply methods and models for time series analysis, selecting the most appropriate tools according to the problem under consideration, estimating alternative models, producing forecasts and assessing their accuracy through suitable criteria, also by using the statistical software R.
Making judgements: ability to critically assess the structure of time-dependent data, the choice of the most appropriate model, the quality of the adopted specification and the interpretation of the results obtained, also through the comparison of alternative models and the verification of the statistical and empirical consistency of the analyses performed.
Communication skills: ability to present and discuss the results of statistical analyses on real time series clearly and technically correctly, using the specific language of the discipline and properly interpreting the outputs produced by the statistical software R.
Learning skills: development of skills useful for the autonomous study of time series analysis methods and for the continuous updating of statistical and computational tools for the study of time-dependent data, also with reference to empirical applications in economic, financial and social contexts.
- Introduction to time series analysis;
- Decomposition of a time series into its components: trend, cycle, seasonality, and irregular component;
- Moving averages;
- Modern approaches to time series analysis;
- Stationary linear ARMA(p, q) models;
- Box–Jenkins methodology;
- Additive generalised models for time series;
- Forecasting and evaluation of forecast accuracy;
- Autoregressive conditional heteroskedasticity models (ARCH and GARCH);
- Use of the R statistical software for empirical time series analysis.
examMode
The exam consists of a written test including five questions, comprising applied exercises, theoretical questions, and interpretation of results produced by the statistical software R.
books
Textbook:
Di Fonzo T., Lisi F. (2005), Economic Time Series: Statistical Analysis and Applications, Rome: Carocci.
Recommended:
Wood S.N. (2017) , Generalized Additive Models: An Introduction with R, Second Edition, New York: CRC Press. (only for the time series analysis with GAMs)
Materials provided by the professor.
classRoomMode
Attendance is not compulsory but is strongly recommended
bibliography
Di Fonzo T., Lisi F. (2005), Serie storiche economiche: analisi statistiche e applicazioni, Roma: Carocci.
Wood S.N. (2017) , Generalized Additive Models: An Introduction with R, Second Edition, New York: CRC Press (only for the time series analysis with GAMs).
121695 - PHYTHON FOR FINANCE
First Semester
4
IINF-05/A
Learning objectives
The course "Python for Finance" aims to equip
students with both basic and advanced skills in Python, with a particular focus on applications in the financial sector. Students will develop proficiency in using programming tools and techniques to address various aspects of financial analysis and management, supporting decision-making processes through the use of data and models.
Dublin Descriptors:
1. Knowledge and understanding: Students will acquire a solid foundation in Python and its use in the financial sector, understanding the fundamental principles of programming and data analysis techniques applied to finance.
2. Applying knowledge and understanding: Students will be able to apply this knowledge to solve real-world financial problems, developing quantitative models and analytical tools to support financial decision-making.
3. Making Judgements: Students will develop the ability to critically evaluate the results of their analyses and models, interpreting data independently and making decisions based on them.
4. Communication skills: Students will be able to clearly and effectively present and explain the results of their analyses and models, using data visualization tools and appropriate technical language.
5. Learning skills: Students will demonstrate the ability to continue learning independently, updating their skills and adapting to new technological and methodological developments in finance and programming.
GRUPPO AFFINI CURRICULUM FINANZA
-
-
-
-
ASSET MANAGEMENT
ANNA MARIA D'ARCANGELIS
First Semester
8
ECON-09/B
Learning objectives
The course provides an advanced treatment of Asset Management processes, with particular emphasis on asset allocation, quantitative portfolio construction, and professional investment management. Building on the foundations of mean–variance theory, the course critically examines traditional portfolio optimization models and introduces innovative approaches such as risk parity, factor investing, and data-driven methodologies.
The course explores the tools used by institutional investors for portfolio construction, monitoring, and evaluation, with particular attention to performance measurement, risk assessment, and performance attribution. It also examines the applications of Artificial Intelligence (AI) and Machine Learning (ML) in asset management and risk management, discussing their opportunities and limitations. Practical applications using MATLAB are included for the implementation of portfolio optimization models and the comparison of traditional and algorithmic approaches. The integration of ESG factors and emerging risks completes the framework, providing an up-to-date perspective on portfolio management in contemporary financial markets.
Upon successful completion of the course, students will have acquired:
a) advanced knowledge of the regulatory framework and the asset management industry (knowledge and understanding);
b) in-depth knowledge of traditional and innovative models of asset allocation, portfolio optimization, and portfolio management, including quantitative and data-driven approaches (knowledge and understanding);
c) the ability to apply advanced tools for portfolio construction and monitoring, including the use of specialized software (applying knowledge and understanding);
d) the ability to critically evaluate investment performance, risk, and portfolio strategies, with particular reference to ESG factors and emerging risks (making judgements);
e) the ability to explore innovative topics through academic and professional literature (learning skills).
The course provides advanced training in the principles of Sustainable Corporate Finance, with particular emphasis on the integration of environmental, social, and governance (ESG) considerations into corporate financial decision-making. The course examines the role of sustainability in investment appraisal, financing decisions, risk management, and long-term value creation, taking into account evolving regulatory requirements and increasing stakeholder demands for transparency and accountability.
Upon successful completion of the course, students will have acquired:
a) advanced knowledge of the principles of Sustainable Corporate Finance and of the regulatory framework governing corporate sustainability (knowledge and understanding);
b) the ability to evaluate investment and financing decisions by considering the economic and financial implications of ESG factors (applying knowledge and understanding);
c) the ability to analyse the impact of sustainability-related issues on firm value, cost of capital, and corporate risk management (making judgements);
d) the ability to interpret sustainability-related information and disclosures in support of financial and strategic decision-making (communication skills);
e) the ability to independently explore innovative topics related to corporate sustainability and long-term value creation (learning skills).
The objective is to provide students with theoretical
knowledge of applied linear algebra and data mining, with particular emphasis on the decomposition of prediction errors in economic and social phenomena. Fundamental statistical concepts (e.g., regression, classification, inference) will be reviewed and presented with a more detailed technical level to provide a deeper theoretical understanding of data analysis.
2. Based on the theoretical knowledge acquired, students will be required to apply what they have learned in analyzing datasets on real or simulated data. Particular emphasis is placed on comparing different methods that can be used to achieve the same data analysis objective, in order to identify the most appropriate one. To this end, students will be required to master the R programming software at an intermediate/advanced level.
3. Based on what they have learned in theory and verified in practice, students must make a judgment on the quality of the data analysis performed. Particular emphasis is placed on highlighting the limitations and critical points of the data analysis performed, always keeping in mind whether the data analysis objective has been effectively achieved (where possible).
4. Students are required to communicate what they have learned theoretically and discovered empirically through data analysis by giving an oral presentation of their results. The presentation should balance the technical content of the work with a more informative nature of the insights gained from the data.
5. The student’s learning ability is tested through the data analysis itself. The in-class analyses, where students will learn the theory and test it, will always be necessarily educational, for example, with pre-selected and pre-processed datasets. The analysis of real data that students are exposed to will necessarily put them in a position to apply what they have learned in an innovative way and to learn new techniques. In general, the course will provide students with all the necessary elements to learn new concepts independently.
1. Knowledge and Understanding
Upon successful completion of the course, students will have acquired advanced theoretical knowledge of applied linear algebra, multivariate statistical methods, and data mining techniques, with particular emphasis on regression, classification, statistical inference, and the prediction of economic and social phenomena. They will understand the theoretical foundations of modern data analysis methods, prediction error decomposition, and the methodological principles underlying the selection and evaluation of statistical models and machine learning algorithms.
2. Applying Knowledge and Understanding
Students will be able to apply multivariate statistical methods and data mining techniques to the analysis of real-world or simulated datasets using the R programming language at an intermediate to advanced level. They will be able to select, implement, compare, and validate alternative analytical approaches according to the objectives of the analysis, interpreting results appropriately and assessing model performance through suitable evaluation metrics.
3. Making Judgements
Students will develop the ability to critically assess the quality and reliability of data analyses by considering the assumptions, limitations, and potential sources of bias associated with different analytical methods. They will be able to formulate independent judgments regarding the suitability of alternative models, identify the most appropriate approach for a given analytical objective, and discuss the strengths, weaknesses, and limitations of the results obtained.
4. Communication Skills
Students will be able to communicate statistical analyses and empirical findings effectively to both technical and non-technical audiences. They will be able to explain the methodologies adopted, justify analytical choices, and present results through clear oral presentations supported by appropriate graphical and quantitative summaries, balancing scientific rigor with effective communication.
5. Learning Skills
Students will acquire the methodological and computational skills necessary to independently learn and apply new techniques in multivariate statistics, data mining, and machine learning. By working with real-world datasets, they will develop the ability to address complex analytical problems, adapt to new data analysis challenges, and continuously update their knowledge in response to advances in statistical methods and data science.
examMode
Student learning will be assessed through a written examination and an oral examination. The written examination is designed to evaluate the understanding of the theoretical concepts and the ability to apply multivariate statistical and data mining methods to quantitative problems, including the use of the programming language. The oral examination will assess students' mastery of the theoretical foundations, their ability to critically interpret analytical results, and their use of appropriate scientific terminology.
books
Teaching materials provided by the instructor during the course.
classRoomMode
not compulsory
120410 - PROFESSIONAL ENGLISH FOR MARKETING AND BUSINESS
Second Semester
4
ANGL-01/C
Learning objectives
This course aims to prepare to know and use the
English language with the aim of progressively achieving a level B eligibility. The comprehension and expression of oral language is privileged, without neglecting the linguistic competence required for a clear and correct written expression. For this purpose, the adopted text allows students to personalize what is highlighted in the classroom through further revision and self-learning systems.
The technical linguistic area of exercise will concern marketing and administration, with appropriate formal lexical insights and drafting of special glossaries useful to the profession. Presentations of scientific topics, conversations, debates, analysis of experiences and personal research: all this converges to form and stimulate creative skills, inspired by the most current issues
119241 - INTERNATIONAL MONETARY ECONOMICS AND POLICY
CHIARA OLDANI
Second Semester
8
ECON-02/A
Learning objectives
Educational objectives: The course aims to provide
advanced knowledge on economic and financial issues relating to the monetary economy.
1) Knowledge and understanding; at the end of the course the student will have to demonstrate that they have understood the main issues of international monetary economics (money, exchange rates, crises, innovations and policy and regulatory measures).
2) Applying knowledge and understanding; The student must be able to read and interpret papers and books on advanced financial economics, as well as evaluate their empirical and methodological contents.
3) Autonomy of judgment (making judgments); At the end of the course, the student will be able to independently read papers and books on advanced financial economics, implementing critical analysis in research.
4) Communication skills; Knowledge of the general part and of the special topics of the course will allow the student to acquire the technical language of the subject allowing them to effectively deal with the discussion of the topics covered
5) Ability to learn (learning skills). At the end of the course, the student will be able to undertake, even independently, subsequent in-depth studies regarding the topics addressed.
The course is divided into two compulsory parts: a. monetary policy and economics; international monetary economics and policy; b. digital finance.
Reference for first part is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, chapters 14, 15, 18, 19, 20, 21, 22.
References on digital finance are available at the web page of the course (https://moodle.unitus.it/moodle/course/view.php?id=1118)
examMode
The final exam will be oral on the course' program (i.e., textbook, PPT files, etc.).
Students who do not attend classes will be examined on the program of the course.
books
Reference for first part is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, chapters 14, 15, 18, 19, 20, 21, 22.
References on digital finance are available at the web page of the course (https://moodle.unitus.it/moodle/course/view.php?id=1118)
Blockchain & cryptocurrencies: Anhert 2022; Auer, Torcero-Lucas 2021; Beltrametti Pittaluga; Halaburda et al 2020; Vollman Weming 2024; Lanciano Previati Ricci 2025
E. Hughes 1993 https://nakamotoinstitute.org/cypherpunk-manifesto/
S. Nakamoto 2009 https://nakamotoinstitute.org/bitcoin/
Artificial intelligence & Surveillance capitalism; Zuboff 2015; Varian 2014; Acemoglu 2021; Acemoglu 2024; Kirton Warren 2018;
mode
Enrolled students should attend classes and present in the second part of the course a written and oral synthesis of one out of the special topics (group assignment). The presentation should be sent to the prof. Oldani (coldani@unitus.it) at least 3 days before the presentation. The file of the presentation can be PPT or Latex. A latex file gives a 1 point bonus in the final exam.
Information, manuals and software are available at https://www.latex-project.org/
The final exam will be oral on the entire program (i.e., textbook, files, etc.); the class presentation of the special topic will weight 30 per cent of the final mark.
Students who do not attend classes and don't present any special topic will have their final exam on the programme, including one special topic to be agreed on with prof. Oldani; students who do not attend classes are not requested to provide any presentation file at the exam.
At the completion of this course, students will be able to:
1. Read an advanced paper in economics
2. Comment on economic and monetary theory
3. Present and discuss research in monetary economics
classRoomMode
Classes take place in person in Viterbo; students who cannot attend classes can access the recordings
bibliography
Reference for the first part of the course is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, capitoli 14, 15, 18, 19, 20, 21, 22.
Papers we will use in the course are:
Masciandaro D. 2018 Central banks and Monetary Policy. Economics and Politics. BAFFI Carefin Paper https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3178576
D. Mugge 2019 The Revenge of Political Arithmetick, FickleFormulas Working Paper 2/2019 https://t.co/VhVpfTpLmU
Reference for first part is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, chapters 14, 15, 18, 19, 20, 21, 22.
References on digital finance are available at the web page of the course (https://moodle.unitus.it/moodle/course/view.php?id=1118)
Blockchain & cryptocurrencies: Anhert 2022; Auer, Torcero-Lucas 2021; Beltrametti Pittaluga; Halaburda et al 2020; Vollman Weming 2024; Lanciano Previati Ricci 2025
E. Hughes 1993 https://nakamotoinstitute.org/cypherpunk-manifesto/
S. Nakamoto 2009 https://nakamotoinstitute.org/bitcoin/
Artificial intelligence & Surveillance capitalism; Zuboff 2015; Varian 2014; Acemoglu 2021; Acemoglu 2024; Kirton Warren 2018;
SUBJECT
SEMESTER
CFU
SSD
LANGUAGE
119239 - VALUATION OF COMPANIES AND EXTRAORDINARY TRANSACTIONS
LUIGI FICI
First Semester
8
SECS-P/07
Learning objectives
The course aims to provide adequate and up-to-date preparation on the valuation of companies and extraordinary operations. In particular, it aims to illustrate the main methods of evaluating companies and to make people understand which method is best suited to the different company realities and extraordinary operations that the company may find itself facing.
Knowledge and Understanding: Students will gain a solid understanding of the main business valuation methods, developing the ability to differentiate between various techniques and their theoretical foundations.
Applied Knowledge and Understanding: Students will be able to apply valuation methods to different business realities and extraordinary operations, assessing which method is most suitable for each specific context.
Autonomy in Judgment: The course promotes autonomy in judgment, enabling students to critically analyze valuation methods and make informed decisions on the most appropriate approach for each situation.
Communication Skills: Students will develop the ability to effectively and clearly communicate business valuation results, adapting technical language to the intended audience.
Learning Ability: Students will acquire skills for independent learning, allowing them to continuously update themselves on evolving business valuation methods and practices in extraordinary operations.
"The course covers the topics, models, and operational techniques involved in the Capital Markets and Investment Banking segment, as conducted by investment banks. The course includes the use of Excel, Matlab, and other programming languages.
Ability to Apply Knowledge and Understanding Students will gain the ability to apply advanced models for risk measurement and management of portfolios and their corresponding hedging operations. They will develop skills related to interest rates and exchange rates, commodities, volatility, and financial engineering for creating tailored financial solutions for corporate or retail clients.
Independent Judgment Students will be provided with exercises and a project work assignment that will help them develop the ability to research and process data and information, choose the most appropriate models to answer research questions, and develop advanced quantitative models to draw conclusions on the topics studied.
Communication Skills The course aims to enhance the ability to communicate results, highlighting critical points and analyzing outputs with independent judgment, utilizing Excel and programming languages.
Learning Skills The course offers opportunities to work in teams, manage and organize a project, and communicate with the instructor. Students will gain knowledge of both traditional and innovative topics in capital markets and investment banking through textbooks and academic or professional articles."
"This course is designed to introduce students to the applications of machine learning (ML) in finance and how fintech companies are using ML to create new financial products and services. The course will cover the fundamental concepts of ML, including supervised and unsupervised learning, neural networks, deep learning, and natural language processing.
KNOWLEDGE AND UNDERSTANDING SKILLS
The course provides the ability to apply and program functional machine learning models to financial analysis.
ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING
The student will learn to apply these concepts to financial data and build predictive models to support financial decision making.
AUTONOMY OF JUDGMENT
The student will be able to critically evaluate the financial issue on which to apply the appropriate machine learning model
COMMUNICATION SKILLS.
The student, through active participation in the course, will be encouraged to critically communicate the skills learned
LEARNING SKILLS
The student through individual study and active participation in the classroom will learn the main techniques of machine learning and have the ability to apply them properly to financial cases."
"The course introduces students tho the fundamentals of R language and of the data analysis environments for R. The laboratory is designed for students who have no, or limited, previous knowledge on R. During the laboratory the students will familiarise with the basic features of the R language, the R and RStudio working environment, and the basic operations for data management and manipulation.
Knowledge and understanding
Know the capabilities and the potential application domains of R
Know how to use R together with other data analysis software (Excel and Stata) for data import and export
Know the basic data objects managed by R and be able to manipulate them
Be able to perform basic math and logical operations on data in R, basic data manipulation activities, and basic descriptive statistics analysis
Know how to graphically represent data in R
Applying knowledge and understanding
Be able to recognise the application domain of the features of R
Starting from a dataset, be able to identify the possible analysis and data manipulation that can be performed on it
Making judgements
Be able to interpret the results of the main data manipulation and analysis activities
Be able to interpret the meaning of error messages provided by the R environment and be able to fix the problems autonomously
Communication skills
Be able to present data in the form of reports or presentations automatically generated by R scripts combining textual descriptive parts, data tables, charts, and results of data analysis
Learning skills
Be able to learn in an autonomous and self-managed way
120512 - RISK MANAGEMENT
GIULIA SCARDOZZIANNA MARIA D'ARCANGELIS
First Semester
8
SECS-P/11
Learning objectives
"This course aims to provide students with knowledge and understanding of the main risk models faced by banking institutions.
Specifically, the course involves the delivery of frontal lectures in which the theoretical foundations of modeling found in the literature are presented (knowledge and understanding), with the help of supplementary readings, especially of a scientific nature and also resorting to practical application through example exercises (applying knowledge and understanding). Specifically, in addition to analyzing traditional models of risk management, the course also pays attention to the evolution of risk analysis in light of Basel III and recent challenges permeating the financial system, such as the use of artificial intelligence and attention to ESG issues, particularly climate risk assessment (learning skills and sustainability). Students are provided with exercises to be carried out independently and in groups, so as to apply advanced modeling and be able to draw conclusions regarding risk management (applying knowledge and understanding and making judgements) and to communicate the results, revealing critical points and analyzing outputs using independent judgment (communication skills).
18487 - REPORTING AND CONTROL OF FINANCIAL INTERMEDIARIES
Second Semester
8
SECS-P/07
Learning objectives
LEARNING OUTCOMES: The course aims to provide students with the tools they need to know how to read the consolidated financial statements of credit and financial intermediaries as well as the documents produced to fulfill the obligations of the third Basel capital agreement with the supervisory authorities (ICAAP, supervisory reports harmonized and non-harmonized) and to external parties (Public disclosure). The course also aims to provide an all-round overview of issues related to the issues of programming and control of financial and credit intermediaries.
KNOWLEDGE AND UNDERSTANDING: At the end of the training the student must have understood aspects of an eminently theoretical nature useful for solving operational problems.
APPLYING KNOWLEDGE AND UNDERSTANDING: The distinctly operational cut of the course must allow the student to have the necessary skills to understand the business reality of an intermediary, by reading his annual report, other documents subject to mandatory disclosure and the main documents of management control.
MAKING JUDGEMENTS: The analysis of a consolidated annual report of a credit intermediary will allow the student to apply all the knowledge acquired in the classroom, to be able to understand the economic and financial balance sheet, the risks assumed, the assets of his economy. The analysis of a dashboard of management control indicators will allow the assessment of the strategic effectiveness and operating efficiency of the credit intermediary to which those data refer.
COMMUNICATION SKILLS: Both the theoretical and operational part of the course will enable the student to acquire the technical language of the subject and to be able to aspire to managerial tasks both within the credit and financial intermediaries and within the companies that provide consulting services and of revision.
LEARNING SKILLS: In addition to knowing how to read the financial statements of credit intermediaries, the documents subject to mandatory disclosure, those produced to fulfill reporting obligations and internal reports of management control, the student will be able to understand techniques, manuals, scientific publications of dissemination or research that have as their object the reporting of the banks.
16428 - THESIS
Second Semester
12
GRUPPO OPZIONALE AFFINI CURR. FINANZA
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SUSTAINABLE CORPORATE FINANCE
PAOLA NASCENZI
Second Semester
8
SECS-P/09
Learning objectives
The course provides advanced training in the principles of Sustainable Corporate Finance, with particular emphasis on the integration of environmental, social, and governance (ESG) considerations into corporate financial decision-making. The course examines the role of sustainability in investment appraisal, financing decisions, risk management, and long-term value creation, taking into account evolving regulatory requirements and increasing stakeholder demands for transparency and accountability.
Upon successful completion of the course, students will have acquired:
a) advanced knowledge of the principles of Sustainable Corporate Finance and of the regulatory framework governing corporate sustainability (knowledge and understanding);
b) the ability to evaluate investment and financing decisions by considering the economic and financial implications of ESG factors (applying knowledge and understanding);
c) the ability to analyse the impact of sustainability-related issues on firm value, cost of capital, and corporate risk management (making judgements);
d) the ability to interpret sustainability-related information and disclosures in support of financial and strategic decision-making (communication skills);
e) the ability to independently explore innovative topics related to corporate sustainability and long-term value creation (learning skills).
121604 - ACCOUNTING AND CONTROL FOR PUBLIC MANAGEMENT
VINCENZO SFORZA
First Semester
8
ECON-06/A
Learning objectives
The course aims to illustrate to the student the
general characteristics of the “universal” company and the public administration. It is proposed, in particular, to identify the organizational and management logics of public administration, analyzing the main change processes that have involved the whole public administration in recent years.
Dublin Descriptors:
a) KNOWLEDGE AND UNDERSTANDING: knowledge
and understanding of the concept of "universal" company and public company.
b) APPLYING KNOWLEDGE AND UNDERSTANDING:
ability to apply the knowledge acquired and to understand and solve problems relating to the management and accounting and budget information system of companies and public administrations (with particular reference to local authorities).
c) MAKING JUDGEMENTS: ability to use the acquired knowledge on a conceptual and operational level with autonomous assessment skills and skills in the various application contexts.
d) COMMUNICATION SKILLS: acquire clear and effective communication skills, thanks to technical language typical of the discipline
e) LEARNING SKILLS: acquire adequate learning skills that allow you to independently address and deepen the main issues of the discipline. This ability will be developed through the active involvement of students through discussions in the classroom and exercises on specific topics related to the course.
The course in Statistical Methods for Business provides students with theoretical and applied skills for data analysis in business contexts, with specific reference to marketing, customer satisfaction, segmentation and user profile analysis. The course combines statistical methods and programming tools in R, with the aim of developing students’ ability to analyse and interpret data and to support data-driven business decisions.
At the end of the course, students will have acquired:
Knowledge and understanding: fundamental knowledge of the main statistical methods for data analysis in business contexts, with specific attention to applications in marketing, customer satisfaction, and the analysis of user behaviour and profiles. Students will also acquire practical knowledge of programming and data analysis tools in R needed to implement the techniques presented during the course.
Applying knowledge and understanding: ability to apply statistical techniques and programming tools in R to real business data and problems, selecting the most appropriate methods according to the objectives of the analysis. Students will be able to use empirical results to support operational and strategic decisions and to propose data-driven solutions in business contexts.
Making judgements: ability to critically assess data quality, the suitability of the statistical techniques used, the reliability of the results obtained and their relevance to the business problem under analysis. Students will also be able to compare alternative methodological approaches and to interpret results while taking into account the limitations of the analyses performed.
Communication skills: ability to present and discuss the results of statistical analyses conducted on business data in a clear, structured and technically appropriate way. Through the preparation and discussion of the final project, students will develop skills in communicating the methods used, the outputs produced and the main operational implications arising from the analysis.
Learning skills: ability to autonomously deepen their knowledge of methods and tools for business data analysis, also through the critical comparison of different methodological solutions. Students will be able to update their statistical and computing skills and adapt them to new problems, datasets and applied contexts in the business field.
The course aims to provide advanced and up-to-date knowledge in the fields of business valuation, extraordinary transactions, and investment decision-making processes. Students will acquire both theoretical knowledge and practical tools to understand, analyze, and estimate the economic value of companies in different business and institutional contexts.
Particular attention will be devoted to the critical analysis of the main valuation methodologies (income-based, cash-flow-based, asset-based, and market-based approaches), highlighting their assumptions, limitations, and appropriate fields of application.
Upon completion of the course, students will be able to:
✔ identify and analyze the key economic, financial, and strategic drivers of corporate value;
✔ critically assess financial statements, business plans, and market information for valuation purposes;
✔ select and apply the most appropriate valuation methodology according to the characteristics of the company and the purpose of the valuation;
✔ interpret valuation outcomes from a professional and decision-making perspective;
✔ understand the role of valuation in mergers and acquisitions, contributions in kind, demergers, transformations, shareholder withdrawal procedures, and leveraged buyouts;
✔ develop analytical and problem-solving skills through the discussion of real-world business cases and investment simulations;
adopt an integrated valuation perspective that combines financial, strategic, organizational, and risk-related factors.
Through a practice-oriented approach inspired by the activities of financial advisors, audit firms, institutional investors, and private equity funds, the course also aims to develop students' ability to formulate independent and well-supported professional judgments in situations characterized by uncertainty and incomplete information.
A) LEARNING OBJECTIVES
The aim of the course is to analyze the interaction between global economic dynamics, local production systems, and individual firms from the perspective of sustainable industrial development. Within this framework, the course will examine the main elements of development processes at both the global and local levels, with particular attention to issues related to technological progress and innovation processes within individual firms as well as inter-firm networks, which are increasingly connected to sustainability challenges, while taking into account the strategic role of development policies. These analyses will be complemented by specific insights into dominant market structures and related business strategies, as well as the role of global value chains and multinational enterprises.
B) EXPECTED LEARNING OUTCOMES
1. Knowledge and understanding:
Students will acquire knowledge of economic theories in order to understand the main global economic dynamics, as well as the processes characterizing local production systems and individual firms
2. Applying knowledge and understanding:
Students will learn the essential tools for the economic analysis and empirical evaluation of business strategies, identifying their main challenges and opportunities.
3. Making judgements:
Students will be able to analyze economic development processes, identifying their significant relationships, as well as the main critical issues and opportunities according to different theoretical approaches with an appropriate critical spirit.
4. Communication skills
Students will be able to present economic concepts and arguments clearly and rigorously, making appropriate use of formulas, graphs, and logical relationships.
5. Learning skills
Students will be able to independently and critically rework the knowledge acquired in the area of sustainable industrial development and related structural change processes at sectoral and enterprise levels.
Educational objectives: The course aims to provide
advanced knowledge on economic and financial issues relating to the monetary economy.
1) Knowledge and understanding; at the end of the course the student will have to demonstrate that they have understood the main issues of international monetary economics (money, exchange rates, crises, innovations and policy and regulatory measures).
2) Applying knowledge and understanding; The student must be able to read and interpret papers and books on advanced financial economics, as well as evaluate their empirical and methodological contents.
3) Autonomy of judgment (making judgments); At the end of the course, the student will be able to independently read papers and books on advanced financial economics, implementing critical analysis in research.
4) Communication skills; Knowledge of the general part and of the special topics of the course will allow the student to acquire the technical language of the subject allowing them to effectively deal with the discussion of the topics covered
5) Ability to learn (learning skills). At the end of the course, the student will be able to undertake, even independently, subsequent in-depth studies regarding the topics addressed.
The course is divided into two compulsory parts: a. monetary policy and economics; international monetary economics and policy; b. digital finance.
Reference for first part is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, chapters 14, 15, 18, 19, 20, 21, 22.
References on digital finance are available at the web page of the course (https://moodle.unitus.it/moodle/course/view.php?id=1118)
examMode
The final exam will be oral on the course' program (i.e., textbook, PPT files, etc.).
Students who do not attend classes will be examined on the program of the course.
books
Reference for first part is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, chapters 14, 15, 18, 19, 20, 21, 22.
References on digital finance are available at the web page of the course (https://moodle.unitus.it/moodle/course/view.php?id=1118)
Blockchain & cryptocurrencies: Anhert 2022; Auer, Torcero-Lucas 2021; Beltrametti Pittaluga; Halaburda et al 2020; Vollman Weming 2024; Lanciano Previati Ricci 2025
E. Hughes 1993 https://nakamotoinstitute.org/cypherpunk-manifesto/
S. Nakamoto 2009 https://nakamotoinstitute.org/bitcoin/
Artificial intelligence & Surveillance capitalism; Zuboff 2015; Varian 2014; Acemoglu 2021; Acemoglu 2024; Kirton Warren 2018;
mode
Enrolled students should attend classes and present in the second part of the course a written and oral synthesis of one out of the special topics (group assignment). The presentation should be sent to the prof. Oldani (coldani@unitus.it) at least 3 days before the presentation. The file of the presentation can be PPT or Latex. A latex file gives a 1 point bonus in the final exam.
Information, manuals and software are available at https://www.latex-project.org/
The final exam will be oral on the entire program (i.e., textbook, files, etc.); the class presentation of the special topic will weight 30 per cent of the final mark.
Students who do not attend classes and don't present any special topic will have their final exam on the programme, including one special topic to be agreed on with prof. Oldani; students who do not attend classes are not requested to provide any presentation file at the exam.
At the completion of this course, students will be able to:
1. Read an advanced paper in economics
2. Comment on economic and monetary theory
3. Present and discuss research in monetary economics
classRoomMode
Classes take place in person in Viterbo; students who cannot attend classes can access the recordings
bibliography
Reference for the first part of the course is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, capitoli 14, 15, 18, 19, 20, 21, 22.
Papers we will use in the course are:
Masciandaro D. 2018 Central banks and Monetary Policy. Economics and Politics. BAFFI Carefin Paper https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3178576
D. Mugge 2019 The Revenge of Political Arithmetick, FickleFormulas Working Paper 2/2019 https://t.co/VhVpfTpLmU
Reference for first part is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, chapters 14, 15, 18, 19, 20, 21, 22.
References on digital finance are available at the web page of the course (https://moodle.unitus.it/moodle/course/view.php?id=1118)
Blockchain & cryptocurrencies: Anhert 2022; Auer, Torcero-Lucas 2021; Beltrametti Pittaluga; Halaburda et al 2020; Vollman Weming 2024; Lanciano Previati Ricci 2025
E. Hughes 1993 https://nakamotoinstitute.org/cypherpunk-manifesto/
S. Nakamoto 2009 https://nakamotoinstitute.org/bitcoin/
Artificial intelligence & Surveillance capitalism; Zuboff 2015; Varian 2014; Acemoglu 2021; Acemoglu 2024; Kirton Warren 2018;
GRUPPO OPZIONALE AFFINI AMBITO AZIENDALE 24-25 CURR. AC
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BUSINESS GROUPS AND FINANCIAL STATEMENT ANALYSIS
GIUSEPPE IANNIELLO
First Semester
8
ECON-06/A
Learning objectives
The purpose of the course is to provide an overview of
the role of accounting information in the perspective of its preparation and use by stakeholders. In particular, it is intended to provide the student with knowledge of two thematic areas: group formation and consolidated account and financial statements analysis to make different economic decisions.
Learning Objectives
1) Knowledge and understanding Knowing the tools of analysis, about groups accounts and financial statements analysis both in their theoretical construction and in their implementation. Civil code regulation, national and international financial reporting standards.
2) Applied knowledge and understanding Learning of group analysis tools and interpreting financial statements. Analysis of case studies.
3) Autonomy of judgment To be able to apply instruments for analyzing business groups and financial statements in a critical and independent way in order to be able to write a report on financial position and performance of operations of a business entity.
4) Communication skills To be able to express the results of a financial statements analysis by preparing a report and accounting documents.
5) Ability to read published accounting information of companies and groups in order to express an assessment of the economic, financial and equity conditions
120410 - PROFESSIONAL ENGLISH FOR MARKETING AND BUSINESS
Second Semester
4
ANGL-01/C
Learning objectives
This course aims to prepare to know and use the
English language with the aim of progressively achieving a level B eligibility. The comprehension and expression of oral language is privileged, without neglecting the linguistic competence required for a clear and correct written expression. For this purpose, the adopted text allows students to personalize what is highlighted in the classroom through further revision and self-learning systems.
The technical linguistic area of exercise will concern marketing and administration, with appropriate formal lexical insights and drafting of special glossaries useful to the profession. Presentations of scientific topics, conversations, debates, analysis of experiences and personal research: all this converges to form and stimulate creative skills, inspired by the most current issues
15797 - INTERNATIONAL ACCOUNTING
EGIDIO GIUSEPPE PERRONE
Second Semester
8
ECON-06/A
Learning objectives
The course aims to lead the student to a significant
knowledge of financial reporting regulated by international accounting standards and aims to make appreciate specificities and elements of distinction compared to other accounting regulations. By understanding the concepts that characterise financial reporting and analysing their regulation in terms of accounting standards, at the end of the course the student will have acquired an adequate level of knowledge of the criteria for forming financial reporting and its interpretation.
Knowledge and understanding - At the end of the learning process the student will have the necessary knowledge to understand financial reporting prepared in compliance with accounting standards. Applied knowledge and understanding - The student should be able to understand accounting standards and to correctly interpret financial reporting prepared according to these standards.
Autonomy of judgment - The student must be able to develop his own autonomy of judgment on the correctness of the assessments made on the basis of different accounting regulations.
The course aims to provide students with the knowledge, tools, and skills needed to understand, analyze, and manage innovation processes within organizations, with attention to technological, strategic, digital, and sustainability-related dynamics.
1. Knowledge and understanding. By the end of the course, students will have acquired theoretical and conceptual knowledge of the main approaches to innovation management, with specific reference to innovation processes, types of innovation, strategic technology management, open innovation, digital transformation, sustainability, and innovative business models.
2. Applying knowledge and understanding. Students will be able to apply models, tools, and methodologies to analyze, design, and manage innovation processes within public and private organizations. They will be able to use tools such as design thinking, the business model canvas, technology scouting, project portfolio management, and innovation ecosystem analysis.
3. Making judgments. Students will be able to critically assess opportunities, risks, and strategic implications related to innovation. They will be able to analyze competitive, technological, and market scenarios and make independent judgements on the economic, organizational, social, and environmental sustainability of innovation projects.
4. Communication skills. Students will be able to communicate innovation ideas, analyses, and projects clearly, effectively, and in a structured manner, using appropriate language in both academic and professional contexts. They will also be able to work in teams, present business cases, and discuss innovative solutions with both specialist and non-specialist audiences.
5. Learning skills. Students will develop the ability to autonomously update their knowledge of innovation, technology, digitalization, and sustainability. They will be able to identify relevant information sources, interpret emerging trends, and continue learning independently in academic, professional, or entrepreneurial contexts.
Part 1 Innovation management
Chapter 1 - Innovation management: an introduction
Chapter 4 - Managing innovation within firms
Chapter 5 - Operations and process innovation
Part 2 Turning technology into business
Chapter 7 - Managing organisational knowledge
Chapter 9 + 10 – R&D, Open Innovation and technology transfer
Part 3 New product development
Chapter 11 - Business models
Chapter 12 - Market adoption and technology diffusion
Chapter 13 - New product development
Chapter 14 - Market research and its influence on new product development
Chapter 15 - Managing the new product development process
examMode
The course requires a written exam consisting of 10 closed-ended questions and 2 open-ended questions.
Students attending lectures will be required to complete ongoing projects and case studies, which will be assessed for the final exam.
Attending students who complete projects in class will take a final exam consisting of only 10 closed-ended questions, to which the project scores will be added.
books
Trott P (2021) Innovation Management and New Product Development 7th edition ISBN 9781292251523 - Pearson
classRoomMode
Attendance is not mandatory. Students who attend will be able to take group projects and receive a grade that will be added to the final written exam (see exam format).
bibliography
During the course, articles and in-depth material will be distributed by the teacher.
121595 - ECONOMICS OF INNOVATION AND MARKET STRATEGIES
LUCA CORREANI
First Semester
8
ECON-04/A
Learning objectives
A. OBJECTIVE.
The course aims to provide students with the theoretical and applied tools needed to understand the role of innovation in competitive processes and firm strategies. Students will acquire knowledge of the main economic models of innovation, the determinants of firms’ strategic choices, mechanisms of technological competition, and their implications for growth, productivity, and market organization. By the end of the course, students will be able to critically analyze firms’ innovation strategies and interpret their economic effects across different sectoral contexts.
B. EXPECTED LEARNING OUTCOMES
1. KNOWLEDGE AND UNDERSTANDING
Students will acquire knowledge and understanding of the main economic theories and analytical frameworks related to innovation, technological change, and firm strategy. They will be able to understand how innovation affects competition, market structure, productivity, and firms’ strategic behavior in different economic and sectoral contexts.
2. APPLYING KNOWLEDGE AND UNDERSTANDING
Students will be able to apply the knowledge acquired to the analysis of real-world cases concerning innovation processes and firm strategies. They will use economic models and analytical tools to interpret firms’ innovation choices, assess competitive dynamics, and understand the effects of innovation on markets, industries, and firm performance.
3. MAKING JUDGEMENTS
Students will develop independent judgement in the critical analysis of innovation processes and firm strategies. They will be able to independently assess firms’ strategic choices, competitive dynamics, and the economic effects of innovation, making informed use of theories, models, and empirical evidence.
4. COMMUNICATIONS
Students will develop communication skills enabling them to clearly and rigorously present and discuss topics related to innovation, technological change, and firm strategies. They will be able to support their analyses using appropriate economic terminology and to communicate results and interpretations to both specialist and non-specialist audiences.
5. LEARNING SKILLS
Students will develop learning skills that enable them to independently deepen their understanding of topics related to innovation, technological change, and firm strategies. They will be able to update and integrate the knowledge acquired by consulting theoretical and empirical sources and by applying the analytical tools of the course to new economic and sectoral contexts. .
I Elements of Microeconomics
II Market Structures and Industrial Organization
III Game Theory and Strategic Interaction
IV Understanding Innovation
V Market Structure and Innovation Incentives
VI Strategic R&D and Innovation Races
VII Intellectual Property, Cooperation, and Technology Markets
VIII Digital Markets, Emerging Technologies, and Innovation Policy
Please note that the topics will not necessarily be covered in the order indicated above.
examMode
The examination consists of a written test in which students are required to answer theoretical questions and solve exercises. The time allowed is two hours. The number of questions and exercises ranges from a minimum of three to a maximum of six, depending on their level of difficulty.
books
It is essential to attend the lectures, preferably in person, and take notes. During each lecture, the relevant pages of the textbooks corresponding to the topics covered will also be indicated.
The reference textbooks are:
Hall, B. H., and Helmers, C. (2024), The Economics of Innovation and Intellectual Property, Oxford University Press.
Belleflamme, P., and Peitz, M. (2016), Industrial Organization: Markets and Strategies, Cambridge University Press.
classRoomMode
Attendance is not compulsory but is strongly recommended.
bibliography
- Hall B.H., Helmers C. (2024) . The economics of innovation and intellectual property . Oxford University press
- Belleflamme P., Peitz M. (2016) Industrial Organization. Market and Strategies. Cambridge University Press
- - ELECTIVE COURSE
First Semester
8
NEW GROUP OTHER ACTIVITIES
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ITALIAN LANGUAGE
First Semester
4
INTERNSHIP AND SEMINARS - OTHER ACTIVITIES
First Semester
8
INTERNSHIP AND SEMINARS - OTHER ACTIVITIES
First Semester
12
121596 - STATISTICS FOR BUSINESS AND ECONOMICS
Second Semester
8
STAT-02/A
Learning objectives
The course aims at providing students with advanced and applied statistical tools for the analysis of economic, business and sustainability data, with specific attention to supporting managerial decision-making in contexts of innovation, digital transformation and sustainable transition.
Knowledge and understanding: students will acquire advanced knowledge of the main statistical tools for the analysis of economic, business and sustainability data, understanding the role of data in the decision-making processes of firms and organisations.
Applying knowledge and understanding: students will be able to apply statistical techniques to real data, select appropriate methods, build indicators, estimate models, interpret results and translate empirical evidence into support for managerial decision-making.
Making judgements: students will be able to critically assess data quality, the reliability of sources, the correctness of the methods used and the interpretative limitations of statistical analyses, distinguishing between correlation, forecasting and causal interpretation.
Communication skills: students will be able to communicate statistical results through tables, graphs, reports and presentations, using language appropriate for both technical audiences and business decision-makers.
Learning skills: students will develop methodological skills useful for independently deepening their knowledge of business analytics, applied econometrics, data science, sustainability analytics and decision support systems.
121597 - MARKET & COMPANY LAW
ERMANNO LA MARCAPRISCILLA PETTITI
Second Semester
8
GIUR-02/A
Learning objectives
Learning Objectives
The course aims to provide students with a solid grounding in the fundamental principles of company law, including its application in situations of corporate crisis, and of European Union competition law. Within this framework, the course examines, on the one hand, the harmonised principles of European company law, with particular reference to sustainability and crisis; on the other hand, the core features of EU competition law, taking into account the evolving, including digital, nature of markets.
Knowledge and understanding
By the end of the course, students will have acquired an in-depth knowledge of the fundamental principles and institutions of European company law and EU competition law, understanding their structure, purposes, and interrelations. Students will be able to grasp the role of the firm within the internal market and to understand the main transformations affecting company law, as well as the evolution of competition law in the context of digital markets.
Applying knowledge and understanding
Students will be able to apply the knowledge acquired to the analysis of concrete cases, assessing the legal implications relating to corporate organization, directors’ duties, including with regard to the prevention of crisis and the resolution of insolvency, corporate governance, and the regulation of competition in both traditional and digital markets, also through the examination of EU legislation and case law.
Making judgements
Students will develop the ability to critically assess the regulatory and interpretative solutions offered by European Union law in the fields of company and competition law, identifying the tensions and balances between freedom of enterprise, sustainability and crisis prevention, as well as between the proper functioning of the market, the protection of competition, and the regulation of digital platforms.
Communication skills
Students will be able to present, in a clear and rigorous manner, the main legal issues relating to European company law, sustainability and corporate crisis, and competition law in traditional and digital markets, using appropriate technical language and demonstrating the ability to synthesize and argue effectively.
Learning skills
Students will acquire the methodological tools necessary to independently explore topics relating to European company law and EU competition law, taking into account the evolution of legislation, case law, and academic debate on issues of crisis, sustainability, and the regulation of digital markets.
The course aims to analyse development processes in terms of their economic, social and environmental dimensions. From this perspective, the main drivers of economic development processes and their interactions with environmental sustainability and social inclusion will be studied. The course will analyse the relevance of structural changes led by technological progress, and their impact on economic development, social inclusion and income inequalities. Attention will be given to international relations concerning both international competitiveness and cooperation, as well as sustainable human development with reference to global market mechanisms and public policies at territorial, national and international levels.
B) EXPECTED LEARNING OUTCOMES
1. Knowledge and understanding ability: the knowledge of theories and policies of development useful to understand the main issues of contemporary economy.
2. Capability to apply knowledge and understanding: the knowledge of concepts and methods to judge the main criticalities and opportunities of economic development.
3. Capability to approach the subject in a critical manner: the capability to identify the main relationships of the economic system to grasp its logic and explain it according to the different theoretical approaches and with a critical capacity.
4. Communication abilities: to knowledge of the analytical rigor through the use of formulas and graphs and with the illustration of logical links.
5. Learning ability: successful condition in learning is the ability to reconstruct autonomously and critically the introductory notions of development economics
Knowledge and comprehension skills
- Know the managerial tools to be applied in a quality management system integrated with I4.0. To know the organization of a quality- and innovation-oriented enterprise.
Ability to apply knowledge and understanding
- Learning the tools needed to properly and efficiently implement a Ǫuality Management System and the tools of I4.0.
Autonomy of judgment
- Know how to identify nonconformities in a quality management system and how to identify and apply I4.0 tools
Communication skills
- Through group activities in the classroom at the end of the teaching, communicative activities capable of presenting and describing changes in the management of a specific organization through the presentation of project work will be refined
Learning ability
- The various teaching methods used will enable the student to develop a practical approach to implementing I4.0 tools integrated with a quality system. The student will accrue a critical appreciation of his or her understanding of key concepts, theoretical frameworks, and practices through the high level of classroom interactions
119244 - COMMERCIAL CRIMINAL LAW AND CORPORATE LIABILITY
LUCA DE ROSA
Second Year / First Semester
8
IUS/17
Learning objectives
"1. Knowledge and understanding:
The course aims to teach and provide an understanding of the current state of positive law in Italy and Europe—specifically of criminal relevance—covering the fundamental themes of commercial and corporate criminal law, the study of Supervisory Authorities, and Market Protection, while also addressing the topic of “Corporate Liability” related to Legislative Decree 231/01 in all its aspects.
2. Applying knowledge and understanding:
The dynamic and practical case-law approach addresses the cases of each topic covered with a view to the applied understanding of the law in relation to different factual realities that require interpretation by the jurist in all their roles.
3. Making judgments:
The exegesis-based analysis of the legal texts enables the development of critical autonomy from an interpretive perspective, which the “jurist” student develops in understanding the practical dynamics of the legal institutions being taught.
4. Communication skills:
Communication will also involve “real” seminars with live connections to financial markets to enhance applied knowledge and refine critical interpretation.
5. Learning skills:
Learning will be based on “facts,” an essential starting point in criminal matters, so that the subsumption of facts under the relevant legal provisions is comprehensive, taking into account applied dogmatics together with case law, including that provided at the European level."
I IL D.LGS. 231/01: LA RESPONSABILITÀ “PENALE” DELLE SOCIETÀ
1. Natura della responsabilità
2. Ambito di applicazione
3. Criteri di attribuzione della responsabilità dell’ente
4. Le sanzioni
5. Le misure cautelari
6. Le vicende modificative dell’ente
II ELEMENTI DI DIRITTO PENALE
III LE FATTISPECIE DI REATO
a. i reati contro la pubblica amministrazione
- Nuove regole per la prevenzione e la repressione della corruzione e della illegalità nella pubblica amministrazione: la L. 190/2012, il Piano Nazionale Anticorruzione, la delibera ANAC 8 giugno 2015, white list e rating di legalità, la norma iso 37001
f. i principali reati societari
k. i reati in materia di sicurezza sul lavoro
1. Art. 25 septies del D.L.vo 231/01
2. I principali soggetti responsabili in materia di Sicurezza sul Lavoro
a. il datore di lavoro
b. il dirigente
c. il preposto
d. i lavoratori
3. Modelli di Organizzazione e Gestione ex art. 30 D.L.vo 81/2008
4. Le prime sentenze 231 in materia di Sicurezza sul Lavoro
l. Focus: i reati in materia di riciclaggio
o.: i reati ambientali
r. reati tributari
IV MODELLI DI ORGANIZZAZIONE GESTIONE E CONTROLLO
1. Attuazione del Modello Organizzativo
2. Rilevanza Processuale del Modello
3. Componenti del Modello
3.1 Modello Parte Generale
3.2 Modello Parte Speciale
3.3 Codice Etico
3.4 Organismo di Vigilanza
a. requisiti
b. poteri
c. composizione
d. Attività dell’OdV
e. Il ruolo dell’OdV in materia di riciclaggio
4. Formalizzazione del Modello Organizzativo
5. Manutenzione del Modello Organizzativo
6. Diffusione del Modello Organizzativo
7. Formazione del Personale
V LA RESPONSABILITÀ “PENALE” DELLE SOCIETÀ NEI GRUPPI
VI LA RESPONSABILITÀ “PENALE” DELLE PERSONE GIURIDICHE NEI PAESI DI COMMON LAW E NEI PRINCIPALI ORDINAMENTI EUROPEI
examMode
The final examination consists of an oral test, in which the student will have to demonstrate awareness of the topics covered in the course.
books
the teaching material consists of the handouts distributed by the professor and available on Moodle portal.
The student will be provided with a copy of the GUIDELINES FOR THE CONSTRUCTION OF THE MODELS OF ORGANIZATION, MANAGEMENT AND CONTROL ACCORDING TO LEGISLATIVE DECREE 8 JUNE 2001, N. 231 issued by Confisdustria also in order to analyze the practical case studies contained therein. Practical cases will be analyzed, the orientations of jurisprudence on the subject and national and international best practices will be analyzed
classRoomMode
frequency is not obligatory
bibliography
see textbooks
119990 - CORPORATE TAX LAW
Second Year / First Semester
8
IUS/12
Learning objectives
"The course aims to achieve the following objectives:
Knowledge and understanding: Acquire in-depth knowledge of corporate tax law, including national and international tax regulations.
Applied knowledge and understanding: Use theoretical knowledge to analyze and resolve practical tax issues faced by businesses.
Autonomy of judgment: Critically evaluate and formulate independent judgments on tax strategies and tax decisions within a business context.
Communication skills: Effectively communicate tax issues, explaining the fiscal implications of business decisions to colleagues, clients, and consultants.
Learning ability: Develop a proactive approach to continuous learning in the field of tax law, enhancing understanding of tax laws and their practical application in a business context."
GRUPPO OPZIONALE AFFINI AMBITO AZIENDALE 24-25 CURR. AC
-
8
-
-
120457 - MANAGEMNT OF INFORMATION SYSTEMS
MARCO SMACCHIA
Second Year / Second Semester
8
SECS-P/10
Learning objectives
The course addresses the topic of digital transformation of organisations, and the consequent impacts on the way modern organisations work and operate. The course invites students to reflect on the changes, opportunities, risks, and consequences on the use of digital technologies in organisational design and change processes, and on the implications for organisational decision making and operational processes.
The course aims at transferring to the students theoretical knowledge and practical skills on the role of digital technologies in organisations, and on the competences and the processes necessary by individuals and organisations to govern this process.
During the course the students will be engaged in learning activities, both theoretical and practical ones, as individuals and in groups. The participation to the course will stimulate in students the development of the following capabilities.
Knowledge and comprehension
Understand the nature and impact of organisational change produced by the introduction of digital technologies in individual and groups behaviour.
Know the main information systems used in organisations.
Know the tools to analyse processes and guide the transformation processes through digital technologies.
Know the tools and the processes for analysing the information needs and for the design of or data analysis and presentation.
Applied knowledge
Being able to identify potential areas of application of digital technologies to solve organisational problems.
Being able to understand and govern the analysis of business processes and their re-engineering in the digital transformation.
Know how to identify and analyse the information needs of an organisation and how to design data analytics tools to satisfy such needs.
Know how to manage a digital transformation process through planning activities and estimating the effort, and know how to control the process using project management tools and techniques
Judgement capabilities
Know the main variables influencing the digital transformation process, know how to analyse them, and be able to judge if and when digital technologies can be used for organisational innovation and change.
Communication capabilities
During the course the students will practice the capabilities of presenting and discussing their ideas on the role of digital technologies in the transformation process of organisations.
Know how to learn
Being able to learn in an autonomous and self-management way.
The course provides an advanced treatment of Asset Management processes, with particular emphasis on asset allocation, quantitative portfolio construction, and professional investment management. Building on the foundations of mean–variance theory, the course critically examines traditional portfolio optimization models and introduces innovative approaches such as risk parity, factor investing, and data-driven methodologies.
The course explores the tools used by institutional investors for portfolio construction, monitoring, and evaluation, with particular attention to performance measurement, risk assessment, and performance attribution. It also examines the applications of Artificial Intelligence (AI) and Machine Learning (ML) in asset management and risk management, discussing their opportunities and limitations. Practical applications using MATLAB are included for the implementation of portfolio optimization models and the comparison of traditional and algorithmic approaches. The integration of ESG factors and emerging risks completes the framework, providing an up-to-date perspective on portfolio management in contemporary financial markets.
Upon successful completion of the course, students will have acquired:
a) advanced knowledge of the regulatory framework and the asset management industry (knowledge and understanding);
b) in-depth knowledge of traditional and innovative models of asset allocation, portfolio optimization, and portfolio management, including quantitative and data-driven approaches (knowledge and understanding);
c) the ability to apply advanced tools for portfolio construction and monitoring, including the use of specialized software (applying knowledge and understanding);
d) the ability to critically evaluate investment performance, risk, and portfolio strategies, with particular reference to ESG factors and emerging risks (making judgements);
e) the ability to explore innovative topics through academic and professional literature (learning skills).
The course provides advanced training in the principles of Sustainable Corporate Finance, with particular emphasis on the integration of environmental, social, and governance (ESG) considerations into corporate financial decision-making. The course examines the role of sustainability in investment appraisal, financing decisions, risk management, and long-term value creation, taking into account evolving regulatory requirements and increasing stakeholder demands for transparency and accountability.
Upon successful completion of the course, students will have acquired:
a) advanced knowledge of the principles of Sustainable Corporate Finance and of the regulatory framework governing corporate sustainability (knowledge and understanding);
b) the ability to evaluate investment and financing decisions by considering the economic and financial implications of ESG factors (applying knowledge and understanding);
c) the ability to analyse the impact of sustainability-related issues on firm value, cost of capital, and corporate risk management (making judgements);
d) the ability to interpret sustainability-related information and disclosures in support of financial and strategic decision-making (communication skills);
e) the ability to independently explore innovative topics related to corporate sustainability and long-term value creation (learning skills).
The objective is to provide students with theoretical
knowledge of applied linear algebra and data mining, with particular emphasis on the decomposition of prediction errors in economic and social phenomena. Fundamental statistical concepts (e.g., regression, classification, inference) will be reviewed and presented with a more detailed technical level to provide a deeper theoretical understanding of data analysis.
2. Based on the theoretical knowledge acquired, students will be required to apply what they have learned in analyzing datasets on real or simulated data. Particular emphasis is placed on comparing different methods that can be used to achieve the same data analysis objective, in order to identify the most appropriate one. To this end, students will be required to master the R programming software at an intermediate/advanced level.
3. Based on what they have learned in theory and verified in practice, students must make a judgment on the quality of the data analysis performed. Particular emphasis is placed on highlighting the limitations and critical points of the data analysis performed, always keeping in mind whether the data analysis objective has been effectively achieved (where possible).
4. Students are required to communicate what they have learned theoretically and discovered empirically through data analysis by giving an oral presentation of their results. The presentation should balance the technical content of the work with a more informative nature of the insights gained from the data.
5. The student’s learning ability is tested through the data analysis itself. The in-class analyses, where students will learn the theory and test it, will always be necessarily educational, for example, with pre-selected and pre-processed datasets. The analysis of real data that students are exposed to will necessarily put them in a position to apply what they have learned in an innovative way and to learn new techniques. In general, the course will provide students with all the necessary elements to learn new concepts independently.
1. Knowledge and Understanding
Upon successful completion of the course, students will have acquired advanced theoretical knowledge of applied linear algebra, multivariate statistical methods, and data mining techniques, with particular emphasis on regression, classification, statistical inference, and the prediction of economic and social phenomena. They will understand the theoretical foundations of modern data analysis methods, prediction error decomposition, and the methodological principles underlying the selection and evaluation of statistical models and machine learning algorithms.
2. Applying Knowledge and Understanding
Students will be able to apply multivariate statistical methods and data mining techniques to the analysis of real-world or simulated datasets using the R programming language at an intermediate to advanced level. They will be able to select, implement, compare, and validate alternative analytical approaches according to the objectives of the analysis, interpreting results appropriately and assessing model performance through suitable evaluation metrics.
3. Making Judgements
Students will develop the ability to critically assess the quality and reliability of data analyses by considering the assumptions, limitations, and potential sources of bias associated with different analytical methods. They will be able to formulate independent judgments regarding the suitability of alternative models, identify the most appropriate approach for a given analytical objective, and discuss the strengths, weaknesses, and limitations of the results obtained.
4. Communication Skills
Students will be able to communicate statistical analyses and empirical findings effectively to both technical and non-technical audiences. They will be able to explain the methodologies adopted, justify analytical choices, and present results through clear oral presentations supported by appropriate graphical and quantitative summaries, balancing scientific rigor with effective communication.
5. Learning Skills
Students will acquire the methodological and computational skills necessary to independently learn and apply new techniques in multivariate statistics, data mining, and machine learning. By working with real-world datasets, they will develop the ability to address complex analytical problems, adapt to new data analysis challenges, and continuously update their knowledge in response to advances in statistical methods and data science.
examMode
Student learning will be assessed through a written examination and an oral examination. The written examination is designed to evaluate the understanding of the theoretical concepts and the ability to apply multivariate statistical and data mining methods to quantitative problems, including the use of the programming language. The oral examination will assess students' mastery of the theoretical foundations, their ability to critically interpret analytical results, and their use of appropriate scientific terminology.
books
Teaching materials provided by the instructor during the course.
classRoomMode
not compulsory
GRUPPO ALTRE ATTIVITA' CURR. FINAN. 24-25
-
4
-
-
120416 - MACHINE LEARNING LAB FOR FINANCE
GIOVANNI TROMBETTA
Second Year / First Semester
4
ING-INF/05
Learning objectives
"This course is designed to introduce students to the applications of machine learning (ML) in finance and how fintech companies are using ML to create new financial products and services. The course will cover the fundamental concepts of ML, including supervised and unsupervised learning, neural networks, deep learning, and natural language processing.
KNOWLEDGE AND UNDERSTANDING SKILLS
The course provides the ability to apply and program functional machine learning models to financial analysis.
ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING
The student will learn to apply these concepts to financial data and build predictive models to support financial decision making.
AUTONOMY OF JUDGMENT
The student will be able to critically evaluate the financial issue on which to apply the appropriate machine learning model
COMMUNICATION SKILLS.
The student, through active participation in the course, will be encouraged to critically communicate the skills learned
LEARNING SKILLS
The student through individual study and active participation in the classroom will learn the main techniques of machine learning and have the ability to apply them properly to financial cases."
120409 - DIGITAL SKILLS LAB: DATA ANALYTICS WITH R
Second Year / First Semester
4
ING-INF/05
Learning objectives
"The course introduces students tho the fundamentals of R language and of the data analysis environments for R. The laboratory is designed for students who have no, or limited, previous knowledge on R. During the laboratory the students will familiarise with the basic features of the R language, the R and RStudio working environment, and the basic operations for data management and manipulation.
Knowledge and understanding
Know the capabilities and the potential application domains of R
Know how to use R together with other data analysis software (Excel and Stata) for data import and export
Know the basic data objects managed by R and be able to manipulate them
Be able to perform basic math and logical operations on data in R, basic data manipulation activities, and basic descriptive statistics analysis
Know how to graphically represent data in R
Applying knowledge and understanding
Be able to recognise the application domain of the features of R
Starting from a dataset, be able to identify the possible analysis and data manipulation that can be performed on it
Making judgements
Be able to interpret the results of the main data manipulation and analysis activities
Be able to interpret the meaning of error messages provided by the R environment and be able to fix the problems autonomously
Communication skills
Be able to present data in the form of reports or presentations automatically generated by R scripts combining textual descriptive parts, data tables, charts, and results of data analysis
Learning skills
Be able to learn in an autonomous and self-managed way
GRUPPO OPZIONALE AFFINI CURR. FINANZA
-
8
-
-
120415 - SUSTAINABLE CORPORATE FINANCE
PAOLA NASCENZI
Second Year / Second Semester
8
SECS-P/09
Learning objectives
The course provides advanced training in the principles of Sustainable Corporate Finance, with particular emphasis on the integration of environmental, social, and governance (ESG) considerations into corporate financial decision-making. The course examines the role of sustainability in investment appraisal, financing decisions, risk management, and long-term value creation, taking into account evolving regulatory requirements and increasing stakeholder demands for transparency and accountability.
Upon successful completion of the course, students will have acquired:
a) advanced knowledge of the principles of Sustainable Corporate Finance and of the regulatory framework governing corporate sustainability (knowledge and understanding);
b) the ability to evaluate investment and financing decisions by considering the economic and financial implications of ESG factors (applying knowledge and understanding);
c) the ability to analyse the impact of sustainability-related issues on firm value, cost of capital, and corporate risk management (making judgements);
d) the ability to interpret sustainability-related information and disclosures in support of financial and strategic decision-making (communication skills);
e) the ability to independently explore innovative topics related to corporate sustainability and long-term value creation (learning skills).
119241 - INTERNATIONAL MONETARY ECONOMICS AND POLICY
CHIARA OLDANI
First Year / Second Semester
8
ECON-02/A
Learning objectives
Educational objectives: The course aims to provide
advanced knowledge on economic and financial issues relating to the monetary economy.
1) Knowledge and understanding; at the end of the course the student will have to demonstrate that they have understood the main issues of international monetary economics (money, exchange rates, crises, innovations and policy and regulatory measures).
2) Applying knowledge and understanding; The student must be able to read and interpret papers and books on advanced financial economics, as well as evaluate their empirical and methodological contents.
3) Autonomy of judgment (making judgments); At the end of the course, the student will be able to independently read papers and books on advanced financial economics, implementing critical analysis in research.
4) Communication skills; Knowledge of the general part and of the special topics of the course will allow the student to acquire the technical language of the subject allowing them to effectively deal with the discussion of the topics covered
5) Ability to learn (learning skills). At the end of the course, the student will be able to undertake, even independently, subsequent in-depth studies regarding the topics addressed.
The course is divided into two compulsory parts: a. monetary policy and economics; international monetary economics and policy; b. digital finance.
Reference for first part is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, chapters 14, 15, 18, 19, 20, 21, 22.
References on digital finance are available at the web page of the course (https://moodle.unitus.it/moodle/course/view.php?id=1118)
examMode
The final exam will be oral on the course' program (i.e., textbook, PPT files, etc.).
Students who do not attend classes will be examined on the program of the course.
books
Reference for first part is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, chapters 14, 15, 18, 19, 20, 21, 22.
References on digital finance are available at the web page of the course (https://moodle.unitus.it/moodle/course/view.php?id=1118)
Blockchain & cryptocurrencies: Anhert 2022; Auer, Torcero-Lucas 2021; Beltrametti Pittaluga; Halaburda et al 2020; Vollman Weming 2024; Lanciano Previati Ricci 2025
E. Hughes 1993 https://nakamotoinstitute.org/cypherpunk-manifesto/
S. Nakamoto 2009 https://nakamotoinstitute.org/bitcoin/
Artificial intelligence & Surveillance capitalism; Zuboff 2015; Varian 2014; Acemoglu 2021; Acemoglu 2024; Kirton Warren 2018;
mode
Enrolled students should attend classes and present in the second part of the course a written and oral synthesis of one out of the special topics (group assignment). The presentation should be sent to the prof. Oldani (coldani@unitus.it) at least 3 days before the presentation. The file of the presentation can be PPT or Latex. A latex file gives a 1 point bonus in the final exam.
Information, manuals and software are available at https://www.latex-project.org/
The final exam will be oral on the entire program (i.e., textbook, files, etc.); the class presentation of the special topic will weight 30 per cent of the final mark.
Students who do not attend classes and don't present any special topic will have their final exam on the programme, including one special topic to be agreed on with prof. Oldani; students who do not attend classes are not requested to provide any presentation file at the exam.
At the completion of this course, students will be able to:
1. Read an advanced paper in economics
2. Comment on economic and monetary theory
3. Present and discuss research in monetary economics
classRoomMode
Classes take place in person in Viterbo; students who cannot attend classes can access the recordings
bibliography
Reference for the first part of the course is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, capitoli 14, 15, 18, 19, 20, 21, 22.
Papers we will use in the course are:
Masciandaro D. 2018 Central banks and Monetary Policy. Economics and Politics. BAFFI Carefin Paper https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3178576
D. Mugge 2019 The Revenge of Political Arithmetick, FickleFormulas Working Paper 2/2019 https://t.co/VhVpfTpLmU
Reference for first part is the Textbook by P. Krugman M. Obstfeld M. Melitz, International Monetary Economics, 2022, 12th Edition, Pearson, chapters 14, 15, 18, 19, 20, 21, 22.
References on digital finance are available at the web page of the course (https://moodle.unitus.it/moodle/course/view.php?id=1118)
Blockchain & cryptocurrencies: Anhert 2022; Auer, Torcero-Lucas 2021; Beltrametti Pittaluga; Halaburda et al 2020; Vollman Weming 2024; Lanciano Previati Ricci 2025
E. Hughes 1993 https://nakamotoinstitute.org/cypherpunk-manifesto/
S. Nakamoto 2009 https://nakamotoinstitute.org/bitcoin/
Artificial intelligence & Surveillance capitalism; Zuboff 2015; Varian 2014; Acemoglu 2021; Acemoglu 2024; Kirton Warren 2018;
GRUPPO OPZIONALE AFFINI AMBITO AZIENDALE 24-25 CURR. AC
-
8
-
-
121610 - BUSINESS GROUPS AND FINANCIAL STATEMENT ANALYSIS
GIUSEPPE IANNIELLO
First Year / Second Semester
8
ECON-06/A
Learning objectives
The purpose of the course is to provide an overview of
the role of accounting information in the perspective of its preparation and use by stakeholders. In particular, it is intended to provide the student with knowledge of two thematic areas: group formation and consolidated account and financial statements analysis to make different economic decisions.
Learning Objectives
1) Knowledge and understanding Knowing the tools of analysis, about groups accounts and financial statements analysis both in their theoretical construction and in their implementation. Civil code regulation, national and international financial reporting standards.
2) Applied knowledge and understanding Learning of group analysis tools and interpreting financial statements. Analysis of case studies.
3) Autonomy of judgment To be able to apply instruments for analyzing business groups and financial statements in a critical and independent way in order to be able to write a report on financial position and performance of operations of a business entity.
4) Communication skills To be able to express the results of a financial statements analysis by preparing a report and accounting documents.
5) Ability to read published accounting information of companies and groups in order to express an assessment of the economic, financial and equity conditions
121600 - INTERNSHIP AND SEMINARS - OTHER ACTIVITIES
First Year / First Semester
8
121649 - INTERNSHIP AND SEMINARS - OTHER ACTIVITIES
First Year / First Semester
12
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