Statistical Sciences

The primary educational objective of the course is the study of applied statistics. Given the vastness of the application domain, it will focus in particular on the quantitative analysis applied to the finance sector and market automation methodologies and algorithms. Students must know how to solve the analytical problems necessary for apply the aforementioned methods and be able to interpret the results that derive from their application to real data. Specific objectives a) Knowledge and ability to understand After attending the course the students must acquire a complete profile of quantitative analyst ("quant"), both regarding the knowledge of the methodologies, as well as regards the ability to implement them in modern programming languages, such as c #, c ++, vb.net, j # and in general, the integrated Visual Studio development environment. b) Ability to apply knowledge and understanding At the end of the course, students are able to model all phases of quantitative analysis, including simulation and modeling processes strategies, calculation of performance indices and construction of empirical probabilities of the main performance indices. c) Autonomy of judgment Students develop critical skills through the creation of new strategies and the corresponding simulation study, both with backtesting and forward testing techniques. Both with simulated data, through mixtures of random processes, and through the historical series observed in the past. d) Communication skills Students, through the study and performance of practical exercises, acquire the technical-scientific language of the discipline, which it must be used appropriately in both the intermediate and final written tests and in the oral tests. Communication skills come also developed through laboratory programming activities and also group research activities. e) Learning ability Students who pass the exam have learned the methods of analysis that allow them to face concrete problems of "quantitative analysis" and if necessary to intervene on any phase of the complex process that goes from the acquisition of the financial data stream in real time, to its statistical analysis for the creation of automation strategies, to the quantitative evaluation of the methodologies. They also have the ability to implement any methodology required in a modern development environment, OOP programming, and advanced graphical interfaces. Statistica Applicata Obiettivi generali L'obiettivo formativo primario dell’insegnamento è lo studio di Temi di Statistica Applicata. Data la vastità del dominio applicativo si focalizzerà in particolare sull'analisi quantitativa applicata al settore della finanza e delle metodologie e algoritmi di automazione dei mercati. Gli studenti dovranno saper risolvere i problemi analitici necessari per applicare i suddetti metodi e saper interpretare i risultati che discendono dalla loro applicazione a dati reali. Obiettivi specifici a) Conoscenza e capacità di comprensione Dopo aver frequentato il corso gli studenti devono acquisire un profilo completo di analista quantitativo ("quant"), sia per quanto concerne la conoscenza delle metodologie, sia per quanto riguarda la capacità di implementarle nell'ambito di linguaggi moderni di programmazione, quali ad esempio c#, c++, vb.net, j# in generale l'ambiente integrato di sviluppo Visual Studio. b) Capacità di applicare conoscenza e comprensione Al termine del corso gli studenti sono in grado modellizzare tutte le fasi dell'analisi quantitativa, inclusi i processi di simulazione, modellizzazione delle strategie, calcolo di indici di performance e costruzione delle distribuzioni empiriche di probabilità dei principali indici di performance. c) Autonomia di giudizio Gli studenti sviluppano capacità critiche attraverso la creazione di nuove strategie e il corrispondente studio simulativo, sia con tecniche di backtesting che forward testing. Sia con dati simulati, mediante misture di processi aleatori, sia mediante le serie storiche osservate nel passato. d) Abilità comunicativa Gli studenti, attraverso lo studio e lo svolgimento di esercizi pratici, acquisiscono il linguaggio tecnico-scientifico della disciplina, che deve essere opportunamente utilizzato sia nelle prove scritte intermedie e finali che nelle prove orali. Le abilità comunicative vengono sviluppate anche attraverso attività programmazione in laboratorio e anche attività di ricerca in gruppi. e) Capacità di apprendimento Gli studenti che superano l’esame hanno appreso i metodi di analisi che consentono loro di affrontare problemi concreti di "quantitative analysis" e se necessario di poter intervenire su qualunque fase del complesso processo che va dall'acquisizione dello stream di dati finanziari in tempo reale, alla sua analisi statistica ai fini della creazione di strategie di automazione, alla valutazione quantitativa delle metodologie. Hanno inoltre la capacità di implementare qualunque metodologia richiesta in un ambiente di sviluppo moderno, di programmazione OOP, e interfacce grafiche avanzate. The primary educational objective of the course is the study of applied statistics. Given the vastness of the application domain, it will focus in particular on the quantitative analysis applied to the finance sector and market automation methodologies and algorithms. Students must know how to solve the analytical problems necessary for apply the aforementioned methods and be able to interpret the results that derive from their application to real data. Specific objectives a) Knowledge and ability to understand After attending the course the students must acquire a complete profile of quantitative analyst ("quant"), both regarding the knowledge of the methodologies, as well as regards the ability to implement them in modern programming languages, such as c #, c ++, vb.net, j # and in general, the integrated Visual Studio development environment. b) Ability to apply knowledge and understanding At the end of the course, students are able to model all phases of quantitative analysis, including simulation and modeling processes strategies, calculation of performance indices and construction of empirical probabilities of the main performance indices. c) Autonomy of judgment Students develop critical skills through the creation of new strategies and the corresponding simulation study, both with backtesting and forward testing techniques. Both with simulated data, through mixtures of random processes, and through the historical series observed in the past. d) Communication skills Students, through the study and performance of practical exercises, acquire the technical-scientific language of the discipline, which it must be used appropriately in both the intermediate and final written tests and in the oral tests. Communication skills come also developed through laboratory programming activities and also group research activities. e) Learning ability Students who pass the exam have learned the methods of analysis that allow them to face concrete problems of "quantitative analysis" and if necessary to intervene on any phase of the complex process that goes from the acquisition of the financial data stream in real time, to its statistical analysis for the creation of automation strategies, to the quantitative evaluation of the methodologies. They also have the ability to implement any methodology required in a modern development environment, OOP programming, and advanced graphical interfaces.