Modelización Cuantitativa para Finanzas Corporativas from Coursera

Este es un curso de modelización cuantitativa pensado para su aplicación en el ámbito de finanzas corporativas. En este curso aprenderás cómo explotar de la mejor forma los datos que alimentan a los modelos financieros.

En la "era de los datos", cada vez más las organizaciones cuentan con información que pueden ser explotada para enriquecer la modelización financiera. Apoyándonos en métodos estadísticos y de modelización, en este curso aprenderás a proyectar variables de interés, a realizar predicciones, a medir y a evaluar la implicancia de riesgos. También aprenderás criterios para la toma decisiones, basadas en la evaluación de escenarios con incertidumbre. Aplicaremos herramientas básicas de análisis estadístico, métodos de regresión simple y multivariado, técnicas de series de temporales, y de predicción frente a una gran cantidad de variables explicativas, entre otras herramientas que estudiaremos con el foco en aplicaciones financieras. Implementaremos los modelos más simples en Excel, y ganaremos agilidad en estimaciones más complejas usando R.

Este es el segundo curso de la serie de Finanzas Corporativas ofrecido por la Universidad Austral.

What's inside

Syllabus

Proyectando el Escenario Esperado y Escenarios de Riesgo

En este módulo introduciremos la proyección de una variable basándonos en la información disponible sobre esa variable. Analizaremos también cómo las proyecciones afectan nuestras decisiones financieras. Nos apoyaremos en los conceptos de proyección de un escenario esperado, la identificación de escenarios de riesgo, y en cuantificar sus probabilidades de ocurrencia. Utilizaremos para esto herramientas clásicas de la estadística frecuentista: los conceptos de escenario esperado, distribución de probabilidad, y el uso de percentiles.

Modelización basada en Regresión

En este módulo cubriremos cómo proyectar una variable incluyendo datos adicionales, aquellos que servirían para explicar o predecir el fenómeno de interés. Nos enfocaremos en modelos de regresión, uno de los métodos más utilizados para la modelización. Comenzaremos por introducir la versión simple, donde una sola variable es utilizada como base de la modelización. Luego, extenderemos el modelo para incluir múltiples variables. Introduciremos los cambios en la interpretación, y los problemas comunes que pueden surgir en la modelización.

Modelos de Series de Tiempo

En los módulos anteriores trabajamos con modelos donde la información temporal (i.e., cuándo ocurrió un evento) es irrelevante. En este módulo extendemos los modelos para acomodar a las Series de Tiempo, que son aquellos procesos en donde la secuencialidad de la información es relevante. Aplicaciones incluyen la proyección del Producto Bruto Interno de un país, la tasa de interés en un mercado, el precio de una acción, etc. Discutiremos formas de modelizar a las series de tiempo por sus principales componentes. Cubriremos también modelos específicos para modelar el componente de autocorrelación temporal. En este módulo también introduciremos al software R para modelar series de tiempo de una manera eficiente.

Enfoque predictivo con aplicaciones en R

En este módulo nos enfocaremos en lo que llamaremos un enfoque predictivo de la modelización. Estos métodos buscan maximizar la capacidad predictiva aun cuando al hacerlo pierden la capacidad explicativa del fenómeno en cuestión. La prioridad del enfoque predictivo es hacer la mejor predicción posible, y para ello es fundamental evitar el sobreajuste de los datos. Aprenderemos a diagnosticar el sobreajuste e introduciremos a los modelos de regularización, un tipo de modelos que permiten limitar el sobreajuste de manera automatizada.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Enseña métodos estadísticos y de modelización para proyectar variables, realizar predicciones, medir y evaluar la implicancia de riesgos

Se enfoca en aplicaciones financieras, lo que lo hace relevante para profesionales en este campo

Utiliza herramientas básicas de análisis estadístico, métodos de regresión, técnicas de series temporales y predicción frente a una gran cantidad de variables explicativas

Aplica modelos más simples en Excel y utiliza R para estimaciones más complejas

Es el segundo curso de la serie de Finanzas Corporativas ofrecido por la Universidad Austral, lo que sugiere un enfoque integral en el tema

Reviews summary

Financial modeling specialization

Financial Modeling for Corporate Finance is a highly rated specialization that teaches students how to apply quantitative modeling techniques to financial data. Students will learn how to use statistical and modeling methods to project variables of interest, make predictions, and measure and evaluate the implications of risk. They will also learn how to make decisions based on the evaluation of scenarios with uncertainty.

Difficult but educational

"El curso estuvo diicil, pero aprendí muchas cosas."

Uses Excel and R

"Ya conocía algunos de los modelos usados aquí, pero no con tal aplicación. Es un curso muy interesante, me encanto la forma en que lo presentan en Excel y R"

Clear explanations of concepts

"Es muy clara la explicación para comprender los conceptos de Regresión y de Ajuste de Modelos."

Modern and practical

"Excelente curso: Moderno y práctico"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Modelización Cuantitativa para Finanzas Corporativas with these activities:

Revisar conceptos básicos de estadística

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Repasar los conceptos fundamentales de estadística te ayudará a comprender mejor los métodos y modelos cuantitativos utilizados en este curso.

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Revisar notas o materiales de estudio de cursos anteriores de estadística.
Realizar problemas de práctica de libros de texto o sitios web.

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Career center

Learners who complete Modelización Cuantitativa para Finanzas Corporativas will develop knowledge and skills that may be useful to these careers:

Financial Analyst

Financial Analysts make recommendations to their clients about which financial products they should buy or sell. They analyze data to make predictions about the economy and financial markets. This course can help Financial Analysts by providing them with the quantitative modeling skills they need to make better predictions and recommendations. Those interested in becoming Financial Analysts may find this course's focus on using statistical methods and modeling to support financial decision-making particularly helpful.

See salaries and explore the career path for Financial Analyst

Quantitative Analyst

Quantitative Analysts develop and use mathematical and statistical models to solve problems in the financial industry. They use these models to make predictions about the economy, financial markets, and individual companies. This course can help Quantitative Analysts by providing them with the quantitative modeling skills they need to develop and use more accurate and sophisticated models. Those interested in becoming Quantitative Analysts may find this course particularly helpful due to its emphasis on using R and Excel to implement models.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty. They use these models to make recommendations to insurance companies and other financial institutions about how to price insurance policies and manage risk. This course can help Actuaries by providing them with the quantitative modeling skills they need to develop and use more accurate and sophisticated models. Those interested in becoming Actuaries may find this course particularly helpful due to its emphasis on using statistical methods and modeling to support financial decision-making.

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Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. They use this information to make recommendations to businesses about how to improve their operations or products. This course can help Data Analysts by providing them with the quantitative modeling skills they need to analyze data more effectively and make better recommendations. Those interested in becoming Data Analysts may find this course helpful due to its focus on using statistical methods and modeling to analyze data.

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Statistician

Statisticians collect, analyze, and interpret data. They use this information to make predictions and recommendations about a wide variety of topics, such as public health, marketing, and finance. This course can help Statisticians by providing them with the quantitative modeling skills they need to analyze data more effectively and make better predictions and recommendations. Those interested in becoming Statisticians may find this course particularly helpful due to its focus on using statistical methods and modeling to analyze data.

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Risk Analyst

Risk Analysts identify and assess risks faced by businesses and organizations. They use this information to develop and implement strategies to mitigate these risks. This course can help Risk Analysts by providing them with the quantitative modeling skills they need to identify and assess risks more effectively and develop more effective mitigation strategies. Those interested in becoming Risk Analysts may find this course particularly helpful due to its focus on using statistical methods and modeling to assess risk.

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Portfolio Manager

Portfolio Managers manage investment portfolios for individuals and institutions. They use their knowledge of financial markets and investment strategies to make decisions about which investments to buy or sell. This course can help Portfolio Managers by providing them with the quantitative modeling skills they need to make better investment decisions. Those interested in becoming Portfolio Managers may find this course particularly helpful due to its emphasis on using statistical methods and modeling to support financial decision-making.

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Financial Modeler

Financial Modelers develop and use financial models to make predictions about the financial performance of businesses and organizations. They use these models to make recommendations about investment decisions, financing decisions, and other financial matters. This course can help Financial Modelers by providing them with the quantitative modeling skills they need to develop and use more accurate and sophisticated models. Those interested in becoming Financial Modelers may find this course particularly helpful due to its focus on using statistical methods and modeling to support financial decision-making.

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Investment Analyst

Investment Analysts research and analyze investment opportunities for individuals and institutions. They use their knowledge of financial markets and investment strategies to make recommendations about which investments to buy or sell. This course can help Investment Analysts by providing them with the quantitative modeling skills they need to make better investment recommendations. Those interested in becoming Investment Analysts may find this course particularly helpful due to its focus on using statistical methods and modeling to analyze investment opportunities.

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Corporate Finance Analyst

Corporate Finance Analysts analyze the financial performance of businesses and organizations. They use this information to make recommendations about investment decisions, financing decisions, and other financial matters. This course can help Corporate Finance Analysts by providing them with the quantitative modeling skills they need to analyze financial performance more effectively and make better recommendations. Those interested in becoming Corporate Finance Analysts may find this course particularly helpful due to its focus on using statistical methods and modeling to analyze financial performance.

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Credit Analyst

Credit Analysts assess the creditworthiness of borrowers. They use this information to make recommendations to lenders about whether or not to lend money to borrowers. This course can help Credit Analysts by providing them with the quantitative modeling skills they need to assess creditworthiness more effectively and make better recommendations. Those interested in becoming Credit Analysts may find this course particularly helpful due to its focus on using statistical methods and modeling to assess risk.

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Insurance Analyst

Insurance Analysts analyze the financial performance of insurance companies. They use this information to make recommendations to investors about whether or not to buy or sell insurance company stocks. This course can help Insurance Analysts by providing them with the quantitative modeling skills they need to analyze financial performance more effectively and make better recommendations. Those interested in becoming Insurance Analysts may find this course particularly helpful due to its focus on using statistical methods and modeling to analyze financial performance.

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Market Research Analyst

Market Research Analysts conduct research to identify and understand the needs of consumers. They use this information to develop and implement marketing strategies. This course can help Market Research Analysts by providing them with the quantitative modeling skills they need to analyze research data more effectively and make better marketing recommendations. Those interested in becoming Market Research Analysts may find this course particularly helpful due to its focus on using statistical methods and modeling to analyze data.

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Business Analyst

Business Analysts use their knowledge of business processes and technology to help businesses improve their operations. They use a variety of techniques, including quantitative modeling, to analyze business data and make recommendations about how to improve efficiency and productivity. This course can help Business Analysts by providing them with the quantitative modeling skills they need to analyze business data more effectively and make better recommendations. Those interested in becoming Business Analysts may find this course particularly helpful due to its focus on using statistical methods and modeling to support decision-making.

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Operations Research Analyst

Operations Research Analysts use mathematical and statistical models to solve problems in a variety of industries, including manufacturing, healthcare, and transportation. They use these models to make recommendations about how to improve efficiency and productivity. This course can help Operations Research Analysts by providing them with the quantitative modeling skills they need to develop and use more accurate and sophisticated models. Those interested in becoming Operations Research Analysts may find this course particularly helpful due to its emphasis on using statistical methods and modeling to support decision-making.

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