Showing posts with label Mathematics. Show all posts
Showing posts with label Mathematics. Show all posts

2/23/2025

No te Pierdas Aprendemos Juntos 2030: Inspiración y Aprendizaje en Cada Charla

Aprendemos Juntos 2030" es una iniciativa de BBVA que no te puedes perder por su calidad, diversidad y la impresionante trayectoria de sus invitados, quienes aportan conocimiento y experiencia única. He visto muchas charlas sobre diversos temas y ninguna me ha decepcionado. Si ya no sabes qué ver en tus plataformas de streaming, échale un vistazo y aprendamos juntos (texto revisado por un LLM) En BBVA creemos posible una vida mejor en un mundo más sostenible y queremos ofrecerte las herramientas para enfrentar los grandes retos del futuro. En este canal descubrirás las historias más inspiradoras y los contenidos más útiles para afrontar tu día a día, animándonos a luchar por una sociedad más inclusiva y respetuosa con el planeta. Suscríbete y no te pierdas todas nuestras novedades, ¡te esperamos! https://www.youtube.com/@AprendemosJuntos/featured

- Pedro

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2/08/2025

Beyond the 60/40 Rule: How Merton’s Theory Optimizes Asset Allocation

A brilliant article by The Economist explores probabilities, risk management, and investment strategies for your hard-earned savings. In a simple, insightful, and compelling way, it revisits a half-century-old investment theory by Robert C. Merton, based on his paper "Lifetime Portfolio Selection Under Uncertainty: The Continuous-Time Case." Merton’s model challenges the traditional 60/40 portfolio rule, instead advocating for an optimal asset allocation based on an investor’s individual risk aversion. Using the Constant Relative Risk Aversion (CRRA) utility function and your risk aversion, his framework determines the ideal split between high-risk assets (stocks) and safe assets (bonds) to maximize returns. In essence, Merton suggests that the percentage allocated to risky assets should be equal to their excess expected return over the risk-free alternative, divided by both personal risk aversion and the square of the risky asset’s volatility. This approach leads to a more dynamic asset allocation, adjusting as these variables change. Take a few minutes to digest this—I'll need more than a couple myself. While the theory offers a sophisticated and theoretically sound approach, applying it in practice is not straightforward. It requires precise estimations of key variables and may involve positions that some investors are unwilling or unable to take (such as short-selling). Additionally, one must be aware of and willing to accept the underlying assumptions and trade-offs. Interestingly, studies suggest that this investment strategy has stood the test of time, potentially delivering a significant premium over the conventional 60/40 approach. I must admit that, despite holding an MSc in Finance, I had never come across this theory before. It has certainly piqued my interest, and I plan to explore it further to see if it can be applied to my portfolio management. Hope you enjoy the article as much as I did! (text revised by a LLM) How much happiness does money buy? https://www.economist.com/christmas-specials/2024/12/19/how-much-happiness-does-money-buy from The Economist

- Pedro

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1/25/2025

How Math Connects Fireflies, Clocks, and Computing

A fascinating video featuring Steve Strogatz explores the power of mathematics and how it reveals hidden patterns in the world that would otherwise remain undiscovered. In one example, Strogatz discusses a study where he and his colleagues explained why fireflies begin flashing in unison. This phenomenon, initially thought to be purely biological, was redefined as a mathematical problem. Building on these findings, engineers developed a method to synchronize small electronic clocks, demonstrating how the mathematical principles from the study extend to fields like distributed computing and sensor networks. Mathematical abstraction—a cornerstone of mathematical reasoning—strips away irrelevant details, allowing us to focus on the fundamental elements of a problem. This approach uncovers connections and commonalities across diverse phenomena and scientific disciplines. I hope you enjoy the video as much as I did! (text revised by a LLM) https://youtu.be/kV-pnbtfraE

- Pedro

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1/11/2025

How Games Shaped Probability, Strategy, and Economics

An excellent Economist’s Podcast that features Kelly Clancy—a neuroscientist, physicist, and author of Playing With Reality—discussing the profound impact of games on our lives and societal dynamics. Clancy emphasizes that games are a powerful form of learning, shaping how we think and interact with the world. Games like Chess, Go, Dice, and Cards introduced humanity to the concept of uncertainty, paving the way for probability theory (via Pascal and Fermat’s correspondence) and, subsequently, modern statistics. The episode also highlights the critical role of war games, such as Chess and Go, which evolved into more complex systems like Kriegsspiel. The latter was instrumental in training military officers and predicting battlefield outcomes, particularly during World War II. Clancy then connects this history to Game Theory, one of the most significant developments in economics, pioneered by John von Neumann. Game Theory has informed concepts like nuclear deterrence and continues to influence modern strategic thinking. However, it’s essential to complement it with insights from behavioral economics to understand human decision-making fully. The takeaway? Games are not just entertainment; they’re essential tools for education and skill-building. They can influence our behavior, shape our knowledge, and enhance problem-solving abilities. For instance, Miegakure (https://miegakure.com/) challenges players to solve problems in four dimensions—a fascinating way to expand your cognitive boundaries. All of this in just 38 minutes (at normal speed)—a fantastic return on your time! (revised by a LLM) The surprising ways in which games have changed the world—an interview with Kelly Clancy https://www.economist.com/podcasts/2024/11/27/the-surprising-ways-in-which-games-have-changed-the-world-an-interview-with-kelly-clancy

- Pedro

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12/07/2024

Einstein: Del Teórico al Comprobado

Es absolutamente fantástico que todavía sigamos comprobando aquello que Einstein había previsto únicamente desde un punto de vista teórico, basándose puramente en sus premisas, conocimientos de física y matemáticas. Hay personas que han tenido (y algunas aún tienen) mentes asombrosas. No conocía lo que era el ZigZag de Einstein, pero ese video lo explica de una forma muy sencilla y clara. (texto revisado por LLM) EL PAÍS https://elpais.com/ciencia/2024-12-07/descubren-el-primer-zig-zag-de-einstein.html

- Pedro

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11/23/2024

Benoît Mandelbrot: Why Fractals and Power Laws Redefine Science and Economics

This 7-hour interview with Benoît Mandelbrot offers a captivating deep dive into his life, encompassing his childhood, upbringing, education, professional career, and groundbreaking research. It provides a thorough perspective on his unique approach to science, emphasizing the interconnectedness of various fields—mathematics, physics, economics, biology, finance, and more. Key insights I took away: Family Influence: Mandelbrot’s family played a critical role in nurturing his interest in mathematics and creating an environment for his intellectual development. Geometric Approach to Mathematics: He championed a visual, geometrical perspective over purely analytical methods. Mentorship and Collaboration: Mandelbrot’s interactions with intellectual giants such as Kolmogorov, Nabokov, Heisenberg, von Neumann, Gaston Maurice Julia, Paul Lévy, and Max Delbrück enriched his understanding across disciplines. Power-Law Distribution: While randomness in physics follows Gaussian distributions, Mandelbrot highlighted the dominance of power-law distributions in social sciences (e.g., Pareto income distribution, city sizes). Role of Private Sector: IBM provided Mandelbrot with the resources and freedom to pursue his groundbreaking work. Measuring Roughness and Fractals: Mandelbrot’s pioneering study of fractals revealed their significance in understanding patterns across multiple domains, including finance. Insights into Finance and Economics: He argued that finance and economics are fundamentally different from physics. Traditional Gaussian approaches to risk management fail to capture the realities of financial systems, which are better modeled using fractal geometry and power-law distributions. Some individuals truly stand apart, and Mandelbrot is one of those rare, extraordinary minds. Personal Takeaway For my own work in finance and economics, this interview reinforced the urgency of studying Mandelbrot’s approaches to risk and systems in depth. If you’re interested and willing to invest the time, I highly recommend watching this interview—it’s an inspiring exploration of a brilliant thinker’s journey. (text revised by LLM) "...Benoit B.[n 1] Mandelbrot[n 2] (20 November 1924 – 14 October 2010) was a Polish-born French-American mathematician and polymath with broad interests in the practical sciences, especially regarding what he labeled as "the art of roughness" of physical phenomena and "the uncontrolled element in life".[6][7][8] He referred to himself as a "fractalist"[9] and is recognized for his contribution to the field of fractal geometry, which included coining the word "fractal", as well as developing a theory of "roughness and self-similarity" in nature.[10] In 1936, at the age of 11, Mandelbrot and his family emigrated from Warsaw, Poland, to France. After World War II ended, Mandelbrot studied mathematics, graduating from universities in Paris and in the United States and receiving a master's degree in aeronautics from the California Institute of Technology. He spent most of his career in both the United States and France, having dual French and American citizenship. In 1958, he began a 35-year career at IBM, where he became an IBM Fellow, and periodically took leaves of absence to teach at Harvard University. At Harvard, following the publication of his study of U.S. commodity markets in relation to cotton futures, he taught economics and applied sciences. Because of his access to IBM's computers, Mandelbrot was one of the first to use computer graphics to create and display fractal geometric images, leading to his discovery of the Mandelbrot set in 1980. He showed how visual complexity can be created from simple rules. He said that things typically considered to be "rough", a "mess", or "chaotic", such as clouds or shorelines, actually had a "degree of order".[11] His math- and geometry-centered research included contributions to such fields as statistical physics, meteorology, hydrology, geomorphology, anatomy, taxonomy, neurology, linguistics, information technology, computer graphics, economics, geology, medicine, physical cosmology, engineering, chaos theory, econophysics, metallurgy, and the social sciences.[12] Toward the end of his career, he was Sterling Professor of Mathematical Sciences at Yale University, where he was the oldest professor in Yale's history to receive tenure.[13] Mandelbrot also held positions at the Pacific Northwest National Laboratory, Université Lille Nord de France, Institute for Advanced Study and Centre National de la Recherche Scientifique. During his career, he received over 15 honorary doctorates and served on many science journals, along with winning numerous awards. His autobiography, The Fractalist: Memoir of a Scientific Maverick, was published posthumously in 2012. ..." https://en.wikipedia.org/wiki/Benoit_Mandelbrot https://youtube.com/playlist?list=PLVV0r6CmEsFwl4HlrIKxKmdpBAGYJ9AbR&si=9_ccF1Tln7wRLTjy

- Pedro

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