"only half of it"
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Wyck Brown commented on Marco Tavora's blog post How the Mathematics of Fractals Can Help Predict Stock Markets Shifts"The initial premise in this article on mean reversion as it relates to asset returns is flawed along the lines of a common misunderstanding of market-based mean reversion. The article states:
"In contrast, the price of a mean-reverting stock…"
Norberto J. Sanchez liked Marco Tavora's blog post How the Mathematics of Fractals Can Help Predict Stock Markets ShiftsWilliam Stowe liked Marco Tavora's blog post How the Mathematics of Fractals Can Help Predict Stock Markets ShiftsNorberto J. Sanchez liked Marco Tavora's blog post How the Mathematics of Fractals Can Help Predict Stock Markets ShiftsHow the Mathematics of Fractals Can Help Predict Stock Markets Shifts
In financial markets, two of the most common trading strategies used by investors are the momentum and mean reversion strategies. If a stock exhibits momentum (or trending behavior as shown in the figure below), its price on the current period is more likely to increase (decrease) if it has…See More
Mike Andresen liked Marco Tavora's blog post Machine Learning and Particle Motion in Liquids: An Elegant LinkMachine Learning and Particle Motion in Liquids: An Elegant Link
The gradient descent algorithm is one of the most popular optimization techniques in machine learning. It comes in three flavors: batch or “vanilla” gradient descent (GD), stochastic gradient descent (SGD), and mini-batch gradient descent which …See More
Profile Information
- Short Bio
- I am a theoretical physicist and data scientist. During my Ph.D. at New York University, my research was on quantum many-body systems out of equilibrium, one of today's hottest research fields in theoretical physics. In 2015 I earned a Ph.D. for my thesis "Prethermalization, universal scaling at macroscopic short times, and thermalization following a quantum quench." Subsequently, I spent two years as a postdoctoral researcher focusing on applications of computational physics methods to areas such as quantum chaos, non-equilibrium quantum dynamics, and thermalization viability. I've published several articles in the most prestigious peer-reviewed journals in the world.
I have 15 years of experience building mathematical/statistical models spanning a wide range of disciplines, including: non-equilibrium quantum systems, marketing attribution for digital and offline channels (using machine learning, game theory, stochastic processes and hierarchical Bayesian models), influencer marketing, marketing mix modeling, record linkage/data matching/entity recognition, conjoint analysis (using support vector machines), bidding optimization for digital media (using original functional optimization techniques) and many others.
I was a speaker at the American Physical Society (APS) March Meeting, the largest physics conference in the United States, in 2013, 2015 and 2016 (for more details and also information about other conferences see my personal website www.marcotavora.me)
In 2017 I co-founded Prior Solutions, a data-driven consulting company with clients in more than ten countries around the world.
- My Web Site Or LinkedIn Profile
- http://marcotavora.me
- Field of Expertise
- Data Science, Machine Learning, Deep Learning
- Professional Status
- Executive
- Years of Experience:
- 15
- Your Company:
- Prior Solutions
- Industry:
- Consulting
- Your Job Title:
- Co-Founder and CTO
- How did you find out about DataScienceCentral?
- Interests:
- Contributing, Networking
- What is your Favorite Data Mining or Analytical Website?
- http://towardsdatascience.com
- What Other Analytical Website do you Recommend?
- http://medium.freecodecamp.org
Marco Tavora's Blog
How the Mathematics of Fractals Can Help Predict Stock Markets Shifts
Posted on July 4, 2019 at 12:30am 1 Comment 3 Likes
In financial markets, two of the most common trading strategies used by investors are the momentum and mean reversion strategies. If a stock exhibits momentum…
Deep Learning Explainability: Hints from Physics
Posted on May 20, 2019 at 11:46am 0 Comments 2 Likes
Nowadays, artificial intelligence is present in almost every part of our lives. Smartphones, social media feeds, recommendation engines, online ad networks, and navigation tools are some…
Machine Learning and Particle Motion in Liquids: An Elegant Link
Posted on May 1, 2019 at 4:57am 0 Comments 1 Like
The gradient descent algorithm is one of the most popular optimization techniques in machine learning. It comes in three flavors: batch or “vanilla” gradient…
ContinueThe Approximation Power of Neural Networks (with Python codes)
Posted on May 1, 2019 at 4:52am 0 Comments 0 Likes
Introduction
It is a well-known fact that neural networks can approximate the output of any continuous mathematical function, no matter how complicated it might be. Take for instance the function below:…
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