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Quantdare

Daring to quantify the markets.Markets are made of numbers, so they should be measurable. It is not easy, but we dare. Our weapons: R, Python, Artificial Intelligence or Machine Learning.

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Quantdare | quantdare.com Reviews
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Daring to quantify the markets.Markets are made of numbers, so they should be measurable. It is not easy, but we dare. Our weapons: R, Python, Artificial Intelligence or Machine Learning.
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artificial intelligence,asset management,risk management,python,quant dare,categories,daring,rcobo,aparra,t fuertes,mplanaslasa,psanchezcri,principal component analysis,ogonzalez,p lópez,libesa,fjrodriguez2,j gonzález,about us,artificial intelligence 27
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Quantdare | quantdare.com Reviews

https://quantdare.com

Daring to quantify the markets.Markets are made of numbers, so they should be measurable. It is not easy, but we dare. Our weapons: R, Python, Artificial Intelligence or Machine Learning.

INTERNAL PAGES

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1

Quantdare

http://quantdare.com/author/mplanaslasa

Lévy flights. Foraging in a finance blog. Markov Switching Regimes say… bear or bullish? 8220;Let’s make a deal”: from TV shows to identifying trends. Sir Bayes: all but not naïve! Confusion matrix & MCC statistic. Una aproximación Risk Parity. Cópulas: una alternativa en la medición de riesgos. El filtro de Kalman. Por qué usar rendimientos logarítmicos? Machine Learning: A Brief Breakdown. Returns clustering with k-Means algorithm. What is the difference between Bagging and Boosting?

2

Quantdare

http://quantdare.com/author/ttannatt

Graph theory: connections in the market. Hierarchical clustering, using it to invest. Outliers: Looking For A Needle In A Haystack. Could the Stochastic Oscillator be a good way to earn money? Performance and correlated assets. Cointegración: Seguimiento sobre cruces cointegrados. Por qué usar rendimientos logarítmicos? Machine Learning: A Brief Breakdown. Returns clustering with k-Means algorithm. What is the difference between Bagging and Boosting? Sir Bayes: all but not naïve!

3

Quantdare

http://quantdare.com/author/aparra

Applying Genetic Algorithms to define a Trading System. There are some things impossible to quantify. How delicious are your mom’s cookies or how exciting is to train a neural network, for example. But financial markets are made of numbers among other things. They should be measurable, quantifiable. Nobody said it was easy. But we dare. Por qué usar rendimientos logarítmicos? Machine Learning: A Brief Breakdown. Returns clustering with k-Means algorithm. Sir Bayes: all but not naïve!

4

Comparing ETF Sector Exposure Using Chord Diagrams

http://quantdare.com/2016/10/comparing-sector-exposure-using-chord-diagrams

Playing with Prophet on Financial Time Series. Using Multidimensional Scaling on financial time series. Exploring Extreme Asset Returns. La Paradoja de Simpson. Caso Práctico: Multidimensional Scaling. There are some things impossible to quantify. How delicious are your mom’s cookies or how exciting is to train a neural network, for example. But financial markets are made of numbers among other things. They should be measurable, quantifiable. Nobody said it was easy. But we dare. The chord chart is an ex...

5

Using Multidimensional Scaling on financial time series

http://quantdare.com/2017/01/using-multidimensional-scaling-on-financial-time-series

Playing with Prophet on Financial Time Series. Comparing ETF Sector Exposure Using Chord Diagrams. Exploring Extreme Asset Returns. La Paradoja de Simpson. Caso Práctico: Multidimensional Scaling. There are some things impossible to quantify. How delicious are your mom’s cookies or how exciting is to train a neural network, for example. But financial markets are made of numbers among other things. They should be measurable, quantifiable. Nobody said it was easy. But we dare. Sir Bayes: all but not naïve!

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turingfinance.com turingfinance.com

Stuart Gordon Reid

http://www.turingfinance.com/author/StuartReid

Turing Finance August 26, 2016. Posts ByStuart Gordon Reid. Lossless Compression Algorithms and Market Efficiency? April 18, 2016 StuartReid. Hacking The Random Walk Hypothesis. We applied the NIST suite of cryptographic tests for randomness to binarized daily market returns. Overall the NIST suite failed on the data. This result was taken to mean that markets are not quite the . Read More. Stock Market Prices Do Not Follow Random Walks. February 8, 2016 StuartReid. A Non-Random Walk down Wall Street.

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Simulated Annealing for Portfolio Optimization

http://www.turingfinance.com/simulated-annealing-for-portfolio-optimization

Turing Finance August 31, 2016. Simulated Annealing for Portfolio Optimization. This article applies the Simulated Annealing (SA) algorithm. Basic Simulated Annealing Algorithm. This real-world concept may, at first, seem quite difficult to translate into an optimization algorithm, however, with some 'algorithmic license' the resulting algorithm is actually quite simple. The simulated annealing algorithm for portfolio optimization essentially only consists of eleven steps, only two of which are reall...

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Computational Decision Making Methods

http://www.turingfinance.com/computational-decision-making-for-finance

Turing Finance August 21, 2016. Computational Decision Making Methods. Artificial intelligence is broadly defined as the ability of an agent or a model to make either optimal or satisficing decisions. How should I allocate my portfolio? Should I buy this stock or not? What should I pay for this security? This article will discuss the applications and challenges of computational decision making and present a taxonomy of computational decision making methods, their strengths, and their weaknesses. I ho...

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To quantify the markets. Suscribe to our newsletter. Using Multidimensional Scaling on financial time series. Applying Genetic Algorithms to define a Trading System. Graph theory: connections in the market. Lévy flights. Foraging in a finance blog. Data Cleansing & Data Transformation. Comparing ETF Sector Exposure Using Chord Diagrams. Learning with kernels: an introductory approach. SVM versus a monkey. Make your bets. Clustering: “Two’s company, three’s a crowd”. Lasso applied in Portfolio Management.

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