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  • The Intuitions Behind Bayesian Optimization with Gaussian Processes

    by Charles Brecque on KDnuggets
    In certain applications the objective function is expensive or difficult to evaluate. In these situations, a general approach consists in creating a simpler surrogate model of the objective function which is cheaper to evaluate and will be used instead to solve the optimization problem. Moreover, due to the high cost of evaluating the objective function, an iterative approach is often recommended. Iterative optimizers work by iteratively requesting […]
  • Forecasting Stock Price Swings with Social Media
    by Charles Brecque on 21/02/2019 at 20:25

    Instagram comments are more important than you thinkToday, more than ever, consumers are able to connect and voice their opinions about their favourite brands through social media. As a result, a brand’s reputation can be made or broken based on their online strategy. Dolce & Gabbana’s downfall and designing clothes which look good on instagram (e.g. big logos) are examples of this new trend. The aim of this short article is to see if we can forecast price swings with […]

  • Forecasting Earning Surprises with Machine Learning
    by Charles Brecque on 12/02/2019 at 13:54

    How to predict which companies will Beat or Miss their Analyst Earnings EstimatesListed companies produce quarterly earnings reports which can cause significant price movements when the results deviate from what the analysts had estimated. This is because according to the Efficient-market hypothesis, asset prices fully reflect all available information and will as a result factor in consensus estimates. In this article we are going to see how we can use Machine Learning to predict whether a […]

  • Risk Management with Clustering
    by Charles Brecque on 08/02/2019 at 14:16

    How to uncover structure bellow the surfaceEvery portfolio manager is evaluated on their Sharpe ratio which measures the associated risk of their return on investment and is given by the following formula:Where:Rp is the return of the portfolioRf is the risk-free return (e.g. treasury bonds)Sigma p is the standard deviation of the portfolio’s excess return and acts as a proxy of the portfolio’s riskThe Sharpe ratio has often been criticised because it assumes that […]

  • Value Investing with Machine Learning
    by Charles Brecque on 30/01/2019 at 14:36

    Your favourite holding period doesn’t have to be forever…The Oracle of Omaha once said:“Price is what you pay, value is what you get.”Warren BuffetBut how can you be certain that you are paying a fair price for an investment? How can you make the most of a fair or unfair situation?This article will show you how you can easily increase your certainty with transparent and interpretable Machine Learning. To do this, we will use Mind Foundry’s Automated […]

  • Augmenting Investment Analysts with Data Science
    by Charles Brecque on 24/01/2019 at 18:49

    (source)How fundamental investing can benefit from Machine LearningFundamental investing consists in building a thesis of how the world spins and where it is heading, and then identifying relevant investments that are aligned with the strategic vision. The second part can be quite tedious as it implies combing through the financial metrics of hundreds to thousands of corporations that fit within the strategy to identify investments that are under or over priced to then buy or sell […]

  • Bayesian Optimization & Quantum Computing
    by Charles Brecque on 08/01/2019 at 14:09

    (source)How Bayesian Optimization can help Quantum Computing become a realityQuantum computers have the potential to be exponentially faster than traditional computers which will revolutionise the way we currently solve a number of applications. You can find out how in this detailed article but we are still years away from general purpose Quantum Computers. However, for certain applications Bayesian Optimization can help stabilise quantum circuits and this article will summarise how OPTaaS […]