FOREX correlation and causality

Consider the seven major currency pairs, sampled hourly over the last six months. We calculate the pairwise Pearson correlation coefficients to determine the degree with which each pair “moves” together: Values near one or negative one indicate high correlation, values with lower absolute value less so. Positive values indicate movement in the same direction; negative […]

a graph-based, large-scale data model for NLP cross-referencing

I find myself in a situation where my team needs to combine several natural language processing (NLP) [1] techniques, each conducted upon the same large set of texts, to derive critical business conclusions. Particularly, we need a way to cross-reference analyses based on common key words across sentences. Toward that end, I designed the following […]

blockchain is punk

Wide distribution of power lies at the heart of anarchistic thinking. While “punk” and “anarchy” do not necessarily imply one another, they often overlap. Punks tend to balk at centralized authority, as do anarchists. A short leap of logic concludes that we therefore dislike centralized technology. Concentration in technology long parallels concentration in political power. […]

fans control the music: using AI to measure fan enthusiasm at EDC

We invented technology to enhance the fan/performer connection. Vote for Team Ambience at EDC! DJs and more traditional musicians require realtime audience feedback during performances. However, often we cannot see our audience—their movement, their facial expressions, etc.—during shows due to stage lighting. Therefore we cannot gauge their enthusiasm, and therefore cannot alter our performance to respond. […]

women’s style recommendation with artificial intelligence (part #2)

In “women’s style recommendation with artificial intelligence (part #1)”, I introduced my work toward developing artificial intelligence (AI) for fashion and style recommendation. Essentially, its an expert system built on a Bayesian belief network. Now I discuss model validation and next steps in the design iteration process. I first wanted to see if the trained […]

women’s style recommendation with artificial intelligence (part #1)

Introduction We know several basic style “rules” (ha!) based on body shape: Skirts: “Apple” Body Shape: IF body shape is apple AND skirt has front zipper THEN don’t wear IF body shape is apple AND skirt has side zipper THEN wear IF body shape is apple AND skirt has no zipper THEN wear “Rectangular” Body […]

toward a gene panel for psychiatric violence

I recently developed a method for specifying a comprehensive gene list for investigating genes related to psychiatric violence, which I describe below. First though, here’s a cool picture from the analysis: Method I started by extracting a list of diseases involving violence from [1], removing epilepsy, dementia, mental retardation (is there a better word for […]

machine learning in FOREX (part one: establishing a performance baseline)

Introduction We’ve been applying machine learning to FOREX price prediction. The performance of our models varies widely, so to establish a baseline we created a simple linear regression model with which we can compare performance of more sophisticated models against. What We Are Trying To Do Given a time-series of 26 four-hour price samples, we […]

autocorrelation in FOREX

To inform the construction of a machine learning-based price prediction algorithm, we want to understand how many lags prove statistically significant with regard to autocorrelation in the seven major FOREX pairs. So we first choose 10,000 random time points between January 1, 2000 and January 1, 2017 for each of the seven pairs. Then we […]