machine learning

The signals of linear regression

There are some problems with linear regression. It can only capture first-order relationships, but when the signal to noise ratio is .05:1, then there’s not much point in worrying about that. Another problem is that it’s slow if you do it the typical way. Most people will just use Matlab’s backslash operator \, or R’s […]

stocastic

Machine Learning: Regression whith stochastic volatility

I had gotten there by a long search that had gone from machine learning, to fast Kalman filters, to Bayesian conjugate linear regression, to representing uncertainty in the covariance using an inverse Wishart prior, to making it time-varying, and allowing heteroschedasticity. I was thinking whith my koukio friends and this paper had all the pieces […]

c++ machine learning

Best Programming Language for Trading Systems?

Currently, I’m working on Learning Machine’s submission for Max Dama’s QuantCup. That involves optimising a “price-time priority limit order matching engine”. More simply, it means ‘making a system which matches buy and sell orders really fast’. * As per the competition rules, I’m programming our entry in the C programming language. But when it comes to our […]

machine learning and trading

Why does value investing work?

Rational, intelligent investors should not simply accept the fact that value investing works simply because it has been quite successful over the decades. Why should we buy “undervalued” assets and expect to sell them at “fair value” in the future? And what process, if any, causes the price to revert back to this “fair value”? […]

.net development

Machine learning and .NET technology initiative

it sounds like a simple question, but the answer isn’t so simple. .NET is a technology initiative, a computing vision, a business strategy, a development platform, a way to deliver services on the Web and probably a lot more things besides. Got all that? ZDNet.com’s Tech Update calls .NET “the ambitious, bet-the-company initiative that aspires […]