WEEKLY DIGEST 2014, November 16 - 23 for Quantitative Analysis, Trading and Development
Quantitative Trading involves the use of computer algorithms and programs based on simple or complex mathematical models to identify and capitalize on available trading opportunities. At the back end, quant trading also involves research work on historical data with an aim to identify profit opportunities.
Goldman becomes largest investor after taking $15 million stake, will be
strategic force as it will help roll out program to its clients. - the article
As quantitative investment methods expand with the increasingly rapid pace of technological innovation, Goldman Sachs Group Inc (NYSE:GS)
today is reported to have invested $15 million in a start-up that
analyzes not just numeric data – as most quantitative programs currently
do – but considers textual context.
The market will go up or down in the next two weeks but this pattern cannot establish the direction with high confidence. As a matter of fact, it could be just a random pattern and we will know more about that when the sample gets close to 250 trades. Given its current frequency of occurrence, this can take about 80 more years. If this post survives in some archive, some quant of the future may confirm that.
Money Management – the Good, the Bad and the Ugly.
The infatuation of futures traders with the subject of money management, (more aptly described as position sizing), is something of a puzzle for someone coming from a background in equities or forex. The idea is, simply, that one can improve one’s trading performance through the judicious use of leverage, increasing the size of a position at times and reducing it at others.
GPU in Python Talk at SyPy Meetup.
20 min talk at Sydney Python (SyPy) meetup on Dec 4th organised by Atlassian (Level 6 341 George St, Sydney) on Using the GPU from Python.
