This is a summary of links featured on Quantocracy on Sunday, 12/13/2015. To see our most recent links, visit the Quant Mashup. Read on readers!
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Interview with Michael Bryant [Better System Trader]Creating robust trading strategies can be a difficult task, sometimes taking months or even years to generate something you find acceptable. Even then, once you start trading it live there is no guarantee itll work in the future. With strategy creation being such an involved process at times, how would you like it if you could just tell the computer the results you wanted and let it figure out
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Maintaining a database of price files in R [R Trader]Doing quantitative research implies a lot of data crunching and one needs clean and reliable data to achieve this. What is really needed is clean data that is easily accessible (even without an internet connection). The most efficient way to do this for me has been to maintain a set of csv files. Obviously this process can be handled in many ways but I found very efficient and simple overtime to
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The Halloween effect with python and pandas [Shifting Sands]The Halloween effect, aka sell in May and go away is the observation that equity market returns tend to be worse over summer time in the northern hemisphere. Anyone who has followed markets for a while has probably noticed a distinct lull over the summer period. But can we quantify this effect, does it really exist? We can and it does, and its simple to show with less than 10 lines of
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Crude Oil and Trend Following [Wisdom Trading]Crude oil has been in the news a lot recently. Just last week, after the OPEC meeting, its price declined by over 10%. With a lot of volatility, we wanted to test how a trend following strategy would have performed on the futures contract in recent history. Here is a quick post showing our benchmark Wisdom State of Trend Following system and the performance it would have produced on a