Quote from: bitinlet on February 26, 2014, 12:12:13 AM

Thanks for the replies, Calhil, Queen and genco. All good points/suggestions. I suppose it would have been useful for me to describe what I was hoping to accomplish from this. My goal was to monitor the overall crypto-market. You can take a quick look at this market here: http://coinmarketcap.com/

Basically, my goal was taking each of these 100 currencies (which is cross-sectional data) and monitoring their behavior over time (longitudinal or time-series data). Combined, we have ourselves a nice panel data set (both cross-sectional and time-series) across cryptocurrencies.

I'd prefer to have a multitude of variables. But, the one's at my disposal are: Price, 24 Hour Volume, and Supply. I can obviously create change variables (such as change in price, change in volume and change in supply).

So, take the historical panel data (over time, across the 100 crypto-currencies), create a model based on those variables (maybe change in price is a function of change in volume and change in supply) and obtain regression results. After we get the results, we can then use those coefficients to forecast each crypto-currency's daily change.

This could be used to pick and choose where you want to place your btc. Maybe today, the model tells me megacoin should yield the best price change. Tomorrow it says doge.

That sort of thing. THanks again for you comments and I'm still interested in your feedback now that I've filled in a bit more info....

Been some time since the last post on this topic. Have you continued the project?