Maybe you've seen this, but we had an intern do some investigation of stock volume anomalies with NuPIC via Grok custom metrics: http://numenta.com/blog/detecting-anomalies-in-stock-volumes.html
We are doing further exploration and research on the application of our algorithms to stock price and volume data - as well as social media data. Hopefully I can provide more details soon. --------- Matt Taylor OS Community Flag-Bearer Numenta On Mon, Dec 15, 2014 at 11:17 AM, Nag Kiran <[email protected]> wrote: > I guess this trick could work in a penny stocks which are mostly bound to > circular trading. These kind of stocks have very little or no influence of > external real time factors. If at all there is any external factor, a simple > trigger might be an anomaly on nupic. But of course, nupic should be able to > learn about these kind of stocks on a ms basis. Bringing in social media > like twitter mentions, web alerts as an external factor might even add more > weight as a "positive anomaly" to take an action on the stock. > Do you think this makes any sense ? just my initial thoughts after reading > this thread. > > > On Mon, Dec 15, 2014 at 7:35 PM, Matthew Taylor <[email protected]> wrote: >> >> Sounds interesting. How would one get this data? >> --------- >> Matt Taylor >> OS Community Flag-Bearer >> Numenta >> >> >> On Fri, Dec 12, 2014 at 5:57 PM, Michael Davidson <[email protected]> >> wrote: >> > Daniel Bell <john.mrdaniel.bell@...> writes: >> > >> >> >> >> >> >> That is certainly understandable and fair. So this is a practical >> > limitation of not having visibility on all of the relevant factors. >> >> Could nupic do this if we theoretically did have all the features that >> > represent the state of the system? >> >> Would a subset of these features, no matter how large, be able to >> >> resolve >> > 'reasonable' predictions? >> >> >> >> >> >> >> >> On Wed, Dec 3, 2014 at 3:16 PM, Matthew Taylor >> > <[email protected]> wrote:Hi Daniel, >> >> Can any one human being predict stock market prices with any accuracy? >> >> If you think about how many factors actually affect even a single >> >> stock price (economy, inflation, weather, time of year, time of day, >> >> moods of investors, CEO scandals, other stock prices, I could go on >> >> and on...), it would be extremely hard to identify them all, much less >> >> isolate them into individual scalar values and feed them into NuPIC. >> >> There are just too many unknown factors involved. Even the best human >> >> minds can't do it. >> >> --------- >> >> Matt Taylor >> >> OS Community Flag-Bearer >> >> Numenta >> >> >> >> On Tue, Dec 2, 2014 at 5:51 PM, Daniel Bell >> >> <john.mrdaniel.bell <at> googlemail.com> wrote: >> >> > Hello, >> >> > >> >> > In one of the talks Jeff Hawkins mentioned that stock market data >> >> > cannot be >> >> > predicted with numenta. Why is this the case? Is it not an >> >> > appropriate >> >> > problem space? >> >> > >> >> > My question here really is, what are the limitations and how do we >> >> > identify >> >> > problem spaces that will work well with numenta and not work well >> >> > prior to >> >> > an attempts to train/predict? >> >> > >> >> > Regards, >> >> > >> >> > Daniel >> >> >> >> >> > >> > >> > Guys, >> > >> > I have for sometime wondered if nupic could take any stock's Depth of >> > Market >> > datafeed (Level II and Time&Sales) and learn the patterns of market >> > participants by their ID's as they post, change and cancel their bids, >> > asks, >> > sizes at different levels to game the stock price. After several days >> > (weeks?) of learning on this high frequency data from the same stock, I >> > wondered if nupic would be able to discern a relationship between the >> > pattern of action throughout the day of certain key participants it had >> > classified as market movers (anomaly detection?) and start to make >> > predictions of price along with confidence scores at different time >> > offsets? >> > When you use the timestamped quote changes of the participants at every >> > level as price is discovered from ms to ms, would nupic show a better >> > grasp >> > of how these influences collude to shove the price one way or another a >> > few >> > seconds or minutes into the future? >> > Macro news forces like economy, inflation, weather, etc. might introduce >> > some noise but would be priced in quickly and in any case, would be >> > represented by the moves of Market Makers being learned from the stream. >> > >> > (Sorry for the crummy run-on sentences, I'm in a hurry tonight.) >> > >> > Michael Davidson >> > >> > >> > >> > >> > >> >
