Murena + Quant = Murena Find
https://linuxnews.de/murena-quandt-murena-find/ #murena #quant

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https://fraxcesco.substack.com/p/the-rei-framework-connecting-artificial #REI #AI #DeFAI #alpha #quant

New #introduction: I’m the Mark Andrews Fellow in Book Science at OBNS (Old Books New Science) Lab, University of Toronto, and a #MedievalManuscripts scholar and cataloguer. My research mainly focuses on later #medieval European #manuscripts with an emphasis on scientific and #quantitative methods, #materiality, and provenance studies.
#BookScience #codicology #palaeography #BookHistory #HeritageScience #parchment #DigitalHumanities #quant #statistics

New #introduction: I’m Oschinsky Research Associate at Cambridge Univ Library, Fellow of Girton College, & a #MedievalManuscripts scholar & cataloguer. My research mainly focuses on later #medieval European #manuscripts with an emphasis on #quantitative methods, materiality, & provenance. I’m about to publish a book on #parchment & have started writing another on legal manuscripts.
#codicology #palaeography #BookHistory #LegalHistory #DigitalHumanities #quant #BookHistodons #Medievodons

Time for #introduction

I’m Dennis and I live in Jersey City. I like #cooking #games #math #comedy and a bunch of other stuff.

Professionally, I do #nlproc #nlp #ml in #finance #quant, but I’m a #stayathomedad to a cute little velociraptor until November. Say hi!

A colleague of mine in psychology recently shared with my the idea of "the troubling trio", characterized by: (1) low statistical power, (2) a surprising result, and (3) a p value only slightly less than 0.05. I hadn't heard this particular phrase before, so I'm sharing it. More people should know why the troubling trio is something to be troubled by, and should be on the lookout for this combination in their work. #datascience #stats #quant https://doi.org/10.1177/0956797615616374

Hi there ! #Introduction time

I have been working as a #datajournalist / #visualjournalist for 9 years, working almost exclusively with #rstats. I am based in #Switzerland.

I work for the Swiss French speaking media #LeTemps. I also teach #datajournalism to (non-geek) journalists. Initially trained as a computational biologist, I was a working as a #quant, before switching to #media

I am well versed into the #tidyverse and #rstats, especially #ggplot2 #sf for #datavisualisation & #ddj

#Introduction: I’m a #medieval #manuscripts scholar and cataloguer, and a Postdoctoral Fellow at University of Toronto. My research mainly focuses on later #MedievalManuscripts from western Europe, with an emphasis on #quantitative methods, materiality, and provenance studies. I’m about to publish my book on #parchment and have just started to write another book on legal manuscripts.
#codicology #palaeography #BookHistory #LegalHistory #DigitalHumanities #quant #BookHistodons #Medievodons

Die besten datensparsamen Suchmaschinen: unsere Artikelserie über Software-Alternativen #Datenschutz #duckduckgo #Givero #JörgBauer #Quant #Startpagecom #SwissCows https://tarnkappe.info/die-besten-datensparsamen-suchmaschinen-unsere-artikelserie-ueber-software-alternativen/

So took me much longer to port my stock trading algorithm over to a proper automated system then I hoped...

I knew I had something impressive because I had backtested a rudementary version of my algorithm and the ROI was astronomical. Problem was the platform I was using was very basic, it couldnt autotrade for me and was almost impossible to code anything too advanced anyway. But it did provide back testing. For some time after that i used the algorithm to trade manually, checking when it told me to buy or sell and doing it. while that proved out the ROI was real it didnt really reach its full potential as I would often trade sometime after the algorithm alerted me.

Now I have everything **finally** automated took two solid months but its working. I have thrown every stock I could find at it and after backing for a year, random years every time, different stock, not **once** has the algorithm lost me a penny at the end of any year. Some stocks it never traded on because the volume was too low and apparently it knows well enough to not go in on those stocks (not entirely sure how honestly even though i wrote the damn thing), for those stocks the ROI is 0 of course. But for every other stock I am coming in multiple times over buy&hold, even when the stock goes negative overall and crashes (it knows when to short)!!!!

I am so excited how well this is working out.

Threw together a parameter optimization algorithm for my stock trading algorithm last night. Nothing too ground breaking but hell-a useful and cool all the same.

There are about a dozen variables, some of which have some limited dependence on each other. I suspect the search space however is relatively simple based on my expiernce os optimizing it by hand with trial and error.

The challenge is the possible valid range of these variables is huge, most bounded at 0 but with a max that is in the hundreds of thousands.

The other challenge is that each test takes a few minutes to perform (simulated over a years worth of data one minute per data point). So even with some extreme multi-core usage and optimization it is too slow for a naive search algorithm to just do a random walk across the problem space.

So the search pattern had to be an exponential one that pulls back on overshoot in a decaying exponential form as well. Identifies the boundaries and then halves each side of the boundary until the boundaries are narrow enough to find a solution. Then it moves onto the next attribute and repeats, after it optimizes them all it does another run through and another (to account for interdependence) until none of the parameters are significantly adjusted.

All this takes several hours to run at least. Still cool to see its working as it drops the error rate significantly and gets to the point where it makes fairly good predictions about how a stock is likely to change in the near future (the value measuring the error against)... in fact i'm amazed just how powerful an accurate this algorithm is at predicting stocks right now.

#Stocks #Stockmarket #investment #quant #Quantitative #math #Science #MachineLearning #AI #ML @Science

Oh, go to hell. I already have the simplest user agent.
Looks like I have to stop using this search engine.

@kuketzblog
Welche Infos u Einschätzungen gibt es bisher zu #quant?