this guy has walked on the exact same path I have. I really wish I had this video years ago when I was first introduced to trading. This is the way. Coding was on my bucket list for years, then I learned how to backtest and realized how much time was wasted manually analyzing data
for data mining the best choice is python ... you can learn it fast. I use C++ since 1997, but when it comes to fast prototyping python beats C++ by light years. I learned it just to be able to datamine. In 100 lines of code I could do analisys, graphs, everything. What you need is a database .. which you can build for yourself by logging data from a platform. I did a lot of cheap solutions. Having access to a good data source is the key. I used Tensorflow to make some neural network to react for pivot points, but it worked pretty poorly :)). It is pretty big amount of work after all.
I recomend python. Beeing fluent in a languege is one thing, but to be a good programmer you need to be able to create abstract models. Without the ability to see the abstract components you cannot write code blocks which fit together seamlesly. That is the hard part. LEarning a language is few days. In python 10 keywords and you are good to go.
Wow great but difficult interview for both parties. Bro you definitely extracted water from a centerblock on this one... he wasn't giving up much at all... yet did give a few generalities.
His website is buildalpha.com it helps you build trading systems without knowing how to coded. For example it offers 5000 entries and 5000 exits . Once you come up with a system you like just print the code for tradestation,python,multicharts etc.... This what the interview was missing. Deeeep
So many generalities ! That is the problem with so many of these interviews. Really doesn't want to give anything away ! For once can we get down to specifics !!!
yeah i think Dave was a bit too general in this one. i get that he doesn't want to give away the "secret sauce" but he could have maybe gone into more detail about how to find edges.
Every word is genuine. My trading is based on his philosophy. I trade 100% transparently on my channel. You can see it in front of your eyes, everyday in live market, the practical aspect of what he covered in his interview.
Even you have done your all 1000 trades in bear market and you are always short and you are right 80% of time. Does it mean you have an edge ? You will be wiped out when bull market will come. You should define your strategy considering all type of market condition.
He's not a really full size quant. He's sort of self-thought, although he thought himself about 5% of what graduate quant knows. So his skill-set is far bellow average. Discretionary traders and quants can't be compared because human brain doesn't work like computer. Human would always see full context of a chart, while computer can follow only 2-3 parameters. That's why human needs less then 50-100 samples and computer needs many thousands. And, that is why human can trade several different patterns together and across multiple markets, while quant would need 5 separate systems. Practically quant has to wait 1,000 trades to scale up with one more contract, which might take a year, while some of discretionary traders go from $500 to $17,000 in two weeks.
Total waste of time. And BTW, you guys don't know what data mining is. You should be pretty embarrassed. The term is the old buzz word for what they have re-branded as Data Science. Data-mining uses statistical algorithms such as clustering, neural networks, and decisions trees to find patterns and relationships in data. It is different than just a trading algorithm which may simply encapsulate your trading rules and not use any statistical methods.
Maaan , I learned more from you than this video lol.Clustering , neural networks and binomial trees , these words I remember from books written about quants
So like being a person who got a math degree and did a capstone on data science I’d say that there’s a subtle difference between data mining and data science I think that data mining has more to do with extracting insights from existing data things like PCA, measures of central tendency, things like making charts and reports. Where as data science involves that but then it’s about making highly logical inferences about unknown things like doing predictions based on observed patterns so like supervised and unsupervised models.
this guy has walked on the exact same path I have. I really wish I had this video years ago when I was first introduced to trading. This is the way. Coding was on my bucket list for years, then I learned how to backtest and realized how much time was wasted manually analyzing data
Do you trade now
for data mining the best choice is python ... you can learn it fast. I use C++ since 1997, but when it comes to fast prototyping python beats C++ by light years. I learned it just to be able to datamine. In 100 lines of code I could do analisys, graphs, everything. What you need is a database .. which you can build for yourself by logging data from a platform. I did a lot of cheap solutions. Having access to a good data source is the key. I used Tensorflow to make some neural network to react for pivot points, but it worked pretty poorly :)). It is pretty big amount of work after all.
I recomend python. Beeing fluent in a languege is one thing, but to be a good programmer you need to be able to create abstract models. Without the ability to see the abstract components you cannot write code blocks which fit together seamlesly. That is the hard part. LEarning a language is few days. In python 10 keywords and you are good to go.
@@zzz_ttt_0091Hi, are you still doing algo trading?
3rd time watching this episode and still getting value out of it - cheers.
Wow great but difficult interview for both parties. Bro you definitely extracted water from a centerblock on this one... he wasn't giving up much at all... yet did give a few generalities.
This was seriously painful to listen to.
Great interview Aaron. Keep up the amazing work, very much appreciated!!!
His website is buildalpha.com it helps you build trading systems without knowing how to coded. For example it offers 5000 entries and 5000 exits . Once you come up with a system you like just print the code for tradestation,python,multicharts etc.... This what the interview was missing. Deeeep
got my golden nugget! good looking out Aaron! your beast bro!
variance testing; that's the gold in this interview: 37:00
I'm a mean reversion trader and it requires more discipline in that its critical to realize when you are wrong.
This one was a gem
Please make more and more and more i love them
Sooo much educational VALUE here :)
Thanks! man for the book ❤️
Anybody have any strategy development books for recommendations? For any programming language. I currently code with python. Using mostly anaconda.
what does he mean saying using open high low data for tech indicator. Is he talking about pre market high lows or first 15 min high or lows?
lol do any of you guys remember the scene on the sopranos where they were trying to inflate the value of webestics and then what happened after? Lmao
wish the janeky bino options scams would stop advertising
Firing questions like a machine gun!
So many generalities ! That is the problem with so many of these interviews. Really doesn't want to give anything away ! For once can we get down to specifics !!!
yeah i think Dave was a bit too general in this one. i get that he doesn't want to give away the "secret sauce" but he could have maybe gone into more detail about how to find edges.
Have to agree. He was to vague.
Every word is genuine. My trading is based on his philosophy. I trade 100% transparently on my channel. You can see it in front of your eyes, everyday in live market, the practical aspect of what he covered in his interview.
Read Tharp,
Thorp
20:37
Even you have done your all 1000 trades in bear market and you are always short and you are right 80% of time. Does it mean you have an edge ? You will be wiped out when bull market will come. You should define your strategy considering all type of market condition.
You wrote this comment in the midst of the craziest Bull Market ever existed. WTF?
The trend is at least part of your edge in either case.
31.00
17
7
He's not a really full size quant. He's sort of self-thought, although he thought himself about 5% of what graduate quant knows. So his skill-set is far bellow average.
Discretionary traders and quants can't be compared because human brain doesn't work like computer. Human would always see full context of a chart, while computer can follow only 2-3 parameters. That's why human needs less then 50-100 samples and computer needs many thousands. And, that is why human can trade several different patterns together and across multiple markets, while quant would need 5 separate systems. Practically quant has to wait 1,000 trades to scale up with one more contract, which might take a year, while some of discretionary traders go from $500 to $17,000 in two weeks.
This guy was speaking in such generalities, I couldn't listen anymore.
Total waste of time. And BTW, you guys don't know what data mining is. You should be pretty embarrassed. The term is the old buzz word for what they have re-branded as Data Science. Data-mining uses statistical algorithms such as clustering, neural networks, and decisions trees to find patterns and relationships in data. It is different than just a trading algorithm which may simply encapsulate your trading rules and not use any statistical methods.
Maaan , I learned more from you than this video lol.Clustering , neural networks and binomial trees , these words I remember from books written about quants
So like being a person who got a math degree and did a capstone on data science I’d say that there’s a subtle difference between data mining and data science I think that data mining has more to do with extracting insights from existing data things like PCA, measures of central tendency, things like making charts and reports. Where as data science involves that but then it’s about making highly logical inferences about unknown things like doing predictions based on observed patterns so like supervised and unsupervised models.
His 'software' sounds like a StrategyQuant ripoff
Bull shit.