Your referential of ignorance must not be generalised especially to knowledge that is well known in floor trading communities. It's true I have began futures when there wasn't electronic yet so I had the chance to know what was a pit. Apart from that as I said it was already known by traders before 1929.
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Patterns and aggregated data as basis for Hidden Markov Models and Bayesian networks
- Thread starter Gringinho
- Start date
My definition of pattern as I have said is from a probabilistic point of view: it is the same definition that you can find in an article like Lequeux or any other researcher's article: something that deviates from random distribution (this means of course not on only one sample but from a probabilistic significance point of view).
Quote from abogdan:
If we are talking about two dimensional sets then any pattern that exists in them could be sufficiently presented by a predicate that is a simple construction of "If - then" statements. Could you be so kind to write one example of such statements so I could understand what are we talking about.
Cheers,
For the joker....er...Harrytrader
"My major current hobby is teasing people who take themselves & the quality of their knowledge too seriously & those who donât have the guts to sometimes say: I donât know...." Nassim Nicholas Taleb
"Long-Term Capital Management was, like Renaissance, a quantitative trading firm. Did you
learn any lessons from its collapse?
Everyone in the company read the book about LTCM. It makes you wary in a general sense. Our
approach is very different. We donât start with models. We start with data. We donât have any
preconceived notions. We look for things that can be replicated thousands of times. A trouble with
convergence trading is that you donât have a time scale. You say that eventually things will come
together. Well, when is eventually?"
"My major current hobby is teasing people who take themselves & the quality of their knowledge too seriously & those who donât have the guts to sometimes say: I donât know...." Nassim Nicholas Taleb
"Long-Term Capital Management was, like Renaissance, a quantitative trading firm. Did you
learn any lessons from its collapse?
Everyone in the company read the book about LTCM. It makes you wary in a general sense. Our
approach is very different. We donât start with models. We start with data. We donât have any
preconceived notions. We look for things that can be replicated thousands of times. A trouble with
convergence trading is that you donât have a time scale. You say that eventually things will come
together. Well, when is eventually?"
1°) Bullshit datas by themselves give nothing if they don't transform into a model
2°) This even make me more laugh because it is nothing marvellous to detect micro-patterns it is trivial that micro-patterns exist in micro-scales as normal law is about big scale then why people consider Renaissance as it was the most advanced research whereas it is based on trivialities as I said ... even more trivial than LTCM which was based on a model that just requires one hypothesis: normal log-law this is trivial (ok I exaggerate they introduced the hypothesis of a risk free interest rate) and really laughable that they could even get a nobel prize for such basicalities ! Generally they chose real economists but the latest years it seems that the lobbying from Wall Street has infiltrated even the temple of nobelians although the economic nobel prize is not the same institution than the one in Science.
3°) Thinking that it is not risky is a fake as the most risk factor here comes from their size: it is systemic risk that they can create by their own weight on the market.
2°) This even make me more laugh because it is nothing marvellous to detect micro-patterns it is trivial that micro-patterns exist in micro-scales as normal law is about big scale then why people consider Renaissance as it was the most advanced research whereas it is based on trivialities as I said ... even more trivial than LTCM which was based on a model that just requires one hypothesis: normal log-law this is trivial (ok I exaggerate they introduced the hypothesis of a risk free interest rate) and really laughable that they could even get a nobel prize for such basicalities ! Generally they chose real economists but the latest years it seems that the lobbying from Wall Street has infiltrated even the temple of nobelians although the economic nobel prize is not the same institution than the one in Science.
3°) Thinking that it is not risky is a fake as the most risk factor here comes from their size: it is systemic risk that they can create by their own weight on the market.
Quote from theplumber:
For the joker....er...Harrytrader
"My major current hobby is teasing people who take themselves & the quality of their knowledge too seriously & those who donât have the guts to sometimes say: I donât know...." Nassim Nicholas Taleb
"Long-Term Capital Management was, like Renaissance, a quantitative trading firm. Did you
learn any lessons from its collapse?
Everyone in the company read the book about LTCM. It makes you wary in a general sense. Our
approach is very different. We donât start with models. We start with data. We donât have any
preconceived notions. We look for things that can be replicated thousands of times. A trouble with
convergence trading is that you donât have a time scale. You say that eventually things will come
together. Well, when is eventually?"
For the joker....er...Harrytrader
"My major current hobby is teasing people who take themselves & the quality of their knowledge too seriously & those who donât have the guts to sometimes say: I donât know...." Nassim Nicholas Taleb
1°) Bullshit datas by themselves give nothing if they don't transform into a model
"Like all quantitative money managers, Renaissance aims to find small market anomalies and
inefficiencies that can support profitable trading on billions of dollars of capital. Though all quant
shops are alike in their dedication to models â Let the best algorithm win! â Renaissanceâs
approach differs from the "convergence trading" popularized by John Meriwetherâs Long-Term
Capital Management and similar arbitrage shops. Convergence traders price financial
instruments based on complex mathematical models, find two different instruments that are
cheap and expensive on a relative basis and then buy one and sell the other, betting that the
prices will, at some point, have to return to their proper level. The Renaissance approach requires
that trades pay off in a limited, specified time frame. And Renaissance traders never override the
models."
"My major current hobby is teasing people who take themselves & the quality of their knowledge too seriously & those who donât have the guts to sometimes say: I donât know...." Nassim Nicholas Taleb
1°) Bullshit datas by themselves give nothing if they don't transform into a model
"Like all quantitative money managers, Renaissance aims to find small market anomalies and
inefficiencies that can support profitable trading on billions of dollars of capital. Though all quant
shops are alike in their dedication to models â Let the best algorithm win! â Renaissanceâs
approach differs from the "convergence trading" popularized by John Meriwetherâs Long-Term
Capital Management and similar arbitrage shops. Convergence traders price financial
instruments based on complex mathematical models, find two different instruments that are
cheap and expensive on a relative basis and then buy one and sell the other, betting that the
prices will, at some point, have to return to their proper level. The Renaissance approach requires
that trades pay off in a limited, specified time frame. And Renaissance traders never override the
models."
For the joker....er...Harrytrader
"My major current hobby is teasing people who take themselves & the quality of their knowledge too seriously & those who donât have the guts to sometimes say: I donât know...." Nassim Nicholas Taleb
2°) This even make me more laugh because it is nothing marvellous to detect micro-patterns it is trivial that micro-patterns exist in micro-scales as normal law is about big scale then why people consider Renaissance as it was the most advanced research whereas it is based on trivialities as I said ... even more trivial than LTCM which was based on a model that just requires one hypothesis: normal log-law this is trivial (ok I exaggerate they introduced the hypothesis of a risk free interest rate) and really laughable that they could even get a nobel prize for such basicalities ! Generally they chose real economists but the latest years it seems that the lobbying from Wall Street has infiltrated even the temple of nobelians although the economic nobel prize is not the same institution than the one in Science.
"For a man who believes in luck, Simons doesnât leave a lot to chance when it comes to recruiting
the staff that builds his trading models. As the firmâs assets grew, Simons recruited top-flight
mathematicians and scientists, including University of Virginia physics professor Robert Lourie
and Bell Labs numbers theorist Peter Weinberger, to research new trading strategies. In recent
years Simons seems to be especially keen on stockpiling computational linguists who have
worked on building computers that can recognize speech. He has hired away a good part of the
speech recognition group from IBM Corp.
Why computational linguists? "Investing and speech recognition are very similar," says one
Renaissance researcher. "In both, youâre trying to guess the next thing that happens."
As a trader, Simons tries to overcome fundamental laws, not discover them. In the case of
quantitative finance, the law is the efficient-markets hypothesis and the belief that markets should
be difficult, but not impossible, to beat.
In his rare discussions of trading, the Renaissance president emphasizes that trading
opportunities are by their nature small and fleeting. "Efficient market theory is correct in that there
are no gross inefficiencies," Simons told the Greenwich Roundtable last year. "But we look at
anomalies that may be small in size and brief in time. We make our forecast. Then, shortly
thereafter, we reevaluate the situation and revise our forecast and our portfolio. We do this all day
long. Weâre always in and out and out and in. So weâre dependent on activity to make money."
Renaissance essentially attempts to predict the future movement of financial instruments, within a
specific time frame, using statistical models. The firm searches for something that might be
producing anomalies in price movements that can be exploited. At Renaissance theyâre called
"signals." The firm builds trading models that fit the data.
When the trading starts, the models run the show. Renaissance has 20 traders who execute at
the lowest cost and without moving markets, crucial requirements for quant investors trading on
narrow margins. But the models decide what to buy and sell. Only in cases of extreme volatility,
or if the signals appear to be weakening, does the firm sometimes manually cut back. Says
Simons, "We donât override the models.""
"My major current hobby is teasing people who take themselves & the quality of their knowledge too seriously & those who donât have the guts to sometimes say: I donât know...." Nassim Nicholas Taleb
2°) This even make me more laugh because it is nothing marvellous to detect micro-patterns it is trivial that micro-patterns exist in micro-scales as normal law is about big scale then why people consider Renaissance as it was the most advanced research whereas it is based on trivialities as I said ... even more trivial than LTCM which was based on a model that just requires one hypothesis: normal log-law this is trivial (ok I exaggerate they introduced the hypothesis of a risk free interest rate) and really laughable that they could even get a nobel prize for such basicalities ! Generally they chose real economists but the latest years it seems that the lobbying from Wall Street has infiltrated even the temple of nobelians although the economic nobel prize is not the same institution than the one in Science.
"For a man who believes in luck, Simons doesnât leave a lot to chance when it comes to recruiting
the staff that builds his trading models. As the firmâs assets grew, Simons recruited top-flight
mathematicians and scientists, including University of Virginia physics professor Robert Lourie
and Bell Labs numbers theorist Peter Weinberger, to research new trading strategies. In recent
years Simons seems to be especially keen on stockpiling computational linguists who have
worked on building computers that can recognize speech. He has hired away a good part of the
speech recognition group from IBM Corp.
Why computational linguists? "Investing and speech recognition are very similar," says one
Renaissance researcher. "In both, youâre trying to guess the next thing that happens."
As a trader, Simons tries to overcome fundamental laws, not discover them. In the case of
quantitative finance, the law is the efficient-markets hypothesis and the belief that markets should
be difficult, but not impossible, to beat.
In his rare discussions of trading, the Renaissance president emphasizes that trading
opportunities are by their nature small and fleeting. "Efficient market theory is correct in that there
are no gross inefficiencies," Simons told the Greenwich Roundtable last year. "But we look at
anomalies that may be small in size and brief in time. We make our forecast. Then, shortly
thereafter, we reevaluate the situation and revise our forecast and our portfolio. We do this all day
long. Weâre always in and out and out and in. So weâre dependent on activity to make money."
Renaissance essentially attempts to predict the future movement of financial instruments, within a
specific time frame, using statistical models. The firm searches for something that might be
producing anomalies in price movements that can be exploited. At Renaissance theyâre called
"signals." The firm builds trading models that fit the data.
When the trading starts, the models run the show. Renaissance has 20 traders who execute at
the lowest cost and without moving markets, crucial requirements for quant investors trading on
narrow margins. But the models decide what to buy and sell. Only in cases of extreme volatility,
or if the signals appear to be weakening, does the firm sometimes manually cut back. Says
Simons, "We donât override the models.""
Hahahaha the typical marketing discourse based solely on self-fabricated reputation ! Emptiness ! I even found one year ago a funny article about a guy working for one of their firm supposedly working on patterns for marketing research : he was denouncing that it was really a joke that all was based on reputation that the firm recruited researchers from Berkeley whereas they didn't even follow the basic protocols of statistics and they sell the research a big packet of money to gullible institutional clients. If I find the archive again I will post the exact article.
Quote from theplumber:
For the joker....er...Harrytrader
"My major current hobby is teasing people who take themselves & the quality of their knowledge too seriously & those who donât have the guts to sometimes say: I donât know...." Nassim Nicholas Taleb
2°) This even make me more laugh because it is nothing marvellous to detect micro-patterns it is trivial that micro-patterns exist in micro-scales as normal law is about big scale then why people consider Renaissance as it was the most advanced research whereas it is based on trivialities as I said ... even more trivial than LTCM which was based on a model that just requires one hypothesis: normal log-law this is trivial (ok I exaggerate they introduced the hypothesis of a risk free interest rate) and really laughable that they could even get a nobel prize for such basicalities ! Generally they chose real economists but the latest years it seems that the lobbying from Wall Street has infiltrated even the temple of nobelians although the economic nobel prize is not the same institution than the one in Science.
"For a man who believes in luck, Simons doesnât leave a lot to chance when it comes to recruiting
the staff that builds his trading models. As the firmâs assets grew, Simons recruited top-flight
mathematicians and scientists, including University of Virginia physics professor Robert Lourie
and Bell Labs numbers theorist Peter Weinberger, to research new trading strategies. In recent
years Simons seems to be especially keen on stockpiling computational linguists who have
worked on building computers that can recognize speech. He has hired away a good part of the
speech recognition group from IBM Corp.
Why computational linguists? "Investing and speech recognition are very similar," says one
Renaissance researcher. "In both, youâre trying to guess the next thing that happens."
As a trader, Simons tries to overcome fundamental laws, not discover them. In the case of
quantitative finance, the law is the efficient-markets hypothesis and the belief that markets should
be difficult, but not impossible, to beat.
In his rare discussions of trading, the Renaissance president emphasizes that trading
opportunities are by their nature small and fleeting. "Efficient market theory is correct in that there
are no gross inefficiencies," Simons told the Greenwich Roundtable last year. "But we look at
anomalies that may be small in size and brief in time. We make our forecast. Then, shortly
thereafter, we reevaluate the situation and revise our forecast and our portfolio. We do this all day
long. Weâre always in and out and out and in. So weâre dependent on activity to make money."
Renaissance essentially attempts to predict the future movement of financial instruments, within a
specific time frame, using statistical models. The firm searches for something that might be
producing anomalies in price movements that can be exploited. At Renaissance theyâre called
"signals." The firm builds trading models that fit the data.
When the trading starts, the models run the show. Renaissance has 20 traders who execute at
the lowest cost and without moving markets, crucial requirements for quant investors trading on
narrow margins. But the models decide what to buy and sell. Only in cases of extreme volatility,
or if the signals appear to be weakening, does the firm sometimes manually cut back. Says
Simons, "We donât override the models.""
Quote from harrytrader:
Hahahaha the typical marketing discourse based solely on self-fabricated reputation ! Emptiness ! I even found one year ago a funny article about a guy working for one of their firm supposedly working on patterns for marketing research : he was denouncing that it was really a joke that all was based on reputation that the firm recruited researchers from Berkeley whereas they didn't even follow the basic protocols of statistics and they sell the research a big packet of money to gullible institutional clients. If I find the archive again I will post the exact article.
For the joker....er...Harrytrader
"My major current hobby is teasing people who take themselves & the quality of their knowledge too seriously & those who donât have the guts to sometimes say: I donât know...." Nassim Nicholas Taleb
Your a fraud and a liar Haweetwada, or is that wannabe trader
After big reverses, Julian Robertson closed down Tiger Management, and
George Soros scaled back the activities of his Quantum Fund this year. John Meriwetherâs Long-
Term Capital Management nearly took down the financial world in 1998.
Simons, by contrast, just keeps getting better. Consider his performance over the past decade.
Since its inception in March 1988, Simonsâ flagship $3.3 billion Medallion fund, has amassed
annual returns of 35.6 percent, compared with 17.9 percent for the Standard & Poorâs 500 index.
For the 11 full years ended December 1999, Medallionâs cumulative returns are an eye-popping
2,478.6 percent (see graph, page 47). Among all offshore funds over that same period, according
to the database run by veteran hedge fund observer Antoine Bernheim, the next-best performer
was Sorosâ Quantum Fund, with a 1,710.1 percent return (see table, page 44).
"Simons is No. 1," says Bernheim. "Ahead of George Soros. Ahead of Mark Kingdon. Ahead of
Bruce Kovner. Ahead of Monroe Trout."
Really laughable : it proves much indeed ! It's like comparing a guy who has been washed out by the previous bubble and the newbie coming in a new one and profiting marvelously and you would pretend that it proves he is best than the first one ?!!! Also statistically speaking it is a nonsense to compare pear and orange than comparing Soros Fund and Renaissance since they are not operating on the same scale as standard deviation is not at all the same see an answer I made to a silly article pretending that you could make +54000% !
http://www.elitetrader.com/vb/showt...59983&highlight=moving+and+average#post259983
Re: Yang on Moving Averages
SQRT((261*(2002-1970))-1)*1*100*3 = +/- 27415 %
this is just a very rough order estimation of performance for buying or selling randomly between 1970 and 2002 that is to say a person could make a POSITIVE performance of an order of 27415% and an other a NEGATIVE performance of - 27415% and not be more or less competant than the first one whose people could think he has a financial genious touch whereas it could be just by chance . And since I used an understimated law by taking a random normal law this order should be much greater in reality and reach 50000 or 100000% so that the numbers below are not significant statistically and that's what economists have already said .
This is a classical flaw in Stock Market similar to the gambler's flaw in casino gambling. The more frequent the trading and the more expanded the total time period the more big the cumulative percentage. As an other consequence and for exactly the same reason it is also a flaw comparing 1 or 2 days moving average results with 200 days moving average because the law of variation is not the same and is more volatile by definition for short than long MA.
This is kind of myth like the martingale for gamblers keep people abreast of finding the holy grail for making eally rich without any effort ... and real edge . Of course counting on chance it's always possible but it is also possible to get ruined as rapidly : -50000% could be as probable as -50000% cumulating all the years.
The vendors of trading systems use the same kind of trick for showing superformance. In fact many if not all trading system testers are flawed with that kind of presentation tool when it is the main if not single possibility of visualising performance. This is only "apparent" performance not true that is to say comparable performance.
http://www.elitetrader.com/vb/showt...59983&highlight=moving+and+average#post259983
Re: Yang on Moving Averages
SQRT((261*(2002-1970))-1)*1*100*3 = +/- 27415 %
this is just a very rough order estimation of performance for buying or selling randomly between 1970 and 2002 that is to say a person could make a POSITIVE performance of an order of 27415% and an other a NEGATIVE performance of - 27415% and not be more or less competant than the first one whose people could think he has a financial genious touch whereas it could be just by chance . And since I used an understimated law by taking a random normal law this order should be much greater in reality and reach 50000 or 100000% so that the numbers below are not significant statistically and that's what economists have already said .
This is a classical flaw in Stock Market similar to the gambler's flaw in casino gambling. The more frequent the trading and the more expanded the total time period the more big the cumulative percentage. As an other consequence and for exactly the same reason it is also a flaw comparing 1 or 2 days moving average results with 200 days moving average because the law of variation is not the same and is more volatile by definition for short than long MA.
This is kind of myth like the martingale for gamblers keep people abreast of finding the holy grail for making eally rich without any effort ... and real edge . Of course counting on chance it's always possible but it is also possible to get ruined as rapidly : -50000% could be as probable as -50000% cumulating all the years.
The vendors of trading systems use the same kind of trick for showing superformance. In fact many if not all trading system testers are flawed with that kind of presentation tool when it is the main if not single possibility of visualising performance. This is only "apparent" performance not true that is to say comparable performance.
Quote from theplumber:
For the joker....er...Harrytrader
"My major current hobby is teasing people who take themselves & the quality of their knowledge too seriously & those who donât have the guts to sometimes say: I donât know...." Nassim Nicholas Taleb
Your a fraud and a liar Haweetwada, or is that wannabe trader
After big reverses, Julian Robertson closed down Tiger Management, and
George Soros scaled back the activities of his Quantum Fund this year. John Meriwetherâs Long-
Term Capital Management nearly took down the financial world in 1998.
Simons, by contrast, just keeps getting better. Consider his performance over the past decade.
Since its inception in March 1988, Simonsâ flagship $3.3 billion Medallion fund, has amassed
annual returns of 35.6 percent, compared with 17.9 percent for the Standard & Poorâs 500 index.
For the 11 full years ended December 1999, Medallionâs cumulative returns are an eye-popping
2,478.6 percent (see graph, page 47). Among all offshore funds over that same period, according
to the database run by veteran hedge fund observer Antoine Bernheim, the next-best performer
was Sorosâ Quantum Fund, with a 1,710.1 percent return (see table, page 44).
"Simons is No. 1," says Bernheim. "Ahead of George Soros. Ahead of Mark Kingdon. Ahead of
Bruce Kovner. Ahead of Monroe Trout."