The effectiveness of the platform is achieved through continuous professional training of algorithmic traders, providing them with educational solutions of modern information technologies,financial engineering and algorithmic trading from well-known experts.Transparency of the ecosystem is ensured by the use of blockchain technology.The records of trading algorithms performance,statistics of all trading algorithms development stages,and developers’ professional background are stored in a distributed ledger (blockchain)
https://www.trackico.io/ico/quantor/
Topic: [ANN] QUANTOR - Quantitative investments in decentralized economy - page 2. (Read 1735 times)
August 02, 2018, 02:32:38 AM
August 01, 2018, 10:21:05 PM
Quantor is an ecosystem that integrates the investment solution market and online learning platform for the currency market, knowledge and skills of investment industry experts and investment algorithm developers.
Right sir.
this platform provides access to industry experts online courses, providing practical knowledge in various fields of algorithmic trading and quantitative finance.
July 29, 2018, 02:47:27 PM
Blockchain technology makes it possible to consider a trading algorithm in conjunction with smart contract,which allows you to automate the financial processes on the platform.
https://tokens.quantor.co/
https://tokens.quantor.co/
July 28, 2018, 11:44:56 AM
We are pleased to announce the participation of Quantor team at Blockchain Summit in Hong Kong.
Right now, speakers and experts are you examining and analyzing the impact various industries that Blockchain presents. Many solution-based case studies and panel discussions are focused are focused on building partnerships in the emerging Blockchain space.
We are welcome to meet with you in Hong Kong at this amazing summit. You can learn more by the following link: http://conference.unicom.co.uk/blockchain-summit/2018/hongkong/
https://i.imgur.com/juFYlqH.jpg
Right now, speakers and experts are you examining and analyzing the impact various industries that Blockchain presents. Many solution-based case studies and panel discussions are focused are focused on building partnerships in the emerging Blockchain space.
We are welcome to meet with you in Hong Kong at this amazing summit. You can learn more by the following link: http://conference.unicom.co.uk/blockchain-summit/2018/hongkong/
https://i.imgur.com/juFYlqH.jpg
July 27, 2018, 09:46:28 AM
The funnel model allows the users most inclined towards algorithmic trading to be attracted, and also the best of them to be selected from all over the world, using online learning technologies.
July 25, 2018, 08:52:47 AM
Quantor participated in “Spot conference” in Hong Kong Stock Exchange
On July 23, co-founder and a representative of the Quantor team Vlad Buchnev took a part in the global international conference “Spot conference” in Hong Kong Stock Exchange (https://www.spotconf.com) devoted to crypto currencies exchanges.
The world’s leading cryptocurrency exchanges came together at the Hong Kong stock exchange to discuss technology and standards, regulation and industry changes. Around 250 key decision makers from top cryptocurrency exchanges participated in the conference including Quantor project representatives. The conference was attended by top cryptocurrency exchanges such Kraken, BitMEX, OKEX, GOPAX, and Huobi. Among well-known companies in crypto space were Kenetic, Bitcoin Association of Hong Kong, Coingekko, and Diginex.
A potential cooperation agreements were discussed between Quantor and representatives of crypto exchanges. The representatives of funds came to conclusion to discuss farther interest to Quantor project and its developing services for crypto investors.
https://i.imgur.com/fgO22F6.jpg
On July 23, co-founder and a representative of the Quantor team Vlad Buchnev took a part in the global international conference “Spot conference” in Hong Kong Stock Exchange (https://www.spotconf.com) devoted to crypto currencies exchanges.
The world’s leading cryptocurrency exchanges came together at the Hong Kong stock exchange to discuss technology and standards, regulation and industry changes. Around 250 key decision makers from top cryptocurrency exchanges participated in the conference including Quantor project representatives. The conference was attended by top cryptocurrency exchanges such Kraken, BitMEX, OKEX, GOPAX, and Huobi. Among well-known companies in crypto space were Kenetic, Bitcoin Association of Hong Kong, Coingekko, and Diginex.
A potential cooperation agreements were discussed between Quantor and representatives of crypto exchanges. The representatives of funds came to conclusion to discuss farther interest to Quantor project and its developing services for crypto investors.
https://i.imgur.com/fgO22F6.jpg
July 24, 2018, 05:59:56 AM
You can buy ETH using Visa or MasterCard 💳
MyEtherWallet undertook another step forward in broadening its solutions for storing Etc20 tokens. New partnership with Simplex brings about user-friendly, convinient and yet secure way. MyEtherWallet users will now be able to buy ETH using their credit cards. The option will be available after easy one-time KYC procedure to avoide platform abuse for laundring money.Simplex is “fully-regulated fintech & crypto company” providing fraudless payment processing solutions. Simplex was ranked in the top 100 by FinTech as one of the global financial market.
https://i.imgur.com/CnBO6dv.png
MyEtherWallet undertook another step forward in broadening its solutions for storing Etc20 tokens. New partnership with Simplex brings about user-friendly, convinient and yet secure way. MyEtherWallet users will now be able to buy ETH using their credit cards. The option will be available after easy one-time KYC procedure to avoide platform abuse for laundring money.Simplex is “fully-regulated fintech & crypto company” providing fraudless payment processing solutions. Simplex was ranked in the top 100 by FinTech as one of the global financial market.
https://i.imgur.com/CnBO6dv.png
July 22, 2018, 01:05:57 PM
The effectiveness of the platform is achieved through continuous professional training of algorithmic traders, providing them with educational solutions of modern information technologies,financial engineering and algorithmic trading from well-known experts.Transparency of the ecosystem is ensured by the use of blockchain technology.
https://icobench.com/ico/quantor
https://icobench.com/ico/quantor
July 15, 2018, 02:25:53 AM
This course covers two of the seven trading strategies that work in emerging markets.The seven include strategies based on momentum, momentum crashes,price reversal, persistence of earnings,quality of earnings,underlying business growth, behavioral biases and textual analysis of business reports about the company.
https://quantor.co/academy-of-online-courses/
https://quantor.co/academy-of-online-courses/
July 14, 2018, 09:12:43 AM
Quantor is an ecosystem that integrates the investment solution market and online learning platform for the currency market, knowledge and skills of investment industry experts and investment algorithm developers.
July 14, 2018, 06:17:20 AM
Loss aversion is not a behavioral bias
In his famous book "Thinking, Fast and Slow", the Nobel laureate Daniel Kahneman described one common example of a behavioral finance bias:
"You are offered a gamble on the toss of a [fair] coin.
If the coin shows tails, you lose $100.
If the coin shows heads, you win $110.
Is this gamble attractive? Would you accept it?"
(I have modified the numbers to be more realistic in a financial market setting, but otherwise it is a direct quote.)
Experiments show that most people would not accept this gamble, even though the expected gain is $5. This is the so-called "loss aversion" behavioral bias, and is considered irrational. Kahneman went on to write that "professional risk takers" (read "traders") are more willing to act rationally and accept this gamble.
It turns out that the loss averse "layman" is the one acting rationally here.
It is true that if we have infinite capital, and can play infinitely many rounds of this game simultaneously, we should expect $5 gain per round. But trading isn't like that. We are dealt one coin at a time, and if we suffer a string of losses, our capital will be depleted and we will be in debtor prison if we keep playing. The proper way to evaluate whether this game is attractive is to evaluate the expected compound rate of growth of our capital.
Let's say we are starting with a capital of $1,000. The expected return of playing this game once is initially 0.005. The standard deviation of the return is 0.105. To simplify matters, let's say we are allowed to adjust the payoff of each round so we have the same expected return and standard deviation of return each round. For e.g. if at some point we earned so much that we doubled our capital to $2,000, we are allowed to win $220 or lose $200 per round. What is the expected growth rate of our capital? According to standard stochastic calculus, in the continuous approximation it is -0.0005125 per round - we are losing, not gaining! The layman is right to refuse this gamble.
Loss aversion, in the context of a risky game played repeatedly, is rational, and not a behavioral bias. Our primitive, primate instinct grasped a truth that behavioral economists cannot. It only seems like a behavioral bias if we take an "ensemble view" (i.e. allowed infinite capital to play many rounds of this game simultaneously), instead of a "time series view" (i.e. allowed only finite capital to play many rounds of this game in sequence, provided we don't go broke at some point). The time series view is the one relevant to all traders. In other words, take time average, not ensemble average, when evaluating real-world risks.
The important difference between ensemble average and time average has been raised in this paper by Ole Peters and Murray Gell-Mann (another Nobel laureate like Kahneman.) It deserves to be much more widely read in the behavioral economics community. But beyond academic interest, there is a practical importance in emphasizing that loss aversion is rational. As traders, we should not only focus on average returns: risks can depress compound returns severely.
Original source:
Read the original article on Dr. Ernest Chan’s blog here
In his famous book "Thinking, Fast and Slow", the Nobel laureate Daniel Kahneman described one common example of a behavioral finance bias:
"You are offered a gamble on the toss of a [fair] coin.
If the coin shows tails, you lose $100.
If the coin shows heads, you win $110.
Is this gamble attractive? Would you accept it?"
(I have modified the numbers to be more realistic in a financial market setting, but otherwise it is a direct quote.)
Experiments show that most people would not accept this gamble, even though the expected gain is $5. This is the so-called "loss aversion" behavioral bias, and is considered irrational. Kahneman went on to write that "professional risk takers" (read "traders") are more willing to act rationally and accept this gamble.
It turns out that the loss averse "layman" is the one acting rationally here.
It is true that if we have infinite capital, and can play infinitely many rounds of this game simultaneously, we should expect $5 gain per round. But trading isn't like that. We are dealt one coin at a time, and if we suffer a string of losses, our capital will be depleted and we will be in debtor prison if we keep playing. The proper way to evaluate whether this game is attractive is to evaluate the expected compound rate of growth of our capital.
Let's say we are starting with a capital of $1,000. The expected return of playing this game once is initially 0.005. The standard deviation of the return is 0.105. To simplify matters, let's say we are allowed to adjust the payoff of each round so we have the same expected return and standard deviation of return each round. For e.g. if at some point we earned so much that we doubled our capital to $2,000, we are allowed to win $220 or lose $200 per round. What is the expected growth rate of our capital? According to standard stochastic calculus, in the continuous approximation it is -0.0005125 per round - we are losing, not gaining! The layman is right to refuse this gamble.
Loss aversion, in the context of a risky game played repeatedly, is rational, and not a behavioral bias. Our primitive, primate instinct grasped a truth that behavioral economists cannot. It only seems like a behavioral bias if we take an "ensemble view" (i.e. allowed infinite capital to play many rounds of this game simultaneously), instead of a "time series view" (i.e. allowed only finite capital to play many rounds of this game in sequence, provided we don't go broke at some point). The time series view is the one relevant to all traders. In other words, take time average, not ensemble average, when evaluating real-world risks.
The important difference between ensemble average and time average has been raised in this paper by Ole Peters and Murray Gell-Mann (another Nobel laureate like Kahneman.) It deserves to be much more widely read in the behavioral economics community. But beyond academic interest, there is a practical importance in emphasizing that loss aversion is rational. As traders, we should not only focus on average returns: risks can depress compound returns severely.
Original source:
Read the original article on Dr. Ernest Chan’s blog here
July 09, 2018, 02:30:16 AM
Dr. Ernest P. Chan
Dr. Ernest P. Chan is the Managing Member of QTS Capital Management, LLC. His career since 1994 has been focusing on the development of statistical models and advanced computer algorithms to find patterns and trends in large quantities of data. He has applied his expertise in statistical pattern recognition to projects ranging from textual retrieval at IBM Research, mining customer relationship data at Morgan Stanley, and statistical arbitrage trading strategy research at Credit Suisse, Mapleridge Capital Management, and other hedge funds.
While at the Human Language Technologies group at IBM T. J. Watson Research Center (Yorktown Heights, NY), Dr. Chan spearheaded IBM’s research effort to develop a system for searching large text databases such as the World Wide Web, catapulting IBM’s reputation as a top player in the field. His system was placed seventh among some forty competitors in a competition sponsored by the National Institute of Science and Technology and the Department of Defense in 1996. At the Data Mining group in Morgan Stanley’s headquarter in New York, Ernie pioneered the application of some of these sophisticated statistical algorithms to the complex task of extracting customer relationships in the Morgan Stanley customer accounts database.
Ernie was invited to join a proprietary trading group at Credit Suisse in New York in 1998 to develop statistical models for equities and futures trading. He later joined Mapleridge Capital Management Corp. in 2002 as a Senior Quantitative Analyst working on futures trading strategies, and then Maple Financial in 2003 as a senior researcher and trader.
Ernie writes the Quantitative Trading blog and was quoted by the New York Times, Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program, Technical Analysis of Stocks and Commodities magazine, Securities Industry News, Automated Trader magazine, and the CFA Institute Magazine on topics related to quantitative trading. In recognition of his expertise in statistical data mining, he was invited to serve on the Program Committees of the International Conference of Knowledge Discovery and Data Mining in 1998. He was an invited speaker at the Automated Trading conference in London, UK, in October 2009, the Market Technicians Association Toronto Annual Conference in 2010, the Quant Invest Canada conference in 2012, and QuantCon in New York in 2015-17. He is the author of “Quantitative Trading: How to Build Your Own Algorithmic Trading Business” and “Algorithmic Trading: Winning Strategies and Their Rationale“, both published by John Wiley & Sons. His new book “Machine Trading: Deploying Computer Algorithms to Conquer the Markets” was published in 2017. Ernie conducts workshops on Statistical Arbitrage, Quantitative Momentum Strategies, and Artificial Intelligence for Traders in London. He was an Adjunct Associate Professor of Finance at Nanyang Technological University in Singapore, and an Industry Fellow of the NTU-SGX Centre for Financial Education, which is jointly set up by NTU and the Singapore Exchange. He also teaches Risk Analytics at Northwestern University’s Master of Science in Predictive Analytics program and supervises student theses there.
Ernie holds a Bachelor of Science degree from University of Toronto in 1988, a Master of Science (1991) and a Doctor of Philosophy (1994) degree in theoretical physics from Cornell University.
Dr. Ernest P. Chan is the Managing Member of QTS Capital Management, LLC. His career since 1994 has been focusing on the development of statistical models and advanced computer algorithms to find patterns and trends in large quantities of data. He has applied his expertise in statistical pattern recognition to projects ranging from textual retrieval at IBM Research, mining customer relationship data at Morgan Stanley, and statistical arbitrage trading strategy research at Credit Suisse, Mapleridge Capital Management, and other hedge funds.
While at the Human Language Technologies group at IBM T. J. Watson Research Center (Yorktown Heights, NY), Dr. Chan spearheaded IBM’s research effort to develop a system for searching large text databases such as the World Wide Web, catapulting IBM’s reputation as a top player in the field. His system was placed seventh among some forty competitors in a competition sponsored by the National Institute of Science and Technology and the Department of Defense in 1996. At the Data Mining group in Morgan Stanley’s headquarter in New York, Ernie pioneered the application of some of these sophisticated statistical algorithms to the complex task of extracting customer relationships in the Morgan Stanley customer accounts database.
Ernie was invited to join a proprietary trading group at Credit Suisse in New York in 1998 to develop statistical models for equities and futures trading. He later joined Mapleridge Capital Management Corp. in 2002 as a Senior Quantitative Analyst working on futures trading strategies, and then Maple Financial in 2003 as a senior researcher and trader.
Ernie writes the Quantitative Trading blog and was quoted by the New York Times, Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program, Technical Analysis of Stocks and Commodities magazine, Securities Industry News, Automated Trader magazine, and the CFA Institute Magazine on topics related to quantitative trading. In recognition of his expertise in statistical data mining, he was invited to serve on the Program Committees of the International Conference of Knowledge Discovery and Data Mining in 1998. He was an invited speaker at the Automated Trading conference in London, UK, in October 2009, the Market Technicians Association Toronto Annual Conference in 2010, the Quant Invest Canada conference in 2012, and QuantCon in New York in 2015-17. He is the author of “Quantitative Trading: How to Build Your Own Algorithmic Trading Business” and “Algorithmic Trading: Winning Strategies and Their Rationale“, both published by John Wiley & Sons. His new book “Machine Trading: Deploying Computer Algorithms to Conquer the Markets” was published in 2017. Ernie conducts workshops on Statistical Arbitrage, Quantitative Momentum Strategies, and Artificial Intelligence for Traders in London. He was an Adjunct Associate Professor of Finance at Nanyang Technological University in Singapore, and an Industry Fellow of the NTU-SGX Centre for Financial Education, which is jointly set up by NTU and the Singapore Exchange. He also teaches Risk Analytics at Northwestern University’s Master of Science in Predictive Analytics program and supervises student theses there.
Ernie holds a Bachelor of Science degree from University of Toronto in 1988, a Master of Science (1991) and a Doctor of Philosophy (1994) degree in theoretical physics from Cornell University.
July 08, 2018, 06:22:01 AM
Five Universities Offer Crypto Courses in Spain, Argentina, and Venezuela
Among major topics of studies are Bitcoin, Ethereum, cryptocurrencies, blockchains, initial coin offerings ICOs, smart contracts, DAOs, and crypto-economics.
https://news.bitcoin.com/universities-crypto-courses-spain-argentina-venezuela/
Among major topics of studies are Bitcoin, Ethereum, cryptocurrencies, blockchains, initial coin offerings ICOs, smart contracts, DAOs, and crypto-economics.
https://news.bitcoin.com/universities-crypto-courses-spain-argentina-venezuela/
July 08, 2018, 03:29:30 AM
Transparency of the ecosystem is ensured by the use of blockchain technology. The records of trading algorithms performance, statistics of all trading algorithms development stages, and developers’ professional background are stored in a distributed ledger.
https://icobench.com/ico/quantor
https://icobench.com/ico/quantor
July 05, 2018, 07:50:46 AM
Quant-developer,as well as an expert teacher,will be able to gather around themselves a group of enthusiasts who will take part in improving an existing algorithm or testing an investment idea.
https://quantor.co
https://quantor.co
July 03, 2018, 04:25:10 AM
as I can see, tokens on the presale are almost not sold(( At this rate, even the soft cap is not collected.
July 02, 2018, 10:18:26 AM
The most important and hot news in #Cryptocurrency World from #Quantor for last week. #cryptocurrency leaders and losers, #blockchain news and strategic changes in global #crypto industry. 2018 June 25 - July 1
June 30, 2018, 07:30:33 AM
On 27.06.2018 team of Quantor have attended BLOCKCHAIN SUMMIT LONDON as experts as to widen our knowledge and get to know new innovations and projects of just as inspired individuals and teams as ours.
https://quantor.co
https://quantor.co
June 24, 2018, 04:27:11 AM
Blockchain technology makes it possible to consider a trading algorithm in conjunction with smart contract, which allows you to automate the financial processes on the platform.
https://tokens.quantor.co/
https://tokens.quantor.co/
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