#books #trading
Making Sense of Chaos: A Better Economics for a Better World
by J. Doyne Farmer
Книга самого Дойна Фармера! Обалдеть!
По факту выясняется, что ничего практически ценного в книге нет, но вы можете получить эстетическое удовольствие от чтения высокоинтеллектуальной литературы, примерно как от произведений Мандельброта и Талеба (если не брать идиотские "случаи из жизни" любимого вымышленного друга Талеба, местного Джона из американского Усть-Пердыщенска).
https://www.amazon.com/Making-Sense-Chaos-Better-Economics/dp/0300273770
Making Sense of Chaos: A Better Economics for a Better World
by J. Doyne Farmer
Книга самого Дойна Фармера! Обалдеть!
По факту выясняется, что ничего практически ценного в книге нет, но вы можете получить эстетическое удовольствие от чтения высокоинтеллектуальной литературы, примерно как от произведений Мандельброта и Талеба (если не брать идиотские "случаи из жизни" любимого вымышленного друга Талеба, местного Джона из американского Усть-Пердыщенска).
https://www.amazon.com/Making-Sense-Chaos-Better-Economics/dp/0300273770
#wisdom
No sensible decision can be made any longer without taking into account not only the world as it is, but the world as it will be.
—Isaac Asimov
No sensible decision can be made any longer without taking into account not only the world as it is, but the world as it will be.
—Isaac Asimov
#wisdom
Quality is never an accident; it is always the result of high intention, sincere effort, intelligent direction and skillful execution.
—William A. Foster
Quality is never an accident; it is always the result of high intention, sincere effort, intelligent direction and skillful execution.
—William A. Foster
#books #trading
Пробежался по книжке Inside the Black Box. Хорошая.
Выписал некоторые определения.
As Dr. Simons puts it, “The advantage scientists bring into the game is less their mathematical or computational skills than their ability to think scientifically.”
Many successful traders subscribe to the old adage, “Cut losers and ride winners.” However, discretionary investors often find it very difficult to realize losses, whereas they are quick to realize gains. This is a welldocumented behavioral bias known as the disposition effect.
The systematic trader is able to make this “rational” decision at a time when there is no pressure, thereby obviating the need to exercise discipline at a time when most people would find it extraordinarily challenging.
A quant systematically applies an alpha-seeking investment strategy that was specified based on exhaustive research.
Our definition of alpha - which I stress is not conventional - is skill in timing the selection and/or sizing of portfolio holdings.
Alpha, the spelled-out version of the Greek letter α, generally is used as a way to quantify the skill of an investor or the return she delivers independently of the moves in the broader market. By conventional definition, alpha is the portion of the investor's return not due to the market benchmark, or, in other words, the value added (or lost) solely because of the manager. The portion of the return which can be attributed to market factors is then referred to as beta.
The software that a quant builds and uses to conduct this timing systematically is known as an alpha model, though there are many synonyms for this term: forecast, factor, alpha, model, strategy, estimator, or predictor. All successful alpha models are designed to have some “edge,” which allows them to anticipate the future with enough accuracy that, after allowing for being wrong at least sometimes and for the cost of trading, they can still make money. In a sense, of the various parts of a quant strategy, the alpha model is the optimist, focused on making money by predicting the future.
An important and not widely understood fact is that there are only a small number of trading strategies that exist for someone seeking alpha. But these basic strategies can be implemented in many ways, making it possible to create an incredible diversity of strategies from a limited set of core ideas. This distinction between the idea and how it is implemented is important to understand.
Most of what theory-driven quants do can be relatively easily fitted into one of eight classes of phenomena: trend, mean reversion, technical sentiment, value/yield, growth/sentiment, supply/demand, quality, and tactical/events.
Пробежался по книжке Inside the Black Box. Хорошая.
Выписал некоторые определения.
As Dr. Simons puts it, “The advantage scientists bring into the game is less their mathematical or computational skills than their ability to think scientifically.”
Many successful traders subscribe to the old adage, “Cut losers and ride winners.” However, discretionary investors often find it very difficult to realize losses, whereas they are quick to realize gains. This is a welldocumented behavioral bias known as the disposition effect.
The systematic trader is able to make this “rational” decision at a time when there is no pressure, thereby obviating the need to exercise discipline at a time when most people would find it extraordinarily challenging.
A quant systematically applies an alpha-seeking investment strategy that was specified based on exhaustive research.
Our definition of alpha - which I stress is not conventional - is skill in timing the selection and/or sizing of portfolio holdings.
Alpha, the spelled-out version of the Greek letter α, generally is used as a way to quantify the skill of an investor or the return she delivers independently of the moves in the broader market. By conventional definition, alpha is the portion of the investor's return not due to the market benchmark, or, in other words, the value added (or lost) solely because of the manager. The portion of the return which can be attributed to market factors is then referred to as beta.
The software that a quant builds and uses to conduct this timing systematically is known as an alpha model, though there are many synonyms for this term: forecast, factor, alpha, model, strategy, estimator, or predictor. All successful alpha models are designed to have some “edge,” which allows them to anticipate the future with enough accuracy that, after allowing for being wrong at least sometimes and for the cost of trading, they can still make money. In a sense, of the various parts of a quant strategy, the alpha model is the optimist, focused on making money by predicting the future.
An important and not widely understood fact is that there are only a small number of trading strategies that exist for someone seeking alpha. But these basic strategies can be implemented in many ways, making it possible to create an incredible diversity of strategies from a limited set of core ideas. This distinction between the idea and how it is implemented is important to understand.
Most of what theory-driven quants do can be relatively easily fitted into one of eight classes of phenomena: trend, mean reversion, technical sentiment, value/yield, growth/sentiment, supply/demand, quality, and tactical/events.
#books #trading
Ещё немного цитат из Inside the Black Box.
Dark pools are created by brokers or independent firms to allow their customers to trade directly with each other in an anonymous way. They arose in part because of concerns about the market impact associated with large orders. On a dark pool, there is no information provided about the limit order book, which contains all the liquidity being provided by market makers and other participants. Customers are simply posting their orders to the pool and if someone happens to want to do the opposite side of those orders, the orders get filled. As a result of this anonymous process of matching orders, the market is less likely to move as much as it would in a more public venue, where automated market-making practitioners require compensation to take the other side of large orders.
The total cost of transactions for an instrument, holding all else (such as liquidity, trend or volatility) constant, can be visualized as a graph with the size of the order (in terms of dollars, shares, contracts, or the like) on the xaxis and the cost of trading on the y-axis. It is generally accepted by the quant community that the shape of this curve is quadratic, which means that the cost gets higher ever more quickly as the size of the trade gets larger (due to market impact).
While a quadratic cost function is the most commonly agreed upon type, it is not universally accepted. There is good evidence that, at least for U.S. equities, cost per share scales with an exponent of 1.5, or in other words, as the square root of trade size. This empirically seems to be a better fit, while also being supported by the knowledge that many market makers and dealers view their inventory risk as scaling the same way—as the square root of its size.
To mitigate the data-burning form of look-ahead bias, some quant shops take reasonably drastic measures, separating the strategy research function from the strategy selection function and withholding a significant portion of the entire database from the researchers. In this way, the researcher, in theory, cannot even see what data he has and doesn't have, making it much more difficult for him to engage in look-ahead activities. Less draconian, the researcher might simply not be allowed to know or see which data are used for the out-of-sample period, or the portions of data used for in- and out-of-sample testing might be varied randomly or without informing the researcher.
It may turn out that the names the strategy wants to short, and in particular, the most successful short picks, are on hard-to-borrow lists. Hard-to-borrow lists are those stocks that are generally restricted from shorting by the broker, because the broker cannot mechanically locate shares to borrow, which is required in the act of shorting.
Mistakes made during research become baked into a strategy for its lifetime, and then the systematic implementation of this error can become devastating. Moreover, the research effort is not a one-time affair. Rather, the quant must continually conduct a vigorous and prolific research program to produce profits consistently over time.
Models are, by definition, generalized representations of the past behavior of the market. More general models are more robust over time, but they are less likely to be very accurate at any point in time. More highly specified models have the chance to be more accurate, but they are also more likely to break down entirely when market conditions change.
The newest member of the quant-specific risk family is contagion, or common investor, risk. By this, we mean that we experience risk not because of the strategy itself but because other investors hold the same strategies.
The best argument against quant investing is that the markets are quasiefficient, nonlinear, dynamic, and adversarial systems, which makes it extremely hard to forecast asset prices. That said, there's enough empirical evidence in the sustained performance of the best quant funds to soundly refute that this difficulty is impossible to overcome.
Ещё немного цитат из Inside the Black Box.
Dark pools are created by brokers or independent firms to allow their customers to trade directly with each other in an anonymous way. They arose in part because of concerns about the market impact associated with large orders. On a dark pool, there is no information provided about the limit order book, which contains all the liquidity being provided by market makers and other participants. Customers are simply posting their orders to the pool and if someone happens to want to do the opposite side of those orders, the orders get filled. As a result of this anonymous process of matching orders, the market is less likely to move as much as it would in a more public venue, where automated market-making practitioners require compensation to take the other side of large orders.
The total cost of transactions for an instrument, holding all else (such as liquidity, trend or volatility) constant, can be visualized as a graph with the size of the order (in terms of dollars, shares, contracts, or the like) on the xaxis and the cost of trading on the y-axis. It is generally accepted by the quant community that the shape of this curve is quadratic, which means that the cost gets higher ever more quickly as the size of the trade gets larger (due to market impact).
While a quadratic cost function is the most commonly agreed upon type, it is not universally accepted. There is good evidence that, at least for U.S. equities, cost per share scales with an exponent of 1.5, or in other words, as the square root of trade size. This empirically seems to be a better fit, while also being supported by the knowledge that many market makers and dealers view their inventory risk as scaling the same way—as the square root of its size.
To mitigate the data-burning form of look-ahead bias, some quant shops take reasonably drastic measures, separating the strategy research function from the strategy selection function and withholding a significant portion of the entire database from the researchers. In this way, the researcher, in theory, cannot even see what data he has and doesn't have, making it much more difficult for him to engage in look-ahead activities. Less draconian, the researcher might simply not be allowed to know or see which data are used for the out-of-sample period, or the portions of data used for in- and out-of-sample testing might be varied randomly or without informing the researcher.
It may turn out that the names the strategy wants to short, and in particular, the most successful short picks, are on hard-to-borrow lists. Hard-to-borrow lists are those stocks that are generally restricted from shorting by the broker, because the broker cannot mechanically locate shares to borrow, which is required in the act of shorting.
Mistakes made during research become baked into a strategy for its lifetime, and then the systematic implementation of this error can become devastating. Moreover, the research effort is not a one-time affair. Rather, the quant must continually conduct a vigorous and prolific research program to produce profits consistently over time.
Models are, by definition, generalized representations of the past behavior of the market. More general models are more robust over time, but they are less likely to be very accurate at any point in time. More highly specified models have the chance to be more accurate, but they are also more likely to break down entirely when market conditions change.
The newest member of the quant-specific risk family is contagion, or common investor, risk. By this, we mean that we experience risk not because of the strategy itself but because other investors hold the same strategies.
The best argument against quant investing is that the markets are quasiefficient, nonlinear, dynamic, and adversarial systems, which makes it extremely hard to forecast asset prices. That said, there's enough empirical evidence in the sustained performance of the best quant funds to soundly refute that this difficulty is impossible to overcome.
#books #trading #english
Ну и в завершение чтения Inside the Black Box.
A valid idea with a valid implementation might make little or no money if there is too much competition, whereas a mediocre strategy might make money if there is none.
A data edge can come from having proprietary access to some sort of data.
There is no secret sauce. We are constantly working to improve every area of our strategy. Our data is constantly being improved, our execution models are constantly being improved, our portfolio construction algorithms are constantly being improved … everything can always be better. We hire the right kinds of people, and we give them an environment in which they can relentlessly work to improve everything we do, little by little.
Список неизвестных/забытых английских слов, встретившихся в книге:
harrying - the act of persistently harassing, annoying, or attacking someone, whether through verbal demands, physical
disturbances, or destructive raids
linchpin - a person or thing vital to an enterprise or organization
reticent - not revealing one's thoughts or feelings readily
avocation - a hobby
cachet - (French pronunciation: [kaʃe]) is a printed or stamped design or inscription
persecution - преследование
lukewarm - тепловатый
replete - сытый
juxtaposition - the fact of two things being seen or placed close together with contrasting effect
fickle - ненадежный, переменный
pervade - (especially of a smell) spread through and be perceived in every part of
usher - to show someone where they should go
derisively To speak or act derisively is to do so in a mocking, scornful, or disrespectful manner, showing a clear lack of respect and treating something as silly or worthless
germane - имеющий отношение к делу, уместный, соответствующий теме или тесно связанный
inimitable - непревзойденный
unassailable - неопровержимый, безупречный
obviate = avoid, prevent
proclivity - склонность
verbiage - словоблудие
congruously - appropriately/aptly
winnow - to remove (as chaff) by a current of air; to free (as grain) from waste in this manner; to remove, separate, or select as if by winnowing; to narrow or reduce; to blow on or fan
Ну и в завершение чтения Inside the Black Box.
A valid idea with a valid implementation might make little or no money if there is too much competition, whereas a mediocre strategy might make money if there is none.
A data edge can come from having proprietary access to some sort of data.
There is no secret sauce. We are constantly working to improve every area of our strategy. Our data is constantly being improved, our execution models are constantly being improved, our portfolio construction algorithms are constantly being improved … everything can always be better. We hire the right kinds of people, and we give them an environment in which they can relentlessly work to improve everything we do, little by little.
Список неизвестных/забытых английских слов, встретившихся в книге:
harrying - the act of persistently harassing, annoying, or attacking someone, whether through verbal demands, physical
disturbances, or destructive raids
linchpin - a person or thing vital to an enterprise or organization
reticent - not revealing one's thoughts or feelings readily
avocation - a hobby
cachet - (French pronunciation: [kaʃe]) is a printed or stamped design or inscription
persecution - преследование
lukewarm - тепловатый
replete - сытый
juxtaposition - the fact of two things being seen or placed close together with contrasting effect
fickle - ненадежный, переменный
pervade - (especially of a smell) spread through and be perceived in every part of
usher - to show someone where they should go
derisively To speak or act derisively is to do so in a mocking, scornful, or disrespectful manner, showing a clear lack of respect and treating something as silly or worthless
germane - имеющий отношение к делу, уместный, соответствующий теме или тесно связанный
inimitable - непревзойденный
unassailable - неопровержимый, безупречный
obviate = avoid, prevent
proclivity - склонность
verbiage - словоблудие
congruously - appropriately/aptly
winnow - to remove (as chaff) by a current of air; to free (as grain) from waste in this manner; to remove, separate, or select as if by winnowing; to narrow or reduce; to blow on or fan
#interview
In a mirror, your right hand becomes left and the left hand becomes right. Why doesn’t your head become legs?
From a quant interview
In a mirror, your right hand becomes left and the left hand becomes right. Why doesn’t your head become legs?
From a quant interview
#interview
Three (𝑥, 𝑦) datasets are represented by scatter plots uniformly filling the three shapes in the following Figure. Rank the datasets by predictive power.
Three (𝑥, 𝑦) datasets are represented by scatter plots uniformly filling the three shapes in the following Figure. Rank the datasets by predictive power.
#crypto
"Согласно данным, основным двигателем роста благосостояния в секторе остаётся биткоин. Количество держателей портфелей стоимостью свыше $1 млн в BTC увеличилось на 70 % по сравнению с предыдущим годом и составило 145 100 человек. На верхнем уровне распределения богатства находятся 450 инвесторов, владеющих как минимум $100 млн в криптовалютах, при этом 36 из них уже считаются миллиардерами."
https://3dnews.ru/1129975/chislo-kriptomillionerov-viroslo-na-40-za-god-teper-ih-241-700
"Согласно данным, основным двигателем роста благосостояния в секторе остаётся биткоин. Количество держателей портфелей стоимостью свыше $1 млн в BTC увеличилось на 70 % по сравнению с предыдущим годом и составило 145 100 человек. На верхнем уровне распределения богатства находятся 450 инвесторов, владеющих как минимум $100 млн в криптовалютах, при этом 36 из них уже считаются миллиардерами."
https://3dnews.ru/1129975/chislo-kriptomillionerov-viroslo-na-40-za-god-teper-ih-241-700
3DNews - Daily Digital Digest
Число криптомиллионеров выросло на 40 % за год — теперь их 241 700
Количество криптовалютных миллионеров в мире выросло на 40 % за последний год и достигло 241 700 человек, сообщает CoinDesk со ссылкой на отчёт консалтинговой компании Henley & Partners. Этот всплеск совпал с общим ростом рынка, капитализация которого в июне…
#wisdom
The first principle is that you must not fool yourself—and you are the easiest person to fool.
Richard Feynman
The first principle is that you must not fool yourself—and you are the easiest person to fool.
Richard Feynman
#stocks
"Акции Nvidia во вторник достигли нового рекорда, поднявшись почти на 3 %, что увеличило рыночную капитализацию производителя чипов до невероятных $4,5 триллиона. За год акции Nvidia выросли примерно на 49 % и продолжают привлекать инвесторов."
https://3dnews.ru/1130094/iipuzir-pokoril-novuyu-vehu-kapitalizatsiya-nvidia-previsila-45-trln
"Акции Nvidia во вторник достигли нового рекорда, поднявшись почти на 3 %, что увеличило рыночную капитализацию производителя чипов до невероятных $4,5 триллиона. За год акции Nvidia выросли примерно на 49 % и продолжают привлекать инвесторов."
https://3dnews.ru/1130094/iipuzir-pokoril-novuyu-vehu-kapitalizatsiya-nvidia-previsila-45-trln
3DNews - Daily Digital Digest
ИИ-пузырь покорил новую веху: капитализация Nvidia превысила $4,5 трлн
Акции Nvidia во вторник достигли нового рекорда, поднявшись почти на 3 %, что увеличило рыночную капитализацию производителя чипов до невероятных $4,5 триллиона. За год акции Nvidia выросли примерно на 49 % и продолжают привлекать инвесторов, поскольку компания…
#science #china
Жаль, про Россию нет подобных новостей
https://3dnews.ru/1130156/kitay-zapustil-samuyu-moshchnuyu-v-mire-tsentrifugu-dlya-eksperimentov-nad-prostranstvom-i-vremenem
Жаль, про Россию нет подобных новостей
https://3dnews.ru/1130156/kitay-zapustil-samuyu-moshchnuyu-v-mire-tsentrifugu-dlya-eksperimentov-nad-prostranstvom-i-vremenem
3DNews - Daily Digital Digest
Китай запустил самую мощную в мире центрифугу для экспериментов над пространством и временем
29 сентября 2025 года в Китае официально была запущена самая мощная в мире центрифуга проекта CHIEF. Установка CHIEF1300 способна создавать ускорение 300g для полезной нагрузки до 22 т. Это на порядок превышает возможности самой передовой американской центрифуги…