gapcap1
10-17-2014, 05:41 PM
back in the day, markets were inefficient and dominated by heavy retail participation. pricing was a value oriented phenomena that actually reflected the laws of supply and demand. technical analysis was more effective back then, because markets were more auto-correlated, and retail participation in the markets contributed to the self-fullfilling prophecy that drives ta. historical price patterns were more reliable, and price reacted in predictable ways after this conditionality was presented. if one could identify these repetitive patterns, then determining path dependency was easy. the markets are now dominated by commercials, commodity funds, indexers, etfs and hfts. the financialization of traded instruments has resulted in more cross asset correlations which have stripped individual assets of their uniqueness, and price discovery and risk transference functions.
over the past decade, institutional management of equity portfolios has increased from 54% to 81% and over the same period, “real institutional trading” has declined from 47% of trading volume to 29%. there are far fewer market participants today than just ten years ago, managing much larger portfolios across more asset classes, and using much less trading. the retail trader has all but disappeared, and traditional traders are predominantly competing against professionals and machines in a relatively illiquid market. this perspective is important to realize, because it underscores how markets have changed. given the near extinction of retail participation, and the almost total dominance of professional and algorithmic trading, it is unlikely that the biases and readily "available" cognitive reference points that are the hallmark of the retail trader, still exert their influence on pricing today.
more than ever, the market is predisposed to preying on unsophisticated traders; and there is no shortage of material for the flexions to practice on to refine their skills. the internet is full of trading forums, venting the opinions of naive wannabe traders who don’t know the difference between a stock and a bond, yet live in the delusional world in which they believe they can better the traders who are rigging the game. at the core of their beliefs is the illusion that they can grind out a living i.e., they can overcome trading friction and be consistent enough to collect a steady paycheck from the market, while taking very little risk and very small profits. they continue to believe in the existence of the exploitable edge that is reproducible on a daily or intra-day basis. and, herein lies the biggest and most stultifying misconception about trading -the belief in the existence of alpha and the denial that the grind is gone.
one of the many advantages of being a local trader on the floor of an exchange was that a trader could earn the bid/offer spread as an incentive for providing liquidity. when a local made a trade he could buy-the-bid and sell-the-offer, which meant he was buying below fair value and selling above fair value. in addition to this edge, traders were able to transact business at a cheaper rate than the public, and had first-hand knowledge of market structure and order flow. this enabled them to trade ahead of large orders and "race" the retail stop orders. a member trader did not have to go far in his quest for alpha.
following decimalization and regulatory initiatives aimed at creating competition between trading venues, the equities market fragmented, and liquidity was dispersed across many lit venues and dark pools. this complexity, combined with exchanges becoming electronic and for-profit, created profit opportunities for technologically sophisticated players. high frequency traders (HFTs) now use ultra-high speed connections with trading venues and sophisticated trading algorithms to exploit inefficiencies created by the new market structure, and to identify patterns in 3rd parties’ trading, so that they can use it to their own advantage in much the same way as the floor trader used his proximal and informational edge to generate alpha.
however, as a short-term, point-and-click, discretionary directional trader, one does not have access to the same process required to generate alpha. for traditional traders, the new market conditions insure that the playing field is tilted against them. retail traders continually find themselves falling behind these new competitors, in large part because the game has changed and because they lack the tools required to compete effectively. nevertheless, as the complexity of trading increases, it is still possible for a trader to separate from the pack and profit. the trader who has the better (more complete) and more timely (current) analysis will enjoy the greatest edge and have the greatest success, because they will have increased the gap between the traders who have adapted to the new environment, and the less informed, less diligent, and less talented ones.
it’s not that alpha doesn’t exist- it just doesn’t exist for the retail trader. what traders earn beyond the risk-free rate is not a true profit but simply factor compensation—the market rate for the risks they take. any positive expectation is the result of accepting that risk: the payment for taking such a position is compensation for risk, not an excess return. so, a trader must assess his approach to trading and decide what steps must be taken to find a proxy for alpha; and it begins with adopting an attitude, that is both realistic and relevant. the best any trader can hope to achieve, under any circumstance, is an incomplete, but probabilistic knowledge of the trading environment. so a trader must realize and accept that the markets are dominated by the rules of chance and randomness, both skill and luck come into play. how traders cope with probabilistic uncertainty and their imperfect view of the market is critical to their success. the essential job of traders then is to reduce uncertainty, not risk.
as a leveraged trader, one makes short-term decisions/trades, but understands what is happening at time frames greater than the one he's currently trading. the decision to trade and its management, flows from an analysis of price action. he is aware traders operate at different time-frames, markets are interconnected, themes abound in markets and that probabilities and departures from value govern trading opportunities. he understands and incorporates relevant informational signals from a wide range of deterministic processes to arrive at a summed probability that acts as deeper context.
he manages the risk through diversification, keeps draw-downs to manageable levels and strikes a balance between profit maximization and loss mitigation by adjusting trade size and stop-loss levels, so that only an extreme event will trigger the stop. he keeps losses in a predetermined range, and prevents getting stopped-out of a potential winner by managing expected value along with p&l, while allowing for a margin of error, so that he may stay-in-the-trade.
he is not concerned about how often he is right about the market, and frequently adds to his winners and turns short-term winning positions into longer ones. yet, never loses sight of the fact there is a downside scenario with an associated probability. the way decisions are evaluated affects the way decisions are made, so one does not allow stress, cognitive load, emotions, and bias, to non-linearly affect the decision process.
smart traders have the capacity to aggregate and synthesize large volumes of information, analyze it, and then derive an edge from it. the primary step in this process is to develop the capability to gather timely information from all the various sources and attach relevance to the information as accurately as possible. then merge both data sets, public information and proprietary tools, to derive insights that are applied in making trading decisions. good traders figure out what game is working and play that game. if they can understand the interactions of the individual factors and their effects on the market as a whole, then they will be able to identify higher order patterns that are the result of these interactions. going beyond the standard correlation/causation question, the trader must ask, does this source of edge make sense? is there a behavioral or structural reason why this source of edge should persist? and he must expect to be surprised and have to make adjustments, and build that into his expectancy.
good traders are always working on themselves, always refining what they do. in an important sense, they don't just use introspection to improve their performance. they work on their performance as a means of extending their personal mastery. the best traders spend significant time generating trade ideas, researching markets, and staying on top of developments worldwide. the ratio of time spent in preparation to time spent actually in trading, is a measure of a trader's professionalism
every trade a trader makes provides an opportunity to learn. gathering information from every trade, as opposed to a select few, helps give the trader a better understanding of how those trades may perform in the future. the more frequent the analysis, the more relevant the findings will be. however, the findings serve a purpose only if they are acted upon. the key is to use information to guide actions whose outcomes are then analyzed and the findings reapplied. this creates a continuous iterative loop that drives towards ever greater efficiency.
if you look at alpha as various types of beta doing different things at different times, then a trader's returns are going to be lumpy and cyclical in nature and performance will revert to the mean. the central message for traders then, is to trade efficiently, and make the most money with the least cost. it's not how often you're right, but how much you're right. if you want to make money, then maximizing geometric returns should be front and center in your thinking.
the market and its past is identical for all observers. yet, the market and the future are understood uniquely by each trader. no matter how crude or refined a method one follows in ascertaining the likelihood of change, it still boils down to surviving against one's own incomplete intellect, a misfired bout of randomness, in controlling the risk, and in executing a set of consistent ideas day in and day out, so that chance can prevail. the opportunity is there for the traditional trader to capture his personal alpha. all he has to do is see the market for what it is, and not what it was, or what it appears to be.
over the past decade, institutional management of equity portfolios has increased from 54% to 81% and over the same period, “real institutional trading” has declined from 47% of trading volume to 29%. there are far fewer market participants today than just ten years ago, managing much larger portfolios across more asset classes, and using much less trading. the retail trader has all but disappeared, and traditional traders are predominantly competing against professionals and machines in a relatively illiquid market. this perspective is important to realize, because it underscores how markets have changed. given the near extinction of retail participation, and the almost total dominance of professional and algorithmic trading, it is unlikely that the biases and readily "available" cognitive reference points that are the hallmark of the retail trader, still exert their influence on pricing today.
more than ever, the market is predisposed to preying on unsophisticated traders; and there is no shortage of material for the flexions to practice on to refine their skills. the internet is full of trading forums, venting the opinions of naive wannabe traders who don’t know the difference between a stock and a bond, yet live in the delusional world in which they believe they can better the traders who are rigging the game. at the core of their beliefs is the illusion that they can grind out a living i.e., they can overcome trading friction and be consistent enough to collect a steady paycheck from the market, while taking very little risk and very small profits. they continue to believe in the existence of the exploitable edge that is reproducible on a daily or intra-day basis. and, herein lies the biggest and most stultifying misconception about trading -the belief in the existence of alpha and the denial that the grind is gone.
one of the many advantages of being a local trader on the floor of an exchange was that a trader could earn the bid/offer spread as an incentive for providing liquidity. when a local made a trade he could buy-the-bid and sell-the-offer, which meant he was buying below fair value and selling above fair value. in addition to this edge, traders were able to transact business at a cheaper rate than the public, and had first-hand knowledge of market structure and order flow. this enabled them to trade ahead of large orders and "race" the retail stop orders. a member trader did not have to go far in his quest for alpha.
following decimalization and regulatory initiatives aimed at creating competition between trading venues, the equities market fragmented, and liquidity was dispersed across many lit venues and dark pools. this complexity, combined with exchanges becoming electronic and for-profit, created profit opportunities for technologically sophisticated players. high frequency traders (HFTs) now use ultra-high speed connections with trading venues and sophisticated trading algorithms to exploit inefficiencies created by the new market structure, and to identify patterns in 3rd parties’ trading, so that they can use it to their own advantage in much the same way as the floor trader used his proximal and informational edge to generate alpha.
however, as a short-term, point-and-click, discretionary directional trader, one does not have access to the same process required to generate alpha. for traditional traders, the new market conditions insure that the playing field is tilted against them. retail traders continually find themselves falling behind these new competitors, in large part because the game has changed and because they lack the tools required to compete effectively. nevertheless, as the complexity of trading increases, it is still possible for a trader to separate from the pack and profit. the trader who has the better (more complete) and more timely (current) analysis will enjoy the greatest edge and have the greatest success, because they will have increased the gap between the traders who have adapted to the new environment, and the less informed, less diligent, and less talented ones.
it’s not that alpha doesn’t exist- it just doesn’t exist for the retail trader. what traders earn beyond the risk-free rate is not a true profit but simply factor compensation—the market rate for the risks they take. any positive expectation is the result of accepting that risk: the payment for taking such a position is compensation for risk, not an excess return. so, a trader must assess his approach to trading and decide what steps must be taken to find a proxy for alpha; and it begins with adopting an attitude, that is both realistic and relevant. the best any trader can hope to achieve, under any circumstance, is an incomplete, but probabilistic knowledge of the trading environment. so a trader must realize and accept that the markets are dominated by the rules of chance and randomness, both skill and luck come into play. how traders cope with probabilistic uncertainty and their imperfect view of the market is critical to their success. the essential job of traders then is to reduce uncertainty, not risk.
as a leveraged trader, one makes short-term decisions/trades, but understands what is happening at time frames greater than the one he's currently trading. the decision to trade and its management, flows from an analysis of price action. he is aware traders operate at different time-frames, markets are interconnected, themes abound in markets and that probabilities and departures from value govern trading opportunities. he understands and incorporates relevant informational signals from a wide range of deterministic processes to arrive at a summed probability that acts as deeper context.
he manages the risk through diversification, keeps draw-downs to manageable levels and strikes a balance between profit maximization and loss mitigation by adjusting trade size and stop-loss levels, so that only an extreme event will trigger the stop. he keeps losses in a predetermined range, and prevents getting stopped-out of a potential winner by managing expected value along with p&l, while allowing for a margin of error, so that he may stay-in-the-trade.
he is not concerned about how often he is right about the market, and frequently adds to his winners and turns short-term winning positions into longer ones. yet, never loses sight of the fact there is a downside scenario with an associated probability. the way decisions are evaluated affects the way decisions are made, so one does not allow stress, cognitive load, emotions, and bias, to non-linearly affect the decision process.
smart traders have the capacity to aggregate and synthesize large volumes of information, analyze it, and then derive an edge from it. the primary step in this process is to develop the capability to gather timely information from all the various sources and attach relevance to the information as accurately as possible. then merge both data sets, public information and proprietary tools, to derive insights that are applied in making trading decisions. good traders figure out what game is working and play that game. if they can understand the interactions of the individual factors and their effects on the market as a whole, then they will be able to identify higher order patterns that are the result of these interactions. going beyond the standard correlation/causation question, the trader must ask, does this source of edge make sense? is there a behavioral or structural reason why this source of edge should persist? and he must expect to be surprised and have to make adjustments, and build that into his expectancy.
good traders are always working on themselves, always refining what they do. in an important sense, they don't just use introspection to improve their performance. they work on their performance as a means of extending their personal mastery. the best traders spend significant time generating trade ideas, researching markets, and staying on top of developments worldwide. the ratio of time spent in preparation to time spent actually in trading, is a measure of a trader's professionalism
every trade a trader makes provides an opportunity to learn. gathering information from every trade, as opposed to a select few, helps give the trader a better understanding of how those trades may perform in the future. the more frequent the analysis, the more relevant the findings will be. however, the findings serve a purpose only if they are acted upon. the key is to use information to guide actions whose outcomes are then analyzed and the findings reapplied. this creates a continuous iterative loop that drives towards ever greater efficiency.
if you look at alpha as various types of beta doing different things at different times, then a trader's returns are going to be lumpy and cyclical in nature and performance will revert to the mean. the central message for traders then, is to trade efficiently, and make the most money with the least cost. it's not how often you're right, but how much you're right. if you want to make money, then maximizing geometric returns should be front and center in your thinking.
the market and its past is identical for all observers. yet, the market and the future are understood uniquely by each trader. no matter how crude or refined a method one follows in ascertaining the likelihood of change, it still boils down to surviving against one's own incomplete intellect, a misfired bout of randomness, in controlling the risk, and in executing a set of consistent ideas day in and day out, so that chance can prevail. the opportunity is there for the traditional trader to capture his personal alpha. all he has to do is see the market for what it is, and not what it was, or what it appears to be.