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Part 1 Why $TICK Can Work
$TICK is the aggregate of stocks ticking up and ticking down in a realtime âsnapshotâ of all NYSE stocks. If 500 more stocks last ticked up than down on the NYSE, $TICK will be 500. The $TICK and $TIKQ (for NASDAQ) indicators are among the only pieces of short term technical data about entire exchanges of stocks publicly available on realtime data streams. While most system developers are concentrating on price information, here is a piece of short-term, aggregated information about thousands of stocks that move major indices.
While âfundamentalâ refers to the underlying condition (usually valuation) of a company or market and âtechnicalâ refers to price transformations, $TICK is neither. It is a mechanical structure of the exchange, describing a unique directional âstateâ of a huge group of securities. If this could be done on the company level, imagine a constant âvoting machineâ that computes internal corporate sentiment by the actions of its employees. Nearly impossible, right? But it certainly would be related in some way to the performance of the company. In the analogy, the exchange is the corporation and $TICK provides a âvoting machine.â
The reason $TICK can work better than traditional indicators is that most indicators are price transformations. Price transformations try to model patterns and in turn statistical edges directly from price changes. This usually does not work exceedingly well without curve fitting, and certainly requires rich diversification among price-based strategies to maintain low volatility characteristics. As a side note, the one major price based strategy that seems to be exploited successfully is the fact that the distribution of price changes have âfat tails.â In other words, price changes that would be unlikely based on a ânormalâ set of random price changes are (relatively) likely in the stock, commodity, and currency markets. Trend following systems exploit this piece of fundamental information by getting aggressive when these out-of-line movements occur. Think about that for a second. Trend following does not work because prices contain all there is to know about the market or because price leads news. It works because the systems are exploiting a fundamental piece of information about the distribution of price changes!
The key to getting a giant edge with technical analysis is to âzoom inâ on the marketâs environment and influences whenever possible. Contrary to popular belief, fundamentals are valuable to technical analysis because they can reveal clues that price alone canât. The best traders in the world agree that technicals should be used in tandem with fundamentals. I personally have always thought fundamentals can be incredibly technical, too!
Many traders are duped into taking âsidesâ of the fundamentalists or technicians. This campy attitude often influences a traderâs rejection of an entire input type. For example, some technicians claim that everything is priced into the markets and therefore price is the only information necessary to gain an edge. If only it were that easy! As mentioned earlier, price alone is the least likely input to yield statistical edge because price patterns can only influence price to a certain degree. There are basically two ways to use price alone to gain a statistical edge. One is to exploit the âfat tailsâ characteristic of financial markets, capturing those few times when big moves occur. A sub-problem of this strategy is to maximize those gains with position sizing, and maximum diversification is necessary. The second way is to use ten sor hundreds of individual adaptive systems that are constantly optimizing and learning which price transformations are currently showing the strongest edges. The first method requires ample diversification, and the second method requires complex programming and computing power. These are major tradeoffs for only using price data!
The point is by remaining open to both technical and fundamental information such as $TICK substructure, itâs easier (but not easy) to gain an edge with classical research methods and fewer resources.
Part 1 Why $TICK Can Work
$TICK is the aggregate of stocks ticking up and ticking down in a realtime âsnapshotâ of all NYSE stocks. If 500 more stocks last ticked up than down on the NYSE, $TICK will be 500. The $TICK and $TIKQ (for NASDAQ) indicators are among the only pieces of short term technical data about entire exchanges of stocks publicly available on realtime data streams. While most system developers are concentrating on price information, here is a piece of short-term, aggregated information about thousands of stocks that move major indices.
While âfundamentalâ refers to the underlying condition (usually valuation) of a company or market and âtechnicalâ refers to price transformations, $TICK is neither. It is a mechanical structure of the exchange, describing a unique directional âstateâ of a huge group of securities. If this could be done on the company level, imagine a constant âvoting machineâ that computes internal corporate sentiment by the actions of its employees. Nearly impossible, right? But it certainly would be related in some way to the performance of the company. In the analogy, the exchange is the corporation and $TICK provides a âvoting machine.â
The reason $TICK can work better than traditional indicators is that most indicators are price transformations. Price transformations try to model patterns and in turn statistical edges directly from price changes. This usually does not work exceedingly well without curve fitting, and certainly requires rich diversification among price-based strategies to maintain low volatility characteristics. As a side note, the one major price based strategy that seems to be exploited successfully is the fact that the distribution of price changes have âfat tails.â In other words, price changes that would be unlikely based on a ânormalâ set of random price changes are (relatively) likely in the stock, commodity, and currency markets. Trend following systems exploit this piece of fundamental information by getting aggressive when these out-of-line movements occur. Think about that for a second. Trend following does not work because prices contain all there is to know about the market or because price leads news. It works because the systems are exploiting a fundamental piece of information about the distribution of price changes!
The key to getting a giant edge with technical analysis is to âzoom inâ on the marketâs environment and influences whenever possible. Contrary to popular belief, fundamentals are valuable to technical analysis because they can reveal clues that price alone canât. The best traders in the world agree that technicals should be used in tandem with fundamentals. I personally have always thought fundamentals can be incredibly technical, too!
Many traders are duped into taking âsidesâ of the fundamentalists or technicians. This campy attitude often influences a traderâs rejection of an entire input type. For example, some technicians claim that everything is priced into the markets and therefore price is the only information necessary to gain an edge. If only it were that easy! As mentioned earlier, price alone is the least likely input to yield statistical edge because price patterns can only influence price to a certain degree. There are basically two ways to use price alone to gain a statistical edge. One is to exploit the âfat tailsâ characteristic of financial markets, capturing those few times when big moves occur. A sub-problem of this strategy is to maximize those gains with position sizing, and maximum diversification is necessary. The second way is to use ten sor hundreds of individual adaptive systems that are constantly optimizing and learning which price transformations are currently showing the strongest edges. The first method requires ample diversification, and the second method requires complex programming and computing power. These are major tradeoffs for only using price data!
The point is by remaining open to both technical and fundamental information such as $TICK substructure, itâs easier (but not easy) to gain an edge with classical research methods and fewer resources.
