Yamato
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page 89, Lunar and Solar Phenomena
page 90, Cycles and Rhythms
I thought cycles and seasonality were the same thing, but here it seems they are not. What I really did with many of my systems is use what they call "cycles". I'll look at seasonality a bit longer and may drop that chapter, too.
page 91, Neural Networks
Wow, this really sounds perfect for many chart patterns: "those recognizable by eye but difficult to define using precise rules". So maybe I should read that chapter as well. And I will in fact. It's already on my list. Damn, I wish I could use neural networks correctly. I really need to quit my job to do this stuff properly.
Genetically Evolved Entry Rules
Yeah, I am now familiar with this stuff, thanks to RiskOptimizer. I must try it again before moving on to the rest of this section. For today I am done with reading. Now I will work more on this concept:
I will try to get RiskOptimizer to do more than just Portfolio Optimization. It will take hours and days to exploit this beautiful little program.
When I'll come back, I'll have to resume from here:
page 91, STANDARDIZED EXITS
Everything is falling apart. The only thing I have right now is this book and the systems and the investors. No capital, just my little debt with my own bank. No help from my parents who don't believe in my trading. I have to keep reading. Just in case things turn out for the best. Right now things are sucking badly. Yes, the systems did make some money, but a ridiculous amount for the many months we've been trading them (5 months).
I'll just keep working, as I always do, whether I am doing good or not.
STANDARDIZED EXITS
Let's hope that now my father won't come home and talk to me about his impending death again. Ok, he just showed up, and I didn't let him talk. I told him about the RiskOptimizer, boring him to death as usual. But he didn't die, because he said he has to die in about 10 years. I don't know why I talk to him anymore. I guess I talked to him because I didn't want him to talk to me. Yeah, that's all it was. I was in the kitchen when he showed up and I could not run fast enough to my room and lock myself in. The disgust from talking to him and seeing him bored will vanish in a few hours, but I didn't have to hear his death talk one more time.
I am not likely to read this chapter. To me it sounds like Nostradamus prophecies. These people are astronomers - they are crazy about this stuff. I am not falling for this stuff. It would be as if I created as system based on vito.Do lunar and solar events influence the markets? Is it possible for an entry model to
capitalize on the price movements induced by such influences? The moon’s role in
the instigation of tides is undisputed. Phases of the moon correlate with rainfall and
with certain biological rhythms, and they influence when farmers plant crops. Solar
phenomena, such as solar flares and sunspots, are also known to impact events on
earth. During periods of high solar activity, magnetic storms occur that can disrupt
power distribution systems, causing serious blackouts. To assume that solar and
lunar phenomena influence the markets is not at all unreasonable; but how might
these influences be used to generate predictive, countertrend entries?
Consider the lunar rhythm: It is not hard to define a model that enters the market
a specified number of days before or after either the full or new moon. The same
applies to solar activity: An entry can be signaled when the sunspot count rises above
some threshold or falls below another threshold. Alternatively, moving averages of
solar activity can be computed and crossovers of these moving averages used to time
market entries. Lunar cycles, sunspots, and other planetary rhythms may have a real,
albeit small, impact on the markets, an impact that might be profitable with a properly
constructed entry model. Whether lunar and solar phenomena actually affect the
markets sufficiently to be taken advantage of by an astute trader is a question for an
empirical investigation, such as that reported in Chapter 9.
page 90, Cycles and Rhythms
Chapter 10 explores cycles and rhythms as a means of timing entries into the market.
The idea behind the use of cycles to time the market is fundamentally simple:
Extrapolate observed cycles into the future, and endeavor to buy the cycle lows
and sell short the cycle highs. If the cycles are sufficiently persistent and accurately
extrapolated, excellent countertrend entries should be the result. If not, the
entries are likely to be poor.
For a very long time, traders have engaged in visual cycle analysis using
charts, drawing tools, and, more recently, charting programs. Although cycles can
be analyzed visually, it is not very difficult to implement cycle recognition and
analysis algorithms in software. Many kinds of algorithms are useful in cycle
analysis-everything from counting the bars between tops or bottoms, to fast
Fourier transforms (FITS) and maximum entropy spectral analyses (MESAS).
Getting such algorithms to work well, however, can be quite a challenge; but having
reliable software for cycle analysis makes it possible to build objective, cyclebased
entry models and to test them on historical data using a trading simulator.
I thought cycles and seasonality were the same thing, but here it seems they are not. What I really did with many of my systems is use what they call "cycles". I'll look at seasonality a bit longer and may drop that chapter, too.
That's right: most of my systems are based on endogenous cycles. I do not use exogenous cycles at all (unless you consider the time of the day and the month of the year an exogenous thing). Ok, I will read the "seasonality" chapter as well, because it's still not clear whether it is what I need or not. So recap on chapters to read: 6, 8, 10, 11, 12.Whether detected visually or by some mathematical algorithm, market
cycles come in many forms. Some cycles are exogenous, i.e., induced by external
phenomena, whether natural or cultural. Seasonal rhythms, anniversary effects,
and cycles tied to periodic events (e.g., presidential elections and earnings reports)
fall into the exogenous category: these cycles are best analyzed with methods that
take the timing of the driving events into account. Other cycles are endogenous;
i.e., their external driving forces are not apparent, and nothing other than price data
is needed to analyze them. The 3-day cycle occasionally observed in the S&P 500
is an example of an endogenous cycle, as is an S-minute cycle observed by the
authors in S&P 500 tick data. Programs based on band-pass filters (Katz and
McCormick, May 1997) and maximum entropy (e.g., MESA96 and TradeCycles)
are good at finding endogenous cycles.
We have already discussed the exogenous seasonal cycles, as well as lunar
and solar rhythms. In Chapter 10, endogenous cycles are explored using a sophisticated
wavelet-based, band-pass filter model.
page 91, Neural Networks
As discussed in Chapter 11, neural network technology is a form of artificial intelligence
(or AI) that arose from endeavors to emulate the kind of information processing
and decision making that occurs in living organisms. Neural networks (or “nets”)
are components that learn and that are useful for pattern recognition, classification,
and prediction. They can cope with probability estimates in uncertain situations and
with “fuzzy” patterns, i.e., those recognizable by eye but difficult to define using precise
rules. Nets can be used to directly detect turning points or forecast price changes,
in an effort to obtain good, predictive, countertrend entry models. They can also vet
entry signals generated by other models. In addition, neural network technology can
help integrate information from both endogenous sources, such as past prices, and
exogenous sources, such as sentiment da@ seasonal data, and intermarket variables,
in a way that benefits the trader. Neural networks can even be trained to recognize
visually detected patterns in charts, and then serve as pattern-recognition blocks within
traditional rule-based systems (Katz and McCormick, November 1997).
Wow, this really sounds perfect for many chart patterns: "those recognizable by eye but difficult to define using precise rules". So maybe I should read that chapter as well. And I will in fact. It's already on my list. Damn, I wish I could use neural networks correctly. I really need to quit my job to do this stuff properly.
Genetically Evolved Entry Rules
Chapter 12 elaborates a study (Katz and McCormick, December 1996) demonstrating
that genetic evolution can be used to create stable and profitable rule-based
entry models. The process involves putting together a set of model
fragments, or “rule templates” and allowing a genetic algorithm (GA) to combine
and complete these fragments to achieve profitable entries. The way the methodology
can discover surprising combinations of rules that consider both endogenous
and exogenous variables, traditional indicators, and even nontraditional
elements (e.g., neural networks) in making high-performance entry decisions will
be examined. Evolutionary model building is one of the most advanced, cuttingedge,
and unusual techniques available to the trading system developer.
Yeah, I am now familiar with this stuff, thanks to RiskOptimizer. I must try it again before moving on to the rest of this section. For today I am done with reading. Now I will work more on this concept:
The process involves putting together a set of model fragments, or “rule templates” and allowing a genetic algorithm (GA) to combine and complete these fragments to achieve profitable entries.
I will try to get RiskOptimizer to do more than just Portfolio Optimization. It will take hours and days to exploit this beautiful little program.
When I'll come back, I'll have to resume from here:
page 91, STANDARDIZED EXITS
Everything is falling apart. The only thing I have right now is this book and the systems and the investors. No capital, just my little debt with my own bank. No help from my parents who don't believe in my trading. I have to keep reading. Just in case things turn out for the best. Right now things are sucking badly. Yes, the systems did make some money, but a ridiculous amount for the many months we've been trading them (5 months).
I'll just keep working, as I always do, whether I am doing good or not.
STANDARDIZED EXITS
Yes, I have that already. I use time exits on every system.To study entries on their own, and to do so in a way that permits valid comparisons
of different strategies, it is essential to implement a srandardized exit that will be
held constant across various tests; this is an aspect of the scientific method that
was discussed earlier. The scientific method involves an effort to hold everything,
except that which is under study, constant in order to obtain reliable information
about the element being manipulated.
Hmm, too much crap for my liking.The standardized exit, used for testing entry models in the following chapters,
incorporates the three functions necessary in any exit model: getting out with a profit
when the market moves sufficiently in the trade’s favor, getting out with a limited
loss when the market moves against the trade, and getting out from a languishing
market after a limited time to conserve margin and reduce exposure. The standard
exit is realized using a combination of a stop order, a limit order, and a market order.
Too complex for me. I don't wanna do it like this. Too many variables.Stop and limit orders are placed when a trade is entered. If either order is
filled within a specified interval, the trade is complete, the remaining order is canceled,
and no additional orders are placed. If, after the allotted interval, neither the
stop nor limit orders are filled, they are canceled and a market order is placed to
force an immediate exit from the trade. The stop order, called a money management
stop, serves to close out a losing position with a small, manageable loss. Taking a
profit is accomplished with the limit order, also called a profit target. Positions that
go nowhere are closed out by the market order. More elaborate exit strategies are
discussed in “Part III: The Study of Exits,” where the entries are standardized.
Let's hope that now my father won't come home and talk to me about his impending death again. Ok, he just showed up, and I didn't let him talk. I told him about the RiskOptimizer, boring him to death as usual. But he didn't die, because he said he has to die in about 10 years. I don't know why I talk to him anymore. I guess I talked to him because I didn't want him to talk to me. Yeah, that's all it was. I was in the kitchen when he showed up and I could not run fast enough to my room and lock myself in. The disgust from talking to him and seeing him bored will vanish in a few hours, but I didn't have to hear his death talk one more time.
Yes, I use this method for entries, on my volatility measures.Money management stops and profit target limits for the standardized exits
are computed using volatility units, rather than fixed dollar amounts, so that they
will have reasonably consistent meaning across eras and markets. Because, e.g., a
$1,000 stop would be considered tight on today’s S&P 500 (yet loose on wheat),
fixed-dollar-amount stops cannot be used when different eras and markets are
being studied. Volatility units are like standard deviations, providing a uniform
scale of measurement. A stop, placed a certain number of volatility units away
from the current price, will have a consistent probability of being triggered in a
given amount of time, regardless of the market. Use of standardized measures permits
meaningful comparisons across markets and times.
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