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A cow\'s technical analysis course (ZT)
Source: gutu
Phase 1 is to learn some traditional technical analysis indicators, such as MACD, KDJ, RSI, etc.. Found significant uncertainty.
Phase 2 study programmed with flying fox, download a lot of people to the indicators, but also learned Vb, found significant uncertainty, although the pattern infinite, but the essence of the traditional technical indicators and there is no difference, are established historical data on the basis of a simple average just all.
3 stage, the pursuit of more powerful statistical analysis, learning the SPASS, playing familiar with time series analysis of ARIMA. Found significant uncertainty. ARIMA residuals of the original white noise is not estimated.
Stage 4, Learning GARCH, damn SPASS actually do not have this tool, only to learn MATLAB7. GARCH playing cooked, we found lot of uncertainty. Original, GARCH is still essentially linear estimation, but will continue to ARIMA ARIMA residuals once. Fainted.
Stage 5, the network N by some people 忽悠 artificial neural network, started to play BP, RBF, found great uncertainty. BP, RBF fitting historical data is simply perfect, but the generalization of the future, simply is. Still did not give up, but also to improve the genetic algorithm crunching, using the chaos theory of phase space improvements, is still dog feces.
6 stage, listening to an artificial intelligence expert, said Nanda, SVM is the most NB, and continue to learn, this thing is difficult, at last, or to the buttoned up, the results found that significant uncertainty. Correct rate was disappointing.
Phase 7, the occasion of a loss, but also say N, is said to be useful wavelet, get looking through the book, feeling extremely difficult. But this time on the technical analysis has been shaken. Met a friend one day, combat expert, I talk to a presentation, discovery, by the wars, or some old-fashioned traditional indicators that the best is to use the magic key to a.
8 stage, at this stage, re-playing that traditional indicators of those few old-fashioned.
-------------------------------------------------- ----------
gutu see posts blind evaluation ：
The cattle were beef cattle in comparison to hard, how much to be versatile, have learned circle, in the jar show show, the stage has been put up pos. Light is no longer useless conclusion ： technical analysis, technical analysis is belated. But he still has not started, or did not find a their own, can make their way to make money with confidence. He only met a play some old-fashioned traditional indicators of the actual master, and re-learn and understand that a few old-fashioned indicators. He may also encounter a few will be different then the actual combat martial arts expert, I do not know how the situation would be?
In short, he had not realized that regular activity performed to set their own way. If the back is long to say, stop there! D D ： ：
一个牛人的技术分析历程(ZT)
来源: gutu 于 09-09-04 19:19:56 [档案] [博客] [旧帖] [转至博客] [给我悄悄话]
一个牛人的技术分析历程（ZT）
第1阶段,是学习一些传统的技术分析指标，如MACD，KDJ，RSI 等等。发现不确定性很大。
第2阶段，学习用飞狐编程序，下载个许多人编制的指标，还学习了Vb，发现不确定性很大，虽然花样无穷，但本质上与传统的技术分析指标没有差别，都是建立在对历史数据简单的各种均线基础上而已。
第3阶段，追求更厉害的统计分析，学习了SPASS，玩熟了时间序列分析ARIMA。发现不确定性很大。原来ARIMA对白噪音的残差没有估计。
第4阶段，学习GARCH，该死的SPASS居然没有这个工具，只好学习MATLAB7。GARCH玩熟後，发现不确定性很大。原来，GARCH本质上依然是线性估计，不过是将ARIMA的残差继续ARIMA了一次。晕倒。
第5阶段，被一些网络N人忽悠人工神经网络，开始玩BP，RBF，发现不确定性很大。BP，RBF对历史数据的拟合简直是完美，但对未来的泛化，简直是。仍然不死心，又捣鼓用遗传算法改进，用混沌理论的相空间改进，依然是狗屎。
第6阶段，听南大的一个人工智能专家说，SVM是目前最NB的，继续学习，这玩意很难，终于还是给搞定了，结果，发现不确定性很大。正确率让人失望。
第7阶段，茫然之际，又有N人说，据说小波可能有用，找来书翻翻，感觉无比艰深。而此时对技术分析已经信心动摇。某日遇一朋友，实战高手，一席交谈演示，发现，靠，实战中还是传统的那几个老掉牙的指标最好，关键是是运用之妙了。
第8阶段，目前阶段，重新玩那传统的那几个老掉牙的指标。
------------------------------------------------------------
gutu看帖瞎评：
这个牛人牛就牛在比较刻苦，多少“十八般武艺”都学了一圈，在坛子里show花架子，摆pos的阶段已经过了。已经不再轻下结论：技术分析无用，技术分析是马後炮。但是他还是没有入门，还是没有找到一个属于自己的，可以让自己有把握地挣钱的方法。他只遇到了一个“玩传统的几个老掉牙的指标”的实战高手，而重新学习与体会那“几个老掉牙”的指标。他可能後来还会遇到几个会不同武功的实战高手，不知情况又会如何？
一句话，他还没有悟到，做股票要有一套属于自己的方法。後面的话再说就长了，就此打住！ ：D ：D
A cow\'s technical analysis course (ZT)
Source: gutu
Phase 1 is to learn some traditional technical analysis indicators, such as MACD, KDJ, RSI, etc.. Found significant uncertainty.
Phase 2 study programmed with flying fox, download a lot of people to the indicators, but also learned Vb, found significant uncertainty, although the pattern infinite, but the essence of the traditional technical indicators and there is no difference, are established historical data on the basis of a simple average just all.
3 stage, the pursuit of more powerful statistical analysis, learning the SPASS, playing familiar with time series analysis of ARIMA. Found significant uncertainty. ARIMA residuals of the original white noise is not estimated.
Stage 4, Learning GARCH, damn SPASS actually do not have this tool, only to learn MATLAB7. GARCH playing cooked, we found lot of uncertainty. Original, GARCH is still essentially linear estimation, but will continue to ARIMA ARIMA residuals once. Fainted.
Stage 5, the network N by some people 忽悠 artificial neural network, started to play BP, RBF, found great uncertainty. BP, RBF fitting historical data is simply perfect, but the generalization of the future, simply is. Still did not give up, but also to improve the genetic algorithm crunching, using the chaos theory of phase space improvements, is still dog feces.
6 stage, listening to an artificial intelligence expert, said Nanda, SVM is the most NB, and continue to learn, this thing is difficult, at last, or to the buttoned up, the results found that significant uncertainty. Correct rate was disappointing.
Phase 7, the occasion of a loss, but also say N, is said to be useful wavelet, get looking through the book, feeling extremely difficult. But this time on the technical analysis has been shaken. Met a friend one day, combat expert, I talk to a presentation, discovery, by the wars, or some old-fashioned traditional indicators that the best is to use the magic key to a.
8 stage, at this stage, re-playing that traditional indicators of those few old-fashioned.
-------------------------------------------------- ----------
gutu see posts blind evaluation ：
The cattle were beef cattle in comparison to hard, how much to be versatile, have learned circle, in the jar show show, the stage has been put up pos. Light is no longer useless conclusion ： technical analysis, technical analysis is belated. But he still has not started, or did not find a their own, can make their way to make money with confidence. He only met a play some old-fashioned traditional indicators of the actual master, and re-learn and understand that a few old-fashioned indicators. He may also encounter a few will be different then the actual combat martial arts expert, I do not know how the situation would be?
In short, he had not realized that regular activity performed to set their own way. If the back is long to say, stop there! D D ： ：
一个牛人的技术分析历程(ZT)
来源: gutu 于 09-09-04 19:19:56 [档案] [博客] [旧帖] [转至博客] [给我悄悄话]
一个牛人的技术分析历程（ZT）
第1阶段,是学习一些传统的技术分析指标，如MACD，KDJ，RSI 等等。发现不确定性很大。
第2阶段，学习用飞狐编程序，下载个许多人编制的指标，还学习了Vb，发现不确定性很大，虽然花样无穷，但本质上与传统的技术分析指标没有差别，都是建立在对历史数据简单的各种均线基础上而已。
第3阶段，追求更厉害的统计分析，学习了SPASS，玩熟了时间序列分析ARIMA。发现不确定性很大。原来ARIMA对白噪音的残差没有估计。
第4阶段，学习GARCH，该死的SPASS居然没有这个工具，只好学习MATLAB7。GARCH玩熟後，发现不确定性很大。原来，GARCH本质上依然是线性估计，不过是将ARIMA的残差继续ARIMA了一次。晕倒。
第5阶段，被一些网络N人忽悠人工神经网络，开始玩BP，RBF，发现不确定性很大。BP，RBF对历史数据的拟合简直是完美，但对未来的泛化，简直是。仍然不死心，又捣鼓用遗传算法改进，用混沌理论的相空间改进，依然是狗屎。
第6阶段，听南大的一个人工智能专家说，SVM是目前最NB的，继续学习，这玩意很难，终于还是给搞定了，结果，发现不确定性很大。正确率让人失望。
第7阶段，茫然之际，又有N人说，据说小波可能有用，找来书翻翻，感觉无比艰深。而此时对技术分析已经信心动摇。某日遇一朋友，实战高手，一席交谈演示，发现，靠，实战中还是传统的那几个老掉牙的指标最好，关键是是运用之妙了。
第8阶段，目前阶段，重新玩那传统的那几个老掉牙的指标。
------------------------------------------------------------
gutu看帖瞎评：
这个牛人牛就牛在比较刻苦，多少“十八般武艺”都学了一圈，在坛子里show花架子，摆pos的阶段已经过了。已经不再轻下结论：技术分析无用，技术分析是马後炮。但是他还是没有入门，还是没有找到一个属于自己的，可以让自己有把握地挣钱的方法。他只遇到了一个“玩传统的几个老掉牙的指标”的实战高手，而重新学习与体会那“几个老掉牙”的指标。他可能後来还会遇到几个会不同武功的实战高手，不知情况又会如何？
一句话，他还没有悟到，做股票要有一套属于自己的方法。後面的话再说就长了，就此打住！ ：D ：D
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