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behavior of a crowd of people It s a herd mentality Crowds will tend to follow each other and want to do the same thing together Raschke notes there is a middle part where the crowds can be correct, but not for long You want to be careful when the crowd gets crowded, she says She explains this concept with the following example: Let s say a stock has rallied up for two days If you ask people about that stock, more than 50 percent will say it has an upside bias, that the stock is going higher the next day There is a school of thought called behavioral finance that explains why people develop biases What is interesting, she says, is there is only a 50-50 chance the stock will be up the third day People have a built-in bias toward whatever the most recent movement was These biases aren t necessarily grounded in logic or rational In general, the decision making of most people tends to be flawed And it is this collective psychology, she notes, that repeatedly shows up as a pattern on a chart or in a sentiment reading When the sentiment readings begin hitting extremes in either direction, you want to be a contrarian, she recommends It doesn t mean you step in front of the train, but you look for other signs the market will go in the opposite direction Specifically, Raschke, as well as other traders, believes that the sentiment survey readings give important clues as to crowd psychology It s also wise, she suggests, to listen to what the markets are telling you: If all of a sudden you saw there was only a 20 percent bearish reading, that would be a warning sign everybody s already long There s no new money coming into the market You would assume the market was ripe for a correction Raschke says that obviously you wouldn t make trading decisions based solely on sentiment surveys, but you would want to consult the chart for other clues, such as support and resistance or a break in the trendline Our job as traders is to analyze things and see if there are warning signs, Raschke says It s not a 100 percent science; there is definitely some art to it But the art comes from experience If a radiologist is reading an X ray, the more experience he has, the more confident he will feel in his diagnosis What you should be wary of, according to Raschke, is conducting your own informal interviews: Just because the friends.

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Figure 53: Measurement bias complementary lter for Example 54 where wk = vk nk and wk N (0, (1 + 2 ) 2 ) Assuming that there is no prior information about B, this is the problem of estimating a constant from independent noise corrupted measurements of the constant that was discussed in Example 53 The solution is 1 r Bk = Bk 1 + ( k Bk 1 ) k starting at k = 1 with B0 = 0 Note that the value of B0 is immaterial 2 The estimation error variance for Bk is PB (k) = (1 + 2 ) Given this k estimate of B, using eqn (571), the value of xk can be computed as xk = zk Bk ,

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1 where the error variance for xk is Px (k) = (1 2 ) k + 2 2 Initially, 2 the variance of x is as the number of measurements k increases, the variance of x decreases toward 2 2 This example has relevance to GPS applications for estimation of ionospheric delay and for carrier smoothing of the pseudorange observable

you hang out with lost their jobs and are gloomy doesn t mean that other people feel that way And that s the whole point of studying the official sentiment polls and surveys, she says They are more effective because they include a broad cross section of people, and not just your friends

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This example is further investigated in Exercise 511 That exercise considers the case where the measurement error process nk is not white Example 55 Section 494 presented a one dimension aided INS example using a state estimation gain vector designed via the pole placement approach That example is continued here using a Kalman lter The state space description and noise covariance matrices are speci ed in Section 494 In the example, the initial error covariance matrix P (0) is assumed to be a zero matrix The performance of the estimator is indicated by error standard devia2 tion plots are shown in the left column of Figure 54 where var( ) = p , p 2 2 b) var( ) = v , and var( = b The portion of this curve that appears as v a wide band in the left column of gures is due to the covariance growth between position measurements followed by the covariance decrease at the measurement instant If the time axis was magni ed, this growth and decrease would be clearly evident as it was in Figure 47 The resulting timevarying Kalman lter gains are plotted in the right column The Kalman

Raschke has learned that to be successful in the market you need to keep an open mind I see people that get stuck on one side of the market or the other, she says There are people who are always bullish or always bearish The biggest mistake people make is not being flexible and, perhaps more important, not admitting when they are wrong What amazes Raschke is that even after 30 years of professional trading, every day I m in the market I realize how much I don t know I am learning something new every day In the past, she never would have looked at global money flows, emerging markets, or the yield-curve relationship But she does now Things are always changing, she points out Even if you re an investor, Raschke suggests, you should look at what the market is doing at least once a week This means using indicators in conjunction with a bar chart And finally, be aware of your own feelings, especially if you are feeling overly bearish or bullish Sometimes our feelings can be indicators as well, she adds

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