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If your eyes gloss over because of all the indicators from which to choose, Steenbarger has some advice There is no reason to look at 100 indicators, Steenbarger quips If you have a watch, you always know the time of day If you have two watches, you never know the time of day With too many indicators, he says you ll always find something that is contradictory Don t keep it simple, because there s a risk it will be simplistic, but keep it focused Find the few indicators that speak to you, that make sense to you, and that you are willing to follow over time Then you can internalize these indicators and get to know them intimately I would rather follow 6 or 7 indicators and really learn their ins and outs rather than 30 in a casual fashion Some traders, especially beginners, don t always know what indicators are supposed to do He gives this advice: The indicator

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which shows that the measured pseudorange s r (t) is proportional to r the time of propagation ts plus the receiver clock error r (t) minus the r satellite clock error s (t ts ) at the time of transmission The time of r propagation will be further analyzed in subsequent sections

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is like a reading a physician takes A physician will read your blood pressure, take your temperature, and test your reflexes But the physician has to interpret the data and put together a diagnosis And that s what traders need to do: look at the indicators and other data, and put together a diagnosis of the market What novice traders often do instead, he cautions, is to think that the indicator itself is the diagnosis and that it will make the decision for them That just doesn t happen Because indicators are not as simplistic and mechanical as many people believe, Steenbarger thinks that some have gotten a bad name: A physician wouldn t prescribe something by running only one test So traders also shouldn t allocate their capital based on the results of one indicator

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8 Given that the state is controllable from the driving noise and is observable from the measurements, the Kalman lter estimation error dynamics are asymptotically stable Therefore, for an observable system, the e ects of the initial conditions (x and P ) decay away and 0 0 do not a ect the solution as k Since the above properties rely on three assumptions, it is natural to consider the reasonableness of these assumptions Although most physical systems are in fact non-linear, the linearity assumption can be locally applied when the system non-linearities are linearizable and the distance from the linearizing trajectory is small These conditions are usually valid in navigation problems, especially when aiding information such as GPS is available The white noise assumption is also valid, since colored driving noise can be modeled by augmenting a linear system with white driving noise to the system model The Gaussian assumption is valid for most driving noise sources as expected based on the Central Limit Theorem [107] Even when an application involves non-Gaussian noise, it is typical to proceed as if the noise source were Gaussian with appropriately de ned rst and second moments In such cases, although a better nonlinear estimator may exist, the Kalman lter will provide the minimum variance, linear, unbiased state estimate

The Kalman lter algorithm as presented in Table 55 is formulated to process a vector of m simultaneous measurements The portion of the measurement update that requires the most computing operations (ie, FLOP s) is the covariance update and gain vector calculation For example, the standard algorithm K x+ P+ = P H R + HP H = x + K( H ) y x = (I KH) P

To be an informed trader, you have to scratch beneath the surface and dig up information that is useful in that diagnostic process Just because an indicator is on a charting system or is mentioned doesn t mean it s an accurate decision guide, Steenbarger warns Obviously, there are no guarantees that any indicator is going to be foolproof Steenbarger, like many traders, is looking for something more concrete I m not looking for specific signals to make a decision, he says I m looking for themes across indicators You get so focused on what one indicator is saying and miss the broader themes No indicator gives a precise prediction all the time, but I think if you look at the weight of the evidence, if you look across indicators, you can make some important decisions

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