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One of my strategies is looking at the spreads between the underlying stocks relative to the actual pricing of ETFs It sounds complicated but it s really not I have to do this because the other volume strategies aren t working The cost to program this data runs into the millions of dollars If I m doing it, you can bet that teams of rocket scientists for all the big trading shops are also doing it It s all wrong The tail is wagging the dog And the dog just happens to be the capital markets that make our economy Sincere: Thanks for sharing your insights

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(5103)

1 with K1 and P+ computed as shown in Table 58 Given x and + , the x1 1 best estimate of the total state after the measurement is 1 1 1 x1 x+ = x + + = x + K1 z1 (5104)

Shah Gilani, a former Wall Street executive and hedge fund manager, runs a private equity firm from his base in Miami and is a contributing editor at MoneyMorningcom He is also editor of the Capital Wave Forecast newsletter and owner of WhatMovesMarketscom WHAT S NEXT

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which is equal to the expected value of x(t1 ) after accounting for the measurement information at time t1 , which is denoted as x+ Because the state 1 correction of eqn (5104) results in x+ (t1 ) = E x+ then it is now true 1 that 1 (5105) + = x+ E x+ = 0 x1 1 The software implementation of the algorithm must make the assignment + = 0 immediately after implementing eqn (5104) Failure to reset x1 + 1 to zero after correcting the total state estimate as in eqn (5104) x would result in double accounting for + in the subsequent measurement x1 correction The result of eqn (5104) serves as the initial condition for the next period of integration Because + = 0, we will have that x = 0 x1 2 and the measurement correction at t2 will still reduce as in eqn (5103) The above procedure can be replicate at each measurement instant Note that it is not proper to state that the error state is not propagated through time It is correct to state that the error state time propagation is trivial and is therefore not implemented A detailed example of the use of the error state to correct the total state is presented in Section 126

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There are many excellent books on Kalman lter theory and design The main references for the presentation of this chapter were [31, 34, 58, 60, 93] The complementary lter and its relation to the Kalman lter is described well in [30, 31] Alternative nonlinear estimation approaches, including the unscented and particle lters, are presented in a uni ed notation similar to that used herein in [121]

The creator of the next indicator, former software engineer Pascal Willain, developed a proprietary indicator to follow institutional volume In the following interview, he gives an explanation of how he uses Effective Volume to gain an edge in the market

Exercise 51 In eqn (522) on p 175, let S = H(H WH) 1 H W 1 If W = R 1 = 2 I show that S = H(H H) 1 H 2 For W symmetric and positive de nite, use direct multiplication to show that S is idempotent 3 Show that (I S) is idempotent

the market, he developed his own price and volume indicator, Effective Volume (EV) (Note: A chart of Effective Volume is located in 12) So Willain quit his job several years ago and concentrated on perfecting his indicator, which reconstructs the original orders the institutions are sending to the market Willain s statistical indicator, which he believes has also been developed by other financial institutions, determines if money is coming into or going out of the market My goal at the beginning was to find out what the institutional players were doing at the transactional level, Willain says, especially at critical points in a trend

Exercise 52 If Y RN 1 , H RN n , and x Rn 1 , the solution to the least squares problem from eqn (525) is x = (H H) 1 H Y (5106)

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