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He has done much more than that: Rocket Science for Traders Cybernetic Analysis Cycle Analytics etc

I would probably say that finding the beginning and end of a trend is not easy. Fine, forget trends and use a highpass or bandpass filter and trade cycles. But then one is left with the same conundrum of forecasting the dominant market frequency. J. Ehlers has a bit to say about that.

Finding a current trend (however one defines it) is easy, and people are not incompetent at finding it. What makes it difficult to profit is that the beginning and end of trends are randomly distributed through time. Prices transition from trending to cycling and nobody knows when that...

To paraphrase W. Churchill "capitalism is about the unequal distribution of the wealth, while socialism is about the equal distribution of the misery." So yes, capitalism is the way to go, but the current system in the US is not going to go on like this indefinitely. It is a house of cards. I'm...

The history of economies with fiat currency and a fractional reserve banking system have not generally ended well. A good read about this subject is "The Creature From Jeckyll Island."

"As far as the laws of mathematics refer to reality, they are not certain, and as far as they are certain, they do not refer to reality.” Albert Einstein Apparently Simmons has found something that makes math and reality converge to a profitable degree. Anyone have a clue what that math is...

Approx. half the people would see a higher low and initiate a long. Approx. half would see failure to break through resistance and initiate a short with the momentum. A few would see nothing and not react, and a few more would see something completely different and act according to their views...

Just keep in mind that if you at all believe in the random walk theory of the markets (geometric brownian motion, with discontinuities (i.e. jumps), and stochastic volatility), then indicators and all of TA is bullshit. The areas where random walk really breaks down of course are trading on...

Absolute anonymity is a weapon of mass destruction, and no government is ever going to allow it.

A more realistic model is to combine Merton-style lognormally distributed jump process to the Heston stochastic volatility process. But this discussion would probably be better suited to the Wilmott forums.

Even geometric brownian motion, which seems to be the best market model currently, produces patterns which look like trends, in hindsight.

You are correct. Surfaces, when properly normalized, are fairly stable over time. But, if you can identify a distortion, that presents a possible opportunity. The distortions, should they occur, would be difficult for a retail trader to exploit. There is no "edge" for a retail trader in in the...

The distortions (or mispricings if you prefer) is were opportunity lies. Filtering these out is throwing away opportunity. Another way to look at it is that you are filtering out the high frequency noise from the signal. Problem is, there is no noise, it is all signal.

The idea of analyzing surfaces is to look for distortions which may present one with a trading opportunity (possibly edge?) I did some investigating of surface distortions perhaps 10 years ago and quickly came to the conclusion that any distortion is going to quickly get arbed away, particularly...

This paper describes how to build a normalized volatility surface. http://thfinance.de/RobertTompkins/EJF2.pdf

The geometric Brownian motion of price and the lognormal distribution are still the best model of market behavior anyone has yet devised. It is not a perfect model, since all financial distributions have some degree of skew and kurtosis to them, which means the underlying processes are more...

Open a spreadsheet and type in this formula: =normsdist(1) which returns .8413, meaning 84% percent of the area under the "bell curve" lies to the left of 1 std. Sell a call option 1 std OTM, and you have an 84% chance of winning at expiration. =normsdist(-1) returns 0.15685, meaning 16% of...

I think John Ehlers no longer recommends the Hilbert Transform because of too much lag in the calculation. He instead recommends the Autocorrelation Periodogram to calculate the dominate cycle.

I wouldn't recommend investing in a "black box" strategy. Do it yourself with simple algorithms like Buy when close has decreased 7 days in a row and close > 200MA, or Buy when 10-day Fisher Transform < -7 and close > 200MA. You will need to add some risk and money management rules in to the...

The volatility parameter, sigma, is the actual or realized volatility of price. It's definition is one standard deviation of the logarithm of the daily percent price change annualized. For example if you are looking at 45 days until expiration, you would calculated the historic realized 45-day...