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The task is to identify when a trend starts or ends, and do it consistently. Consistently is extremely difficult to do. Some people say that you should just look to take the meat in the middle of the trend swings. I have never found enough meat there to be profitable. Repeatability is almost...

Consider that the Islamic faith considers Jesus to have been a real person. They do not recognize him as God of course, just a prophet of God.

Another Sunday, another 1000 pushups. It's not as impressive as it sounds. It may be a high count, but doing 100 every hour doesn't ever really produce a good pump or lactic acid burn. I'm considering going to higher rep counts in the set, and fewer sets.

If you are interested in a method utilizing standard deviations, look at John Ehlers' Fisher Transform. You still are required to choose a lookback period however. Since market data is fractal in nature, one value of N is probably just as good (or meaningless) as any other value of N.

Yes, but the transitions between trend and chop occur randomly in time, and at all time frames. However, the nature of the randomness is such that using Gaussian statistics to analyze markets is not so accurate of a model either. It's a tough game to be sure.

I have never timed it, but I would guess 250-300. I am doing 1000 pushups today. 100 every hour.

It's not just about the probability of winning (or odds in this case), but the payoff that one should care about. So 99:1 that I'll win a penny or lose $1,000,000 is a terrible proposition. 99:1 I'll win $1 or lose $2 is a much better bet. Payoff = probability*(reward/risk).

First, in trading, you never can know the true odds, only an estimate. Second, the odds aren't always at some fixed percent. Third, look to maximize payoff, not just probability. payoff = probability*(reward/risk)

Not enough precision in that answer. Is a pullback a pullback or a trend change? If a pull back, what percent do you do you call it at? High an low are only relative, not absolute. High and low need to be put into some sort of context, whether by fundamental or technical analysis.

John Ehlers has done a lot of work on identifying cycles in the markets using DSP. Just Google his work, and specifically his work on finding the "Dominant Cycle." Now, there is a philosophical argument to be made against using DSP to analyze financial data. DSP was designed for use with...

C++ code for IV using the method of bisections with a call, and the BS model. http://finance.bi.no/~bernt/gcc_prog/algoritms_v1/algoritms/node8.html#SECTION00423000000000000000

Yes, the better way to do this is to filter backward, then filter forward, instead of filtering forward and then backward as in my first spreadsheet. This avoids having to estimate startup values at the hard right edge of the chart. See attached examples.

1. For the degree of precision needed in trading zero phase == zero lag. 2. It does change the value of some of the past data, but past data is not what you trade on. You trade on the hard right edge of the chart only, and can thus can be used in real time if needed. 3. ??? 4. This is not...

You know I didn't invent this math or this method. It really is zero lag. See attached spreadsheet for daily Merck data. The only parameter you need to change is the period (cell C1), which has the effect of changing the filter cutoff frequency.

I recently discovered how to implement a zero lag filter and wanted to share it here. Use your favorite IIR (recursive) filter and use in a bidirectional (aka forward-backward) method. https://www.dspguide.com/ch19/4.htm This works by forward filtering price using the recursive feature of an...

TA in general will only have 50% precision at best if price moves are random. I still use TA in order to give some kind of context to the meaning of high and low, and in order to get at least slightly higher odds than 50/50 to a price move. As for RSI specifically, I would urge folks to read...

Not unless your average gains exceed your average losses. It's called a positive expectancy system. Everyone has losses, but almost no one has a positive expectancy trading system. You can determine expectancy through rigorous backtesting or by empirical results (ie trail and error.) The later...

There are a million ways to define a trend, but you will never find one that is more than 50% accurate (you know, geometric brownian motion and all.)

So what specific methods were these guys using that you "bought into" and is that something that could be replicated easily buy a retail trader? You mention time and sales. Is it just identifying direction of large order flow and riding coat tails, or is it turning the market during slow periods...

Since prices are assumed to move via Geometric Brownian Motion, the geometric mean is what you should use. Although the difference in accuracy between arithmetic, geometric, and harmonic means is small and probably will not make a difference to your trading methodology or returns.