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#1 Posted : Friday, January 6, 2006 3:40:17 PM(UTC)

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“The Encyclopaedia of Technical market Indicators” by Robert W Colby.
Published by McGraw-Hill. 2nd Edition About £35-£45 2003. ISBN 0-07-012057-9
A thick heavy book with 820 pages. I find it stimulating and well worth a read.

Colby reviews and tests 127 technical analysis indicators. He used Metastock to produce his results. He concludes that market prices move in trends and price trends persist. The best indicators for profit are Exponential Moving Average & Weighted Moving Average, plus Percentage Hughes AD oscillator with 8 parameters and some others.
Many indicators were worse than buy-and-hold even though some gave very high win rates. Although high win/loss rate is an obsession of novices, Colby favoured high reward/risk ratio (total net profit to maximum equity drawdown).

Colby describes how many of the top traders in the world, like Jack D Schwager, use back testing to prove their trading strategies. He mentions Richard Dennis turned $400 into $200M in 16 yrs dealing in the Chicago Futures market. Dennis taught his trading rules to 23 raw trainees whom he called his turtles. 20 out of 23 got average returns of 100% pa.

Indicator table
Each indicator is described in detail with the Metastock formula and system testing report (P&L summary stats). Colby trades using purely mechanical signals with no subjectivity, no sophisticated technical analysis and no judgement. He provides a 4 page table to rank the indicators by:
• Versus buy & hold = Overall percentage superiority of the indicator compared with buy-and-hold net profit amount.
• Annual relative advantage (percentage) compared with buy-and-hold.
• L & S % win (Long & short percentage win)
• Short % win (Short percentage win)
• Average trades per year – results showed huge variation from 0.2 trades pa to 141 trades pa. (Helpful for day traders and long term swing traders to see which indicator best suits their trading style).
• Profit loss index = $ amount of winners to losers. Worst performance is –100. Best is +100; zero when profit equals loss.

Colby’s Methodology - Nine steps to walk-forward simulation.
1. Form hypothesis. Both long & short trades are taken where possible. Dealing costs are ignored.
2. Get data – he used the DJ Ind Avg from 1900-98
3. Check data
4 Segment data in fixed length time periods. He used various periods such as DJ 1900-15, 1915-37, 1937-92, 1992-98
5 Optimise the earliest data segment to avoid curve fitting.
6 Walk-forward – the indicator is projected forward in time on next and more recent segments – to test the out-of-sample & unseen data.
7 Add walk-forward data segment from step 6 to optimised from step 5.
8 Repeat steps 5-7 until all unseen data is used.
9 Evaluate results.

Reviewed by Alphateam – Jan 2005
#2 Posted : Friday, January 6, 2006 4:10:08 PM(UTC)

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Thanks for the review Alpha :)
#3 Posted : Saturday, January 7, 2006 1:39:38 AM(UTC)

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I found that every system tested was optimized, they all lacked the use of a latch or system device to only test the first occurance of the signal.

The best ideas that can be found from this book are the odd indicators that can be derived and then traded
#4 Posted : Saturday, January 7, 2006 3:55:15 AM(UTC)

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Thanks for the excellent review, Alpha.

Colby favored high reward/risk ratio (total net profit to maximum equity drawdown).

Not good enough.

Given some luck, it is possible to have a historical maximum equity drawdown of $0. A system's large initial profit, can sometimes translate into a max equity drawdown of $0, even if it doesn't make another penny in profit for years to come and actually loses $ since the initial period.
This doesn't mean that the strategy is risk-free by any means.

Drawdown (i.e., the risk of losing all trading capital and going broke) should be measured from equity peak to trough, and the largest historical drawdown should then be used as the benchmark for possible future risk. After all, there is always the chance that the trader begins trading at the peak of the system's performance, and is looking at a major loss period ahead.

Sharpe ratio and other popular methods of measuring risk don't take into account real-world risk.

Dealing costs are ignored.

Big mistake.
Transaction costs (brokerage + slippage, spread) take out a large chunk of profits, specially when trading regularly. It's not unusual to see total transaction costs of 10%pa for EOD strategies, and 20%pa or more for more active ones. Remember, these costs come straight out of profits, or worse, are added to losses.

By not including transaction costs, it's impossible to compare Buy & Hold with very active trading strategies, such as day trading.

Normalizing risk - comparing apples to apples.

Trading strategy results should always be normalized to risk before any comparison can be made.

Let's take these two theoretical strategy examples:

1) Trading strategy A averages 20%pa net profit with a maximum historical drawdown (capital peak to trough) of 50%.

2) Trading strategy B averages 10%pa with a max historical drawdown of 20%.

Directly comparing strategy profits A to B, would result in the mistaken view that A is twice as profitable as B - whereas in fact, a potential trader (assuming a sound mind) would scale back position size when trading the riskier system A. Decreasing position size will then result in reduced potential profits.

So, normalizing A and B profits to max historical risk (downsizing position size in A to match risk in B), would eventually equate with:

1) Trading strategy A now averages 8%pa with a normalized max historical drawdown (peak to trough) of 20%.

2) Trading strategy B averages 10%pa with a max historical drawdown (peak to trough) of 20%.

Therefore, after normalizing for risk, trading strategy B actually outperforms trading strategy A in the real world.

Buy & Hold and trading strategies cannot be compared directly without first normalizing to risk. Buy & Hold often carries large drawdowns.

More on this (and Relative Strength Comparisons) in an upcoming article in the Feb issue of MSTT.

jose '-)
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