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Building Your Trading System – Part 3
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Building Your Trading System – Part 3

by ScottMarch 11, 2014

This is Scott, filling in for Mole this week, and I’d like to continue with our work on System Building and optimization.  Today we move away from the intangibles and get deep into the weeds of classifying and measuring market type and looking at how to find a prospective edge, choose an initial stop and an entry technique, and do some preliminary backtesting to work out if we have something real or are we curve fitting.

If you haven’t read my earlier posts here and here you may wish to do so.

In my experience when I hear a trader identify as ” I’m a discretionary trader” this is really subconscious code for “I want to do what I want when I want and I don’t want to have any restrictions on what I can and can’t do!” Implicit in that you can almost hear the 5 year old inside your subconscious screaming “na na na na na you can’t make me trade with your stupid rules! I’ll do what I want!!”.In almost every case of the so called “discretionary trader” ongoing performance monitoring, emotional state monitoring and mistake monitoring are absent, save a quick glance at P&L. The benefits of trading within either a strict set of rules or a loose set of guidelines are huge.

The first principle that really needs to be set in stone is that

It is madness to build a trading system and expect it to work all the time – You must build a system with a certain market type in mind

Markets change character on multiple timeframes. There are NO setups, indicators or entry techniques that work perfectly at all times, and you should not believe anyone who says any different. In 2009 I first noticed that Ivan’s setups (see the cheat sheet above) would regularly give me periods with 8 or 9 winners in a row, and then give me periods of 8 or 9 losers in a row. I was intrigued about this, and wondered if I could improve my systems by standing aside from the losing times. Ivan is well aware of this property inherent to markets, which he calls easytime/hardtime. For those who trade Ivan’s patterns, because they mostly have very tight stops at the highs or lows of previous bars, when markets get choppy you get a lot of stopped out trades. When markets become smooth and orderly with few overlapping bars Ivan’s patterns perform with a huge edge. The same thing is inherent in momentum based indicators, which are a significant edge in sideways markets which are not high volatility, but which are a negative edge in strongly trending markets. Overall if you measure the edge of something like MACD or Stochastics you will find a negative edge, but if you are particular about the type of market phase you apply it to you these indicators can still be useful.

Some points, in no particular order about volatility and markets are below. If you read these closely you can see that the natural flow of markets from quiet to volatile and back again is something of an edge in itself, and this property is the basis of many of the edges I will outline below.

  • Another way of saying “choppy markets with lots of overlapping bars” is LOW VOLATILITY.
  • Another way of saying “few overlapping bars” is RISING VOLATILITY.
  • Sideways markets are INHERENTLY DIFFERENT from trending markets
  • Low volatility markets (on a daily timeframe) make day trading harder and swing trading and position trading easier. Think about all the “day traders” who could not trade after the dot.com boom ended.
  • In low volatility trending markets (like the low volatility melt up in the stock market the last few years) counter trend trades have a DRAMATICALLY LOWER chance of working.
  • Extremes in both HIGH AND LOW VOLATILITY are unsustainable and indicate a market with the potential to change character
  • Bull quiet markets last the longest time. Bear quiet markets last the shortest time and arguably it is not worth developing systems for these markets.
  • The highest probability for market phase following a low volatility sideways phase is a high volatility trending phase
  • The highest probability for market phase following a low volatility trending phase is a high volatility trending phase in the opposite direction.

Excuse my shitty drawing, but in the broad strokes this is what the different market types look like. Obviously designing a system for any one of these market types overall is doable. A 5 year old could see that building systems for sideways markets should be based around the fundamental principle of buy low-sell high, and that in a sideways quiet market scalping is going to be better than trying to hold for a bigger move. A 5 year old can also see that building a system for bull quiet markets (what we have now) is very very different than building a system for bull volatile market. As a general rule the systems we build are a reflection of our personality. Extremely smart people (like my mentor Ivan) tend to build incredibly complex systems with many moving parts. This is great for him and allows him to trade them with very high levels of efficiency, as it is a closer match with his psychology, but objectively adds nothing to the overall system performance. Quite often you see this phenomenon with highly intelligent value investors also. People who are extremely experienced at market flow and philosophically without serious psychological issues can operate with a far greater degree of discretion and intuition, and this is why some of the very best world class traders claim to have no method at all. They do have a method, it is just hard to see.

DIFFERENT MEASURES OF VOLATILITY AND CHOOSING ONE

The seminal masterwork on Volatility is by Professor Benoit Mandelbrot (RIP) and it is something that every serious trader should read.

There are pros and cons to all these measures. Also volatility for an intraday trader is very different from what a daily chart or stock trader would measure and daily volatility measures are of limited use. In my experience the ideal measures of volatility in a practical sense are in comparison to the previous 100-200 bars of data.

Method – Visual

Obviously this is a highly subjective method, but the principle is clear. Once markets start getting choppy they tend to remain choppy for a long time. Once markets break out from this choppy action they tend to be easier to trade, and stay this way for quite some time. If you look closely you can see that the part I have labeled “low volatility” is in fact a small range inside period on a higher timeframe. This is the market theory underpinning the most fundamental of Ivan’s setups. Al Brooks has an excellent method for short term trading, when there are many choppy overlapping bars he stands aside until the market starts getting easy to trade again. There is a lot of wisdom in this. Markets are not easy to trade all the time.

Method – Average True Range.

You should note that ATR can give a misleading view, because it is measuring the actual distance the market moved on average. As price goes up, obviously the same move is a lower move in percentage terms, and this is addressed in Ken Long’s Volstat Indicator, which converts ATR to a percentage of price, then adds a 100 period 1 standard deviation bollinger to it, to show in an objective sense whether volatility is comparatively high or low compared to the last 100 bars. Another alternative is using ATR crossovers, where you plot a short term and a longer term ATR and volatility is considered rising when a short term crosses above a long term ATR. You should note that since ATR is calculated by averaging closes in the past it is lagging, the predictive component of this indicator comes from understanding the phases of the market and that high volatility follows low volatility as naturally as night follows day.

If you were a stock picker this type of measure would be fine for classifying market type. We can see that as a general rule Bull Quiet markets are a stock trader’s dream run, and that by monitoring overall market volatility in an objective fashion we can identify periods of historically extreme low volatility where it is best to reduce risk and periods where volatility spikes where we want to be out of the market or trading a different system altogether.

Obviously our current low volatility bull market is very similar to the previous low volatility bull market of 2006. Pullbacks in a low volatility market tend to be shallow and buying strong stocks at a market pullback would be a strong edge. In fact designing a system for just this type of market alone would be EASY! RSI, Stochastics, MACD – all would work fine in this sort of market. The only thing is, this system would fall completely apart when the market classification changes from bull quiet to something else. If this is your goal (building a system for Bull Quiet Markets like the one we have now) you should have a trigger for stopping use of the system.

Method – Standard Deviation/ Bollinger Bandwidth

Since the calculations for Bollinger Bandwidth are based on the standard deviation of the last X closes, these two measures of volatility are virtually identical. There are inherent mathematical problems with this calculation because it is calculated on the SQUARE OF THE VARIANCE FROM THE MEAN. Because of the nature of squaring numbers once the average of standard deviation over, say 20 bars rises, it will not come down straight away. There are various proposed fixes to this including “standard error bands” (google them). As a general proposition standard deviation is an extremely sensitive measure of volatility as opposed to ATR which is badly lagging. It is very useful for VOLATILITY BREAKOUT SYSTEMS where an uptick in volatility from a historic low is a strong indicator of increased volatility in the future. As an aside this is a property of many complex systems, including the wind pressure in hurricanes, and the hydraulic pressure around a boat propeller.

Some points about this measure of volatility

  • Like all robust concepts, the actual parameters still work within a large range. Anything from 12-40 will give acceptable results and 20, the default on most charting packages is fine
  • The best use for this measure is not as a market classification but as a precondition to scan for stocks or markets that are statistically at unsustainable levels of low volatility and likely to break out. Extremely favorable risk/reward opportunities exist at these points
  • Pattern based setups and classical charting patterns have dramatically increased odds of working during the rising volatility phases

Method – VIX (or equivalents for other markets)

The VIX is calculated based on implied volatility of front month index futures, and in my opinion is more useful as a component of a trading system for a given market type than as a classification of it’s own. The reason is that VIX can spike impossibly high, and fall just as fast. Foolish people are always doing things like drawing trendlines and calculating indicators on it, without understanding the true nature of the VIX is not a market but a mathematical abstraction. You can see that in QUIET BULL markets where counter trend trades are statistically unlikely to work, that going long the market at VIX extremes is a significant edge. The expert on VIX is Bill Luby and his blog has many useful insights.

Method – SQN

This method was invented by Van Tharp for objectively measuring system performance, before it was discovered that this is a useful measure of overall market type. I also find it useful as a measure of trend smoothness at lower timeframes, and you can potentially think about using it as a component in your trading systems to preselect the smoothest and easiest to trade trends. The formula to calculate SQN is:

SQN = root(n) * expectancy / stdev(R) 

When calculating SQN for a market instead of for a trading system you substitute the average change in price for expectancy. This is the latest from Van’s website (and copyright vantharp.com) – I recommend readers taking a look at his weekly emails if you cannot find the indicator for your charting package.

************************* Mole comment ***********************

I would like to add a bit more detail here if I may (which I obviously do), in particular as SQN is a very important measure affecting all aspects of system trading. Let’s go back to ‘expectancy’ which is a common measure in itself and as Scott shows above is in fact one component of the SQN formula:

Expectancy is very simple – it’s your profit percentage per win multiplied by your win rate minus your loss percentage per loss multiplied by your loss rate:

Expectancy = (Win % * Average Win) – (Loss % * Average Loss)

Expectancy tells you what you can expect to make (win or lose) for every dollar risked. Casinos make money because the expectancy of every one of their games is in their favor. Play long enough and you are expected to lose and they are expected to win because the “odds” are in their favor.

Example:

You have a system that wins 30% of the time. When it wins it nets you 5R while losing trades lose 1R:

(0.3 * 5) – (0.7 * 1) = 1.5 – 0.7 = 0.8

So even though this system loses 70% of the time over time you can expect to make 0.8R on each trade. As you now understand R this also means that if you risked $1000 on each trade you can expect to make $800 on each trade on average (not over three trades but over hundreds).

Measuring expectancy alone however is insufficient. Opportunity is another concept that is often forgotten. Let’s assume you have the same system as shown above (i.e. 0.8R expectancy) but it only triggers 10 times per year. Let’s disregard the fact that this is too small a sample size for a moment. Instead let’s consider that taking such a small amount of trades per year will not bank you much coin. So clearly the frequency of trades and the average standard deviation need to be factored in order to define the amount of opportunity. Given the same expectancy a system that triggers 100 or 200 times a year is clearly preferable to one that only triggers 10 or 20 times.

Which brings us to SQN – system quality number – which was developed by Van Tharp and is used to evaluate the overall quality of a trading system. The formula once again:

SQN = root(n) * expectancy / stdev(R)

root(n) – the square root of the number of all trades
expectancy – as shown above and measured in R multiples
stdev(R) – the standard deviation of your profit/loss R multiples

Usually a SQN score of between 1.6 – 1.9 is considered poor but tradable. 2.0 – 2.5 is average. 2.5 – 2.9 is good and anything above 3.0 is deemed excellent.

Given the above we have a system that makes 0.8R per trade and let’s assume the standard deviation is 2.5R and that we make 100 trades in one year. The SQN of this system is:

SQN = root(100) * 0.8 / 2.5 – 10 * 0.8 / 2.5 = 3.20 (which is excellent)

However if you would make only 25 trades per year with this same system the SQN would drop down to 1.6. Barely tradable due to lack of opportunity. The higher the SQN the better your system and the easier it gets to meet your trading objective with position sizing.

********************* End of Mole comment *******************

Stockpickers should note. We are, by definition, closer to the end than the beginning of the bull quiet market. The previous bull quiet market lasted 5 years, and the current one has lasted 5 years. Nobody can predict when this will end, but there are really only two possibilities. Going out with a bang, on increased volatility like the dot-com mania, the bitcoin mania, any mania you want to name, or going out with a whimper like the last great bull market ended. In any case the clues as to changing market type will be present for those who are alert, and overwhelmingly the odds for the next market type we experience (but this could be years in the future – nobody has a crystal ball) will be either BULL VOLATILE or BEAR VOLATILE. Successful traders over the last 5 years will need to adjust their style or face ruin.

DO I ABSOLUTELY NEED TO CLASSIFY MARKET TYPE BEFORE BUILDING MY SYSTEM?

No, actually you don’t – there is a workaround. Particularly for short term systems and FX/Comoddities systems you can build into the system inherently that it will only be active in certain types of markets. If you are preselecting for a trend on multiple timeframes, then you know you will only be trading trending markets. If you are looking to only trade bollinger band extremes where volatility is not at historic lows or historic highs then by definition you will be trading markets you can classify as “sideways normal”.

How do I classify whether a market is trending?

There are many ways to do this, from simple to complicated. A short list below

  • A long term moving average like a 200 SMA or 200 EMA
  • A higher timeframe like weekly or monthly charts
  • Classical charting definitions like a bull market making a series of higher highs and higher lows
  • Ken Long’s Stretchstat concept, which involves  calculating how much price is above or below (in percentage terms) the 200 SMA and overlaying a 60 period lookback 1 standard deviation band upon this. His idea is that markets are trending when they are spending more than usual time above the 200 SMA and vice versa. This works quite well
  • Pick a series of moving averages, preferably exponential and define the market as “trending” when all of them are in the correct order from lowest to highest or vice versa

Choosing a Market Edge

I’m going to preface this by saying that most of you already know all the market edges you will ever need. There is absolutely no need to obsessively complicated edges and my experience is that simple market concepts, around for hundreds of years, are the most robust and the least likely to be curve fitting. This is a list of edges off the top of my head that could easily be the basis for complete trading systems.

  • In trending markets pullbacks to a moving average (of your choice) are an edge
  • In trending markets pullbacks to a trendline are an edge
  • In spike and channel markets (channel) Buying at the lower channel with a target at the upper channel is an edge
  • In sideways markets buying at support and selling at resistance is an edge
  • Market Sentiment measures are an edge, but only at extremes
  • In sideways markets that are not at extremes of low volatility buying at the lower bollinger and shorting at the upper bollinger is an edge
  • Confluence support holding (where you have support on different timeframes and different methods) is an edge
  • In sideways (trading range) markets where the higher timeframes are trending the trading range is more likely to resolve in the direction of the higher timeframe trend.
  • In sideways markets that ARE at extremes of low volatility breakouts (closes outside the bollinger) are statistically likely to continue
  • Multiple timeframes are an edge. ie Trends are strongest when they exist on daily/weekly/monthly and intraday timeframes
  • In low volatility environments counter trend trades are a negative edge. Stated another way, in a low volatility uptrend getting long once you see a valid short setup is an edge
  • Sector Rotation is an edge
  • Intermarket Comparisons (Dow Theory) is an edge and discrepancies between related markets (gold v silver for example) often happen at turning points
  • Classical charting patterns (Things like double tops, retests, triangles, flags) are an edge in certain environments. Ivan’s patterns are objective definitions of these sorts of things.
  • The best time to trade counter trend (short) is on a retest of the old high. However applied indiscriminately this is a negative edge, most top picking exercises in a bull trend will fail.
I have never seen a good system that is not built around simple, demonstrably provable and universally accepted principles of market price action that virtually all traders know!

Now what you should do is pick one simple concept and build a system around it. I’m going to show you an example of how to test a hypothesis and build up a system from a raw concept using Mole’s market lens, which many of you use. I’m not guaranteeing that this will work, in fact this is the first time in my life I’ve turned my mind to the concept and I want to illustrate the mental process involved.

Mole uses both 60 min and daily charts with a 25 period and 100 period bollinger and SMA. On the chart below the blue solid line is the 100 period bollinger and the blue dotted line is the 100 period SMA, while the red lines are the 25 period SMA

Let’s build a system around low volatility sideways markets. In these markets both support and resistance are more likely to hold, so a reasonable hypothesis to test is the following:

In sideways quiet markets on the daily timeframe, should we fade (trade opposite) of the 25 period bollinger on 60 min timeframe where market is also sideways and volatility is normal or high? Is this an edge?

The first thing to do is be a scientist and generate a hypothesis, do a quick test and see if it bears turning into a theory with more testing. You might have many failed hypothesis’s and should test them quickly. Spend an hour, no more, and decide if something bears further investigation.

Let’s bring up Mole’s other chart, using the same period, from 9th October to 21 November. Judging by eye (this is just a hypothesis test) I have marked the two periods of sideways markets which are not extremes of low volatility. I’ve marked the touches of the bollingers with green arrows.

Now visually, there is something there. The bollingers appear to be respected, and with the right initial stop choice, and the right campaign management we might have something there. The big question is how do we choose our initial parameters to test with.

Pay Attention – This is important

As a general rule we are looking to make at LEAST 2:1 and preferably 3:1 risk to reward on our good trades. So it’s quite obvious that an example of a good trade is buying at the lower band and selling at the upper band. The average width of the bands in those period in the boxes is approximately 75 pips (no need to be exact) therefore a good initial parameter to test with would be approximately 1/3 the width of the band, which happens to be almost exactly the same as the 14 period ATR which averages 25 pips. For consistency sake we will test with an initial stop of 1 ATR(14)

How do we know what targets to use?

Well this is fascinating, because on edges that are STRONG you don’t actually change the overall return that much by changing exit parameters. You do, however dramatically change the tradeability and quality of systems. You want to eyeball the sample and guesstimate the winning percentage of getting 1R, where R is the size of your stop. In other words I’m guessing what percentage of the time you are going to risk 25 pips to gain 25 pips. Here I’m going to just roughly guess the result as W L W W W W W W L ie 7 wins 2 losses. I’m going to add in an extra couple of losers just to random things out a little and get to a rough guestimate of 63% wins. You should know that NOTHING in the real world is better than 65% in the long run. If I trade this for 100 trades at this rate I’ll have 63R from winning trades and -37R from losing trades giving me 26R overall or a guestimated expectancy of .26R per trade. That is bang on what you should expect from an unoptimized system, and with some work we should be able to get this much much better.

Now NONE of this is real or particularly accurate but it’s a nice place to start.

Now let’s break out a pencil and paper and do a real test, one for exiting at 1R, and one for exiting at 2R. No need for computer backtesting, and in fact it is counter productive. If you operate on the principle of “like things behave alike” you can look for repeatable situations. Rather than curve fitting you approach from market principles first and work backwards. Based on what I know about markets I think it is highly likely that when the daily market is going sideways in low volatility and the 60 minute is going sideways in low volatility (without extremely low) then the bollinger band is support that should hold, most times.

We had 9 trades, 8 wins, and all 8 of those made at least 2R. That is fantastic, returning 15R in total over 9 trades is rockstar performance. If you can do even 1/4 as good in the long run you are going to be rich. Sadly but obviously however this is not a statistically significant sample. This is cause for further testing on exactly the same basis to see if the edge is real. After you ascertain if you have a real edge you can go on to optimize your system for system quality number and build a suitable campaign management and exit algo around it. I’ll cover that tomorrow, it gets quite heavy.

What do you do at this point? Try exactly the same thing, and keep building until you have 50-100 trades, done just like this, with pencil and paper. It doesn’t take long, it would take you 2 hours at most to do 100 trades across different markets and times.

So In Conclusion

  • Don’t try to build a Rube Goldberg machine.
  • Objectively complicated systems don’t necessarily test better than simple things.
  • Choose a market type and an edge which you think is real based on WHAT YOU KNOW ABOUT MARKETS, not based on data from a spreadsheet.
  • Choose an initial stop to test with that you can see a good trade being at least 2:1 and ideally 3:1 risk reward.
  • Test with pencil and paper, don’t engage programmers
  • Once you bang out enough W/L simple pen and paper testing to have confidence in your edge, you can go on to optimize campaign management and exits, which I cover in exhaustive detail tomorrow.

Scott Phillips

 


About The Author
Scott
  • ablebonus

    Scott, I really appreciate you taking the time to share your experiences here. Great insight and very helpful to see your thought process.

  • http://evilspeculator.com molecool

    Please reload this post, I added a section on SQN vs. expectancy.

  • Ronebadger

    Good stuff! Thanks Scott!

  • Sentiment Updates

    Great article although I strongly disagree that we’re near the end of a bull market and therefore trading styles have to change. I can throw up about 6 long term indicators (that have nothing to do with price, but are more valuation style indicators) that show the market is 10-30% undervalued right now looking out a few years.

    Did you know that there were 2 major bull runs in the last 100 years that lasted 20 years (1980-2000 and 1945-1965)? The bull cycles tend to last 20 years and the bear cycles last 10 years. Even though there may have been 10-20% corrections at various times, like the crash of 87, anyone who bought in the breakout years of the early 80’s (equivalent to today), were completely unaffected by that crash, since they were already up huge multiples.

  • http://evilspeculator.com molecool

    “I strongly disagree that we’re near the end of a bull market and therefore trading styles have to change. I can throw up about 6 long term indicators (that have nothing to do with price, but are more valuation style indicators) that show the market is 10-30% undervalued right now looking out a few years.”

    Please go back to the previous article in this series and read them again. Your opinion doesn’t matter, neither does mine. Even a 5% variance in your data can means months or years – so from a trading prospective this is absolutely negligible. If the trend changes we’ll get PLENTY of head warnings.

  • https://twitter.com/#!/fresbee2010 fresbee

    unbelievable that you are putting such gems at such a low cost. This is Gold.

    Thanks mole and scott.

  • http://dartht.blogspot.com/ Gold_Gerb

    excellent post, this shall take time to soak in.

    15R? too good to be true, it’s certainly a trap. 😉
    http://s1.postimg.org/f9dbirfl9/itsatrap.png

  • https://twitter.com/#!/fresbee2010 fresbee

    the issue after studying this is the same I have been having with the target placement being chosen:

    Targets are based independent of the actual market conditions. The target seems to be a *pure* function of what you are prepared to lose. The target logically needs to be based on a likely area of resistance or at least based on a reversal format on a lower timeframe from the one you entered or something that is market related.

    Right now because there is obsession to make more than I am ready to risk, the target placement becomes a bit arbitrary.

    Have you tested a scenario where targets are derived off actual reversal signals in the market?

  • ridingwaves

    Great read and powerful information..now putting it to use thru a thick head is another thing altogether

  • http://dartht.blogspot.com/ Gold_Gerb
  • http://evilspeculator.com molecool

    Reversal indicator signals are inherently lagging – there are some momo signals I follow but they are not reliable enough and are mostly long term.

  • mugabe

    The simplest system you’ve ever seen
    Here are the rules for this system.
    If the current price is higher than the price one year ago, go long.
    If the current price is lower than one year ago, go short.
    I ran this system on a broad set of diversified futures markets,
    covering all asset classes. But a system so simple cannot possibly work,
    right? It doesn’t even have any technical indicators. Well, judge for
    yourself…
    goo.gl/fb/cNHxm

  • mugabe

    ‘The target logically needs to be based on a likely area of resistance or
    at least based on a reversal format on a lower timeframe from the one
    you entered or something that is market related.’
    ‘likely’, ‘market-related’- this assumes that these are reliable pointers. are they? or is this a TA trap?

    It seems to me that percentages are less subjective, although you may not follow the -R, +2R rule.
    The main problem with the +2R rule as I see it is that it goes against market momentum and removes the possibliity of locking in possible mega-profits.

  • ridingwaves

    ROSG-love it..ABIO maybe next

    OXGN..traders like Roth presentation…low float, could move fast…tight stop with this dog

  • Dyellowflash

    If my opinion is needed here, I was short from the top but is currently long bcos if current low is clinically broken, it shld bcom Down TD but so far not shown to be so on ZL yet.

  • Ronebadger

    “clinically broken”?

  • aiki

    You will probably hear this a lot from me: Thank you Scott and Mole for these excellent posts. Will take a good while to absorb it. Your effort is much appreciated!

  • Dyellowflash

    yeah… i supposed that low aint clinically broken. guess my philo/ops in day-scalp trading is based on double negative logic. You cant be certain of “what is”, but u might be able to be certain of “what aint”.

  • Dyellowflash

    got to be nimble here. that early double whipsaw messed up by usual system and idt it will give me any signals until the next Dax session starts. i am still on down TD alert.

  • http://evilspeculator.com molecool

    Pretty nice Mole reversal signal today.

  • http://evilspeculator.com molecool

    Draw down average? Expectancy? SQN?

  • http://dartht.blogspot.com/ Gold_Gerb

    In regards to trends, I use Keltner channels to give me a picture of “both sides of the river bank”.
    it greatly helps me in avoiding bias, and execute plans accordingly.

    as long as the price is above the median, the median continues to rise.
    what I haven’t worked out is the tactics that work for ‘me’.

    http://s3.postimg.org/jqjqjvlib/Corp_Bonds.png

  • Dyellowflash

    So… I was right about shorting copper from yesterday’s posting, but unfortunately only caught the small move of 250 pips, did not reload after TP and it ran a full 1000 pips. Cant be helped. I dont have a system for copper and any trades i made on it is considered present from the one up there.

  • Rightside_ot_trade

    Please provide a chart with yearly candles

  • teslaman

    Speculative long at DJI 16357 with tight stop. There is some support at the 30min 200BOL and a bit on the Hourly. Lets see how it plays out.
    http://prntscr.com/2zx4g8

  • teslaman

    At this point any rally doesn’t seem to be much supported by USD/JPY. Looking to take profits if/when the 20MA is hit on the 10min frame. However, If it breaks it with conviction I will be looking at the 50MA.
    http://prntscr.com/2zxdiy

  • RUFCrazy2

    SQN question Mole – I have 3 ES models. When combined they performed with the following stats form Jan 2012 to date – 100% out of sample walkforwards. Seems to me models can be combined to generate a higher SQN, provided you are sufficently capitalized – right ? Expecatancy was bit low but this a generally a low vol Fed induced period. They performed a lot betetr in 2008, 2010 & 2011 as far as expectancy.

  • RUFCrazy2

    Looks like it didn’t show the graphic, hmmm, trying again with Jing.

  • RUFCrazy2

    Monthly with Drawdown

  • http://evilspeculator.com molecool

    Not sure what you mean but the downside of trading several systems in tandem is that you will run into correlation problems. This is something we needed to address with Heisenberg and thus we are using filters to keep us out of too many related trades. The same scenarios would apply if you were to trade three systems on the same symbols – depending on the time periods you may have too much overlap. Plus your also will start having issues with margin unless you split everything into separate accounts OR reduce position sizes.

  • http://evilspeculator.com molecool

    “So… I was right about shorting copper from yesterday’s posting”

    Please ponder about what may be wrong with that sentence. Hint – revisit the last two posts.

  • vladv

    “This simple strategy showed annualized return of 22% against a max drawdown of 26% and a Sharpe ratio of 1.1. ” thats a quote from the site that provided the rules. FWIW, the Sharpe ratio and van Tharps SQN are very similar in the sense that the Sharpe ratio can be considered as “”daily” trades that provide you with an expected daily return which is compared to the volatility of those daily returns

  • RUFCrazy2

    Using 2 accounts, one is daytrader so easy enough to do. Correct the biggest concern is probably collinearity, can see on the monthly details..

  • RUFCrazy2

    The observation was that if your models don’t trade enough, you may be able to combine several model results and calculate a combined SQN. Works best if as you mentioned results are not too highly correlated.

  • Scott Phillips

    This is a complicated question and I’ll be addressing it in today’s post on entry and exit techniques and optimizing for SQN (for systems as opposed for market type measuring) is extremely interesting. Could you please recalculate your SQN on the basis of using a maximum of 100 trades (square root of 100 instead of square root 512) and caluclating the expectancy of the trades in R not in $$.

  • SirDagonet

    The author (of the strategy) also says: “This strategy with a universe of 100 [futures] markets is not realistic for smaller portfolios. And by smaller, I mean less than a few millions.”

    However, he does add: “But… this model actual works quite well on smaller number of contracts as well. I’ll do another post this week on this model, using lower number of markets and making it more accessible for smaller sized accounts.”

  • Scott Phillips

    What are the system goals here? Are you cool spending 9 months in drawdown (you may be). What is the fundamental principle of markets you are basing it on? (if you can take one thing from my post today, take that, that there is really basic and fundamental stuff about markets that better systems are built on)

    Also you MUST UNDERSTAND that it is impossible for your system to work all the time. Your dream of a set n forget system is not gonna happen. Work out a market classification schema that suits the timeframe your system trades (see post) and work out which market types your system works in and which it does not. Throw away the shit times, then you might have something.

    You are going down the classic route of failed traders. Spending a lot of time to convince yourself it’s good. Here’s the thing. It WILL BE GOOD sometimes. It WILL BE SHIT in others. Your job is to work out, reliably which are the good and which are the shit times.

  • SirDagonet

    “You should know that NOTHING in the real world is better than 65% in the long run.”

    Perhaps nothing in the real world to which an “average investor/trader” has access?

    http://blogs.marketwatch.com/thetell/2014/03/11/virtus-one-trading-loss-in-four-years-incredible-experts-say/

    Drop the flame-thrower, Scott… I realize (I think) the intended target audience of this blog is not HFT… And, LTCM had a phenomenal
    track record until the time “when genius failed”…

    Thus far, an absolutely fantastic series of articles. Lucid, organized, obviously the result of much expenditure of your time and an exceedingly generous sharing of your knowledge and experience.

  • http://evilspeculator.com molecool

    It’s important that the campaigns are not overlapping, indeed.

  • http://evilspeculator.com molecool

    Unfortunately running HFT algos is beyond my pay grade and although it’s very impressive it does not exist in our retail world. Thus your slightly edited quote is appropriate.

  • Scott Phillips

    Before I posted again I read the comment section for the last few months that I missed. This is the guy who pops in every day and tells everyone how he top and bottom ticks the market. Mate here’s the thing, you aren’t fooling anybody 😉 Rats you should know there are 2 ways only to top/bottom tick the market – one is to badly overtrade all the time and hemorrhage your account away. The second is to trade without stops or with incredibly wide stops, risking a huge loss for a tiny win. Then you can jump on and claim victory. The *best* intraday traders in the world are no better than 60% win rate, and many world class traders are less than 50% win rate.

  • Scott Phillips

    Perfectly good method of classifying trends. Your trailing stop there is going to be badly subobtimal, and today I’ll show you how to clean that shit up and capture more of your trend.

  • http://evilspeculator.com molecool

    Hey, it worked for the turtles.

  • Scott Phillips

    Most futures markets are based on USD, and most futures markets measure real items like lumber and pork bellies which are inflationary. Therefore this method could have a basis.

  • Scott Phillips

    Did you READ my post? I’m not choosing a target for the system. I’m simplifying the system design process to allow you to quickly test with pen and paper whether you have an edge or you are curve fitting.

    Today we will look at exit algos in detail. Beginners love systems with “go long when RSI/MACD/custom indictor is xxx then go short again when it is xxxx” I have NEVER EVER seen a system like that not blow up its owner

  • Scott Phillips

    It’s not a rule its a method for quickly testing your edge to see if it is worth doing further work. A good winning trade should be making at LEAST twice what you are risking, and ideally 3x what you are risking. Not all of them, but the good ones. If you can’t just eyeball your chart and honestly say you don’t have a CHANCE of getting a 3R winner, then you are not trading a good traders equation. I’m not ruling out the possibility of 10R or 20R winners but I am nowhere NEAR getting to that stage at this point in system design.

    Heres a general rule – If you can’t outline in 20 words what your edge is you DO NOT HAVE AN EDGE. Your edge might be “trending markets tend to continue” or something thats based on a property of markets. If its a complicated formula you spent years developing and won’t share because you don’t want it getting out, then it is almost certainly not an edge.

  • tradem4alpha

    Scott, with all due respect, you should check his comments regarding the indices (DAX and US based) and if you read them in real time…they look freakish. He has a system of multiple fills (4 in total)…and in a lot of moments he picks the bottom (or top) to the tick…trust me…I read the comments in real time…he claims a win rate of around 84%…I do not know if it is that high (personally I do not think that it is that high), but it is clearly over 60-65%.

  • Scott Phillips

    Again – DO YOU GUYS FUCKING READ? I’m not some market predictor saying “the end is nigh”. Predictions of all sorts, both bull and bear are bullshit. You sound like you are locked into your own prediction model, and prediction models are all, 100% without exception bullshit.

    How would you know when the current market will end? You WOULDN’T. I wouldn’t! Nobody does, not even Janet Yellen!!!

    The future is unknown, and comprised of unknowable variables.

    What I did say is that the current market type is QUIET BULL. Yes we have had 20 year bull markets before. From 82-86 we had a quiet bull, then in 87 the market went to VOLATILE BULL, up super strongly and crashed. Volatility fell into another quiet bull market (which as I said last a long time) then went up strongly in a mania and then crashed.

    It is a reasonable possibility that we go to a mania from here and shoot up HARD. The signs will be clear. It is a reasonable probability that we continue as we are now for another few years. But make no mistake we are 5 years in, and on a journey from the start to the end we are no longer at the start.

  • Scott Phillips

    It’s not real. He’s not posting his stops. This guy is NOT a profitable trader nor a pro – I bet me left testicle on it. I know traders, I know winning traders, how they think and how they act. I (and anyone else who is a pro trader) can tell by reading a few days of comments that this guy is not a good trader in any objective sense.

  • Scott Phillips

    You are correct – HFT is better than 65% (way better) and HFT firms are the most profitable businesses in the world pound for pound. I looked heavily at starting a HFT based business since I have the capital for the equipment and understand the math models they use. Bottom line it was going to be a multi million dollar exercise just to set up, let alone attract the right talent. I wouldn’t have gotten any change from $5 mio, which is above my pay grade.

    I repeat – NO MARKET EDGES ARE BETTER THAN 65% in the real world. HFT is NOT a market edge it is a mechanical edge based on technology. Mechanical edges ALL disappear over time, those firms are in a constant arms race to shave a few nano seconds.

  • http://dartht.blogspot.com/ Gold_Gerb

    sweeet!

    (yes, badly suboptimal)

  • Scott Phillips

    The flamethrower exists because unfortunately after years of Mole and I telling the participants here to trade like winners and not like losers, sadly loser thinking abounds.

    I’m offering a sincere and heartfelt warning that I DON’T THINK MANY OF YOU IF ANY WILL SURVIVE IN THE MARKETS DOING WHAT YOU ARE DOING. Most of you are blowing up.

    I’m also offering you a systematic solution before I disappear. Personally I wish somebody had told me this stuff years ago, it is information hard won, and to my knowledge not available anywhere else in complete form.

  • Scott Phillips

    Thats OK – my stuff on exits today is going to blow you away :)

  • ridingwaves

    BAM….OXGN a/H +2.98…..that’s some easy R’s…..

  • tradem4alpha

    Heck, when he says “this is the bottom (top)” and the DAX prints x number, I assume that is his stop…anyway thanks for all the effort you are putting in providing all this information for us and…can you give your email and skype again? I would love to talk to you more, considering that you will be here a short time.

  • newbfxtrader

    Yep. I use a modifed form of the turtles method.

  • RUFCrazy2

    The math on expectancy is the same whether using R or $’s. Here are results of 2 of the 3 models I have combined from 2007 – 2013 100% out sample – I refit paramters annually. I have filters that stop me from shorting in bull trend markets and vice versa, but I am sure moodels would benfit from some better code in whipsaw markets. But these models kick serious ass in high vol markets. Yes I am seeking all weather results. Results actually go back to 2004 similar profile although 2005/6 were about half as good due to lack of volatility. Note the recovery period in months. Not too bad.

  • Scott Phillips

    Definitely has potential, and performance could easily be tripled or more in my opinion.
    Also, for measuring SQN you should STOP at 100 trades for the “n” which you take the square root of. Otherwise you can make average systems look good by taking many trades.
    If you calculate SQN based on a maximum of 100 (you still calculate expectancy and stdev based on the whole lot, just multiply by 10, the sqrt of 100 instead of the sqrt of your number of trades) you will see that on most years your systems objectively test at average at best.

    FYI a SQN(100) of 2.0 is “average but tradeable” which except for 2008 (which did much better) is pretty ordinary. Logic would tell me that 2008 was a high volatility bear market and this system may hit the ball out of the park next time we have that situation. It also did well in 2011 when we had some significant downside for 5 months.

    This is a system with a real edge, with objectively mediocre performance, roughly in the same range as CrazyIvan (my one-size-fits-all system)

    It is simply NOT POSSIBLE for “all weather” results to rise above the mediocre, and your results here reflect that. Everyone gets so defensive about this stuff. It is plainly obvious that your system performs better in high volatility than low volatility.

  • Scott Phillips

    My skype is “wealthawareness” and I always answer questions that make sense.

  • Scott Phillips

    Perfectly good place to start. You can improve the crap out of that method, because so many people trade it now it is a very small edge as standard.

  • Kudos

    Scott, this series is absolutely phenomenal to read. I will be printing and archiving it. I love just learning about things that I have not been able to even think about properly. I’ve just been developing one system and I find it difficult to understand when to alter strategies. My strategies do include specific characteristics that target extremes in volatility and trend trading and I’m trying to refine a system. If you are on the edge of figuring out what it would take to do something consistently and build a system, this is an amazing framework. Thank you

  • RUFCrazy2

    Thanks for the feedback and that’s pretty much what I think believe it or not. Mediocre on average and destroys in the rare higher vol markets. I am going to see if I can separate out my models following your advice – bear high vol, trending bull, whipsaw. Afraid I will not have the best ideas for identifying entry and exit into chop markets but I can try.The potential is why I emailed you previously as I know I have some awesome RBT rules that could certainly be improved.

  • RUFCrazy2

    OK now I think get what you’re saying about SQN, basically expectancy is more impoortant than # opportunities – and I agree. Somewhat embarrasingly, I have probably 3,000 + hrs (maybe 4,000 hrs, pains me think) in devlopment on these… lol, slow learner

  • Scott Phillips

    No its the ratio of expectancy to standard deviation which is important. I’ll cover it all, don’t worry

  • phantomflash

    Scott, this is absolutely fantastic stuff, and I know everyone greatly appreciates it. It will take a while to all sink in properly. I have passed the links on to some friends, with high recommendations. One thing I noticed — near the top of today’s post, you have links to the two prior ones — except they link to the respective comment sections, not the top of the posts.

  • Scott Phillips

    ok I’ll fix that later – thanks

  • Rightside_ot_trade

    /SI shooting star in a downtrend on the daily after piercing the weekly 25ma and touching the monthly 100 today

  • aiki

    I have some simple, but important, questions concerning volatility, ISL and execution times.

    The framework you have us working thru now has me thinking about building several systems that function best in bull quiet, bull volatile, bear volatile or sideways quiet Vol regimes. Mostly I’m just going to start over again from scratch with my thinking with the benefit of these posts, so here come the questions…

    If (one) of my jobs is to find areas of low (or extreme low) volatility that is about to expand into a higher vol regime (it always does…) an ISL based on ATR is going to be far tighter than the expanding candles that come as vol increases. Using a recent low for ISL makes sense, some multiple of ATR, or maybe some MA, a net line – what should I be looking at? ISL is going to determine my R, so it is important to size it correctly both as to initial entry risk control, but more importantly for campaign management.

    Also, I’m hoping to to rebuild my systems to run daily or longer, meaning I don’t trade much during market hours: since premkt up until 10:10 or so is usually noisy, what would you recommend in terms of submitting limits for entries, execution time wise? I’ve used the short close for futures entries & adjustments, etc. Anyone have a thought about equities?

    Thanks a bunch –

  • http://dartht.blogspot.com/ Gold_Gerb

    whoa. (hourly gold squeeze)

  • aiki

    Gerb, you mentioned keltners. have you ever looked into bollingers inside keltners? After reading today’s post, I’ve been going over every way I’ve ever seen (or used myself) to value Volatility. Stretchstat looks like the answer, but I don’t have the code for TOS.

  • http://dartht.blogspot.com/ Gold_Gerb

    nope. sounds interesting.

    Scott put out a link once on “Bollinger on Bollinger Bands”.
    I need to refresh on that one.

  • http://dartht.blogspot.com/ Gold_Gerb
  • aiki

    That’s it. I believe the other idea may be using two sets of bollingers: one at 1 stdev and another at 2 stdev. I read about it in one of Kathy Lien’s articles somewhere. Google double bollinger. What else are you using to measure volatility?

  • https://twitter.com/#!/fresbee2010 fresbee

    cool thanks boss.

  • http://dartht.blogspot.com/ Gold_Gerb

    is that what it’s called. I use it all the time on /ES.

    http://s9.postimg.org/z91pac7bz/sideways.png

    I don’t care to measure volatility, I can spot it on a chart.

  • aiki

    Excellent! So for you it is useful…I will look into it more. Thx.
    As to Vol, for now, I need to see the numbers – my subjective view has been far too subjective in the past. I am going to rebuild my systems to function as objectively as possible so that even a bonehead like me can execute them. Or die trying (not impossible…)

  • http://dartht.blogspot.com/ Gold_Gerb

    yes. it has been useful. don’t let the nonstandard deviations scare you. just been tweaked from past history/battles.
    YMMV.

  • http://evilspeculator.com molecool

    This is how you do it, mate. Forget everything else and consider this your Phoenix out of the ashes moment.

  • http://dartht.blogspot.com/ Gold_Gerb

    just remember, even a perfect system will have rough spots. it takes time to build confidence.
    and that is something I hope Scott covers. “when do you take your system offline suspecting something’s broken, or push on through”.

  • aiki

    all good questions – I’m just reevaluating everything about this game, from the bottom up, as of now.

  • Sean

    I’ve been thinking about this as well… my thoughts are to look at losing streaks and see if it is near what I initially expected for the system… if it is way out of whack, then I would stop trading that system until I figured out why the real world trades are differing from expectations… using the formulas below and your initial parameters/expectations you can figure out if there is a 60% chance of 10 losers in a row or 1% chance and move forward accordingly.

    http://pages.stern.nyu.edu/~churvich/Undergrad/Handouts4/13-Streak.pdf

  • Scott Phillips

    Bollinger inside keltners are a real and excellent edge. I built a system around them in 2010. John Carters TTQ squeeze indicator is based on this, suggest you look at his videos tradethemarkets dot com

  • Scott Phillips

    Kathy Lien is very dangerous to listen to, the pimples on my ass know more about trading than her

  • Scott Phillips

    In my production systems I try and get in on the low side of the volatility cycle, allowing me to trade massive positions for the same risk. I regularly max out the available leverage FX trading.

    As a general rule most people put the stops too close at the start of the trade and too wide at the end of the trade

  • Scott Phillips

    Nope. Trust me, that guy has nothing at all you want to copy

  • http://dartht.blogspot.com/ Gold_Gerb

    I did not, need that visual
    *gag*

  • Scott Phillips

    If trading was HER ass she couldn’t find it with both hands. Just scroll back through her “predictions” for the last month. Seriously Amotka is like Paul Tudor Jones next to her

  • Scott Phillips

    Don’t worry that stuff will be covered in the detail appropriate for this very very important topic.

  • Scott Phillips

    Sean, for most of my trading life I’ve used low SQN systems trying for “one size fits all” analysis. At least once a year I got a string of losers which would make me cry, 8,9, or 10 in a row. Since I switched to this method of system building it is unusual to get those big losing streaks.

    Logically if you can get 10 losers in a row you cannot trade with 2% R values, else you kill your account. So the solution is to tweak the exit algo to reduce losing streaks and drawdowns, at the expense of outlier wins. In essence you gotta bank some singles instead of trying for the home run.

    I’m going to show you over the next few days some of my secret sauce to increase your winning percentage by around 7 points, (from 55 to 62 for example) by sacrificing some of your winnings and taking partial profits early. There is a mathematical formula you can use to work out, what is precisely optimal and I will show you how I do it.

  • Scott Phillips

    Todays post will cover this

  • http://evilspeculator.com molecool

    See my email today!

  • aiki

    Will do.

    Ps – I don’t care about Lien’s (or anyone’s) predictions: if if have learned nothing else here it’s that predictions (and especially my own about tops and bottoms) are worse than useless, they are bad trading mojo.

  • Scott Phillips

    NEW POST – sorry its not what you were hoping for, its taking longer than I anticipated

  • vladv

    A smaller portfolio will most likely perform better. If you construct a large 100+ futures market portfolio and trade all those markets indiscriminately you will be taking on a lot of correlated positions. Being Long 10yr notes in long term trend following is the same as being long the 5 yr note, being long the bund etc. The same can be said for most of the currency futures, grains etc. If you add a portfolio manager to your trading system that limits “group” positions to only 1 or 2 markets within each group, you will get most of the benefits of portfolio diversification, whilst keeping correlation risk under control (caveat emptor – correlations are not stable). That way a smaller account would be more able to meet the margin requirements of maintaining the various simultaneous positions.

    Something that all trend followers need to bear in mind is that the actual signal for entry is a tiny part of the overall trading system. Risk control in all its different facets from position sizing to position correlation risk, drawdown controls etc are the key to a good trend following program.

  • vladv

    the information that you are posting is great!