BlueHorseshoe

Using ATR and also Standard Deviation for stop-losses and profit targets seems to be quite common. It's usually pretty easy to set up on your chart by adapting an exisiting indicator (such as the Keltner Channel for ATR or the Bollinger Bands for Standard Deviation). Commonly, you'd want to leave the number of periods over which the volatility measure is calculated at an appropriate level (usually something shorter than the default though - you might look at something like the last 8 periods), but drop the average around which the bands are plotted down to 1 (ie. just the close). This means that the channel will now plot, for example, 1.5 eight-period Average True Ranges above the closing price - if you enter on the close then your profit target is the upper band. Obviously you can adjust the number of ATRs you wish to target. A slightly more sophisticated method is to use plot the upper band based ATRs/SDevs of the high price, around a one period average of the highs, and the lower band based based ATRs/SDevs of the low price, around a one period average of the lows. The idea here is to make a distinction between bullish volatility and bearish volatility. If you happen to use TradeStation as your trading platform, then I can probably post some EL code for this. Hope that's helpful, and doesn't just read as complete gibberish!

I personally no longer use or a fixed profit target or stop-loss when trading, and I agree with you that this can be the optimal solution for many systems. While I can assure you that I have thought about (and researched) this point thoroughly, I may of course be completely wrong! What I am looking for is someone to provide convincing proof that I am wrong - I then won't hesitate in re-evaluating my stance on scaling out. I disagree with the third point you make above - you need the ability to SUBTRACT contracts when you experience a drawdown. Any trader has the option of adding contracts when increased capital justifies doing so. A higher target will typically pay off more, but get hit less often, and the lesser target will pay less and get hit more frequently. Are the two equivalent in terms of their perfomance? I would argue that this seldom proves to be the case: one will always perform better than the other, and this is the target that would ideally be used.

I have no idea whether Tim Racette or any other educator in the industry actually trades - my post wasn't intended as a slight against Racette or his company, but as a criticism of the specific concept that he was advocating in that particular post. I am sure there are plenty of people who do trade, including profitable traders, who scale out of their positions. I certainly experimented with it at one stage with a live account, and didn't obviously lose money because of it. But then I'm talking about maybe fifteen trades - hardly a representative data set. Leter on, once I started looking at how systems performed across thousands of trades, it became abundantly clear that scaling out of profitable positions did not improve the results. That's why I am hoping that there will be some advocate of scaling out who is able to offer something more than just anecdotal evidence of the benefits of doing so . . .

Hi Predictor, I agree that you are effectively trading two-three systems. However, all but one of these systems are bound to be less than optimal in their performance, and so their ability to smooth the equity curve is doubtful. They'll certainly smooth the upside of the equity curve, as scaling out of profitable positions will have most impact on the upside of the equity curve, but they'll do nothing to smooth the downside of the equity curve. Why? Think back to my original example - when you get it wrong you're still going to lose exactly the same amount as you would have when you didn't scale out of profitable positions. Your risk remains unchanged. Larger scale (as in seriously large, institutional) traders do supposedly scale into positions. But they do so begrudgingly. They'd much sooner go 'all in' and 'all out' at the optimal entry and exit; they only scale execution as a compromise measure to reduce the impact of large orders on the market.

Hi DionysusToast, I have certainly seen pretty convincing evidence for scaling into positions, even the controversial practice of 'averaging down' . . . But I have never seen any objective system that benefits in terms of overall profitability from the scaling out of profitable positions. Can you put forward a mathematical argument for this? Yes, you may know people who make money scaling out - the trader in my original example made money - just less than they would if they hadn't scaled out. Are the people you know who make money scaling out able to provide any hard evidence that their performance would have been poorer if they hadn't scaled out? My challenge still stands - I defy anyone on this forum to provide hard evidence of any strategy that benefits from the scaling out of profitable positions.

Yes, this probably is just a semantical argument really. I think the importance of how a trader approaches the concept of 'prediction' is probably more psychological than anything else, and it's very clear from your post(s) that you're not some novice who believes that there's some secret key to unlock and predict the markets! I suppose what I am arguing is that we should 'predict' the net outcome of large number of trades, not 'predict' the outcome of any one individual trade. As for justifying MP and how it has helped me in my trading - well the answer is not at all! I'm not a Market Profile trader and don't know much about it - my original involvement in this thread was just in trying to support the validity of 'mean reversion' as a method of market analysis.

This is exceptionally BAD advice. Scaling out of profitable positions is the precise opposite of what you should be doing. It's reducing the amount of profit that you take, yet doing nothing to diminish your risk. Scaled out profit taking completely skews the risk:reward ratio of any profitable strategy. Let's look at a simplified example: STRATEGY A: Trades two contracts and places a twenty point stop and a fourty point profit target for each. It has a 50% win rate. Over ten trades its net performance will be (5*40*2) - (5*20*2) = 200. STRATEGY B: Trades two contracts and places a twenty point stop, with a twenty point target for one contract and a fourty point target for the other. It has a 50% win rate. Of the winning trades, 50% are exited at the first twenty point profit target, and 50% at the second fourty point profit target. Over ten trades its net performance will be ((2.5*20*2)+(2.5*40*2)) - (5*20*2) = 100. Someone is sure to point out that this is a simplified example using made up figures. However, adjust the figures as you will, using real market data, and you'll find that the example above holds true. The reason is simple: the more optimal profit target (and risk:reward ratio) is either twenty points (1:1), in which case it makes sense to take profits on both contracts at a twenty point target, or it is fourty points (1:2), in which it makes sense to hold on to both contracts and exit at the fourty point target. Scaled out positions reduce reward, but leave risk the same. Profit taking feels good, and that's why the likes of Racette, Carter, etc are keen to promote 'scaling out'. I defy Tim Racette, or anybody else on this forum, to provide hard evidence of any objective trading strategy that benefits from the scaling out of profitable positions (no need to disclose the underlying strategy, of course!). And apologies for the fact that this post seems rather confrontational in tone - it's just that some things really annoy me!

Yes, because it moves, or changes. That would be my understanding of 'dynamic' (ie as an antonym to 'static') - did you have a different meaning of 'dynamic' in mind? While I agree that there are pitfalls and limitations to basing market decisions on the past, I think that's about the best that we can do. I know that I can't predict the future as you seem to suggest, otherwise I would forget about trading and just buy a lottery ticket this weekend. So I'm very much of the opinion that predicting the nature of future price movement is a fool's errand, and that the best we can achieve is to trade according to historical probabilities. In the markets I trade, these statistical probabilities favour a reversion to the mean. I should add that I am using the term 'mean' in a very loose sense now. A better description of this belief would be to say something like 'a market is more likely to head back where it just came from than to explore new price territory'.

I think that maybe I introduced the phrase "fair value" into this thread earlier, so sorry if that's muddied the waters - is "fair value" an MP term? Nevertheless, I would assert that any price level at which signficant volumes of trading occur represent areas of "fair value". If prices weren't considered "fair" at these levels, why would so many buyers and sellers be willing to execute orders at them? So whilst it perhaps doesn't say anything objective about fairness of price, I think that it does say something objective about other market participant's subjective assessment of fairness of price. Does that make sense?

Surely although a gaussian distribution is not dynamic, the mean around which the distribution occurs IS dynamic, as the average value series changes through time? I'm not saying that this represents a total justification for market profile though.

Hi LastNinja2 I know nothing about tape-reading at all I'm afraid. However, I would recommend that you consider trading the underlying instrument rather than spreadbetting. I know that there are serious tax advantages for us living here in the UK with spreadbetting, but I think it's completely unsuitable for scalping, or any kind of high frequency day-trading. The last time that I met with someone from the leading spreadbetting firm (not sure whether I'm allowed to name it on this forum!), he explicitly stated that all their clients who are consistently profitable are those who hold positions for longer periods. As I'm sure you're aware, there can also be other issues with Spreadbetting in terms of execution, slippage, requotes etc. Basically, it's great for swing and position trading, but I think it can pretty much anihalate any short term edge that you may find. Moving from spreadbetting to futures was one of the single most profitable developments I made in my own trading - I went from treading water to profitability without changing any other aspect of what I was doing. I hope that's helpful to you.

Thanks for the resonse. I disagree with you about the languages aspect - I'm a perfectly proficient programmer in several languages, and pretty confident that I could teach myself C++ if I wanted. But I think the main barriers to HFT are broader technical issues - for example, I wouldn't have a clue about how to go about obtaining the low latency order routing that the HFTs enjoy. And I think that most people at the large HFT firms would be equally ignorant - it's my understanding that they tend to be made up of specialist teams, each of which only really understand their own job. Anyway, as I said before, its impressive that you've managed to get such a system off the ground single-handedly, so good luck for the future and for your capital management enterprise!

Thanks for the link - a useful and interesting thread, by the looks of it!

If what you're saying is true, then it would appear that I stand corrected! However, I'm assuming that you'd agree that you're in a very small minority of those who posess anything like the skill base to do so. To save me trecking away to read the SEC's definition, would you provide a summary? And, if you're willing to divulge the information, with what frequency your own system trades, and what type of instruments? I'm guessing the paperwork involved in setting up a fund is as much hassle as setting up an HFT system, isn't it?

If you can do this then you're a step ahead of me! My tape-reading skills are pretty non existent, so I pretty much ignore T&S. Obviously I have many times been filled 3-4 ticks from the high/low, and even at it, but this is far from the norm - to be able to do so with any regularity would certainly improve my performance. One of the issues I've found with T&S is that most information about how to interpret it is based around stocks. Can you recommend any good reasources on tape reading for futures? I've asked this question in other forums and basically been told - "you need to put in the screen time", which I don't consider terribly helpful! Thanks.

I definitely agree with this. In practice, pretty much any intraday breakout strategy that I have seen that performs remotely well in the ES is one that focusses on the latter half of the cash session. The flipside of this is the fact that within the first hour or so of trading, mean reversion strategies can be profitable with absolutely no directional bias - ie fading any kind of significant movement off the open - such is the structureless price behaviour of the open.

You're much better off starting out with swing trading in my opinion. The settings that I've suggested above are an ideal non-optimised solution for most instruments where this strategy will work. If anything, I would consider optimising the length of the SMA used for trend filtering before I would consider optimising the RSI settings. What are you trading - individual stocks, futures, forex? This type of strategy will work best in markets that show less inclination to trend and more tendency to trade back in the direction from which they've just come - the S&P500 (and instruments that track it such as the @ES futures contract or the SPY ('Spider') Exchange Traded Fund) are probably the best examples of this. You might also like to look at the British Pound, Gold, or other indices such as the FTSE, DAX, or Nikkei.

An interesting study. However, I'd be much more intrested in other metrics (profit factor, maximum drawdown, symmetry of long and short performance) before focussing on Net Profit as you suggest.

I'm making this statement in the same tentative vein as your original post . . . I would typically expect a market to move back towards a prior value area once it has left it. I would tend to associate the increased volume of trading as signaling agreement between both buyers and sellers that this price level represents fair value. When price moves away from this level, it will more often than not gravitate back towards it - the market exists to facilitate trade and match buyers and sellers afterall, and the fair value level is the price at which thej most trade was recently facilitated. There are obviously two ways that this can occur: 1) Price moves away from the value area and then there is a substantial reversal, taking it back through it. 2) Price moves away from the value area to begin a new trend, and then pulls back to the value area before re-comencing the trending action. The third possibility, of course, is that price breaks out of the value area and never looks back! This would usually only happen when significant new information enters the market. If clean breakouts such as this occurred with any regularity then I'm sure we'd all be trading them. From what you say in your original post, I think this probably confirms your current way of thinking about value though, and will be of little help in developing it. I suppose the useful thing to know would be how widely a particular price level is considered fair value - an informed guess could then be made about whether price movement has exhausted interest at that level and is unlikely to gravitate back towards it . . .

Hi Tams, I wasn't really remarking about any particular strategy, but the statistical tendency for the S&P500 to revert to its mean. An obvious rationale for this would be the fact that its such a large index - movement in any one single component stock has a fairly negligble effect upon the index, which is seldom more than an aggregate of masses of conflicting market information. On average, the index makes very little new headway in any timeframe (compared to other instruments). I feel that I should probably be supporting this with some hard statistics, and I don't have anything to hand! One place that backs up similar assertions with figures is the now defunct Brett Steenbarger 'Traderfeed' blog (I'm not sure I can give out a URL on this forum, but a google search for 'Steenbarger Mean Reversion' pulls it up as the top entry). One simple way to exploit this tendency for mean reversion in the ES in any timeframe, I guess, would be to take the other side of any breakout. This is not a new idea though - in fact it's a similar concept to the 'Turtle Soup' strategy given in the 'Street Smarts' book. An issue for many traders with this type of approach though, is that it almost requires a greater than 1:1 ratio of risk to reward - we tend to be told that "large R multiples" (that old Van Tharp term) are the way to go, and we should "cut losses short". In terms of mean reversion trading this would be poor advice. Before I'm accused of hi-jacking a thread that is meant to be about Market Profile, I'll leave it there I think!

Here are three suggestions that I hope will be useful: 1) You might find it useful to take a look at the formula for Larry William's 'Greatest Swing Value' indicator. This is based upon a very similar concept to the Kaufmann one you discuss, though interestingly Williams recommends a very short lookback setting of just three or four periods. 2) Another thing to investigate would be 'Heikin-Ashi' candlesticks. One of the main advantages of these are that they don't contain an variable look-back parameter, so the possibility of curve fitting or over optimisation is removed - handy! A variant of the Heikin-Ashi formula was popularised by the Trade the Markets bunch - it's basically intended to produce a 'less choppy' signal series. Like all such things, it's swings and roundabouts: sometimes it filters false signals, and sometimes it gives delayed signals for true trend changes. I haven't made any direct performance comparisson between traditional Heikin-Ashi and this modified version, so I can't make any authoritative statement about which is the better tool. 3) As I'm sure you've heard many times elsewhere, in trading 'simple' is normally 'best'. The best definition of trend you're likely to achieve is with a (correctly) optimised Simple Moving Average. Hope that's useful - has anyone else got any other suggestions on this?

I am certainly no expert on Market Profile, but I can tell you that the ES (or other S&P500 tracking instruments such as SPY) are just about the best place to employ mean reversion strategies - if you can't make them work here then you're not likely to make them work elsewhere! Apart from the ES, other (large) stock indices tend to exhibit a strong tendency towards mean reversion, so the Nikkei, FTSE, and Dax would all be woth examining. I hope that's helpful, and sorry I can't answer your other MP questions!

This is a very fair point - I didn't mean to dismiss the relevance of volume data altogether!

Glad that was useful to you. It's reassuring to hear that you're intending using this method for swing trading. Though this kind of strategy can be profitable intraday, you're on a lot less steady ground! The purpose of the 200SMA is to provide a simple definition of the longer term trend. When the trend is up, and price is trading above the 200SMA, then when a pullback generates an oversold reading from the RSI this signals a long entry. So long entries are only taken above the SMA and short entries below. This simple filter is remarkably effective. The 200 period MA is just suggested as a broad way of diferentiating between bull and bear markets, and by no means will it be optimal for every market. Trading the S&P500 index over the past ten years, for example, a 170SMA would have provided the best results. However, there are many pitfalls associated with over-optimisation of parameters and the curve-fitting of system variables to specific data sets that you should be wary of. Someone else has posted regarding using the RSI for exits - this is an excellent suggestion, as it will provide a stop loss that adapts to changing market conditions.

One of the advantages of this style of trading is that you can use limit orders for entry and (profitable) exits (though it's going to be a market order to get out at a loss). Not needing to worry about the effects of slippage therefore makes it much easier to have confidence in the results of backtests where you require price to trade through the limit order - in fact, the such results should represent a 'worst case' scenario. However, the effect that SIUYA describes above will only ever be exaggerated by the use of limit orders.