In the Hot hands feature Dave's Goofiz Future is there in the 5 days interval with 14K gains, but my Dow Seer Company made 16K in the last 5 days, so shouldn't that be hotter than Goofiz's future? I guess it has to do how the Hot hands are calculated, maybe on a weekly base?I would like to suggest that Hot Hands be treated somewhat differently;
The shorter term data (less than 60 days) is irrelevant to an astute investor - it is more just for fun and bragging rights (one reason why I suspect the competitions site will vanish soon). What would be useful would be lists of the top 5 or 10 systems in any given category. You might show the top system for each of Day trading, Medium and Long term. And the top system for Stocks, Bonds, Futures, Forex. and maybe the top overall systems for the past 1, 3, 6, 9 and 12 months. All this without charts or anything, just a table, listing the systems and pertinent summary stats. This will allow people to quickly browse the top systems. Then, you could make the categories clickable, and there would be a page for each category ranking ALL the systems that fit the category. You should also allow ranking not only by P/L but also by W:L, Sharpe Ratio, Drawdown % (when available) and average trade (when available)
This would not only provide better exposure to newer systems, but also simplify your search engine, which would no longer be used to find systems by performance criteria, but simply by name/market etc. The performance criteria search would be done using the HotHands tables.
Hope I’m not beating a dead horse here!
Though I agree in principle that there are better ways of presenting the data for searching the systems, research indicates significant evidence that the “dividing line” between short- and long-term time frames for most futures, forex and stocks is right around eight to 10 days. Therefore, I feel an effective trading system can be developed using two different time framesa short-term (2 to 9.9 periods) for the market’s frantic, random side and a long-term system (10 to 64 periods) for the market’s steady, trending side. Day-trading would be less than 2 days average trade length. Medium-term could be considered 10-37 days, and long-term 37-64 days though not necessary. Any system with an average trade length greater than 64 days would be an ultra long-term system.
The reason for presenting graphs is the belief that “A picture is worth a thousand words” but the theory of concepts in fact teaches us that “A word is worth a thousand pictures.” In that sense, the Average trade data or Expectancy would be a good statistic. % drawdown statistic does not really paint an accurate picture of the value of an system at C2, because options are not yet available on futures and forex at C2, but only on stocks, so comparing systems that trade forex and futures also inaddition to stocks (hedge funds) with those that trade only stocks, based on % drawdown would be grossly unfair.
rgds, Pal
Midas Long-Term Value
Midas Short-Term Value
I will have to disagree with you on the value of DD (%drawdown). While I admit that a lack of certain instruments on C2 can handicap a given system, from a risk management perspective - there are many ways to emulate an option position using the available instruments. It’s tedious, but it would work from an assessment point of view - and it is a simple thing to educate your clients to fill the option order (say for a futures option) and ignore the orders for the synthetic position. All that aside, DD is a critical due diligence criteria for assessing any financial risk. DD tells you what is the worst possible loss you will receive before knowing that a system is broken. That may be 150% of worst DD or 200% or more, but at least it is a specific metric. Without it, you have no way to measure relative risk of different systems. You also have no way to determine the adjustment factor for position sizing if you are not comfortable with the developer’s default DD (which is a function of trade risk and therefore position size). I know a lot of developers who are comfortable with a 50% DD to get 300% ROA, but there are not a lot of investors who would be comfortable with that. They would be comfortable with 25% DD to get 150% ROA though - But if they don’t know that the DD is 50%, how can they know to adjust?!
Finally; regardless of what you trade, or how many markets your system uses to achieve its goals, the bottom line is that your equity curve (on C2) will have an average and max DD value - it’s inescapeable. That metric should be published. If the lack of certain derivative instruments is a problem for your system, then it is a problem for the W:L and the Net Profit and ALL of the metrics of your system, not just DD.
As to comparing systems that trade apples versus systems that trade fruit salad - you are correct that it is unfair for developers to compare the two on equal footing. It is NOT, however, unfair to compare them on equal footing from a subscriber’s perspective. The subscriber is someone who has money to invest, and they have their personal risk thresholds and profit goals. They (if they are smart) don’t care what market or instrument they are trading, they want to see a system that gives them the risk profile they can handle with the maximum amount of profit possible. A metric for an investor is Annualised Return / 2 MaxDD. Where a value of 2 is looking really good (ROA >= 4 x DD). This tells the investor that for a risk of x% they can reasonably expect to earn an average of 4x% annually. This is a value that speaks to the heart of the investor. They may not be comfortable with futures and options and forex, that’s fine, they will select a stocks only system - but they will still want to see DD to know what their worst case scenario is!
You have to make a paradigm shift away from evaluating strategies based on net profit. Forget the net profit, forget drawdown, forget number of wins in a row, forget everything else Tradestation shows you in the Strategy Summary. These things mean nothing for strategy comparisons, because everyone has a subjective opinion about which of those measurements matter most.
In your mind you must decouple the entry/exit rules from “net profit” performance or “annualized return” performance. Instead, think of a strategy like this:
Entry rules control risk. Entries don’t determine winners or losers!
Exit rules determine profits or losses (winners or losers).
Entry and exit rules together determine expectancy and opportunity.
Position sizing determines your net profit or return, as well as maximum drawdown.
The risk of a trade is defined as the dollar amount that the trade would lose per contract if it were a loss. Commonly, the trade risk is taken as the size of the money management stop applied, if any, to each trade. If your system doesnt use protective (money management) stops as mine doesn’t, the risk can be taken as the largest historical loss. This was the approach Ralph Vince adopted in his book Portfolio Management Formulas.
rgds, Pal
I agree Pal, money/risk management is a key requirement in design, and once implemented creates a direct proportional relationship between trade risk and Max DD. Because, as you must know, the max DD is the result of a set of discrete trades that created the worst losing run in terms of points that the system experienced. If you trade large, the DD is large, if you trade small, the DD is small. However, that doesn’t change the fact that the DD is important - as it relates to trade risk. It is still a function of determining what is the DIP that you are likely to experience given your particular trade risk tolerance - or vice versa - what is your optimal trade risk given your max DD tolerance. I suppose the KEY metric is what is that ratio between trade risk and maxDD - sorta like, how many consecutive stop losses can my system handle and still be within norms as tested. (if you use stop losses).
As an aside, my suggested ROA%/2maxDD% would give the same value regardless of individual trade risk since the units cancel out. What you show above as way of defining trading parameters is valid and logical - and is in effect reiterating what I said - except that I should have known better than to quote $, since the system design process is about ratios and percentages, not absolute gains/losses.
You and I are saying similar things from different angles I suspect.
Also,
In my mind, curve fitting means either using different systems for different markets, or using different parameters of the same system for different markets, and this is not valid technical analysis. Instead, one should trade the moves, rather than markets.
Historical testing via computer means feeding a set of numbers (open, low, close prices), and receiving back an output set of rules that hopefully will make money trading. The numbers themselves do not have names, and the computer doesn’t recognize the difference between ‘Beans’ or ‘Bonds’. For a system to be valid, it must work on all numbers tested, not just those with certain names and not others with different names.
If a system works on Bonds and not on Beans, this system is curve fitted over a specific set of data (Bonds) and it loses all statistical validity. To believe it will work in the future as it has worked in the past is very dangerous.
Also, different markets do not have different personalities. Again, they are reduced to just being a set of numbers or a bunch of algorithms. If a channel breakout (or any other) method is successful, then the same parameter must be used for all the markets, for the same reasons as above. You cannot use a 20-day channel in Silver and a 40-day channel in Corn, this also falls under the crime of curve fitting.
I therefore take exception to any system, that either only trades one specific market (stocks or forex) or group of markets (Energy or Grains or Cattle), or trades different markets using different parameters or rules of the same system. All this proves is what has worked best in the past, and this will usually not continue to work in the future, as there is no correlation under this scenario and history wont ever repeat itself exactly (though those who forget history are condemned to repeat it.)
This is not specifically written to condemn any particular system vendor. This is a clarification of my definitions of ‘optimizing’ and ‘curve fitting’, and a warning as to what types of trading systems may be valid and what to stay away from.
Although I have never personally worked with any of the systems covered by Futures Truth, I have no doubt that they are all curve-fitted. Any ‘system’ that purports to specialize in one market is optimized for that particular set of data.
Some people will say that different markets have individual characteristics or personalities. This may be true to a limited extent. However, in testing, a computer doesn’t ‘know’ what market it is examining. All the computer knows is a bunch of numbers (highs, lows, closes), from which it attempts to produce an algorithm to explain or predict price behavior.
For a system to be valid, it should work over a given set of numbers (data). Whether those numbers have a name such as 'Beans" or 'Bonds" is (and should be) irrelevant to the data and to the testing program.
Lots of systems make money when they trend and lose money when they don’t. This is not surprising. The best that you can hope for is to create a system that is profitable over time over a wide range of markets/asset classes. Systems such as the Turtles use, makes money when the markets trend and loses money when they don’t (no surprise).
rgds, Pal
My max risk is 1% of my account equity on each trade (the “1% rule”) adjusted by the dollar volatility. A less risky alternative is to optimize using Monte Carlo analysis and with a specified limit on the maximum allowable drawdown. This will generally yield a much smaller and therefore less risky fixed fraction. This has to be tailor made for each investor/trader based on their risk tolerance and return expectation.
Sometimes, when the inevitable short-term counter trend moves comes along, I may be forced to exit my existing position at a loss or profit and if it is a large loss, carry this loss till the time the short-term signal ends, especially if there are no options to use as an hedge at C2, as in futures and forex. When the short-term signal ends, I add on to my losing positions in the expectation that the long-term signal in effect will take hold. A better strategy would be to buy options to hedge your existing position when the short-term counter trend moves comes along. But that is not possible at C2 for certain instruments, so I’m forced to increase my position size and consequently I’m foced to break this 1% rule.
Also, relying on the historical sequence of trades is risky in that the sequence of profits and losses in the future may be less favorable than what was encountered historically. As a result, the drawdowns in the future could be much larger than predicted by the historical sequence of trades. Performing a Monte Carlo analysis on the trade sequence is one way to generate a more conservative estimate of the future worst-case drawdown.
Position sizing can be used to increase returns, reduce risk, improve the risk/return ratio, and smooth the equity curve, among other goals, but the lack of certain instruments does hamper achieving these objectives in an efficient manner.
Position sizing is particularly important when leverage is involved, as with futures trading. If you trade too many futures contracts, a string of losses could force you to stop trading. In fact, with the built-in leverage of futures, one could lose more money than one have in their account. On the other hand, if one trades too few contracts, much of their account equity will sit idle, which will hurt their performance. Finding the right balance is a key element of risk management.
rgds, Pal
Okay Pal;
Please take none of this personally - this is a rebuttal to your comments above.
First: You say that any system that can’t trade across any data source is by definition curve fit. I believe the British word is Bollocks! In fact, a system that trades across any market is ALSO curve fit - just curve fit to that set of markets, or more correctly, curve fit to MARKETs in general - it would probably suck at modeling corporate IRR.
You also imply in your wording that it is a computer that “discovers” or “creates” the algorithms that result from optimisation. I would suggest that this is clearly false (if that was the intended meaning). Computers process, people create. My systems are all day traders (I have several longer term systems, but I don’t have the patience to trade them, or the time (for now) to publish them.) and intraday market activity versus daily/weekly market activity is a lot like the difference between quantum mechanics and general relativity - they both describe the same thing at different scales, and they are (to date) unreconcilable as models.
Different markets have different cycles and trends affecting their longer term activity - and these cycles and trends are apparent at the daily/weekly level - they are all but invisible intraday. Also, differing volatility characteristics linked to liquidity, correlation with economic data, and percentage participation by speculators, hedgers, institutions and retail investors cause intraday activity to differ greatly between markets. While I agree that a generalised swing/breakout system could be viable on short timeframes across many markets, it would not be the optimal day trading model. In day trading you need to deal with both trending and range bound days within the same system. If you only wait for trend days, you might as well bump up to the daily timeframe, you’ll make more money on the same number of trades.
My systems are all based on the same set of models - all of the models are proven, time tested basic technical analysis patterns that have high probability of success. They are different for each market they trade because each market has different characteristics. For example, the ES and to a lesser degree the SP have a very high speculative population and therefore it is quite common to see false moves intraday. Forex by comparison has a much smaller speculative population; False moves are less common, once a market moves is a direction, it tends (more so than the ES/SP) to continue in that direction, at least during prime time. The bottom line; my systems make money when the market trends, and make more when it chops - they only tend to lose when the market oscilates intraday between trend and chop - it happens, but not too much.
The clue to the differences between the “one system for all markets” school and the “each system unto its market” school lies in the “pre-automation” reality of the markets. Pre automation, there were effectively two speculative players in the markets; The trader and the investor. The investor had a system that looked for value, fundamentals, and opportunity. They looked across many markets and picked and chose their instruments based on each instruments inherent opportunity at the time. And their horizon was long term (> month). Then you had the trader; The trader would be in the thick of it at the exchange, they would take trades on only a few markets in general, markets they knew very well (one could say that their brain was curve fit to the market), and they would seize opportunities as they presented themselves - not because of fundamental analysis, but technical analysis concepts like OB/OS and strength and weakness. Their time horizon was much shorter (< 2 weeks usually) and they had many more trades with somewhat smaller profits per trade.
The same paradigm applies to system designers. There are those who seek opportunity across the broader market, with a consistent rule set that seeks out opportunity and limits risk. Then there are those who seek a lucrative liquid market and develop a set of rules that maximizes the realisation of opportunity while minimising risk within that environment.
Both are curve fitting, because their system is based on “what worked.” Even the Turtles is based on “what worked.” I rewrote the Turtle System to be market aware - adjusting all of it’s generalised parameters based upon the data it was trading (doing so dynamically and independent of any “inputs”). The performance of the system doubled, primarily because the adaptive parameters kept it out of a lot of fake out trades in certain markets. I will probably publish that system in here one day, just for fun - but I don’t think many will subscribe to a system that keeps them in up to 10 markets for up to a year at a time - especially futures markets!
I am enjoying this exchange immensely, by the way!
I think you missed most of my points. I don’t trade markets, I trade the moves. You need to come around to the idea of trading moves, rather than markets. Some traders hold on to a position, and keep changing their systems to fit it - other traders hold on to their systems and keep changing their portfolios to fit it.
Computers are just machines programmed by humans. They can’t think independently because they lack a soul or ego which is the faculty that thinks, feels, judges and acts.
Since trendiness is a proven characteristic of commodity markets, given a long enough sample period (i.e. 20 years) almost all the markets yield positive results.
However, in any given year, since there are only a few good trends, most of the markets will prove unprofitable. This is not a reason to abandon the system, or to eliminate (temporarily) unprofitable markets from the portfolio. In fact, the markets that have lost the most money recently (due to being in a consolidation) will probably be the best in the future (when they finally hit a trend).
Trend following is basic to life. Sir Francis Bacon (15611626)noticed runs and consolidations 400 years ago. The aim of diversification is to cancel out the short term noise and enjoy the overall signal.
1. By definition, if you make money in the markets, you are on the right side of a trend. No trend, no profit, period. So it comes down to how do you get on and off a trend at the right time, and how heavy do you bet so you don’t stub out during the corrections.
Buffett uses fundamentals … and missed the great run up in tech stocks. Of course, you can use many methods to miss markets, so I don’t think he has any unique ability in that area. Mostly, Buffet has a great attitude; he has the seemingly infinite patience, courage and humility of, well, a Warren Buffett. Plus he has a secret advisor in Charlie Munger.
2. There are at least as many ways to approach the markets as there are traders. I feel every successful strategy has to exploit some or another trend.
Trend followers look for trends directly in the price (and get some whipsaws).
Fundamentalists look to predict inevitable trends by looking at underlying factors (and are often early and / or wrong).
Arbitrageurs and swing traders feed on small imbalances (and sometimes find out these imbalances are just the start of a bigger trend.)
Contrarians look to take the opposite side from the public (and sometimes find the public just keeps the trend going and going.)
2) Also, does a trend follower need to be in the market all the time in order to catch the big move?
2. No, he just needs to be in for the big moves, and it’s also nice to be out during choppy whipsaw markets.
3. The trend following strategy does not anticipate anything. The trader might anticipate a top or a bottom, and stick to his system anyway.
Well, if it’s on the news, then you can bet on it. Of course, you might very well lose your bet, or miss a good one.
Trend followers do not trade in anticipation of anything, nor do they try to figure things out. They simply go with the trend.
Figuring-out and anticipating events are things that fundamentalists, and weathermen do. They engage the processes of analysis and anticipation, with similar results. The best ones learn simply to predict the trend will continue for a while.
Long-term trading has an advantage, in that the transaction costs are small relative to the average move. Some traders might find it difficult to sit tight through prolonged corrections.
Most markets creep along most of the time and then make a nice move, sooner or later.
Finally, If one could learn to tell when the markets will trend and when they will be in a trading range, they wouldn’t need to know much else to make money. One can visually eyeball a chart and tell if it’s in a trend or consolidation, but that still doesn’t tell one much about the future; a valid case for expert judgment (based on a strategy) in trading and investment.
rgds, Pal
I think you have hit the nail right on the head - you trade moves, I trade markets. I trade trend following, swing, stochastic, statistical and contrarian techniques. I have a model that both follows and anticipates depending on environment and is tunable to any signal to noise ratio, such that it benefits from about 50% of the signal, and a good 20% of the noise. However, it is not a system that watches and waits for a move - It evaluates (based on human logic) the environment, and makes a decision. It then monitors progress and may (or may not) reverse or exit (all again based on human logic).
As I said above; You trade relativistic space, and I trade the quantum void. You have no idea how perfect a metaphor that is for the differences between you and I. Your approach is proven, valid and very profitable. So is mine. Simply, on a macro scale, your approach is valid and mine in ridiculous. Conversely, on the micro scale, my approach is more valid as I deal with intraday quanta which respond more to probabilistic analysis than to concepts of newtonian velocity, acceleration, phase shift and momentum.
Is man capable of certainty? Since man has a faculty of knowledge and nonomniscience is no obstacle to its use, there is only one rational answer: certainly.
Man, however, is the living being with a volitional, conceptual consciousness. As such, leaving aside his internal bodily processes, he has no inbuilt goal or standard of value; he follows no automatic course of action; he must follow a specific course of action if he is to be successsful and the first step in this course of action is the fact that man needs to act “Long-range”.
“Long-range” means allowing for or extending into the more distant future. A man is long-range to the extent that he chooses his actions with reference to such a future. This kind of man sets goals that demand action across a significant time span; and, being concerned with such goals, he also weighs consequences, the future consequences of his present behavior. By contrast, a man is ultra short-range if, indifferent to the future, he seeks merely the immediate satisfaction of an impulse, without thought for any other ends or results.
An animal has no need or capacity to be long-range, at least not in the human sense. An animal does not choose its goals-nature takes care of that; so it can act safely on any random impulse. Within the limits of the possible, that impulse is programmed to be pro-life. But man cannot rely safely on random impulse. If he is to be successful, he has to assess any potential actions’s relationship to it. He has to plan a course of behavior deliberatly, committing himself to a long-range purpose, then integrating to it all of his goals, desires and activities. Only in this way can the attainment of an ultimate purpose become an issue within his conscious control.
An action undertaken by an ultra short-range mentality may lead accidently to a beneficial result. If one buys whatever one stumbles across on the spur of the moment, without reference to reasons, purposes, or effects, one may get away with it for a while; but only for a while.
Consistency, in regard to any goal beyond the perceptual level or routine, cannot be achieved by sense perception (validation of axioms), subconscious habit or luck. It can be achieved only by the aid of explicit values and knowledge gained by applying logic to facts.
Any person in a free society can choose to brush reason aside but,
since there is no agency to deflect the principle of justice, such
persons do not set the long-range economic terms of the society. If
a man succumbs to a buying spree in a bull market while ignoring a company’s fundamentals-he loses out, and he continues to lose unless he learns a better approach. The system thus institutionalizes, though it cannot compel, respect for reality-and men’s economic (and other) evaluations are set accordingly.
Market value, in essence, is the most rational assessment of a
product that a free society can reach at a given time; and there is
always a tendency for this assessment to approach the product’s
objective value, as people gain the requisite knowledge. In time,
barring accidents, the two assessments coincide. The creative
minority grasps the objective value of a good or service, then
teaches it to the public, which is eventually lifted to the creators’
level of development. “It is in this sense,” that the free market is
not ruled by the intellectual criteria of the majority, which
prevail only at and for any given moment; the free market is ruled
by those who are able to see and plan long-range-and the better the mind, the longer the range.
I would be curious to know about your day trading system. What is the name of your day trading system at C2. What are its relevant statistics like W:L ratio, # of trades, Sharpe Ratio and $win per share/contract, Average Trade $, Average Trade %, Expectancy etc.,
rgds, Pal
