{"id":15707,"date":"2011-11-29T10:54:53","date_gmt":"2011-11-29T15:54:53","guid":{"rendered":"http:\/\/www.smbtraining.com\/blog\/?p=15707"},"modified":"2011-11-29T12:43:16","modified_gmt":"2011-11-29T17:43:16","slug":"a-few-spins-of-the-wheel","status":"publish","type":"post","link":"https:\/\/www.smbtraining.com\/blog\/a-few-spins-of-the-wheel","title":{"rendered":"A Few Spins Of The Wheel"},"content":{"rendered":"

Last week we talked about the casino\u2019s edge which in the trading world is called expectancy, but all that expectancy tells us is whether or not our trading strategy is likely to be profitable or not\u2014but not how much money we might make.\u00a0 How profitable depends on how often we have a chance to trade our system\u2014will it be a few times a year, a few times a week, or many times per day.<\/p>\n

And this is also how our casino makes money\u2014calculating the edge is easy, but the number of hands dealt or spins of the wheel in an hour start to tell us the profit potential.\u00a0 Going back to the statistics from a real casino in Las Vegas, let\u2019s look at how profitable a few games are when we combine their edge with hands (spins) per hour\u2014let\u2019s assume a $10 average bet, and ten bettors per table, except for Black Jack where we assume five bettors per table:<\/p>\n\n\n\n\n\n\n\n
Game<\/strong><\/td>\nHouse Edge<\/strong><\/td>\nHands Per Hour<\/strong><\/td>\nRevenue Per Hour Per Bettor<\/strong><\/td>\nRevenue Per Hour<\/strong><\/td>\n<\/tr>\n
Baccarat<\/td>\n1.2%<\/td>\n72<\/td>\n$8.64<\/td>\n$86.40<\/td>\n<\/tr>\n
Black Jack<\/td>\n0.8%<\/td>\n70<\/td>\n$5.60<\/td>\n$28.00<\/td>\n<\/tr>\n
Craps<\/td>\n1.6%<\/td>\n48<\/td>\n$7.68<\/td>\n$76.80<\/td>\n<\/tr>\n
Roulette<\/td>\n5.3%<\/td>\n38<\/td>\n$20.14<\/td>\n$201.40<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Ever wonder why so many people play Black Jack??\u00a0 They can play for a very long time before losing all their money.\u00a0 For example, if a bettor came in with $200 and was placing $10 bets, he could still be playing at the Black Jack tables 35 hours later, but the odds are he would have blown everything in just ten hours at the Roulette table.<\/p>\n

And of course the house likes someone with a hot hand since it draws more and more people to the table which increases the total number of bettors and the total amount bet.\u00a0 It\u2019s a numbers game, and while it is impossible to predict the house take for any given day, it is quite simple to predict it for longer timeframes.<\/p>\n

And so it is with a trading system that has been thoroughly vetted.\u00a0 Total profit potential is the expectancy times the number of trades per day\u2014sometimes called opportunity.\u00a0 And of course we have to account for commissions and slippage, which have a minimal impact on positions held for days or even months, but which can destroy the returns on an otherwise profitable system that trades several times per day.<\/p>\n

1)\u00a0\u00a0\u00a0\u00a0\u00a0 We will assume the same trading system is used for each timeframe, and that it generates a trade on average every 20 bars.\u00a0 If it is applied to a weekly chart, there would be a trade every 20 weeks, or about 2.6 times per year.\u00a0 With a daily chart, it would be every 20 days, or about 12.5 trades per year, and so on.<\/p>\n

2)\u00a0\u00a0\u00a0\u00a0\u00a0 Let\u2019s assume that the expectancy is based on an average position size of $10,000.<\/p>\n

3)\u00a0\u00a0\u00a0\u00a0\u00a0 We will also assume friction to be $0.03 per trade, where friction is defined as commissions plus slippage.<\/p>\n

4)\u00a0\u00a0\u00a0\u00a0\u00a0 Return on capital assumes no leverage\u2014return on buying power would be higher in all timeframes, and much higher at the lower timeframes.<\/p>\n\n\n\n\n\n\n\n\n\n
Periodicity<\/strong><\/td>\nExpectancy<\/strong><\/td>\nAfter Friction<\/strong><\/td>\nTrades Per Day<\/strong><\/td>\nGross $$ Per Day<\/strong><\/td>\nGross $$ Per year<\/strong><\/td>\nReturn On Capital<\/strong><\/td>\n<\/tr>\n
Weekly<\/td>\n$500.00<\/td>\n$499.97<\/td>\n0.01<\/td>\n$5.00<\/td>\n$1249.92<\/td>\n12.5%<\/td>\n<\/tr>\n
Daily<\/td>\n$125.00<\/td>\n$124.97<\/td>\n0.05<\/td>\n$6.25<\/td>\n$1562.13<\/td>\n15.6%<\/td>\n<\/tr>\n
Hourly<\/td>\n$30.00<\/td>\n$29.97<\/td>\n0.35<\/td>\n$10.49<\/td>\n$2622.38<\/td>\n26.2%<\/td>\n<\/tr>\n
15 Minutes<\/td>\n$15.00<\/td>\n$14.47<\/td>\n1.3<\/td>\n$18.81<\/td>\n$4702.75<\/td>\n47.0%<\/td>\n<\/tr>\n
3 Minutes<\/td>\n$4.00<\/td>\n$3.97<\/td>\n6.5<\/td>\n$25.81<\/td>\n$6451.25<\/td>\n64.5%<\/td>\n<\/tr>\n
1 Minute<\/td>\n$2.00<\/td>\n$1.97<\/td>\n19.5<\/td>\n$38.42<\/td>\n$9603.75<\/td>\n96.0%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

And this is where systems trading starts to really shine\u2014at the lower timeframes where we can trade tens or hundreds or even thousands of different stocks concurrently.<\/p>\n

The high frequency and ultra high frequency strategies are an extreme example of this where they make hundreds of thousands of trades per day\u2014even millions of trades per day–often with a gross return of a fraction of a penny per trade. Even at $0.001 expectancy per trade (net of friction), 100,000 trades would yield $100, and assuming the same $10,000 position size, that is $25,000 per year which is about 250% return on capital unleveraged\u2014not too shabby\u2014and of course the machines make many more trades than that and the position sizes are much larger\u2014do the arithmetic and you will see why high frequency trading has become the new best thing.<\/p>\n

There are really three basic approaches to systems trading:<\/p>\n

1)\u00a0\u00a0\u00a0\u00a0\u00a0 The algorithms generate signals that a discretionary trader uses in conjunction with his normal strategies.<\/p>\n

2)\u00a0\u00a0\u00a0\u00a0\u00a0 The system is traded as a gray box where a human trader decides whether or not to take each signal.<\/p>\n

3)\u00a0\u00a0\u00a0\u00a0\u00a0 And as a black box where the computer takes every signal.<\/p>\n

This mirrors the number of trades that can be executed per day.<\/p>\n

1)\u00a0\u00a0\u00a0\u00a0\u00a0 If a discretionary trader uses the signals in conjunction with his other strategies, hopefully his returns per trade will improve, but it is unlikely he will see a significant increase in the number of trades per day that he can handle.<\/p>\n

2)\u00a0\u00a0\u00a0\u00a0\u00a0 If a trader operates with a gray box, there not only is the possibility of higher returns per trade, but significantly more trades per day, so the return on capital or buying power can be significantly improved.<\/p>\n

3)\u00a0\u00a0\u00a0\u00a0\u00a0 And of course a black box can handle an unlimited number of trades, so the only question is what is the lowest timeframe in which the algorithms will deliver a positive expectancy net of all friction, and what is the total number of stocks, FX pairs, commodities and so forth that can be traded at the modeled expectancy.\u00a0 For example, some strategies might be better using high beta stocks while others are better with low beta stocks, and of course if the strategy trades long\/short, it might not always have an ample list of easy to borrow shares depending on market conditions.<\/p>\n

Next time we will look at how you can lose all your money even with a trading system that has a high expectancy<\/p>\n

Author:\u00a0 Rick Martin<\/p>\n

For more information or answers to your questions, email Rick at rmartin@smbcap.com<\/em><\/p>\n

Hypothetical computer simulated performance results are believed to be accurately presented. However, they are not guaranteed as to accuracy or completeness and are subject to change without any notice. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Since, also, the trades have not actually been executed; the results may have been under or over compensated for the impact, if any, of certain market factors such as liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any portfolio will, or is likely to achieve profits or losses similar to those shown. All investments and trades carry risks.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Last week we talked about the casino\u2019s edge which in the trading world is called expectancy, but all that expectancy tells us is whether or not our trading strategy is likely to be profitable or not\u2014but not how much money we might make.\u00a0 How profitable depends on how often we have a chance to trade our system\u2014will it be a … Read More<\/a><\/p>\n","protected":false},"author":921,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1,1936,1938,1937],"tags":[238,1947,1376,4702,1944],"class_list":["post-15707","post","type-post","status-publish","format-standard","hentry","category-general-comments-2","category-ricks-blogs","category-systems-development","category-systems-trading","tag-black-box-trading","tag-gray-box","tag-p","tag-systems-trading","tag-trading-systems","no-post-thumbnail"],"yoast_head":"\nA Few Spins Of The Wheel | SMB Training<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.smbtraining.com\/blog\/a-few-spins-of-the-wheel\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A Few Spins Of The Wheel | SMB Training\" \/>\n<meta property=\"og:description\" content=\"Last week we talked about the casino\u2019s edge which in the trading world is called expectancy, but all that expectancy tells us is whether or not our trading strategy is likely to be profitable or not\u2014but not how much money we might make.\u00a0 How profitable depends on how often we have a chance to trade our system\u2014will it be a ... 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