{"id":9585,"date":"2011-02-01T22:38:00","date_gmt":"2011-02-02T03:38:00","guid":{"rendered":"http:\/\/www.smbtraining.com\/blog\/?p=9585"},"modified":"2011-02-02T01:04:31","modified_gmt":"2011-02-02T06:04:31","slug":"evaluating-your-trading-results-44","status":"publish","type":"post","link":"https:\/\/www.smbtraining.com\/blog\/evaluating-your-trading-results-44","title":{"rendered":"Evaluating your trading results (4\/4)"},"content":{"rendered":"<p>This turned into a four part series when <a href=\"http:\/\/www.smbtraining.com\/blog\/evaluating-your-trading-results-34\">yesterday&#8217;s post<\/a> on evaluating your daily performance ended up being longer than I planned.\u00a0 It is especially important that you understand the information from the <a href=\"http:\/\/www.smbtraining.com\/blog\/evaluating-your-trading-results-part-23\">second post<\/a> in this series before reading this post, which will focus on actually quantifying your edge in your trading plays.<\/p>\n<p>As a starting point, you need to have a significant set of data from a fairly large set of trades.\u00a0 I would suggest that these should be categorized according to the type of trading play, and that analysis be done on each category separately (though you may also find value in doing all of your trades as one large set.\u00a0 You may be surprised to find out that some kinds of trades, which you thought were very profitable, might not actually be worth as much time as you&#8217;re spending on them.\u00a0 Conversely, there may be a set of trades that you are not really focusing on that are quietly churning out small profits, and this set of trades could represent a real opportunity if you can play them more aggressively.<\/p>\n<p>This issue of how to divide your trades into categories is not trivial.\u00a0 It is tempting to create a category for every variation of trade, but, at the end of the day, you will end up with categories that are too specific and have too few trades in them to be useful.\u00a0 In my playbook I have basically four broad categories of trades:\u00a0 In play scalps (breaking news midday, or on the open), pullbacks, end of trend patterns and breakouts.\u00a0 I have many different ways to get into and manage these trades, but I basically label each trade with one of these four broad categories.\u00a0 If you are an active trader, it is easy to end up with a dozen or more categories, but this level of detail can quickly become unmanageable.\u00a0 Rather than making a firm plan at the beginning, most traders will find it is better to start keeping records and then start adjusting as need be.<\/p>\n<p>I touched on this in the previous post, but it is important enough to repeat here.\u00a0 You must think about how to standardize your trades.\u00a0 Working in raw dollars is not that useful.\u00a0 Percentages (of the stock price) might be a better metric (hint: if you use percentages I would multiply everything by 100 or even 10,000 because our brains deal with numbers like 42 a lot better than .0042.)\u00a0 My preference is to standardize everything for the risk I was taking on the trade, which is a number that absolutely must be recorded at the time you put the trade on.\u00a0 I cannot overemphasize this enough &#8212; if you do not standardize your numbers, you won&#8217;t get meaningful information.\u00a0 One trade in AAPL or PCLN can swamp a lot of trades in lower priced stocks.<\/p>\n<p>Take a look at the following table of theoretical trades:<\/p>\n<p><a href=\"http:\/\/www.smbtraining.com\/blog\/wp-content\/uploads\/2011\/02\/HOME-2-1-2011-7.47.42-PM.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-9602\" title=\"HOME 2-1-2011 7.47.42 PM\" src=\"http:\/\/www.smbtraining.com\/blog\/wp-content\/uploads\/2011\/02\/HOME-2-1-2011-7.47.42-PM.png\" alt=\"\" width=\"555\" height=\"164\" srcset=\"\/\/www.smbtraining.com\/blog\/wp-content\/uploads\/2011\/02\/HOME-2-1-2011-7.47.42-PM.png 555w, \/\/www.smbtraining.com\/blog\/wp-content\/uploads\/2011\/02\/HOME-2-1-2011-7.47.42-PM-300x88.png 300w\" sizes=\"auto, (max-width: 555px) 100vw, 555px\" \/><\/a><\/p>\n<p>I hate to repeat information from an earlier post, but let&#8217;s just make sure we are on the same page with this table.\u00a0 Everything on the blue side is collected from your trade blotter and everything in red is calculated.\u00a0 (I thought I was being helpful when I put the formulas on the sheet, until I realized that I did not include column labels!\u00a0 The leftmost column in the table is &#8216;C&#8217;.)\u00a0 A few reminders about the blue columns:\u00a0 Entry and Exit are average prices if your trade included multiple entries.\u00a0 Initial stop should be recorded at the time of entry.\u00a0 In this table, I assumed a constant $1,000 risk per trade, so the number of shares reflects that risk level.\u00a0 Obviously, you would record what you actually traded.<\/p>\n<p>The first calculated field is <strong>P&amp;L<\/strong>, which is <strong>your profit\/loss as a ratio of the amount you risked on the trade<\/strong>.\u00a0 This, to me, is the absolute bottom line and the single most important statistic you need to track.\u00a0 This is also what is commonly called your risk\/reward ratio, but there is no guessing or speculation about what you intended&#8211;this is your <em>realized<\/em> risk reward.\u00a0 Looking at the numbers in the table above, I see a huge red flag:\u00a0 a trade with a loss of -1.3 times the intended risk in the trade.\u00a0 For a daytrader, this should happen very rarely.\u00a0 (Swing traders will have some surprises on gap openings&#8230; my single biggest loss was -4.5 times the intended risk on the trade on a gap open.)<\/p>\n<p>You should also run basic statistics on this column.\u00a0 Knowing your mean, median and standard deviation of this number for different categories of trades will tell you a lot about your actual edge in the market.\u00a0 (Many traders who think they are trading with 1:2 or 1:3 reward to risk will have some real surprises when they actually run these numbers.)\u00a0 In addition, you should probably run sets of numbers on winning and losing trades separately.\u00a0 I have found interesting information in the differing variances of each set, and also in the the analysis of outliers.<\/p>\n<p>Consider next the <strong>MFE <\/strong>(Maximum Favorable Excursion), which is the furthest the trade ever moved in your favor between your entry and exit time.\u00a0 We should think about an important and fairly widespread misconception here.\u00a0 Some people believe that the &#8220;reward&#8221; part of the risk\/reward equation comes from this number, but this is absolutely false.\u00a0 Risk reward is what you execute on a specific trade or over a large set of trades; this number only shows you how well you could have done with perfect foresight.\u00a0 (Imagine selling the exact high tick of every move.)\u00a0 Subtracting your <strong>PL <\/strong>from the<strong> MFE%<\/strong> column shows your &#8220;give up&#8221;, or how much open P&amp;L you gave back in any open trade, which is another important stat (not shown in the table above) to track.\u00a0 Obviously, there will be a lot of variability in this number, but if you&#8217;re seeing that it is very large relative to your P&amp;L (say, giveup is 1.2 and average P&amp;L is 0.8) might suggest that you could be more proactive about taking profits because, on average, you are leaving a lot of money on the table.<\/p>\n<p>The remaining column, the <strong>MAE <\/strong>(Maximum Adverse Excursion), is the furthest the trade went against you from the point you entered.\u00a0 (If you are respecting your stops, this should almost never be less than -1.0, so the trader in this example has some explaining to do!)\u00a0 One good way to look at this number is as a measure of &#8220;heat&#8221;&#8211;how much heat you are taking in each trade.\u00a0 Again, think about how you might use this number.\u00a0 If you are seeing very large numbers here on average, perhaps it would be appropriate to scale into your trades a bit more rather than going all in.<\/p>\n<p>For simplicity&#8217;s sake, I calculate one more number not shown in the table, a simple &#8220;indicator variable&#8221; that is a 0 if the trade was a loser (PL &lt; 0) and a 1 if it was a winner.\u00a0 This might seem like a silly number to calculate, but if you have this column set up like this, you can simply average it to find your win ratio.\u00a0 (In the example above, you would have 1,1,0 and 1, which averages to .75 = 75% win ratio.)\u00a0 I segregate winning and losing trades into separate groups and calculate stats on them, so I can easily calculate the <em><a href=\"http:\/\/www.smbtraining.com\/blog\/can-a-smaller-stop-carry-more-risk-than-a-large-stop\">expected value<\/a> <\/em>of any trade in my playbook using the simple formula of <em>winning percentage * average win &#8211; losing percentage * average loss<\/em>.\u00a0 Remember, the beauty of this system is that these results are based on actual, hard, executed numbers, with no guesswork or wishful thinking involved.<\/p>\n<p>All of these numbers are only meaningful across a significant sample size (say 20-30 trades in each category), and they are also not valid if your execution is not stable.\u00a0 If you are a new or developing trader and have made significant changes to your trading style across the period you are analyzing, then you are comparing apples to oranges at each end of the time period.\u00a0 (There are tools for dealing with this kind of style drift, but they are a bit beyond the scope of this article.\u00a0 At any rate, you should strive to execute consistently.)\u00a0 In my opinion, the most important use of this kind of analysis is twofold.\u00a0 First, you cannot possibly understand your true edge in the market without doing some kind of analysis like this.\u00a0 Especially for developing traders, this is a critical point.\u00a0 Perhaps even more importantly, it will show you the right kinds of questions to ask of your trading.\u00a0 This kind of analysis can be a critical part of your toolset and an important part of your development as a trader.\u00a0 I hope this series has given you some ideas and can provide a good starting point for you to refine your own analysis of your performance.<\/p>\n<div id=\"_mcePaste\" style=\"position: absolute; left: -10000px; top: 353px; width: 1px; height: 1px; overflow: hidden;\">\n<table border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"295\">\n<col style=\"width: 42pt;\" span=\"3\" width=\"56\"><\/col>\n<col style=\"width: 53pt;\" width=\"71\"><\/col>\n<col style=\"width: 42pt;\" width=\"56\"><\/col>\n<tbody>\n<tr style=\"height: 11.25pt;\" height=\"15\">\n<td class=\"xl66\" style=\"height: 11.25pt; width: 42pt; font-size: 8pt; color: white; font-weight: 700; text-decoration: none; font-family: Calibri; background: none repeat scroll 0% 0% black;\" width=\"56\" height=\"15\">Entry<\/td>\n<td class=\"xl66\" style=\"width: 42pt; font-size: 8pt; color: white; font-weight: 700; text-decoration: none; font-family: Calibri; background: none repeat scroll 0% 0% black;\" width=\"56\">Exit<\/td>\n<td class=\"xl66\" style=\"width: 42pt; font-size: 8pt; color: white; font-weight: 700; text-decoration: none; font-family: Calibri; background: none repeat scroll 0% 0% black;\" width=\"56\">L\/S<\/td>\n<td class=\"xl66\" style=\"width: 53pt; font-size: 8pt; color: white; font-weight: 700; text-decoration: none; font-family: Calibri; background: none repeat scroll 0% 0% black;\" width=\"71\">Initial   Stop<\/td>\n<td class=\"xl66\" style=\"width: 42pt; font-size: 8pt; color: white; font-weight: 700; text-decoration: none; font-family: Calibri; background: none repeat scroll 0% 0% black;\" width=\"56\">Shares<\/td>\n<\/tr>\n<tr style=\"height: 11.25pt;\" height=\"15\">\n<td class=\"xl63\" style=\"height: 11.25pt; font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri;\" height=\"15\" align=\"right\">20.00<\/td>\n<td class=\"xl63\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\" align=\"right\">25.00<\/td>\n<td class=\"xl67\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\">L<span> <\/span><\/td>\n<td class=\"xl64\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\" align=\"right\">18.25<\/td>\n<td class=\"xl65\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\" align=\"right\">571<\/td>\n<\/tr>\n<tr style=\"height: 11.25pt;\" height=\"15\">\n<td class=\"xl63\" style=\"height: 11.25pt; font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri;\" height=\"15\" align=\"right\">25.00<\/td>\n<td class=\"xl63\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\" align=\"right\">25.75<\/td>\n<td class=\"xl67\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\">L<span> <\/span><\/td>\n<td class=\"xl64\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\" align=\"right\">23.50<\/td>\n<td class=\"xl65\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\" align=\"right\">667<\/td>\n<\/tr>\n<tr style=\"height: 11.25pt;\" height=\"15\">\n<td class=\"xl63\" style=\"height: 11.25pt; font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri;\" height=\"15\" align=\"right\">50.00<\/td>\n<td class=\"xl63\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\" align=\"right\">50.65<\/td>\n<td class=\"xl67\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\">S<span> <\/span><\/td>\n<td class=\"xl64\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\" align=\"right\">50.50<\/td>\n<td class=\"xl65\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium medium solid none none black -moz-use-text-color -moz-use-text-color;\" align=\"right\">2,000<\/td>\n<\/tr>\n<tr style=\"height: 11.25pt;\" height=\"15\">\n<td class=\"xl63\" style=\"height: 11.25pt; font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri;\" height=\"15\" align=\"right\">114.00<\/td>\n<td class=\"xl63\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium solid none black -moz-use-text-color;\" align=\"right\">113.25<\/td>\n<td class=\"xl67\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium solid none black -moz-use-text-color;\">S<span> <\/span><\/td>\n<td class=\"xl64\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium solid none black -moz-use-text-color;\" align=\"right\">118.50<\/td>\n<td class=\"xl65\" style=\"font-size: 8pt; color: black; font-weight: 400; text-decoration: none; font-family: Calibri; border: 0.5pt medium solid none black -moz-use-text-color;\" align=\"right\">222<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p><a href=\"http:\/\/www.twitter.com\/AdamG_SMB\"><img decoding=\"async\" src=\"http:\/\/twitter-badges.s3.amazonaws.com\/follow_me-c.png\" alt=\"Follow AdamG_SMB on Twitter\" \/><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>How to use statistics to analyze your trading setups and individual trades.<\/p>\n","protected":false},"author":388,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[943,1,1373],"tags":[939,1496,1528,1529,1583,1581,1486,188,749,1582],"class_list":["post-9585","post","type-post","status-publish","format-standard","hentry","category-adam-grimess-blogs","category-general-comments-2","category-trading-lesson","tag-analysis","tag-expected-value","tag-mae","tag-mfe","tag-pl","tag-performance-analysis","tag-reward","tag-risk","tag-statistics","tag-win-ratio","no-post-thumbnail"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.1.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Evaluating your trading results (4\/4) | 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\" 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