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Thomas Bulkowski’s successful investment activities allowed him to retire at age 36. He is an internationally known author and trader with 30+ years of stock market experience and widely regarded as a leading expert on chart patterns. He may be reached at

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Bulkowski's Trade Review

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Busted
Patterns
Candles Chart
Patterns
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Patterns
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Market
Industrials (^DJI):
Transports (^DJT):
Utilities (^DJU):
Nasdaq (^IXIC):
S&P500 (^GSPC):
As of 07/20/2017
21,612 -28.97 -0.1%
9,483 -92.64 -1.0%
720 5.10 0.7%
6,390 4.96 0.1%
2,473 -0.38 0.0%
YTD
9.4%
4.9%
9.1%
18.7%
10.5%
Tom's Targets    Overview: 07/14/2017
21,850 or 21,000 by 08/01/2017
9,950 or 9,400 by 08/01/2017
725 or 685 by 08/01/2017
6,450 or 6,175 by 08/01/2017
2,525 or 2,400 by 08/01/2017

Written by and copyright © 2005-2017 by Thomas N. Bulkowski. All rights reserved. Disclaimer: You alone are responsible for your investment decisions. See Privacy/Disclaimer for more information.

 

Have you looked at your trades recently? Often, I wait for year end before looking them over, but I want to pass on to you a few tips based on my results. If you want to check your trades, I have created a sample Excel spreadsheet that does some of what I will be discussing. It requires you to enter details of each trade and if you do this as you trade, it makes it easier to track them than trying to type in all of your trades at one sitting.

Trade Review: The Sell Side

My spreadsheet shows trades since I began investing nearly 30 years ago. I sorted them by the sale date and looked at the four combinations of winning and losing trades. Here is the result.

 WinLose
Win29%18%
Lose18%35%

Sorted by SELL date

You read this table in row-column order. For example, a losing trade (row) is followed by a winning one (column) 18% of the time. I highlight the entry in red.

The table says that when I take a loss, I should avoid the next trade because it is twice as likely to become a loss (35%) than a win (18%). That is useful information, but only if I trade sequentially -- one stock at a time (which I don't do). I hold a diversified portfolio of stocks.

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Trade Review: Buying Results

Sorting by the buy date changes the results.

 WinLose
Win25%22%
Lose22%31%

Sorted by BUY date

Here we see results that are more evenly distributed, meaning the numbers are closer to the same value. If a position ends in a loss, the next one is likely to be a loss, too (31%). If the trade is a winner, the next trade is also likely to be a winner (25%).

What these two tables tell me is that if I sell a stock for a loss, I should be extra cautious about placing a new trade because it could also end in a loss. That is common sense, or course, but it doesn't quite jive with the results.

Since I diversify my holdings, I could sell several positions because of a short-term retrace and hold others (like utilities, which I like for the income and cap gains if you buy them cheaply enough). Clearly, though, adding new positions when the market trends upward is smart. Avoid adding new positions when the market is dropping is also smart. I am sure some of you found that out in 2008 (downtrend) and from March 2009 (up trend).

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Trade Review: Best Day of Week To Buy and Sell

I sorted all of my trades by days of the week in which I bought a stock and another set for the days I sold a stock. Then I compared those trades winning or losing on that day to all trades on that day to get a percentage. Here is what I found.

 MondayTuesdayWednesdayThursdayFriday
Buy/Win43%45%47%45%52%
Buy/Loss58%55%53%55%48%
Sell/Win38%57%28%61%47%
Sell/Loss52%43%72%39%53%

I will explain the results below.

Buys

 MondayTuesdayWednesdayThursdayFriday
Buy/Win43%45%47%45%52%
Buy/Loss58%55%53%55%48%

If I look at my losing trades (buy side only), the lowest percentage of losers is 48% on Friday compared to the highest, 58% on Monday. In other words, I do best if I buy on Friday and avoid trading on Monday.

For winning trades when buying, Friday also shows the most winners (52%) and Monday has the fewest (43%).

Sales

 MondayTuesdayWednesdayThursdayFriday
Sell/Win38%57%28%61%47%
Sell/Loss52%43%72%39%53%

For sales, the days that post a loss most often are Wednesday's (72%) and the fewest losses occur on Thursday's (39%).

Winning trades, when sorted by the sell date, occur most often on Thursday (61%) with the fewest on Wednesday. In other words, if I hold off selling until Thursday, I increase the changes of booking a gain.

For my trades, if I buy on Friday's and sell on Thursday's, I tend to score the most winning trades.

Trade Review: Best Month to Buy and Sell

In this test, I used the gain or loss and mapped when I bought or sold shares. Based on the median values (since averages can be skewed by a few large values), the best time to buy is between August to December, preferably in March (best) or September (second best).

On the sell side, the January to May period results in the best gains with a spike in May.

As many of you know, September is supposed to be the worst performing month for the Dow, so that also represents a good time to buy. There is also a saying "Sell in May and go away." That holds true for my trades.

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Trade Review: The Most Profitable Buy Patterns

By keeping track of your trading by style, you can determine what works best for you. On my spreadsheet of trades, I have not only the chart patterns that I have traded but other styles as well. Fundamentals, 2B, averaging up or down, support/resistance, day trade, dividends, and so on are some of the choices.

None of the patterns I trade stand out as particularly profitable or frequently traded. That's because I have traded many patterns over the years and won and lost money on them in almost equal measure. The sample size on them is just too small.

My most profitable pattern is a rectangle bottom, but I only traded that once and happened to win big when I did. In the early days of my plying the markets, I used fundamental analysis and have logged almost 100 trades using fundamentals as the reason for buying. But the method has worked just 55% of the time. The total profit is huge but on an average or median basis, the numbers are nothing to write home about.

My guess is that even though the sample counts are low, you'll want to review the list of the most profitable patterns or trading style, so here it is, followed by the number of trades and win/loss ratio. The composition of this list is based on the median return and the description is the reason for entry, not exit, based on data ending July 21, 2009.

Description# of
Trades
Win/Loss
Rectangle bottom1100%
Fibonacci retrace4100%
Broadening bottom3100%
Rounding top250%
Horn bottom475%
Rounding bottom1070%
Long-term holding4100%
Trendline580%
Averaging down2352%
1-2-3 trend change367%

Track your trades by trading style and that may help you discover what works best for you. If you are eclectic like me, you may bounce from style to style as each setup, each reason for buying is different. You can also track the sell side, too. Find out the best exit strategies that mix best with your trading style.

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Trade Review: The Best Exit Strategies

Based on the chart pattern or trading style and the median profit, the following table lists the most profitable exit strategies that I have used, based on data ending July 21, 2009. Round number SAR means selling when price reaches a round number, such as 10, 20 or 30 and price reverses there.

A long shadow or tail is a chart pattern that suggests price will move in the direction opposite the tail. Downward tails are more reliable than upward ones and you should wait the next day to confirm it really was a tail, because price can overlap much of the tail's move.

Description# of
Trades
Win/Loss
Buyout6100%
Round number SAR1100%
Trend change8100%
Long shadow2100%
3 falling peaks2100%
Ascending scallop1100%
Inverted dead-cat bounce13100%
Measured move up1100%
Eve & Adam double top1100%
Hit target2100%

As you can see, I did not use these strategies often, but they worked well (large profits) when I did.

-- Thomas Bulkowski

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Written by and copyright © 2005-2017 by Thomas N. Bulkowski. All rights reserved. Disclaimer: You alone are responsible for your investment decisions. See Privacy/Disclaimer for more information. An elephant is a mouse with a Microsoft operating system.