Taking Advantage of an Analyst's Changed Recommendation

On Friday morning, I came across the following tweet:

@Street_Insider Goldman Sachs Removed Amazon $AMZN from their Conviction Buy List. Keeps Buy rating and ups tgt to $195

In the trading account we came in long Amazon.com stock and short Oct8 155 Calls (paired). When I came across the @Street_Insider tweet, my reaction was that the Goldman Sachs recommendation to remove the stock from the Conviction Buy List but up the stock price target was a wash and that if the stock sold off on the news, the move should be faded.

Then I tweeted:

@biggercapital Will be fading RT @Street_Insider: Goldman Sachs Removed Amazon $AMZN from their Conviction Buy List. Keeps Buy rating and ups tgt to $195

After making the first profitable trade (see the trade blotter below), I tweeted:

@biggercapital Thank you $GS for $AMZN call. We know your game. Will fade more later on on a selloff from these levels.

Getting into second profitable trade:

@biggercapital back in $AMZN 153.5

Getting out:

@biggercapital out of $AMZN 154.5

One final tweet:

@biggercapital The difference between a buy and a conviction buy? More $$ in $GS pocket, never be fooled. $AMZN

During the selloff we had the opportunity to unwind the AMZN Oct8 155 Calls and sell the Oct15 155Calls for a nice spread.

Click to enlarge. 

Ka-ching! Are there other ways you know of to take advantage of an analysts' recommendations?

Written by Michael Bigger. Follow me on Twitter and StockTwits. 

Learning The UTX-GE Spread

Written by Norm Winer. Follow me on Twitter and StockTwits

The October 4, 2010 issue of Barron’s included a positive article about United Technologies Corporation (UTX). The article cited the company’s balanced business portfolio and the fact that it generates over half its revenue outside the United States as attributes that help it do well in any economic environment.

For me, the more interesting part of the article was the comparison made to General Electric (GE). According to the article, the companies are both large industrial conglomerates, but while GE is certainly better known, UTX may have the more balanced business portfolio. The article noted that “some who follow UTX liken it to GE without the beleaguered financial division.”

Based on the article, I decided to initiate the following spread trade: buy one UTX, sell four GE. I haven’t followed either stock very closely, so I put the trade on small to start. I paid $5.25 per spread on 10/6/10. As of the afternoon of 10/7/10, it was trading at about $4.65. Given the size of the position and the nature of the two companies, I view this trade as a low-risk way to learn the spread.  

Where Good Trading Concepts Come From

Written by Michael Bigger. Follow me on Twitter.

Here is what I learned about creativity and trading from Steve Johnson's video "Where Good Ideas Come From."

Where Good Ideas Come From: The Natural History of Innovation (Amazon Link)

1. Pay attention to your slow hunches.
2. Increase your connectedness.
3. Create your own spaces where ideas can mingle. 
4. Invite others to join the discussion.
5. Promote the collision of hunches.
6. Look for (listen) and borrow the missing piece.
7. Share your ideas.
8. Mash up other people's trading methods with your own system.

Here is an example of how we combined two hunches to build one of our algorithmic trading strategies: When I first sat down to create our trading system, I thought I wanted to exploit single-stock fluctuations. I was not sure how to go about it. I was stuck. I was listening, though—listening to my trading beliefs, other successful traders, and hedge fund customers. One afternoon, I was spending time with Alex Perelberg, an accomplished trader and a colleague, when I stumbled onto the insight that completed my puzzle. I listened to what Alex had to say about how he trades, and it hit me between the eyes. With this insight in hand, I started building our system, and it worked beautifully.   

Anything else you learned from this video?

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AOI Capital's Overview of Capital Raising

Written by Joe MacLean. Follow me on Twitter.

Despite a generally difficult fund-raising environment for hedge funds, particularly those of small and emerging managers, investors continue to look for talented, skill-based managers.

Investors are particularly looking for highly liquid, trading-oriented strategies. They also favor strategies with an algorithmic engine. 

Here is more color about fund-raising from a previous post written by Michael Bigger.

What Have We Got—Is It Marketable?

Written by Michael Bigger. Follow me on Twitter.

Click For Larger ImageTwo components of our algorithm workflow ask “What have we got?” and “Is it marketable?” The algo’s performance answers the first question. How your strategy and your operation rank against your competition will answer the second.

 

 

The Aurum Report contains a gold mine of data on hedge funds' performance. Explore the stats for some of the top hedge funds and get a sense of how marketable your strategy is. While you're browsing, check out the return of my previous employer, D. E. Shaw, on page 74. That is Alpha! Unfortunately, Aurum removed this report from the internet recently. In a nutshell, as of July 2008, the DE Shaw Oculus International Fund had a compound annual return of 24.77% since inception with an annual standard deviation of 9% and a Sharpe ratio of 1.99.

 

 

If your strategy does not clear the bar, don’t give up. Iterate!

 

  

Trading Spreads GDX GLD

Written by Norm Winer. Follow me on Twitter.

We had noticed in the past two months that the ratio of the price of GLD (Gold ETF) to the price of GDX (Gold Miners ETF) had steadily declined. Perhaps it was an indication that the market was not factoring a potential gold price correction into the price of GDX. Overall, the GLD to GDX price ratio has been very volatile the past two and a half years. We believed we could capitalize on this volatility.

With these trends in mind, on September 21, we bought many of the following spreads: 4 * GLD - 9 * GDX at 9:31 AM for a $3.37 debit. As gold prices declined, the spread quickly widened. We sold the spread about seven minutes later at $5.59, for a $2.22 gain per one hundred spreads. The spread eventually widened much more before the Fed meeting as gold continued to sell off, but it narrowed again to opening levels when gold rallied after the Fed meeting.

Since the 21^st the volatility of this spread has increased and we have traded in and out of it three times for a profit. We are trading this product from a volatility and correlation framework. 

Trading Methods

Written by Michael Bigger. Follow me on Twitter.

When I traded single-stock derivatives at D.E. Shaw, I was fascinated by observing my boss trade S&P options. He made money consistently while taking very little risk. He was a trading magician. He knew his options market, especially the S&P, and he knew how to trade spreads. He was constantly trading in and out, squeezing juice out of the lemon. The lemon never ran out of juice! It was a wonderful thing—a winning trading method.

He started his career trading options for O’Connor & Associates and later for Swiss Bank before joining D.E. Shaw. All of them are/were great trading houses.

I am telling you this story because I want to highlight the importance of trading methods for traders. At Bigger Capital, we use several methods that include but are not limited to convexity, volatility, and correlation. Our trading methods are responsible for generating most of our trading profits. Recipes are very important, but the method you use for squeezing the juice out of the lemon is even more so.

We have learned so much by studying how other people apply their methods. Here is a list of some of the trading methods you might want to investigate:

• Direction
• Basket
• Correlation
• Volatility
• Delta neutral
• Algorithmic
• Market making
• Day trading
• Swing trading
• Trend trading
• Volatility trading
• Pairs trading
• Value
• Shorts
• News
• Follow

Expand your horizon. Explore the methods you know little about. Even better, develop your own.

Trader Matt Busigin Asks about the Risk Profile of Our Algorithmic Trading Portfolio

Written by Michael Bigger. Follow me on Twitter.

Matt (@mbusigin) asks, “Do you run a delta-neutral book? Is there a long for every short? Do you manually adjust your exposure to the ‘risk trade’?”

 

Our answers: 

 

1. We run a delta-neutral book -10 percent to +5 percent of net exposure. Right now, we run it at -8 percent (it has something to do with correlation). Our long position is 100 percent of capital balanced by a similar amount of aggregate short positions. Our gross exposure is about 200 percent of invested capital. 

 

2. No. The number of individual long and short positions is not equal. 

 

3. We do electronically hedge the aggregate residual “risk trade” exposure.

 

 

We hope these answers help you understand how we shape the risk profile of our algorithmic portfolio. Keep the questions coming!

 

Dynamic Hedge: What Science Can't Explain About Testosterone, Cortisol, and Compounding Trading Losses

Written by Michael Bigger. Follow me on Twitter.

The folks at Dynamic Hedge have a fabulous blog post titled What Science Can’t Explain About Testosterone, Cortisol, and Compounding Trading Losses. The post discusses the role of testosterone and cortisol in trading. The big lessons for traders are “learn to harness these chemicals” and don’t overleverage.

 Here is how we go about this in our investment and trading activities:

• Trading: Our trading is done primarily by an algorithm and is thus not subject to these influences. Decisions are made based on strict rules that are not influenced by fear or overconfidence.
• Investment: We have increased our timeframe to three to five years. Increasing your time frame removes the emotional component created by short-term fluctuations. We invest less but much better. We try to take advantage of these influences.

The following excerpts from our e-book, In Praise of Speculation! demonstrate how the above trading methodology limit the negative effects of hormones:

On May 6, 2010 at about 2:45 pm, the stock market experienced a stunning 9 percent drop followed by a partial recovery. The frantic action was over by 3 pm…

Our algorithm made 70 basis points on that day. This was a pretty good result considering the SPYs were down about 3.50 percent. More importantly, we had the opportunity to see how the algorithm behaves during a sharp drop. This was a dream come true as the algorithm stayed positive throughout the episode.

The algorithm did very well because during the fall, it unwound the stocks in the portfolio that did not move very much, according to our metrics, and it bought stocks that were decimated. When the gap between each group of stocks narrowed after 3 pm we generated profits. We doubt we could have taken advantage of this discrepancy without the help of computers. 

In the above example, the algorithm made decisions that we might not have had the fortitude to make on our own. Or as the author of the Dynamic Hedge blog would see it, excessive cortisol levels would have prevented us from having a very profitable day. Did that ever happen to you?

42 Tips to Help You Scale Your Trading Business

Written by Michael Bigger. Follow me on Twitter.

 

 

A week ago, while traveling in Portugal, I took a sheet of paper, a pen, and some Sharpies and I jotted down the concepts that we have used to scale our algorithmic trading business from 20 stocks to 300 over a one year period. The traders interested in scaling their "One Good Trade"  framework will have an interest in this.

 

I was flowing, so the material is not organized in a logical manner.

 

1. Sandbox: be a kid. Play, experiment, and tinker. Drift aimlessly. Waste time. (Frank Oppenheimer).
2. Free your trading thoughts. Let the bits flow. Put it out there. Watch the ants pick it up and help you add value. They will help you grow as a trader.
3. Embrace the network.
4. It’s all about expected value per trade, repetition and processes, not about the outcome of one individual trade. (Mike Bellafiore)
5. Iterate in small increments: you will break through the big trading challenges. (Jeff Bezos)
6. Listen: build a listening station and listen. Listen to people and listen to the market.
7. Capture that trade that has worked for you! Repeat, repeat, improve and repeat.
8. Learn from the laws of nature: Nature optimizes resource usage.
9. Everyone is a genius for at least five minutes a day (I’ve forgotten who said that). Capture that moment. Make the best of this information.
10. Promote greatness wherever you find it.
11. Tools are important. Our tools change us. Vice versa. Embrace the coolest financial tools.  Better yet, develop your own.
12. Recipes can make you an insane amount of money. An algorithm is a recipe. You hate the word  'algo'. Ok, forget that. Instead, use technology to create a potent recipe.  
13. Get to the essence of a thesis.
14. Catalyze: promote your catalyst.
15. In a fast changing world, find the constants: manage to your constants. (Bezos)
16. Find out how much Big Mac is in that trading thesis of yours.
17. Delight!
18. Remove friction.
19. Experience creative flow.
20. Go where the competition is low. (Charlie Munger)
21. Take a walk in the dark alleys (Bezos). Sometimes “Something Incredibly Wonderful Happens.”  Follow the lead of Frank Oppenheimer.
22. Compound money, knowledge, and meaningful relationships.
23. The best teachers are mistakes—make plenty of them—and mediocrity—improve on it.
24. Invert, always invert (Munger).
25. Ship: blog posts, e-books, projects, trade ideas, algorithms, etc. (Seth Godin). Last week,  I published an e-book globally on the Kindle platform. It won't be a bestsellers, but I get the  chance to promote the great work of John James Butler. It is a speculation classic, a money  maker  for anyone who dares to listen to what he had to say. Must read. You can get it here.
26. Listen to your web outreach: what resonates?
27. Be curious about other people’s methods.
28. Seek the exceptional. (@derekhernquist)
29. Find your One Good Trade framework. (Bellafiore)
30. Monitor frictionless channels on the Internet: sales channels, chat channels, etc.
31. Listen to customers more than management when building your trading thesis.
32. Experience the customer experience.
33. Practice.
34. Embrace minimalism. It allows a trader to feel more comfortable taking risk. (@evbogue, @chicagosean)
35. The power of Y: simplify, amplify, $y.
36. Mashup recipes, ideas, and other stuff. The e-book I created is a mashup. The interview  @chicagosean did with @evbogue is also a mashup. Great work Everett and Sean.
37. Big positions have dis-economies of scale.
38. Use APIs....Make your trading platform API centric.
39. Promote greatness. Ooops, a repeat.
40. Ask so what?
41. Simplify. Yup, repeated, it is that important.
42. Twitter, more specifically on StockTwits.

 

Want to learn more about a particular bullet point? Search for the specific topic on this site. I most likely wrote a post about it. 

 

Also...please don't forget to share this article. Other traders could benefit from the information.

What Would Chuck Prince Say to the 30 Year Treasuries Buyers?

From our e-book In Praise of Speculation!

When everyone is playing musical chairs and capital is flowing abundantly, you should play defense. On July 10, 2007, Chuck Prince, then CEO of Citigroup, said,

“When the music stops in terms of liquidity, things will be complicated. But as long as the music is playing, you’ve got to get up and dance. We’re still dancing.” Citigroup's stock price soon thereafter collapsed. On November 2, 2007, Prince resigned.

The moral of the story: Don’t play musical chairs. There must be lower hanging fruits somewhere else. No?