The Volatility Optical Illusion

Written by Michael Bigger. Follow me on Twitter.

The stock market is a great optical illusion. When prices march much higher, volatility decreases but instability in the system increases. The opposite is true after a big fall. Volatility is high but stability increases.

These statements lead us to state the following dualities:

• Perceived instability is stable.
• Perceived stability is unstable.

  

What are some of the signs we believe indicate instability?

• Low implied volatility.
• A P/E ratio much higher than historical levels.
• Lower than typical implied options correlation.
• A decline in dividend yield. 
• Your cab driver is talking about stocks.

 What are some of the signs indicating a stable market?

• High implied volatility.
• P/E ratios comparable to or lower than historical levels.
• High implied options correlation.
• An increase in dividend yield.
• Panic in the market.

We have been fooled many times by Mr. Market. Have you?

What Can Sharks Teach Us about Algorithmic Trading?

Written by Michael Bigger. Follow me on Twitter.

 

 

Earlier, I wrote a few blog posts about some promising applications of the Lévy flight. Recently, Twitter user @ashrust led me to the article “Sharks’ Hunting Strategies More Like Physics Than Biology,” written by Brandon Keim, which considers Levy flight principles. Keim’s article opens up another rich vein ripe for financial exploration: how sharks respond to the supply of food could have interesting implications for finance. 

 

As a result of reading this article, I am thinking about potential algorithmic trading applications. At this exploratory stage, I can only ask questions, and I cannot provide any answers. This is what I am thinking about:

 

• When sharks can’t find food, “they abandon Brownian motion...for what’s known as Lévy flight.” Since financial markets provide scarce abnormal return opportunities, their participants might be following a Lévy flight in their search for these returns. Do participants get tripped up (compounding poor returns) by getting bored and moving from one Lévy flight cluster to the next? 

 

• Modeling the stock market as a Brownian motion with a growth rate and some gapping mechanisms works very well. Is duality between output and behavior at work here, or is it just that the sum of Lévy flights approximates the regular Brownian motion?

  

• Toward the end of a bear market with long opportunities littering the landscape, do participants revert to a Brownian motion mode? If so, can we measure this migration? If so, can we use it to predict the end of the bear market? 

 

• How do we decode opportunity markers? Can we gain insight from the sharks’ ability to decode food markers? Are abilities irrelevant? If so, are we left to the mercy of a stochastic process? Can one develop the ability to observe humans the same way scientists have the ability to observe the sharks from outside the system? Could that lead to the mother of all money-making insight?

  

• Are pheromones present in these processes? 

 

• During a financial bubble, are participants leaving the stochastic process method for a linear process when following the leading lemmings?

 

Help me think about this, okay?

 

The Skillful Robot

Written by Michael Bigger. Follow me on Twitter.

 

 

I get a kick of following Twitter user and algorithm expert @milktrader. I enjoy reading his blog. Recently, Milk Trader wrote a great blog post entitled robot (SPX) = $. It got me thinking about what skills one must have to become a great trading algorithm designer. In the second paragraph, he says “Skill acquisition involves getting re-acquainted with higher math and getting some solid programming proficiency under your belt.”

 

From my experience, math and programming skills are not enough to turn you into an algorithmic trader. Sure, they are important, but if you lack those skills you can always purchase them. What you need are algorithmic trading design skills: you must be good at creating algorithms from trading methods. I wrote a blog post about this topic entitled Financial Artistry, not Financial Engineering.

 

Be creative, experiment, observe how nature works and how humans behave, and apply your findings to the market. In our search for a great algorithm, we should heed Frank Oppenheimer’s philosophy: “Oppenheimer stressed the importance of play, courage, and guesswork Science.” Something Incredibly Wonderful Happens: Frank Oppenheimer and the World He Made Up (Amazon affiliate link).

 

There is no need for the creative algo trader to go back to making cheese. Iterate until you succeed. Will you?

Trading Straddles

Written by Michael Bigger. Follow me on Twitter.

 

 

 

The other day, I had an exchange about the difficulty of trading options straddles with Twitter user @chicagosean. The Twitter thread is listed below. Sean's issue is that he seems to lose money on the call leg of the options when the stocks move up. Sean is not the only one in this camp. Many experienced options traders have the same problem. Who wants to own bleeding calls on a stock that gently marches upward? Most of us don't. Call buying is appropriate for market makers; value investors with a big, bullish view on a stock; and the traders who think a company might be taken over.

 

If you want to short the stock via the puts or own volatility on a stock, buy cheap 10 to 30 delta puts. These are your best bet. The trick with these is to be right on your view and not pay much for the options. The best scenario for this bet is a big gap down in stock price with the cheap options exploding on the move, making you richer. If the stock moves up in the short run, you will lose money on the delta of the options, but the options will slide up the skew and they should trade at a higher implied volatility.

 

That being said, the current environment is not very favorable for options buyers. Think about it this way: over the last century, the S&P 500 has traded at an average P/E of 13, and the standard deviation of market returns is about 20 percent. Today, the S&P is trading at about a P/E of 13, but VIX is at 35.32. That is paying a big price for volatility for a market that is trading at its average valuation. Just before the financial crisis started, the S&P was trading at 18 P/E and VIX was at 10. It was a better environment for options buyers then.

 

Twitter Discussion:

 

chicagosean: Its starting to think its pointless to be a long holder of call 

chicagosean: long straddles, even if bot at low vol, up moves are rarely rewarding - or in my case, never. Might as well just buy puts. Thoughts? 8:49 AM May 18th 

 

biggercapital: @chicagosean If you trade the gamma then it is a pure vol trade and if you pay low and it moves alot you make $ 8:53 AM May 18th

biggercapital: @chicagosean yeah implieds usually go down when price goes up but that is the beauty as you want buy cheap vol on expensive stocks ;-) $8:54 AM May 18th

 

chicagosean: biggercapital if it moves alot to the downside, yeah. Great trade. But if it moves alot to the upside, it never seems worth it. For me.9:00 AM May 18th 

 

biggercapital: @chicagosean what kind of vol r u buying? 10 ish 20 ish 30 ish 40ish higher than that?9:23 AM May 18th

biggercapital: @chicagosean what deltas of the puts and calls r u buying?9:24 AM May 18th

 

chicagosean: biggercapital I'm a buyer when vol is coming in, seller when its going out. And I've been maintaining neutral delta.9:25 AM May 18th 

chicagosean: biggercapital when I enter the straddles or strangles, I'm always entering at or near the money.9:28 AM May 18th

 

biggercapital: @chicagosean IMO atm will decay vol fast on a move up and vol is not cheap right now9:50 AM May 18th 

 

chicagosean: So, in your opinion, if I wanted to go short 50 deltas, would it be best to purchase 2 OTM puts with -25 deltas each rather than 1 ATM put?9:56 AM May 18th

chicagosean:..is that only in this environment? or would this be a smarter move in most (assuming I wanted to be short deltas)?9:56 AM May 18th

 

biggercapital: my preference for short deltas are the 10 to 30 delta puts9:58 AM May 18th

 

chicagosean: bang for the buck? less vol and theta hit? all of the above?10:00 AM May 18th

chicagosean: ....I appreciate your insight. Feel free to tell me to stop bothering you at any time :)10:00 AM May 18th

 

biggercapital: yes, especially on a gap down. Then the options explode10:01 AM May 18th

biggercapital: is good, if I don't answer on the spot that means busy but will come back to ur question10:02 AM May 18th

biggercapital: feeling though is overall options are very expensive now, hard bet10:02 AM May 18th

 

chicagosean: thesis I'm working with is that I'm trying to always be positioned long vol (more when its cheap, less when its expensive)...10:05 AM May 18th

chicagosean:..and just playing with different ways to best take advantage of this stance. Been doing straddles, but I haven't liked the overall results10:06 AM May 18th

chicagosean: seems the best way to play it is to simply be long puts, while managing risk properly. (only commiting x% of capital)10:08 AM May 18th

 

biggercapital: that makes sense 10:16 AM May 18th

 

Algorithmic Trading: Frank Oppenheimer and the Importance of Play $$

Written by Michael Bigger. Follow me on Twitter.

I am reading Something Incredibly Wonderful Happens, Frank Oppenheimer and the World He  Made Up (Amazon Affiliate link). 

In this book, Frank Oppenheimer discusses the importance of play:

So much time is spent just playing around with no particular end in mind," he wrote: "One sort of mindlessly observes how something works or doesn't work or what its features are, much as I did when, as a child, I used to go around the house with an empty milk bottle pouring a little bit of every chemical, every drug, every spice into the bottle to see what would happen. Of course, nothing happened. I ended up with a sticky grey-brown mess, which I threw out in disgust. Much research ends up with the same amorphous mess and is or should be thrown out only to then start playing around in some other way. But a research physicist gets paid for this 'waste of time' and so do the people who develops exhibits in the Exploratorium. Occasionally though, something incredibly wonderful happens."

 "He asked his friend Bob Karpus, a physicist at the University of California at Berkeley, if he thought there was anything a young person must learn before it is too late, and Karpus's answer was: "play."

I wrote many posts about the importance of playing in the sandbox for algorithmic trading designers. These posts can be found here. What is your take on the importance of play for building profitable algorithms?

Review of The Boy Who Harnessed the Wind: A Metaphor for Algorithmic Trading?

Written by Michael Bigger. Follow me on Twitter.

I just finished reading William Kamkwamba's The Boy Who Harnessed The Wind: Creating Currents of Electricity and Hope (Amazon e-book Affiliate Link). The book tells William's inspiring story of growing up in rural Malawi. Young William, with odds strongly stacked against him, decided to build a windmill to improve his family's standard of living.

We can use the way William went about building his contraption as a metaphor for how to go about building your trading algorithm from scratch. Everyone interested in algorithmic trading should read William's story.

The odds of you succeeding in building an algorithm are high. They don't even compare to the odds William faced. I wrote All You Need to Start Algorithmic Trading to help you get there.

"If you want to make it, all you have to do is try," wrote William.

Then...Try. Why not?

Building your Trading Algorithm around Constants

Written by Michael Bigger. Follow me on Twitter.

 

 

A constant is something that is changeless or a quantity that does not vary. The concept of constant in trading is really important. Let me explain why. 

 

In a fast-changing world, consistency is only possible if you manage to some things that do not change. If you don’t manage to the constants, you will most likely be all over the place and compound return negatively. You need a beacon, and your set of investment/trading constants is that beacon. I discuss Jeff Bezos' opinion on the topic in this blog post. 

 

Bezos says: “It is important to focus on what’s not going to change in the next five to ten years.” The same is true with investment management strategy.

 

What’s not going to change in your investing or trading business in the next five to ten years? You might want to build your strategy around that.

 

Here is a list of some of the constants I use:

 

• Stocks fluctuate: they are volatile.

• If you see a roach in the cupboard, you will find many more: Cockroach Theory.

• Stocks are manipulated.

• Investors and traders overreact.

• In aggregate, diversified portfolios track the market return minus some.

• In aggregate, if a stock move after an analyst makes a recommendation, the move should   be faded.

• In a Levy flight news cluster, most sharp moves are erroneous.

• Intrinsic value has a much lower volatility than its corresponding stock price.

• Traders, when trading, behave like animals.

• Efficient market hypothesis: the market is information efficient. EMH does not mean securities are priced right.

• Positive information about a security takes more time to be reflected in stock price than negative information.

• Shelby Davis's Law: “A purchaser of common stocks makes most of his money in a bear market; he does not know it yet.”

• Corollary to Shelby Davis's Law: A seller of common stocks creates most of his value in a bull market, but he does not know it yet.

• Customers are more truthful than management.

• When opinions are diverse, stock prices approach fair value.

• When opinions are similar, stock prices diverge from fair value.

• Investors are fickle when they lose money.

 

Anything else I should be thinking about? Let me know.

 

 

Update on Wednesday, August 4, 2010 at 3:08PM by Michael Bigger

 Here is another constant:

•  Much of the prevailing information about the stock market is misleading.

#FF @LDrogen @paulwoll @TVN_Kevin . Here is why:

I follow these traders on Twitter for the following reasons:

@LDrogen: Leigh gives great trading advice (via stockTwits TV, Blog, etc). He likes hockey a lot, unfortunately not the right team ;-). Go Habs Go!

@paulwoll: This trader knows his stuff and he is generous with his ideas. Listen to how he hedges his positions.

@TVN_Kevin: I like his Fades and Fills reports. I highly recommend reading them!

Remembering the 2:45 pm Stock Market Crash

Written by Michael Bigger. Follow me on Twitter.

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.

I am writing this post to keep a record of the events and to show how we reacted to the precipitous decline.

Let's start with a dramatic recording of how the events unfolded in the S&P 500 futures pit (the graph of the price action is at the bottom of the post):

 Market Crash Recording (Duration: 11 minutes)

Our algorithm made 70 basis points on that day. This is a pretty good result considering the SPYs were down about 3.50 percent. More importantly, we had the opportunity to see how it 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.

How did you do on that day?

Here is a list of my Twitter posts during that day (if you can't tolerate some cursing don't read these posts):

Going to write a blog post tonight about today's events. I want my kids to read it when older $$

7:18 PM May 6th via TweetDeck

esoap
All charts useless without removing the hour horribilus. As goes the hour so goes the annus? A true test for Dippy and the invisible hand$$
5:46 PM May 6th via TweetDeck

@Maelstrom01 well played! Yes , via my gigantic position
4:51 PM May 6th via TweetDeck

@TVN_Kevin Cheers Kevin! What a crazy day.
4:51 PM May 6th via TweetDeck in reply to TVN_Kevin

@chicagosean thanks the RT. Ihope you have a good one also!
4:48 PM May 6th via TweetDeck in reply to chicagosean

@momomiester I got it now. On the selloff, my algo lit up green, so in addition to it buying stock, I tried to buy as much as everything
4:28 PM May 6th via TweetDeck

Time for a beer on the trading desk. Well deserved $$
4:21 PM May 6th via TweetDeck

@momomiester confused about the question. in Algorithm book, we trade like crazy. Not in investment book

@Maelstrom01 In our investment book we buy 1 stock once every 3 years or so. $crox is a huge position
4:16 PM May 6th via TweetDeck in reply to Maelstrom01

$onty halted
4:13 PM May 6th via TweetDeck

$crox look at these growth rates!
4:10 PM May 6th via TweetDeck

@MikeDancy easy mr. Dancy... GO HABS GO! ;-)
4:06 PM May 6th via TweetDeck in reply to MikeDancy

crocodile scaring the hell out of shorts. $crox
3:47 PM May 6th via TweetDeck

$crox on deck, shorts are covering
3:45 PM May 6th via TweetDeck

options markets widening big. Money for IB $IBKR
3:44 PM May 6th via TweetDeck

very impress by how Interactive Brokers's API and connectivity handled the load $IBKR
3:41 PM May 6th via TweetDeck

@borjasluis bought $crox at 8.54 can't beliueve this
2:58 PM May 6th via TweetDeck in reply to borjasluis

everything RT @borjasluis: @biggercapital jajajjaa, What are you buying? your algo must be given you a market take over, buy, buy, buy
2:57 PM May 6th via TweetDeck

Mortimer: I am fuckin buying!
2:51 PM May 6th via TweetDeck

Greece can keeps its olive, we'll keep our cash RT @hblodget: Stock market crashes as Europe implodes http://bit.ly/dh6vYZ Dow down -230
2:14 PM May 6th via TweetDeck

SPY Price Graph

"Why are 25 Hedge Fund Managers Worth 658,000 Teachers?"

Written by Michael Bigger. Follow me on Twitter.

This was the poignant question asked of Umair Haque by one of his Twitter followers. Haque answered this question in a thought-provoking blog post: The Efficient Community Hypothesis (ECH). 

Haque starts his analysis with the Efficient Market Hypothesis: "the prices of securities reflect all known information that impact their values. The hypothesis does not claim that the market price is always right."

Then he goes on to propose his own hypothesis. He states, "Call it the Efficient Community Hypothesis. It says: where efficient markets incorporate 'all known information,' efficient communities incorporate 'the best known information.'" Brilliant!

Think about it this way: an efficient community is an effective community of ants that extracts the best-known information from all available information.

Haque continues, "Organizations that can seed efficient communities stand to gain a disruptive information advantage" More brilliance! 

Haque concludes his post with the following statement: "In markets alone, assets are never priced correctly, and fund managers earn mega-bucks. But in a market embedded in a community? Well, the tables might turn: Maybe 658,000 fund managers are worth 25 teachers."

I don't think the tables will turn. Fund managers are already seeding more efficient financial communities.

I can think of many ways to incorporate Haque's ECH into my trading algorithm. What about you?