First Week of Trading

Please note: I will be talking about strictly screen trading in this article. I know nothing about floor trading or the crazy symbols they use.

Trading is a major rush for me. Given how much fun I had, it is hard to believe that traders get paid (besides compensating for stress). Every trainee loves trading, but not all of us loved how low our P/Ls were on the first week. I lost a good deal of money, down about 700 (this is pretty consistent among the trainees).

I know many of you read this blog so I would finally get to the part where I talk about: what is trading like? I will split the below in as many perspectives as I have time to write.

Trading as Math
You do second grade math all the time. You need add / subtract quickly and consistently. The more difficult math (some of which may be found here) is for thinking at home and developing strategy. You are unlikely to use it throughout the day.

Often, you will want to recalculate the theoretical value of what you want to trade. You will need to instinctively be able to find the middle of the spread. Sometimes, you want to be in the middle of one and lifting the offer on another. That means the high end of the spread is worth entering the transaction for you, so you transact with the person and buy high. (Otherwise, you would join the bid, which basically means that you are willing to transact if someone wants to come sell to you)

Trading as a Game
Trading is just like playing a computer game, except your mom won't get upset if you play. Many of the concepts I apply get good at a real time strategy game, I am trying to apply to trading.

Knowledge

1. Learn all the statistics - what is the correlation between futures price falling and vol going up; how much deviation is likely in each greek; what news affects the prices; how does it affect the price; etc.
   
2. Understand your role in the game - what is your advantage (if you think you have one); how can you exploit your core competency fully?
3. Weakness - once you understand your strength, you should understand how your strategy can be gamed; are you doing mental math fast enough, are you misreading what the market is saying
4. Analogies - what is trading like? What do thinking or non thinking beings do to survive / thrive in these types of environments
5. Next Steps, Frameworks, and Discussion - people have theories, learning them is good
   

I used to play a game called Rise of Nations. At a job interview, my interviewer told me his children played the same game. Since I was an expert in the game, he asked which nation I liked to play. The answer is that I play every nation on random. In a real game, every strategy has a weakness and telling your opponent anything, is too much.

Preferences

1. Change screen content - the more you see the more you know, but also the more you slow down the computer
2. Visualizations - a friend of mine wanted to switch the cursor icon to all black so that he could see it better, I changed the font size so that I could see more on the screen
3. Window Placement - self explanatory
   

Speed and Consistency

1. Hot key usage - you should know most of the hotkeys after week; there are hundreds of key combinations that can do the same thing; some will be easier at first but don't have the speed potential of others
   
2. Mouse sensitivity - you should get used a mouse with a higher sensitivity (you can change this in the control panel)
   
3. Mechanical Weakness - you will sell futures when you need to buy futures or hedge correctly but too slow; you will accidentally increase vol when you should decrease vol; you will enable your computer to do trades when you want to stop (these get less and less likely as I continue to list them).
   
4. Hand Eye Coordination - Programs like EyeQ and THINKfast may help you improve your mechanical skills
   

Trading as a Psychological Experience
The market is risk-neutral. You will often face the market with less than perfect objectivity. You will probably lose upside potential due to fear. I will list some examples of each type of feeling. There will be times where you follow an example and you are not feeling any of these. There are always exceptions.

• Fear / Nervousness - Example 1: Lets say you got a good deal on a call option that you bought for 2,15 when you thought it was worth 2,18. You are sitting with some greeks that could potentially move against you. The only way to hedge is to sell your call option. Some time passes and the market is willing to buy the option for 2,20 from you. You decide you will sell and just take your profits. Is this a good move? If you took the 'fear' header seriously then you probably know that I'm going to say not to do this. It is likely that the market wants to buy the option for 2,20 because it is worth a bit more than 2,20. This fear is very dangerous because it can be rationally justified (although poorly) with arguments due to mean reversion. Or even more poorly with the gamblers fallacy.
  
• Greed - This is the exact opposite of fear. You are holding a position that you think is overvalued, but you think that the market might continue to pay you off due to some sort of momentum argument. Way back in your head you know that if you think something is overvalued, you should hedge it. When you are greedy though, you are likely to believe that you are smarter than everyone else and reject the signs that tell you to get out of a position.
  
• Wishful thinking - You just lost a lot of money because a position that you were about to hedge swiftly moved against you. You decide you should wait because the market must return to its original levels and hedging now, for a loss, would be stupid. More often than not, this is just wishful thinking.
  
• Frustration - You just lost a lot of money unexpectedly and someone is whistling a terrible rendition of Bach. Resist the urge to break things. It is unlikely that you will get violent , but you will have trouble making sound decisions.
• Everyone has there own 'pet peeves.' Mine are vibrations that I can feel (especially my chair being touched, humming, tapping on the desk or by feet). It is a fact that it is impossible to live without making vibrations, and yet -- I don't like feeling other's vibrations. You might have an aversion to gum smacking. These things need to be communicated clearly and without malice if you hope to overcome this weakness as easily as possible. Combined with regular frustration, pet peeves can seriously debilitate your ability to perform at the highest level.
  
• Happiness / Laziness - You just made a ton of money without even trying. You decide to sit back, relax, and stop trading.
  
• Sadness - I just lost a lot of money. I am not going to trade any more today.
  

I went to the streets to see what the traders had to say about trading:
"awesome," said one. "fantabulous," said another. The average trader doesn't seem to like to talk all that much. The average wholesale trader -- that's another story.

Who would be good?

• Strong self discipline
• Consistent, quick mental math
  
• Likes computer games
• Likes chance games (most people do not like chance games)
  
• Interested in finance
• Can accept the risk of failure
• Likes computer screens
• Interested in making money
  

Answers to previous Math Finance Questions:
1) You own a stock. It exhibits 0% vol for 3 months and then 30% vol for the next three months. What's your average vol for the 6 months? (hint: variance is additive) I was surprised that no one answered this question correctly. Volatility is the square root of variance, so you have to square the volatility and then average to get the average variance. Then you have to take the square root to get the average vol. As the picture at the top of the post shows, vol is just another name for the standard deviation.
There are two reasons why I am stressing this:

1. Everyone seems to be able to say "volatility grows at the square root of time," but can't prove it. Take year 1 vol = v, year 2 vol = v as well. Square both to get v^2 + v^2 = 2v^2 for the 2 year variance. Now just take the square root.
   
2. Natenberg's treatment of volatility is poor relative to the rest of the book. He just averages volatility. Clearly, vol does not average.
   

2 and 3) I am going to wait until some more people try to answer these.

4) According to Hami: covariance is the measure of how the deviations of two variables match each other. Correlation is an adjusted measure of covariance when the variables have been standardized, or made comparable in magnitude and dispersion.
- Exactly, measures like Beta are Covariance. Statistical correlations of say, vol and futures, do not speak of magnitude (be careful!).

Math of Finance Questions: (I don't know the answers)
1) What is a good predictor of market spikiness? (This can be mathematical or non mathematical)
2) On what days do you expect larger market movements? Why?

Note: Do you like writing or even hearing yourself talk? Do you like finance, math, or trading? I am considering opening up this blog to a couple who want to write good stuff. Please email me at igor.schmertzler@gmail.com

Ps: If I have time, I will write about adverse selection.

Financial Math

Money Management (sometimes incorporated within risk management)
"Ralph Vince did an experiment with forty Ph.D.s. He ruled out
doctorates with a background in statistics or trading. All others were
qualified. The forty doctorates were given a computer game to trade.
They started with $10,000 and were given a 100 trials in a game in
which they would win 60% of the time. When they won, they won the
amount of money they risked in that trial. When they lost, they lost the
amount of money they risked for that trial.

This is a much better game than you’ll ever find in Las Vegas. Yet
guess how many of the Ph.D’s had made money at the end of 100
trials? When the results were tabulated, only two of them made
money. The other 38 lost money. Imagine that! 95% of them lost
money playing a game in which the odds of winning were better
than any game in Las Vegas. Why? The reason they lost was their
adoption of the gambler’s fallacy and the resulting poor money
management." -Van Tharp (who also has a blog, which is not very good)

If you make 10% on your investment in the first year and lose 10% on your investment in the second year, how much money do you have? Ans: (1+ -.1) * (1+ .1) = .99 [y0ou lost 1% of your wealth]. Take aways:

1. Note that this doesn't matter whether you made the 10% first or if you lost the 10% first.
2. If you instead didn't reinvest your winnings, you would have broken even. [ex. you have $100, (100 * 1.10) = 110, save 10 dollars then (100 * .9) = 90. Then take the 10 out of savings and you have broken even.
3. What happens when variance increases? Lets say the stock loses 20% in one year and gains 20% in the other year. Like the example above, this is an arithmetic average of 0%. But the math, with reinvestment, looks like this : (1.2 * .8 = .96 ) You just lost 4% of your wealth. As variance increases, geometric returns fall. The geometric will always lag the arithmetic return with any variance / volatility. Your actual loss due to geometric growth lagging arithmetic growth is half the variance. (see kelly criterion formula at top, read fortune's formula, and check out wikipedia)
   
4. You can diversify out of this. Lets say you invest in both stocks in one year. That way, you do break even! Check it out.

Arithmetic of Geometric
If you reinvest your money, it gets multiplied. If a company reinvests it own money, why shouldn't its money get multiplied as well? This multiplication phenomenon is why stocks are said to grow geometrically. (The way that mathematics simplifies multiplication is with the log function.)

"One of the many hearts of this book is the broader concept of decision
making in environments characterized by geometric consequences.
An environment of geometric consequence is an environment
where a quantity that you have to work with today is a function of prior
outcomes. I think this covers most environments we live in! Optimal f is
the regulator of growth in such environments" - Ralph Vince, Mathematics of Money Management

Optimal f is related to the Kelly Criterion but is supposed to be more robust for different distributions. Hopefully, I will get a chance to write more about this interesting subject. Please see the above book for more.

Dimensionless Risk Measures [slash comparing apples to oranges]
When something is dimensionless, it is called a scalar. Suppose you sit down at a new desk and your risk measures show 200 vega and 2000 delta. As a trader, you do not have a stance on which way the underlying or vol is going to go, but unwinding your position may cost a lot of money. Between delta and vega, which is the bigger risk? Experienced traders will give you the same philosophical answer: it depends.

Lets work on a simpler problem. Can we even compare two different deltas?
If delta really acts log normally then the magnitude of its change will be scaled by the size of the underlying. That is, delta is supposed to be your change in price (or your change in wealth) with respect to a one point move in the underlying. But lognormal dynamics say that the chance of the stock changing by 1 percent not by 1 point. That means, that you have to scale delta by the underlying value to take out the percentage effect.

Let say you have delta on an index. In particular, you invest in the Dow and have a delta of 10. The index is at 14,000, so your delta * index = 140,000. Someone else has delta of 100 on Nasdaq, which happens (very conveniently) to be trading at 1,400. Her delta * index is 140,000 also. Who has the bigger risk here? (ans: Some stocks move with greater variation than others.) The scale of variation is called beta. This is the amount that a stock (or whatever) moves with respect to the market. If the Dow has a beta of one and the Nasdaq has a beta of two, then if the market moves by 1%, then nasdaq will move by twice as much as Dow. For that reason, you have to multiply beta into the equation. (From what I understand, multiplying by beta is not common in trading. Please send me an email or leave a comment if you have a good argument on why beta is not multiplied in.)

So how do we compare delta risk to vega risk. One thing is for sure, the variance of underlying (for delta) and variance of volatility (for vega) are of great importance. Each has, in theory, a distribution associated with them. Variance of delta is supposed to be log normal but the variance of volatility isn't. It would be nice to take the standard deviation of delta and the standard deviation of volatility to compare one to the other, but when the shape of distribution is so different, this leads to many problems. (can you think of any?)

With all of the theoretical problems associated with taking the standard deviation in the underlying and the standard deviation in volatility, a trader could move to new desks with a greater understanding of what is happening. The variance of volatility grows as the option get close to expiration so some help from projected risks might help a trader really get a good feel. I believe this would really help.

The arguments against this type of approach [as I see them. ie, there may be more :) ]:

1. What about the correlation between a change in underlying and the respective change in volatility? (This type of thinking leads instead to simulations and VaR)
   
2. The measure would give the trader the false feeling of confidence but would in reality be very unreliable
3. The computational intensity isn't worth the marginal return

Topics for Next Week

• How does it feel to trade
• Equation fitting: Taylor explained and little on Fourier (don't worry, I already wrote half)
  
• Functions of a trader that can and can't be automated (scary topic for many traders to consider)
  
• Adverse selection (those that transact with you are likely to know something you don't)
  

Math of Finance Questions

1. You own a stock. It exhibits 0% vol for 3 months and then 30% vol for the next three months. What's your average vol for the 6 months? (hint: variance is additive)
   
2. If the underlying makes 20% in one day. How should the implied volatility curve move? Keep in mind, this updates your information about the vol of the stock. There is no single right answer. (please email your thoughts)
3. How is question two altered when the underlying makes 20% but no news is released?!
4. What is the difference between correlation and covariance? (The untrained always say correlation when they mean covariance.)
   

Format
I have gotten some comments that the presentation is somewhat complex or unclear. I will do everything I can to improve clarity and remove mistakes, but I cannot simplify topics any further. I will post any links to the topics I discuss for those that don't understand but want to understand.