Another Kacy & Clayton song... love their sound but still find the lyrics largely unintelligible. Not thrilled with the official video; I prefer to make up my own story to match the song.
Notes for Chat with Traders, Episodes 149 and 150
Episodes 149 & 150 ... Aaron Brown (59:21, 64:19)
Interesting guy ... clearly not a conventional thinker or person ... I enjoyed it.
- At AQR ($200 billion quant fund) for a decade
- Didn't like the commute to AQR
- Liked reading numbers in back of newspaper (sports and financial statistics) as a boy
- Read Thorp's Beat the Dealer, fascinated by it
- Grew up in the western US in the 1960s (Seattle)
- Became obsessed with money around age 14 in the early 1970s
- People who lost their jobs in the neighborhood disappeared; it was creepy
- Very shy kid, 14 years old, tried to play poker to make money, and it worked
- Went to Harvard, took a lot of math and statistics, graduate courses only, Harrison White signed off on it
- Harvard grad students are dumber than Harvard undergrads, classes more interesting at grad level
- Becoming better known as pro poker player ... also did a lot of sports betting
- It's hard to scale up when you win at poker
- Your unconscious brain wins poker at the highest levels, not understanding the numbers
- Have to enlist your unconscious brain to win at high levels of poker
- Don't let fear and greed drown out the quiet voices in your brain
- Good traders use their unconscious brain to make good trades
- Sleep deprivation stimulates a certain kind of learning
- You need to know yourself, what motivates you
- Your conscious brain isn't consulted when you make decisions, you just make up excuses after the fact
- 1978-79, people didn't really know how to trade options
- If you could do option math in your head, you could make money
- Floor trading options you can pick up crumbs, but you can't scale
- They were worried about the speed of sound in a 20 foot radius around options specialist post [not the speed of light as in the HFT age, a funny comment]
- You had to physically be in the pit, and the trades were small time, no big lots
- Couldn't get rich betting sports games, but you could get rich running a bookie operation
- Entered Ph.D. program in finance at U. of Chicago
- Managed billion dollar bond fund in the 1980s
- Head of mortgage securities
- Crash of 1987 hurt everyone
- Became a professor for a time
- Went to work for JP Morgan
- It's easy to make money, but hard to keep it
- Invented the term "risk management" (outside of the insurance industry), didn't mean "risk minimization"
- Front office risk manager decides how much traders can bet
- CEO talks to middle office risk manager who talks to the front office risk manager who talks to the traders
- Started at AQR in May 2007 and crisis hit in August 2007
- Cut risk in late July 2007 just by chance
- Losing a worst-case loss for a year every day, day after day, for three days
- Cliff Asness called the bottom of it, whether by chance or not, no one knows [Cliff is now a billionaire]
- Quant equity crisis of 2007, everyone forgot about it after the 2008 crisis hit
- Featured in Scott Patterson's book, The Quants
- 3000 longs and 3000 shorts simultaneously, make tiny gains with massive leverage, that's the idea
- Quant equity funds all had overlapping positions, this was part of the problem
- Funds don't have to report their short positions, only longs
- Brokers can tell you what is Hard To Borrow
- Quants are engineers, logical ... learn from mistakes
- Quants don't like to change bet size just because of losses, hate drawdown control policies
- Down 10% in a month, whether through losses or redemptions, clients can terminate contracts
- Let investors out who want to get out, you don't want them in your fund anyway
- You never want to be in a trade where the risk is managing you
- All words for risk have some opinion attached to it (either positive or negative)
- Traders have a very different idea about risk
- Risk is something we exploit, it's like energy, and we respect it
- Most people like predictability, but some people are more spontaneous
- Gamblers and thrill seekers trade with no edge
- The goal of trading is making money, that's your job, nothing else matters
- Most people don't know why they do what they do
- Most people who try to trade are pursuing some silly illusion
- The best traders do it because they can't imagine doing anything else
- You want to start risk taking when you're young, can't do it when there are "adult stakes"
- The best traders are really bad about explaining how they manage risk
- Traders who try to swing big to make up for past losses, it's a disaster
- But you have to be willing to make big bets even after a series of losses
- How far do things have to go against you before you know that you're wrong?
- Traders internalize two ideas: they might be right and they might be wrong
- How much does it make if you're right, how much does it lose if you're wrong?
- Only need two scenarios in your mind for any trade
- You equally weight both scenarios in your mind
- How much are you willing to lose when you're wrong? Must decide this first
- Most traders leave too much money on the table most of the time
- Most traders spend 80% of pre-trade strategy about capping the downside
- They should spend 80% of the time figuring out what they're going to do if they're right
- How do you exit a trade when you're right? This is the key question
- Some people want to win a lot of pots (at poker) instead of winning a big pot
- You have to know who you are ... do you prefer scalping (winning lots of pots) or holding for a larger gain (winning an occasional big pot)?
- You should know your profit ratio: average win on winning trades divided by the average loss on losing trades
- Your win ratio is going to be whatever it is... think harder about your profit ratio
- Don't try to guess what will happen, just prepare for what might happen
- Risk avoidance mistake: start small and then get bigger (you should reverse this)
- Plan for success! Pick a size and stick with it
- Emotional decision making means reckless decisions
- Focus on median outcomes (not the average outcome) ... look for good median outcomes
- Kelly Criterion teaches us that if you take more risk, all you do is increase probablity and size of bad outcomes
- Every trader MUST understand the Kelly Criterion (read Thorp's book)
- Haghani experiment with bet size with biased coin very telling ... most people (financial professionals) went broke!
- Every finance professor in the country should have been shocked by the Haghani Experiment (but they didn't care)
- Things happen that you can't put in your probability model
- 1% of the time you have no idea what's going to happen -- it's not predictable
- Takes significant amount of resources to maintain a Value at Risk model
- Good non-specialist description of VaR: Financial Risk Management for Dummies (a book he wrote)
- Kelly Criterion teaches you to design trades with maximum loss in mind given your edge ... gets you in the right ballpark
- Haghani Experiment proved most people have no idea how to size a bet
- Professional gamblers he asked all instantly knew the optimal bet size in the Haghani Experiment
- His website: www.eraider.com (lots of fascinating stuff on there)
I Got Nothin' But the Whistle and the Steam
The great Jerry Douglas....
Learning How To Let Some Doors Stay Shut
This girl can (flat)pick ... wow ... love it.
Hope Nobody Has a Sharpened Word
Like the song ... did not picture a morbidly obese guy in trucker cap when I first heard it, but there we are....
Bitcoin Sell Setup Finally Appears on 24-hour Chart
The waves are very clear in the Bitcoin (as they are in most speculative manias) ... if Bitcoin breaks below the 16,000 level, then the targets that come into play are 10,900, 8,800, and 3,600. Since these targets are based on the 24-hour chart, it will take weeks [er, months] for them to play out, but that's my take on things.
Price could push above wave C without triggering below 16,000, possibly setting up a higher wave C, but unless the major wave 5 is "invalidated" (price moving above it), this looks very bearish to me.
Above the Madding Crowd
Not "far from," but above. And that's not a bugger, it's a nose ring. I like her voice and this song....
In Sunny Days or Stormy Weather
An aged Al Martino making a hash of the original lyrics (she turns to touch it, indeed!) and forgetting a line, but this is a great song and his (earlier recorded) version remains the best:
One of Sixteen Vestal Virgins
Great song ... maybe one of the greatest drug overdose songs of all time.
Notes for Chat with Traders, Episode 153
Episode 153 ... Xiao Qiao (64:39)
- Studied engineering, math, finance, statistics
- [Is he first generation Chinese-American or did he grow up in China? Moved to America as a child? Fluent English, but non-native to my ear]
- Liked Applied Mathematics
- Both parents are engineers (Dad a mechanical engineer)
- Did materials science engineering, didn't like working in a lab
- Went to grad school for finance, Ph.D. program, University of Chicago
- Probability theory, applied statistics, linear algebra
- Asset pricing research
- Preferred to go into industry rather than become an academic
- Was teaching assistant for Eugene Fama in his asset pricing class
- Fama demanded that students be both precise and concise
- Lars Hansen taught him to take economics seriously, always apply economic thinking
- Five years to complete a Ph.D. in finance at Chicago
- Enjoyed playing blackjack in college
- Blair Hull's personal assistant emailed him about market timing paper Hull was writing
- Hit it off with Blair Hull, agreed to co-author paper on market timing
- A Practitioner's Defense of Return Predictability
- Team play for blackjack important, MIT team employed this method
- Don't play if you don't have an edge
- Bet table minimum when the house has the edge
- Bet size hugely important once you have an edge
- Most people who try to play to win don't have an edge
- Academic research divided about market timing
- Return predictability (can we forecast returns?)
- Forecasting equity premium, combining return predictors
- Modeling six month ahead excess returns
- Examples of return predictors: PE ratio, CAKE ratio, variance risk premium, etc.
- Forecasting horizon shortened to one month for next white paper
- Return Predictability and Market-Timing: A One-Month Model
- Reads a lot of academic research papers for his current job
- Likes Frank Diebold's blog
- [I guess he went to U Penn undergrad]
- [Losing listeners in the late 30 minutes mark as talk strays into CAPM]
- Try ideas yourself, don't just read about ideas
- Simple linear regression goes a long way toward telling you if your hypothesis is any good
- Lower frequency risk premiums: holding period in months, execution doesn't matter much
- R, Python, Matlab code will be fast enough to implement
- Higher frequency trading: holding period is intraday or days... execution becomes very important
- Execution is where you make a significant fraction of your profits if your holding period is short
- C++ necessary then ... code needs to be fast enough to trade in real time
- Backtests are inevitably overfitted ... need to use out of sample data to test your model
- Look at: Returns, Cumulative returns, Sharpe Ratios, Volatility, Cumulative Drawdown, Maximum Drawdown, Tail Correlation
- Tail events, extreme events ... look how your model does during these
- Trading costs, transaction costs, turnover, slippage are supremely important ... academics ignore these factors ("market microstructure")
- Intermediaries are all-important, can make or break your returns ... practitioners are well aware of this, academics ignore it
- Risk premiums important, but market impact, liquidity equally important
- Rebalancing a portfolio during illiquid periods will affect returns
- Frequency of rebalancing also important
- His website
- This Xiao Qiao should not be confused with Zhou Yu's wife, the anime girl
- He is not on Twitter