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
Averaging Down Down Down
Madaz shared some nice footage of his live trading in $DPW on December 13, 2017. I've cued the video to the point where he is trying to buy a dip, but his timing is off, and he ends up adding every ten cents (averaging down) to his position and then instantly scratches the trade at the first opportunity.
I've often suspected that this is how Madaz battles his way out when he finds himself on the wrong side of the market, but this is the first live footage I've seen that proves it. You don't have to watch the whole video, just those three or so minutes.
Here are the details on the initial entry, adds, and sale (times approximate):
9:33:22 Buys 5000 shares @ $5.80 ($29,000 total)
9:33:39 Buys 5000 shares @ $5.77 ($5.785 average) ($57,850 total)
9:33:51 Buys 5000 shares @ $5.70 ($5.755263 average) ($86,329 total)
9:33:58 Buys 5000 shares @ $5.60 ($5.716448 average) ($114,329 total)
9:34:07 Buys 5000 shares @ $5.50 ($5.673158 average) ($141,829 total)
9:34:55 Buys 5000 shares @ $5.50 ($5.644298 average) ($169,328 total)
(States $5.50 as his uncle point, will cut loss below there, total loss would be around $5,000 if he were able to sell 30,000 @ $5.49)
9:37:00 Sells 30,000 at $5.70 (scratches the trade with ~$1800 gain)
Obviously you need nerves of steel to attempt this kind of trading. Also the reflexes required to enter orders at this speed are impressive. In the end he's risking around $5,000 on this one trade, which is a number you should keep in mind when reviewing his total daily P&L which he faithfully posts on Twitter. He's generous to share these live trading videos and should be followed closely.
She Comes In Innocence and Patchouli
Not incense, innocence. Al Stewart reminds me of some famous actress, the body language, the eyes, but I can't figure out who (figured it out, he reminds me of my daughter's Kindergarten teacher) .... Great song.
As Sexy As a CPAP Machine
This is the irresistible look I sport at bedtime. Goodnight, ladies!
Play Twice As Better Than I Will
The great Del McCoury Band on the mystery of musical prodigy....
Dirty Dozen, Long Only Portfolio, End of November 2017
No changes this month.
ETF Trading Portfolio Update -- End of November 2017
No changes this month. I have captured this giant bull market with very few whipsaws. Look through the entire time-stamped history, if you have the time.
