In Sunny Days or Stormy Weather

Added on by C. Maoxian.

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: 

Notes for Chat with Traders, Episode 153

Added on by C. Maoxian.

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

Added on by C. Maoxian.

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

Added on by C. Maoxian.

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. 

Notes for Chat with Traders, Episode 151

Added on by C. Maoxian.

Episode 151 ... Rick Lane (66:03)

Trading Technologies CEO
Recently purchased trade surveillance software company, Neurensic
Finding bad behavior while avoiding false positives
Accurately identifying trader intent hard to do
Machine learning can be applied, fewer false positives
Neurensic score useful for compliance
MiFID II compliance ... European financial regulations -- futures markets
Every algo needs to be tested, see if it sets off red flags
AI will have applications across trading, not just compliance
MiFID II becomes live January 2, 2018 ... all automated traders aware of this
Lane formerly worked for consulting firm, modeling and simulation of war games, combat modeling, terrorist network growth
Cousin was big floor trader in interest rate futures
Cousin anticipated end of physical trading floors, knew everything would be automated
Cousin invited Lane to come work in Chicago
2005 the trading floor was still madness, 2006 you could hear a pin drop
Applying graph theory to terrorist network modeling
He's a coder, not a trader
Built visual interface that floor traders could use on their handhelds, any dummy could use it
[Lane has similar voice and pacing as Obama ... a Chicago thing?]
Technology had disrupted every industry, cousin anticipated same for futures trading
Georgia Tech undergrad, zero exposure to financial markets
Took him six months just to learn the mechanics of markets (what's a bid and offer, etc.)
Ultra-low latency trading strategies can be dangerous, need serious safeguards
Trading tools as loaded weapons ... risk of serious loss
Writing code for traders serious business, can't be cavalier
Software they wrote for internal purposes called "Algo Design Lab"
Trading Technologies, the 800-lb. gorilla, didn't have anything like their tools in 2008  
Trading Technologies acquired their software in 2010
Lane left and went to Google, but came back to TT within a year
He's a developer who is also a CEO ... an analytical thinker, still builds code to this day
Scale and latency problems guys at Google face are a cakewalk compared with FinTech problems
Shaving five microseconds off from tick to trade is a great  challenge
30 milliseconds is a lifetime (time to return Google search results)
Different exchanges, different rules, different regulatory regimes -- all challenging problems to solve
The most sophisticated hedge funds / prop firms have already reached the limits of latency race (nanoseconds ... speed of light constraints)
Trading algos embedded in FPGA, in silicon chips, in network switches
Making a fix in an embedded algo in a network switch hard to do
Hardware-based solutions for automated trading makes it fast, software too slow
Switches themselves can decode price updates, gain meaning, and change its own price; never sent to server
TT has big internship program
Definition of "trader" has fundamentally changed in recent years
Now traders are all computer science, math, engineering grads [not Neanderthal basket weavers like me]
www.tradingtechnologies.com
Twitter: @r1ck_l4n3

 

TV Shows Watched -- Shooter

Added on by C. Maoxian.

A Twitterer appreciated my recommendation of "Fauda" and tried to return the favor by recommending that I check out "Shooter." I watched the first episode from the first season and wasn't thrilled for the following reasons:

  • War Porn
  • Fetishizes guns (and I'm a pro-gun guy)
  • Fetishizes violence, including political assassination
  • Token black characters (but don't worry, one is immediately killed off)
  • Weak acting
  • Lame made-for-commercial-TV vibe
  • Dumb story

I won't continue to watch this one and don't recommend it.

 Practice Pumpkins (though not filled with red food coloring)

Practice Pumpkins (though not filled with red food coloring)

Everything Looks Perfect From Far Away

Added on by C. Maoxian.

Great cover ... love this girl's voice, reminds me of Tracyanne Campbell's (of Camera Obscura) ... hilarious crowd shots in this video ... when I was a kid, we took a trip to Scandinavia and were in Finland ... we took a public bus somewhere and had to walk to the back of the bus, and when we got to the back, my family spontaneously burst into laughter because we'd never seen a more grim-looking group of people in one spot -- sort of like this crowd of killjoys. The hipster band's energy offsets them well. 

Notes for Chat with Traders, Episode 148

Added on by C. Maoxian.

Episode 148 ... John Grady (83:26)

  • 41 years old
  • Learned about Level 2 at prop firm in Colorado
  • Next worked at prop firm in Chicago
  • In Chicago was the first time he saw Depth of Market (DOM) for futures
  • [Has a southern twang, wonder where he's from?]
  • Look for big orders
  • Guys on the floor weren't geniuses, they just understood order flow
  • Left prop firm, on his own now for ten years
  • Order book also know as Depth of Market (DOM) matrix
  • When you see market orders wiping out limit orders, you know someone is moving size
  • Volume is most important, price chart doesn't represent volume as well as the DOM
  • Important volume to watch is at each price within the DOM (horizontal bar) 
  • Jigsaw is the DOM he uses
  • Trades Treasuries exclusively
  • Treasuries are liquid, logical and steady ... bank-traded and the banks are trading spreads 
  • Crude oil, for example, is thin and erratic ... easily manipulated
  • Can't ramp up your size trading gold, for example, you'll max your size at 10 or 20 contracts
  • With Treasuries you can trade 100 or 200 contracts the same way you can trade a ten lot
  • He trades outrights, only watches the spreads, doesn't trade them
  • Market context is important, depending on the regular news releases
  • No real average number of trades for him, can go from two to twenty trades a day
  • Extraordinarily boring to take three trades a day as an order flow trader, but that's the job
  • Trading requires tremendous patience and discipline
  • Almost all of his losses are the result of forcing trades out of boredom
  • People who trade from home need ten times the discipline (no in-office banter to distract them)
  • You start surfing the net out of boredom, that's the exact moment a trade sets up
  • When you see you've missed the trade, you chase, and end up losing (of course)
  • He might hold a trade for ten seconds to ten, twelve, twenty minutes
  • Market moves two ticks in his favor, he can always scratch the trade
  • On average holds trades three to twelve minutes
  • Retail traders try to trail a stop instead of just taking a trade off -- a mistake
  • If he gets out too early, he'll instantly re-enter
  • He figures out his trade size based on the situation
  • He think in terms of ticks, how many ticks will he possibly lose, sizes appropriately
  • Sometimes you need five ticks of leeway, just have to give it room, size appropriately 
  • Never move your stop loss
  • Don't turn a planned three tick loss into an eight tick loss by pulling your stop
  • He always places an emergency stop loss in the market (3-5 ticks away)
  • Manually figures out the exit, Treasuries liquid enough to do this
  • He markets out, doesn't want to chase out with a limit order
  • He always wants to use a limit order, but often circumstances don't allow
  • Use a market order to get the fill, sometimes you just have to pay up
  • He goes all in and all out, no scaling
  • Don't screw up your risk reward by scaling in or scaling out
  • Most people screw up scaling, they average losers and minimize their winners
  • Big differences among markets ... must choose the right market to trade
  • To trade DAX you need orders in the book, it can reverse in seconds ... too thin!
  • Automated orders are essential in thin markets like DAX or Gold
  • Liquid markets like Treasuries, S&P, Bobl, Eurostoxx, can use discretion, manually adjust orders
  • Try to watch total amount of contracts at each price
  • Specialize in one market, study that one DOM and only that
  • Same players in the same markets every day, they behave consistently
  • You must record your trading screen or do market replay
  • Pay attention to market turning points when you're watching the replay
  • Fast forward, rewind, pause ... study the replay closely.
  • You will learn more from watching replays for a month than you will from journaling trades for a year
  • You need a lot of study and screen time with a good DOM
  • Only three good depth of market providers:
  1. Jigsaw has inside columns, uptick/downtick splits are key column, exlcusive to them ($50 a month, stupid cheap)
  2. TT's X_Trader
  3. CQG
  • No subsititute for screen time
  • When learning, watch two to three hours a day, don't watch all day
  • Then open a live account and start trading one lots, enter the fire
  • Anyone trading a longer time frame doesn't need the DOM
  • Most people shouldn't swing trade: too many things can happen to take you out
  • HFT can spike things up and down in seconds
  • If you think you know where the market will be in two hours, you're delusional
  • People who understand fundamentals, that's a different kind of trading
  • Swing trading is the worst, just crazy that people try to do it
  • He's never met a successful swing trader, and he's been around awhile [me too]
  • You can predict the next six minutes better than you can the next sixty minutes
  • If you trade size, you can scalp for six cents ... sensible only with serious size
  • Fifteen or even ten years ago, the speed of trading very different
  • You could hit a big order as it was leaving, not anymore!
  • HFTs try to be in a breakeven trade immediately
  • HFTs will instantly scratch if they think they're on the wrong side [they never reveal scratch rate]
  • HFTs want to risk nothing to make something 
  • You need to be able to anticipate so much more in the age of HFT
  • There's a lack of volatility today too, so much volume now, nothing can run anymore
  • His edge is in his discretion
  • If AI develops that can replicate that human discretion, the human traders will not be able to compete
  • Best AI can already beat best human chess players, trading similar to chess
  • The big guys have the speed locked down, huge unfair advantage
  • Market makers game the time-price priority of the book
  • HFT get a free look from their constant partial fills [the bastards], you can't compete with that
  • By knowing your market, you can spot the spoof orders more easily
  • Spoofing happens all day every day
  • "Order Flow Basics" -- basic principles video
  • "Order Flow Scalping" -- a popular video of his
  • www.nobsdaytrading.com
  • Twitter: @nobsdaytrading

Movies Watched -- The Dark Horse

Added on by C. Maoxian.

124 minutes long so at least 24 to 34 minutes too long. A W.D. By movie (written and directed by the same person). It started off well. About a mentally ill Maori guy (New Zealand) ... one-time chess champion. You feel bad for him, mental illness is no joke. I was not aware of the whole Maori underclass thing, so that was enlightening. "Genesis" ends up finding some purpose in life by coaching a chess club for poor Maori kids. 

There are some good lines, some good scenes, but it ran too long. And it was kind of hit you over the head preachy in the end. I loved it at first, then only started liking it, and by the end, I wasn't that thrilled with it. If you're interested in mental illness, the Maori underclass, or chess, you might want to see it ... otherwise avoid it.

 A king for a king

A king for a king

280 Killed Twitter

Added on by C. Maoxian.

Since Twitter rolled out the 280 character limit, my timeline has been destroyed. All of the charm and cleverness that the service once had is gone. I follow around 295 people ... about 25 have them have quit Twitter (since T___p was elected), and a half dozen or so have unfollowed me since I said I'd block anyone who tweeted >140.

This month I will systematically go through my following list and unfollow anyone who is tweeting over 140. I might end up following no one this way, but so be it.  You can rest assured that none of my tweets will ever exceed 140 characters. 

deadtwitter.jpg