Tag Archives: Trading Show

Automated trading tips from Trading Show NYC

Automated trading tips from Trading Show NYC

Big thanks to the NYC Contact for sending this

The Trading Show NYC 2015 Summary:

This was the best trading show out of the three I went to!

——————————————————-
The Triple Crown of Technology

Once basic infrastructure is in place
the focus is on getting as close to zero as possible

1) Zero Cost
2) Zero Latency
3) Zero Time to Market
—————————————————–
Trade Metrics

1) P/L + Max Drawdown
2) Cash Flows from long term trading activity
3) Discounted Cash Flows from long term trading activity

—————————————————–
Tiered Data Pipeline

L1 Cache -> L2 Cache -> L3 Cache -> Memory -> SSDs -> Spinning Disks

Avoid backup in Data Pipline by using 8K circular queues that are cleaned at the speed necessary
to keep them empty (using multi-threaded cleanup code)

XPoint Tech as the next high speed storage after DRAM Flash (PCI-V3.0 SSD)

Merchant Silicon (Run on bare metal switches) vs x86 Architecture (Run on OS)

Speed Improvement in separation of concerns techniques

VMs -> Containers -> Binaries

AMPS -> Streaming DB with Filtering Capabilities

Kafka -> Subscriber Model/No Filtering

—————————————
Kernel Bypass Technique:

Turn UserSpace Kernel into Packet Processor
to accelerate overall networking speed.

Solarfare:
http://www.solarflare.com/
—————————————

Tick Timestamp Issues:

1) Time Granularity
2) Time Synchronization across different markets

—————————————–

Trading Strategy Evaluation:

1) Does the algorithm mirror the trading strategy?

2) Does it minimize trading cost?

3) Max Alpha

4) P/L Stability

—————————————–

Quantum Computing:
1) 2^N Total Solution Space where N is the total number of qbits

2) Superposition of the QBit (bit is both zero and one at the same time)

3) Quantum Entanglement -> Probability Distribution describes
how many and which qbits are affected.

4) Quantum Tunneling -> Can tunnel through 3D Landscape or Volatility Surfaces
1,000 qbit CPU yields 2^1000 solution space
Multiple parameter optimization problem must first be converted to a
binary optimization problem before the Quantum Computer can solve it.

Brute force simple binary algorithm which is great for differential evolution optimization
algorithms.

http://www.solarflare.com/

 

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Who is going to these trading quant shows #Quantcon Trading Show Coast Random Walkers? Oh me oh my

Who is going to these trading quant shows #Quantcon Trading Show Coast Random Walkers? Oh me oh my

So many to choose from, you find them worthwhile?

http://www.quantcon.com/

http://www.terrapinn.com/conference/trading-show-west-coast/data/brochure.pdf

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Eat chips,drink, complain about code,worry over Risk & argue about Maths&Finance

Thursday, Jan 29, 2015, 6:00 PM

The Counting House
50 Cornhill London, GB

89 Random Walkers Went

There will be signs and the sound of quants, risk managers, traders and other abusers of mathematics, finance and technology having fun and eating chips.

Check out this Meetup →

 

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

THE TRADING SHOW NYC -2014 review by Sholom

THE TRADING SHOW NYC -2014 review by Sholom

THE TRADING SHOW NYC -2014

 

This year the trading show was one day instead of two due to Sudden drop-offs in attendance on the second day. Terrapinn used some statistical analysis across all their events and detected this attendance pattern.

 

First up was Bruno Dupire – Bloomberg Quantitative Research.

 

Quantitative Volatility:

 

– Fair Value Skew (Curve) : , You always need to determine a fair value price before you can trade.

 

– Risk Premium = Market Value- Fair Value

 

– Delta Hedging Cost = Frequency of Hedging * Risk Premium

 

– Periodicity -> Path dependent volatility

 

– Mean reversion:

Over Time -> wait for the price to return to a specific price level.

Over Space -> multi-asset arbitrage with rebalancing.

Changing the weights of the asset allocation.

 

– Theoretical skew constructed from price history.

 

Long skewness not related to short skewness.

 

Mistakes:

 

1) Creating a frequency histogram of returns and then trying extrapolate these returns into future.

 

2) Monte Carlo on daily returns (assumes return independence)

gives you something very flat due to central limit theorem.

 

Backtest your delta hedging:

 

1) Discounted average of the intrinsic value from re-centered 3 month ATM option histogram.

 

2) Compute IV which makes delta hedging a Martingale.

 

Fair price is the average square of the price difference weighted by gammas.

 

Risk Premium = IV – HV

 

IV = Market Price

HV = Fair Price

 

Alternative risk premium:

 

HV10 – HV50

 

IV10 – IV50 (IV is much more volatile than HV)

 

For IV50 and HV50, remove all outliers:

 

Types of Outliers:

 

Explicit Exogenous Outliers –> White Swans (Macro Events)

Implicit Exogenous Outliers –> Gray Swans (Macro Events)

Hidden Exogenous Outliers -> Black Swans (Unknown)

Explicit Endogenous Outliers –> (Market Hedging /Operations)

Implicit Endogenous Outliers –> Dragon Kings (Market GARCH/Fat Tail Dynamics)

 

Quant Risk Roundtable:

 

-The Fed has become a bank that is highly political.

It is scared, highly reactive, and will never raise rates until

It is forced to.

 

– What forces the Fed to Act?

1) Inflation/Unemployment balancing mandate

(Inflation Target = 2%, Unemployment Target = 5%)

2) The Bond Market

3) Public pressure

 

—————

Bond ETF future crisis?

What happens when the bond market crashes?

Bond ETFs that were very liquid will have a very illiquid underlying. Will Bond ETFs get a government bail out?

That may NOT be too big to fail.

 

Thanks to him for doing this review

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Anyone going to the NYC Trading Show? Here is the entire programme

Anyone going to the NYC Trading Show? Here is the entire programme

Thanks to Sholom for highliting. I also need to mention that Terrapin folks have been wanting me to go to the big on in Chicago which I won’t be going to unfortunately.

http://www.terrapinn.com/conference/the-trading-show-new-york/programme.stm

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