EXANTE: Practical aspects of algorithmic trading. Bitcoin hedge fund. SSE Riga lecture 23.01.2014....

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Practical Aspects of Algorithmic Trading. Bitcoin hedge fund. Gatis Eglitis, Managing Partner Sergey Troshin, Ph.D., Head of IT Strategy and Operations Part 2: Algo trading

Transcript of EXANTE: Practical aspects of algorithmic trading. Bitcoin hedge fund. SSE Riga lecture 23.01.2014....

Practical Aspects of

Algorithmic Trading.

Bitcoin hedge fund.

Gatis Eglitis, Managing Partner

Sergey Troshin, Ph.D., Head of IT Strategy and Operations

Part 2: Algo trading

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Algorithmic trading Modeling the strategy

Implementing the model

Result analysis

Production

Choosing a broker Prices

Technologies

Stability

What is next?

Contents

Algorithmic trading

Automatic trading

HFT – high

frequency trading

Strategy implementation

Automatic trading

Buy-side Sell-side

Statistical

arbitrage VWAPMarket Making / HFT

Trend

following

Arbitrage

Smart order

routing

Algo trading strategies

Arbitrage

GAZPRU

(MICEX)

On new tick:

ogzd_rub = convert(ogzd, usd_rub)spread = normalize(ogzd_rub/gazpru)

changedSpread()

OGZD

(LSE)

USD/RUB

(FOREX)

LIMIT (LSE)

London Server

Filled (size)

MARKET (MICEX)

Filled (price)

On change spread:if (spread > threshold) place_limit(OGZD, price, size)

On limit fill:If (limit_is_filled) place_market(GAZPRU, size)

Arbitrage strategy

Parameters: threshold

Volume Weighted Average Price

Data Guess Model Approval

Algorithm creation cycle

Historical Data

Completeness

Symbols

Exchanges

News

Depth

Past

Precision

Order Book

Quality

Splits etc.

Gaps

Timestamps

Data Rendering

Huge Volume

Processing Speed

Technical analysis

Иллюстрация с panopticon.com

Guess and Knowledge

Intuition

EmpiricalFundamental

Trading Model

Alfa Algorithm Risks Expenses

Approval. Pre-trade Analysis

Input

• Historical data

• Market influence modeling

• Configuration parameters

Backtesting

• Prototype (R / Python / Java / C++ / Mathlab/ Erlang / …)

• GPU

• Cluster / Cloud / …

Result

•Possible income

•Risks

•Real Expenses

Backtest Results

Param 1 Param 2 … Income Expenses

X1 Y1 … 10% 4%

X1 Y2 … 15% 11%

… … … … …

Xn Yn … 5% 2%

Execution with:

o same input data

odifferent set of parameters values

Computational Technologies

Software Overclocking FPGA

Multi-core GPGPU Cloudx32 x200 x30000

Data Guess Model Approval

Algorithm creation cycle

Ready to Production?

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Choosing a broker

Prime broker

…Retail broker

Broker

Volumes Delays Commissions

Broker Connection

Broker

Client Computer

Trading terminal

Algorithm

Control

Trading

Internal

Protocol

Broker Connection

Broker

Client ComputerWidely used protocols:

FIX, Plaza2, Technology

providers, Custom

TraderAlgorithm

Broker Connection

Broker Client Computer

RDP, SSH

Trader

Algorithm

General

Exchanges/Markets coverage

Trading volumes

Regulation issues

Legal issues

Commissions and fees

Technology

Market data

Delays

Market Depth Best Bid Offer

Trades

Execution

Delays

Client side / Server side

Pre-trade risks, Software

Connection

Protocol

Virtual Machines

Co-location

Control

Trades Export

Interface

Error handling

Servers and locations

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What is next?

Post trade analysis

Excel Program

Charts Model

Export Trade Results

Compare with model

Algorithmic Trader

Technology

Math

Finance

Questions?Sergey Troshin, Director

+356 2015 0000, [email protected]

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NEXT GENERATION

PRIME BROKER