Basic Program on Algorithmic Quantitative Trading

Regular price Rs.14,160.00


 Basic Info : Course on Algorithmic Quantitative Trading
Level : Beginner
Commitment  : 12 hours of study, 2 Days, 8 sessions of 1.5 hours
Language : English
How To Pass : Attend all sessions and complete all assignments to pass the course

What Will I Learn

At the end of this course you will:

  • Network with data providers & brokers
  • Join Quant & Algo-trading firms
  • Automate your own trading strategies
  • Start your own Algo trading desk

Curriculum

  • Introduction to algorithmic trading (AT)
  • Building blocks of the algorithms
  • What, why, how, where off AT
  • Introduction to agency and prop side algorithms
  • Agency algo: VWAP, TWAP, Inline, Aggressive, Passive
  • Prop algo: Pairs, Trend following, High frequency etc.
  • Introduction to DMA, DSA, dark-pool, flash trading

  • Mathematical elements of AT (std, correl analysis)
  • Spread, volume curve and volatility introduction
  • Mean reversion and momentum introduction
  • Hands on training on designing a VWAP algorithm on Excel
  • Hands on training on designing an automated pair-trading algorithm on Excel

  • Lifecycle in development of AT
  • Hands on in back-testing and Monte Carlo simulation
  • Alpha generation: hands on using regression in Excel
  • Stress-test and simulated trading
  • Algorithm deployment and execution: CTCL, DMA, FIX etc.
  • Connectivity to liquidity pools: Exchanges, ECN, inter-dealer broker
  • Testing methods and live trading consideration

  • Introduction to risks in AT
  • Risk management in design and when live
  • Why quants fail (E.g.: LTCM)? Is it a new age nuclear race?
  • Examples from 1987, 2001 to recent US intra-day crash
  • Speed, co-location, latency, precision and scalability
  • Connectivity to liquidity pools: Exchanges, ECN, inter-dealer broker
  • Testing methods and live trading consideration
  • Trading costs: spreads, brokerage, turnover charges
  • Roles: trader, quant, IT, risk manager, compliance

  • Jargons in AT and what it means to a layman
  • History of AT
  • Automated scalping
  • Transaction cost reduction: VWAP, TWAP, Sniper, Slicers
  • Index arbitrage and Program trading, Options Trading
  • Dark pool strategies
  • Market making (sell-side) vs. liquidity extraction (buy-side)
  • High frequency / Ultra high frequency: low latency trading
  • Trend following, pair trading, delta neutral strategies, arbitrage

  • Business aspect of AT
  • Launch of AT, target markets, client-driven or product-driven?
  • Cost of development and deployment: OMS, systems, data, team
  • Integration with internal systems: OMS, compliance, back-office
  • Vendors and 3rd party: data, development, launch, maintenance
  • Revenue models on Agency: brokerage, guaranteed VWAP orders, slippage control, DMA/DSA
  • Revenue models on prop side
  • Competitive factors: slippage, execution, diversified algo
  • Maintenance and improvisation: factors and costing

  • Global trends in AT
  • What GS, MS, JPM, CS, DB, UBS etc. are doing?
  • Role of AT across multiple exchanges: E.g.: Flash Trading, SOR
  • Business strategies for sustainable growth and profitability globally: new markets, better algo, new products
  • Major trends across US, Europe and Asia-Pac
  • Government and regulatory structures globally
  • Volume generated globally using AT vs conventional trading
  • Exchanges, competition and a rush to attract AT volume

  • Where India stands in AT
  • Current regulatory approvals and exchange initiatives in India
  • Taxation, transaction cost in India: set-back to AT?
  • Current trends in India market: agency side, prop side
  • Current state of AT: Institutions (large orders) and arbitrage
  • Is AT possible and profitable at retail client level: If yes how?
  • Indian exchange challenges: cancellation, consumption of bandwidth, mad-liquidity rush, critical network issues
  • Growth projections in volume, market share and turnover using AT in next 3-5 years – India and globally

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