Volarb Flow Overview

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A systematic approach to the Sell Side's traditional customer-facing options business

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Volarb Flow Overview

  1. 1. Volatility Arbitrage & Flow Trading The Use of Quantitative Strategies for Portfolio Hedging and Inventory Management Contact: David Hamilton Phone: 917.499.7331 davidehamil@gmail.com
  2. 2. Introduction The purpose of this overview is to demonstrate the merits of using a calculated, systematic approach to handle client-driven trading flows. By employing quantitative valuation methods and strategies, a Dealer can be extremely proactive in the pricing, hedging and risk management of its customer facilitation- an activity that is, by definition, innately reactive. Specific topics will include: • Volume & order flow in the US options market. • The basics of Flow Trading. • A systematic approach to client flows. • Specific examples of a systematic approach. 2
  3. 3. US Options Market: Volume & Order Flow The US Options Market has seen unprecedented growth over the last decade. • Listed volumes currently average approximately 16 million contracts per day and are traded across 12 exchanges. • Options on ETFs have been the largest growing class in volume over recent years (~35% of ADV). Index products, primarily SPX options and VIX options & futures have seen the biggest increases on a risk-adjusted basis. • 30-40% of ADV comes from the top 100 most liquid single stock options. 15 October 2013 Total Volume Index Contracts % Volume 17,998,392 100.00% 2,185,534 928,517 1,114,243 12.14% 5.16% 6.19% 15,812,858 2,916,586 3,550,814 87.86% 16.20% 19.73% Top 250 Equity Top 100 Equity Equities #101-250 7,807,041 6,280,238 1,526,803 43.38% 34.89% 8.48% Remaining Equity & ETF 1,538,417 8.55% SPX VIX Equity & ETF SPY Top 50 ETF (ex-SPY) Source: Options Clearing Corporation. 3
  4. 4. US Options Market: Volume & Order Flow Source: TABB Group/Hanweck Associates. • Approximately 70% of volume in single stock options comes from the top 100 names. 40% of volume comes from just the top 10! • As liquidity increases and direct access to onscreen markets becomes cheaper and more prevalent, Customers (especially ones who are vol-savvy) could increasingly shift their Dealer facilitation requests to less liquid stocks (names 100 and above) and pit-traded index products (SPX, VIX). 4
  5. 5. US Options Market: Volume & Order Flow • The increase in VIX option volumes from 2006-present bears this out: • Expanding client interest and liquidity presents an opportunity for extensive commission capture and employment of unique vol-of-vol strategies and hedging: 2 Perfect Replication of VIX T 1 2 VIX T1   2 T  ST T  pricet ln 1  ST1     ST ST T   2 2  pricet  ln 1  ln 1  S 0 T S0   T  pricet PF  We can buy today a PF which gives VIX2T1 at T1: buy T2 options and sell T1 options. Source: B. Dupire, Bloomberg. 5
  6. 6. Flow Trading: the Basics Flow Trading, by its very nature, is largely a reactive practice for liquidity providers. While Dealers are instrumental in deciding the price at which a given transaction takes place, it is their Clients who initially dictate its major components: • Underlying Stock, ETF or Index • Structure (outright, delta-neutral, spreads) • Size (# of contracts/vega) • Maturity These criteria must be evaluated quickly to determine a level that is competitive enough to win the trade, yet commensurate with the amount of risk involved. 6
  7. 7. Flow Trading: the Basics When evaluating the dynamics of each potential trade, particularly with single stock options, Dealers are required to simultaneously consider multiple risk factors: • Liquidity Should a client facilitation occur, how easily can the Dealer trade out of or hedge the resulting position? • Valuation Metrics Current price/implied volatility vs. historical norms. Is a given interest rich or cheap in terms of a Dealer’s proprietary pricing methods? • Binary Event Risk Is it highly probable that a one-off event (upcoming earnings, takeover/merger, Stage 3 Biotech) will impact a given interest? By adopting a systematic approach to pricing, hedging and risk management, Dealers can greatly improve the speed and efficiency with which they handle their client flows. 7
  8. 8. Client Flows (Platform Overview) Quick Hedge Client Trade is Flipped/Spread vs: Client Options Flow • Inventory (Flow & Corporate) • Layoff Clients • EMM Desk • Onscreen Markets • Secondary Mkt. (IBDs) Dealer Strategic Hedge Client Trade hedged via: • Relative Value Arbitrage (stocks, ETFs) • Volatility Index Arbitrage (SPX, VIX – index vol/skew vs. vol-of-vol) • Dispersion (stocks, ETFs, Index) 8
  9. 9. Client Flows: a Systematic Approach • Determine if a given interest warrants a “Quick” or “Strategic” hedge. Identification Valuation & Optimization • “Quick” Hedge: Determine “Best Fit” solution given current inventory, appetite of Layoff Clients, available liquidity onscreen and Secondary Market demand from IBDs. • “Strategic” Hedge: - Determine valuation by simple means or multi-factor model. - Choose strategy that provides optimal context for managing the residual risk that would result from client facilitation. 9
  10. 10. Client Flows: a Systematic Approach Dealer facilitation in less liquid stocks (names 100+) and ETFs presents an opportunity for wider trading margins, but requires longer holding periods and dynamic inventory management to realize trading profits. Using quantitative valuation methods and strategies to price, hedge and manage risk with lower-tier interests has multiple benefits: • Can dramatically reduce costly residual positions • Maximizes commission capture and trade p/l • Keeps trading staff focused on client pricing, highly liquid stocks (names 0-100) & ETFs and special profit opportunities. Examples - Relative Value Arbitrage Determines richness/cheapness of individual stock/ETF vols using mutltifactor model with technical and fundamental inputs. Long/short portfolio of the largest outliers is constructed and held to allow valuations to revert towards their forecasted mean. - Volatility Index Arbitrage & Dispersion 10
  11. 11. Relative Value Arbitrage (1 Month Maturity) 10-Year Backtested Returns, Jan 2002-Jan 2012 Average (vols x 100) Sharpe Stdev 2002-2011 2010-2011 0.0300 0.0151 2.2601 1.3197 0.0459 0.0395 Bin Frequency -0.06 5 -0.04 5 -0.02 15 0 30 0.02 50 0.04 40 0.06 42 0.08 25 > 0.08 28 11
  12. 12. Relative Value Arbitrage (3 Month Maturity) 10-Year Backtested Returns, Jan 2002-Jan 2012 2002-2011 2010-2011 Average (vols x 100) 0.0283 0.0286 Sharpe 1.8259 1.9300 Stdev 0.0537 0.0513 Bin Frequency -0.06 6 -0.04 13 -0.02 21 0 28 0.02 39 0.04 38 0.06 30 0.08 25 > 0.08 31 12

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