1. Carol Osler, Discussant Stern Microstructure: May 8, 2015

2. » Forex doesn’t “close” ˃Still need benchmark prices ˃1993: WM Co + Reuter “Fixes“ ˃Most influential: 4pm London time » Customers submit orders to dealers for trades @ Fix ˃3:45pm deadline for 4pm Fix ˃Dealers commit to trade with customer @ Fix price » Fix traders = Fund managers to avoid tracking risk ˃Large orders ˃Many executed simultaneously  High volatility pre-Fix

3. » 2011: Melvin & Prins highlight high volatility @ Fix ˃“London 4pm Fix: The most important FX institution you never heard of” ˃Focus on end-month ˃Surprisingly: Does not document volatility ˃Just analyzes it +Provides explanation based on portfolio hedging –  Equity returns   Hedging flows @ Fix   Volatility @ Fix – Substantiates with regression analysis +Highlights perverse incentives of Fix trading: Maximize price move » Hedging perspective suggests Fix volatility self-reinforcing ˃Hedge trades @ Fix   Volatility @ Fix   Tracking risk ˃Could explain secular rise in Fix volatility

4. » At Fix, incentive is to Maximize price move S S Normal Trade Dealer quotes prices Sells to customer B Dealer buys, Closes position Slippage Incentive: Minimize price move Standard techniques: Split trades …. S Fix Trade Dealer learns Amount to sell S Dealer sells Closes position Incentive: Maximize price move New techniques …. B Dealer Buys Fix S B B Slippage

5. » June 2013, Bloomberg: Traders colluding to manipulate Fix prices in chat rooms ˃Fall 2013: Many traders put on leave, fired, etc. Civil suits filed Revised version of Melvin & Prins (Nov 2013) Says nothing about dealer incentives to maximize price moves * ˃2014: Traders on leave are fired or “resign” (total 20+) Civil suits combined to class action suit ˃Late 2014: Banks pay big fines to CFTC, FCA, others Tantalizing chat details courtesy of regulators “Cartel” “Let’s double-team them” ….. ˃Future …. Criminal suits against individual traders?

6. » Thoroughly documents unusual dynamics around 4pm Fix ˃315 Charts, 14 Tables, average entries/table = 290, 4-6 significant digits Section 3. Volatility @ Fix +How big is Fix volatility relative to long-run volatility? Small +How big is Fix volatility end-month vs. mid-month? Much bigger +How big is daily volatility relative to returns @ macro horizons?Very Big Section 4. Placebo: Volatility away from Fix +How big is volatility at normal times vs. the Fix? Small +Has distribution of normal returns shifted over time?Not much Section 5. What exactly happens pre-Fix? +Big moves beginning 3:45, especially end-month Section 6. What exactly happens post-Fix? +Less volatility than pre-Fix +Some retracement of biggest pre-Fix moves

7. » Evidence for high volatility around 4pm Fix Frequency distribution, pre-Fix returns Non-Fix Mid-month Fix End-Month Fix -20 -10 0 10 20 EUR/USD 5 Min

8. » Retracement tendency is “remarkable” » >75 th percentile end-month Mid-month avg End-month avg 20 15 20 5 0 -5 -10 -15 -20 3pm 3:30 4:00 4:30 5:00 Basis Points

9. » Retracement tendency provides profitable trading strategy ˃Sell @ 4pm if price rises 3:45 – 4:00, vice versa ˃For end-month, profitable & high Sharpe even after transaction costs ˃Reliable? Assumes can always trade at prices in dataset +At month-end Fix, EUR Fix trading sometimes > $500 (FCA) +EUR 4pm limit-order-book cumulative depth averages $170-$210 million +Hmmmmm » Suggestion: Examine retracement at longer horizons ˃For end-month Fixes, major share of pre-fix returns typically reversed by noon the next day

10. » Documentation seems to be paper’s primary goal » “Behavior of spot rates in the minutes immediately before and after 4:00 pm are [sic] quite unlike that observed at other times” » Paper wisely careful about “collusion” ˃… if indeed [collusion] took place, could [it] have materially affected the determination of the Fix to the detriment of participants in the forex and other financial markets. This paper presents statistical evidence pertinent to this issue. » Also: Insights from standard models » Section 2: “Standard model” = Portfolio Shifts (PS) ˃Designed to capture forex market “over the trading day” ˃Batch trades in sequences of 3 with specific characters +Customer (Random Investors)  Dealer +Dealer  Dealer +Dealer  Customer (Risk-averse Investors)

11. » Volatility is to be expected with portfolio rebalancing ˃If many funds want to sell foreign currency, other agents must buy +Dealers do not hold positions overnight +Contrast with Duane’s perspective – rebalancing not fundamental information ˃In PS model, “other agents” are other investors +Price falls to create bigger risk premium on foreign currency ˃In reality, “other agents” also include firms who import/export +Price falls to make imports of foreign goods cheaper ˃Evidence to date supports active role of import/export firms in absorbing financial rebalancing flows

12. » Is PS model consistent with observed behavior around Fix? » PS model does not predict surge, 3:45-4:00, and retracement +Model implies instantaneous jump at 3:45 to end-of-day price +No retracement » Is PS the only relevant model? ˃Advantage: Incorporates market’s 2 tiers ˃But Fix price dynamics occur entirely within interdealer market ˃Any dealing model potentially helpful Importers, Exporters Asset Mgrs Dealer

13. » Could be fruitful to examine other models ˃PS assumes perfect competition among dealers +True in 2002 +But interdealer market now highly concentrated +Insights from models of imperfect competition? – E.g. Holden & Subrahmanyam (1992) rat race – Predicts smooth price approach to new equilibrium after information ˃PS assumes dealers know ALL customer order flow when trading with other dealers +But in reality … they don’t (and wish they did …..) +Most existing models assume incomplete dealer information +Insights from classic Figlewski (1981)?

14. » Could be fruitful to examine other models ˃PS dealers are combination of Seppi’s informed & rebalancing traders – Know customer rebalancing flows – Are (essentially) doing the trading for customer – Have good information about true value » Because it depends on magnitude of rebalancing +Insights from Seppi’s model? ˃PS assumes batch trades in sequences of 3 with specific character +But allegations of manipulation describe attempts to exploit continuous trading process +Insights from Kyle models with many trades or from sequential- trade models?

15. » Could be fruitful to design other models ˃PS assumes dealer incentives = Bank incentives +But in reality, alleged collusive activities violated bank policies – Collusion allegations include sharing client order information – “Compliance” offices routinely stress importance of protecting client information – Dealers may have maximized own bonuses at bank expense – Model with agency costs (& chat rooms = low costs of collusion?) ˃PS assumes dealers first trade with customer, then cover their position +But sequence reversed for Fix trades +Reverse sequence creates perverse incentives (Melvin & Prins 2011) +Optimizing model of Fix trading?

16. » Thorough documentation of price dynamics @ London 4pm Fix ˃Exchange rate behavior provides great puzzles » Interesting discussion of whether dynamics fit PS model ˃Recommend examine whether dynamics fit other standard models ˃Maybe develop new models consistent with institutional constraints and incentives unique to Fix » Other suggestions ˃Trimming tables, charts ˃Measures more closely tailored to examining potential influence of Fix ˃-- offline