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New Micro Exchange Rate Economics

New Micro Exchange Rate Economics. Keynote Address March 2003 Richard K. Lyons U.C. Berkeley and NBER These slides and other resources in New Micro (e.g., working paper clearinghouse) are available at: faculty.haas.berkeley.edu/lyons. New Micro: Introduction. Information Focus

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New Micro Exchange Rate Economics

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  1. New Micro Exchange Rate Economics Keynote Address March 2003 Richard K. Lyons U.C. Berkeley and NBER These slides and other resources in New Micro (e.g., working paper clearinghouse) are available at: faculty.haas.berkeley.edu/lyons

  2. New Micro: Introduction Information Focus (1) What is the nature of the information the FX market is aggregating? (2) How does it achieve this aggregation? Tools Largely from microstructure finance • Provides theoretical and empirical guidance

  3. Information Focus (1) Public domain: current macro variables • But inflation, Y, Ms, and NX are micro data aggregated months later by official inst. Any impounding in price in the meantime? • Also, what about disagreement on implications, even if observed simultaneously? (2) Public domain: future macro variables • How are variations in individuals’ expectations impounded in price if not common knowledge? (3) Non-public domain: asset pricing variables • What about shocks to money demands, shocks to hedging demands, or shocks to risk prefs? How are these impounded in price? (4) Non-public domain: other variables • What about information regarding the strategic choices of others, or information about behaviorally-motivated actions of others, how are these impounded in price?

  4. Modern Exch. Rate Economics Modern ER Econ. Micro-founded Non-rational New Macro New Micro • Focus: sub-opt. behavior • Approach: trending from noise, feedback, & chartism to behavioral econ. • Focus: info econ. of fin. markets • Info structure: dispersed info • Disconnect Q: why macro so little ER impact? • Focus: supply side of real econ. • Info structure: CK (com. knowl.) • Disconnect Q: why ER so little macro impact?

  5. Order Flow: An Information Vehicle (1) Order flow is sum of signed trades (not volume) • Signed according to which side initiates • Quoting marketmaker is non-initiating side • Auction structure: limit order is non-initiating (2) Order flow is not the same as net demand • OF measures transactions (i.e., demands after price has adjusted) • Think of overshooting model: ↑ $ demand → ↑ in $’s price, but no executed transactions initiated by $ buyers along the way, nor any imbalance in dollar buying at the new price. • Unlike net demand, cum. OF may ≠ 0 • In some models cum. OF follows RW • Price impact differs depending on trader identity • Link to info econ: whose trades info rich? (3) Another perspective: information is in the shifts • How ID demand and supply curves? • Think of scatter in P-Q space • Exclusion restrict.: shifts (vs moving along) • Microstructure theory: IDs shifting

  6. Public info Price Order Flow’s Role Graphically MacroApproach Microstructure Approach Private info Order flow Price Hybrid Information Order flow Price

  7. New Micro: Frequently Asked Questions • Isn’t order flow just demand? • No, as addressed earlier (transactions≠demand) • With two sides to every trade, what can we learn? • True, but they need not be symmetric: one side may be a demand curve shift, the other a price-induced movement along a stable demand curve • Price impounds info in the shift • But isn’t order flow an endogenous variable? • Yes, but so are all the traditional macro variables we have been using in empirical exchange rate models (e.g., output, money, interest rates, and inflation). • The key is determining the underlying shocks (information) that drive order flow. • Strategies for doing so are outlined below • Might causality also go in reverse, from price to order flow? • Surely the answer is yes. For example, price changes induce movements along demand curves, which can in turn produce initiated trades, i.e., order flow. Price changes can also cause demand curves to shift, e.g., at times of market stress (due to capital constraints, etc.). • On average, price-induced order flow in FX data appears to be negative (Evans and Lyons 2002 JME, 2003 NBER; Tien 2002) • So reverse causality does not account for the strong positive correlation between OF and ER changes. • Don’t lose perspective: that causality can run both ways does not mean that order flow is not the cause of most ER variation.

  8. New Micro: Frequently Asked Questions • Can the info conveyed by flow be fundamental? • Yes, even if “fundamental” is defined narrowly to mean money supply and income (Ms and Y). • 2 examples above: (1) micro data not yet officially aggregated and (2) individuals’ changing expectations of future M and Y • There is evidence that flows forecast future U.S. money growth and real output (Evans and Lyons NSF 2003) • Even if not reflecting narrow fundamentals, OF can convey info about mkt-clearing risk premia (a la Portfolio Balance models) • Examples above: shocks to hedging demands and to risk preferences • PB effects not traditionally called “fundamental” • As empirical question, remains open • Do order flow effects on ERs persist? • Theory: persistence depends on info type • Distinguish nominal ER effects from real • Data: much evidence that nominal ER effects do persist (Evans and Lyons 2002 JPE, Payne JIE forthcoming, Killeen et al. 2001 NBER, Froot and Ramadorai 2002 NBER). • Multi-year plots are not consistent with impact that fades in months or less: levels would not track over years unless impact persists over years • Profits: Rapid mean reversion of OF effects would imply trading strategies so profitable that they’re unrealistic

  9. What Info Drives Order Flow? 4 Lines of Empirical Attack (so far) (1) Macro news: OF less important then? • Empirical: may be more important—helps market aggregate differential interpretations • Example on next slide (2) Disaggregate OF: identity matters? • Empirical: differential price impact across trader types shows which types best informed (3) Cross Currency: $/€ trades info for $/¥? • Empirical: pattern of cross-market effects shows whether info specific to $, €, or ¥ (4) Macro expectations: OF proxy changes? • Price depends expected future macro • OF measures expectational “votes” over time?

  10. Does Macro News Drive Order Flow? Total Variation* 10% 20% 40% 30% _______ 100% (1) Public news impounded immediately and directly (2) Public news impounded via OF (3) OF unrelated to macro news (à la Evans & Lyons 2002 JPE) (4) Don’t know * See Evans and Lyons, “How is Macro News Transmitted to Exchange Rates” (NBER 9433, Jan. 2003) for estimation details.

  11. Payoffs Risk Related Concentrated Action likely here? Dispersed Taxonomy of Information Types • Traditional split: public vs private • Public: to be impounded in price without order flow role, not only must data be commonly observed, but traders must also agree on ER implications (i.e., plenty of room for OF role). • Private: as noted, many sub-categories within • Private information 2x2 Note: in a risk neutral world, only the payoff column is relevant.

  12. From Causes to Consequences • Thus far work mostly on identifying the causes of order flow’s information role • E.g., identifying the underlying information that causes flow. • But what are the consequences of order flow conveying information? • Application: International Currencies • Why do some currencies play a disproportionate international role? • Big question with a long history • Does the finding that order flow conveys information have any implications?

  13. Information Approach to Int’l Currencies • Paper (with Michael Moore) addresses a specific dimension of the international role of currencies: the pattern of cross-currency exchange. • Currency competition outcomes driven by relative transaction costs across markets. • Information approach is radically different from two traditional approaches. • Market-size approach (e.g., Krugman 1980 JMCB, Rey 2001 RES): transaction costs are a decreasing function of total volume traded. • Emphasis on resulting increasing returns and multiple equilibria: more trade reduces trans costs, which promotes more trade. • Marketmaker-risk approach (e.g., Black 1991 JIMF and Hartmann 1998 CUP book): adds exchange rate volatility to the determinants of transaction costs.

  14. Analytical Results • Indeterminacy: Info dimension resolves traditional indeterminacy of currency trade patterns (by mitigating the concentrating force of market size economies). • Asset Trade: Pattern of currency trade not driven by the pattern of real trade, as in traditional models, but instead by the pattern of asset trade. • Exchange Rate: Whether transactions are executed directly or indirectly effects exchange rate determination (because these trading methods do not reveal the same information). • Missing Markets: Model provides a new rationale for why some currency pairs never trade directly: information is not sufficiently symmetric to induce participation.

  15. Empirical Results • Paper is first integrated analysis of transactions in a triangle of markets ($,€, ¥) • Predictions • Coefficient signs • Matrix positive semi-definite • Matrix symmetric • Table 1 • Coefficient signs all correct (and significant) • Semi-definiteness borne out • Problems with symmetry • 86% is ratio of indirect to direct ¥/€ trading

  16. Concluding Remarks • Strength of New Micro is its empirical basis • Caveat of data availability • Theoretical work behind, but catching up • E.g., Hau & Rey (here), Bacchetta & van Wincoop (2002) • Much being done, both causes & consequences • Outward reaching • New macro models • Asset pricing • Traditional portfolio balance models • Behavioral finance

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