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Secondary Transaction Costs in Bonds

Secondary Transaction Costs in Bonds. Larry Harris. Formal Disclaimer. The Securities and Exchange Commission, as a matter of policy, disclaims responsibility for any private publication or statement by any of its employees.

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Secondary Transaction Costs in Bonds

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  1. Secondary Transaction Costs in Bonds Larry Harris

  2. Formal Disclaimer • The Securities and Exchange Commission, as a matter of policy, disclaims responsibility for any private publication or statement by any of its employees. • The views expressed herein are those of the author and do not necessarily reflect the views of the Commission or of the authors’ colleagues upon the staff of the Commission.

  3. Secondary Bond Markets • Corporate bonds. • Municipal bonds. • Government bonds.

  4. Bond Market Characteristics • Many securities. • Infrequently traded. • Almost no contemporaneous price transparency. • Almost no quotes.

  5. The Main Policy Issue • How does market opacity affect liquidity? • New car dealer comparison. • Comparison to equity markets.

  6. Important Issues • What are secondary transaction costs in the bond markets? • What determines these costs? • How does bond complexity affect these costs?

  7. The Research Program • Examine all municipal (MSRB) and corporate (TRACE) bond trades. • Measure average transaction costs for each bond. • Identify cross-sectional determinants of these costs. • Identify how costs change when bond trades become more transparent.

  8. The Samples

  9. The MRSB Sample • Broker-dealers report all municipal bond trades to the MRSB. • Price, time, size, dealer, customer side. • Our one-year sample period:November 1999 – October 2000. • These data are now available on the next day on the Internet.

  10. The TRACE Sample • Broker-dealers report all corporate bond trades to the NASD. • Price, time, size, dealer, customer side. • Our one-year sample period:January 2003 – December 2003.

  11. MRSB Sample Selection (from Section 3.1) Deleted: Unknown securities Derivatives Variable rate bonds Missing data Unidentified cost Pricing errors regressions

  12. TRACE Sample Selection (from Table 1) Same deletion criteria as applied to the MSRB sample.

  13. MSRB Bond Characteristics

  14. TRACE Bond Characteristics(from Table 2)

  15. MSRB Characteristics(from Table 1, Panel B) Credit Quality

  16. TRACE Characteristics(from Table 1, Panel B) Credit Quality

  17. Municipal Bond Complexity Features • Callable • Sinking fund • Extraordinary call • Nonstandard interest payment frequency • Nonstandard interest accrual method • Credit enhanced

  18. MSRB Characteristics(from Table 1, Panel D) Bond Complexity

  19. MRSB Transparency • During most of the sample period, bond trades were made public on the next day if the bond traded four times. • Transparency and trade activity therefore are correlated.

  20. Corporate Transparency • NYSE ABS bond trades are completely transparent. • Trades for TRACE-transparent bonds were reported with a 45 minute lag. • Bonds have been made TRACE-transparent based on credit quality and original issue size (IOS).

  21. TRACE-Transparent Bonds • Throughout 2003: All bonds rated A and above with original issue size>$1B. • March 1, 2003: All bonds rated A and above with $100M>OIS>$B. • April 14, 2003: 120 bonds rated BBB with stratified original issue sizes.

  22. 2003 Corporate Transparency (from Table 1, Panel D)

  23. Transaction Cost Measurement Methods

  24. Benchmark Methods • Most transaction cost measures require price benchmarks. • Quotes • Average price: Warga and others • Closing or opening prices • Without benchmarks, we must use econometric methods.

  25. Econometric Approaches • Bid/ask bounce is due to transaction costs. • Measure the bounce. • The Roll Serial covariance spread estimator. • Regression methods useful when we know the side trade initiators (customers) are on.

  26. A Constructive Introduction to Our Econometric Method

  27. Price and Value • Log Price = Log Value +/- trade cost • Let Qtindicate with values 1, or -1 whether trade t was initiated by a customer buyer or seller.

  28. Add Interdealer Trades • Let Itindicate with values 1 or 0 whether trade t was an interdealer trade. • Set Qt to 0 for interdealer trades. • Let dt be the unknown interdealer price impact.

  29. Let Cost Vary with Size • An average response function plus a random error.

  30. Bond Transaction Returns • Log price change between trades tand s produces a regression equation. (The trades need not be in order.)

  31. Model Value Returns • Bond value returns have drift, common, and idiosyncratic components. • Random in bond-specific value.

  32. The Cost Function • Municipal bonds: • Corporate bonds:

  33. The Regression Model Combining terms gives

  34. The Error Term has variance where Dts =0, 1, or 2 counts the interdealer trades among trades t and s.

  35. Estimation Strategy • Estimate the model without the indices for each bond. • Adjust prices to remove trade costs. • Use repeat sales methods to compute the indices. • Involves weighted regressions. • Re-estimate the model with the indices.

  36. Weighted Least Squares • Estimate the model with OLS for each bond. • Use pooled constrained WLS to regress the squared residuals on independent variables to estimate the variance components. • Re-estimate the model with WLS. • Iterate until convergence.

  37. Cost Estimates • Estimated cost for a given size is • The estimate error variance is

  38. Mean Cost Estimates • Compute weighted means across bonds. For weights, use estimates of the precision of the cost estimate (inverse estimator error variance). • The data thus tell us where the information is.

  39. Results

  40. Mean Estimated Municipal Transaction Costs (Figure 1)

  41. Mean Estimated Corporate Transaction Costs (Figure 1)

  42. Alternative Cost Functions(Municipal Figure 2)

  43. By Trading Activity (Muni’s)

  44. By Trading Activity (Corp’s)

  45. By Credit Quality (Muni’s)

  46. By Credit Quality (Corp’s)

  47. By Issue Size (Muni’s)

  48. By Issue Size (Corp’s)

  49. By Bond Complexity (Muni’s)

  50. By Time Since Issuance (Muni’s)

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