wenhao li graduate school of business, stanford jonathan wallen

Intermediary Funding Costs and Short-Term Risk Premia Wenhao Li Graduate School of Business, Stanford Jonathan Wallen Graduate School of Business, Stanford Introduction Model Data and Measurements Conclusion • Test Prediction 1: Risk Premia Empirical Results • Research question: How are short-term risk premia priced? • Evidence: Across three asset classes, including equities, bonds, and currencies, short-term risk premia (return reversals) increase with intermediary leverage and asset idiosyncratic risk. • Summary: Funding costs ⇒ Short-term risk premia ! Expected Change Day 0 Price − FundamentalValue 0 Increase in idiosyncratic volatility 1 2 3 4 5 Increase in leverage Liquid Shock Intermediary leverage reflects funding costs. Model Predictions 1. Short-term risk premia increase with leverage and idiosyncratic risks. – Intuition: borrowing costs are higher for riskier intermediaries and riskier positions ⇒ greater price impact 2. All else equal, intermediaries with higher leverage participate less in market making. 3. Market wide risk sharing: when one intermediary experiences a capital shock, another steps in. 4. Upward sloping supply curve of market making with respect to leverage. • Across markets, intermediaries earn short-term risk premia of 50 to 80 basis points. • Short-term risk premia increase by about 37 bps for bonds and 103 bps for equities when intermediary leverage is high. • Risk premia increase by 67-100 bps across three asset classes when idiosyncratic risk is high. • Intermediaries pull back from market making activities after a capital shock, but increase trading when other intermediaries are shocked. • Due to capacity limits, the supply of market making is upward sloping with respect to leverage. Price data • Corporate bond (2002-2015) from TRACE. • S&P500 equities (1990-2015) from CRSP. • Currencies (1990-2015) from Bloomberg. • FISD bond data (1994-2014). Dealer identity revealed. Intermediary balance sheet data • Merged CRSP-Compustat Measurements • Idiosyncratic risks: Residual variance of asset returns, with a three-month rolling window. • Leverage: (Aggregate/Individual) market leverage • Risk Premia = Δ %,’→’)* / ’ , subsequent 5-day return after a liquidity shock. Risk-Neutral Investors Risk-Neutral Intermediaries ℓ Leverage Holding ! Search Buyers " # Competitive and Centralized Funding Market Liquidity Shock ! Search Buyers Empirical Results • Risk Premia, Idiosyncratic Risks, and Leverage Sell shocks push trading price below fundamental value, and the magnitude depends on leverage and idiosyncratic volatility. Data of Equities The three lines are highly correlated Unit: bps Regressions (1) (3) (5) in use the full sample, while (2) (4) (6) exclude crisis. Errors are clustered by year-asset. Year and asset fixed-effects are controlled. Increase in risk premia when idio-risk is high Increase in risk premia when leverage is high • Test Prediction 2: Leverage and Market Making Activity Regressions (1) (3) (5) in use the full sample, while (2) (4) (6) exclude crisis. Errors are clustered by year-asset in (1) and (2), by year in (3)-(6). Year fixed effects are included. Intermediary level data Data aggregated by intermediary Consistently negative (FISD Data) • Test Prediction 3: Competition • Test Prediction 4: Upward Sloping Supply Curve Regressions (1) (3) (5) in use the full sample, while (2) (4) (6) exclude crisis. Errors are clustered by year. Intermediary fixed effects are included. Dollar volume High leverage intermediaries respond 7 times more than low leverage intermediaries to changes in demand shock, as shown in • Leverage Distribution and Idiosyncratic Volatility Market Leverage Year Idiosyncratic Volatility Heterogeneity in idiosyncratic volatility Systematic volatility is small compared to idiosyncratic volatility Average leverage ≈ 7

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Intermediary Funding Costs and Short-Term Risk PremiaWenhao Li

Graduate School of Business, Stanford

Jonathan Wallen

Graduate School of Business, Stanford

Introduction

Model

Data and Measurements

Conclusion

• TestPrediction1:RiskPremia

Empirical Results• Researchquestion:Howareshort-termriskpremiapriced?• Evidence:Acrossthreeassetclasses,includingequities,bonds,andcurrencies,short-termriskpremia(returnreversals)increasewithintermediaryleverageandassetidiosyncraticrisk.• Summary:Fundingcosts⇒ Short-termriskpremia

ExpectedChange

Day0

Price− FundamentalValue

Increaseinidiosyncraticvolatility

1 2 3 4 5

Increasein leverage

LiquidShock

Intermediaryleverage reflectsfundingcosts.

ModelPredictions1. Short-termriskpremiaincreasewithleverageand

idiosyncraticrisks.– Intuition:borrowingcostsarehigherforriskier

intermediariesandriskierpositions⇒ greaterpriceimpact

2. Allelseequal,intermediarieswithhigherleverageparticipatelessinmarketmaking.

3. Marketwiderisksharing:whenoneintermediaryexperiencesacapitalshock,anotherstepsin.

4. Upwardslopingsupplycurveofmarketmakingwithrespecttoleverage.

• Acrossmarkets,intermediariesearnshort-termriskpremiaof50to80basispoints.• Short-termriskpremiaincreasebyabout37bpsforbondsand103bpsforequitieswhenintermediaryleverageishigh.• Riskpremiaincreaseby67-100bpsacrossthreeassetclasseswhenidiosyncraticriskishigh.• Intermediariespullbackfrommarketmakingactivitiesafteracapitalshock,butincreasetradingwhenotherintermediariesareshocked.• Duetocapacitylimits,thesupplyofmarketmakingisupwardslopingwithrespecttoleverage.

Pricedata• Corporatebond(2002-2015)fromTRACE.• S&P500equities(1990-2015)fromCRSP.• Currencies(1990-2015)fromBloomberg.• FISDbonddata(1994-2014).Dealeridentityrevealed.Intermediarybalancesheetdata• MergedCRSP-CompustatMeasurements• Idiosyncraticrisks:Residualvarianceofassetreturns,withathree-monthrollingwindow.• Leverage:(Aggregate/Individual)marketleverage• RiskPremia= Δ𝑃%,'→')*/𝑃',subsequent5-dayreturnafteraliquidityshock.

Risk-NeutralInvestors

Risk-NeutralIntermediaries

ℓ

Leverage

Holding!

SearchBuyers"#

CompetitiveandCentralizedFundingMarket

LiquidityShock! SearchBuyers

Empirical Results• RiskPremia,IdiosyncraticRisks,andLeverage

Sellshockspushtradingpricebelowfundamentalvalue,andthemagnitudedependsonleverageandidiosyncraticvolatility.

DataofEquities

Thethreelinesarehighly

correlated

Unit:bps

Regressions(1)(3)(5)inusethefullsample,while(2)(4)(6)excludecrisis.Errorsareclusteredbyyear-asset.Yearandassetfixed-effectsarecontrolled.

Increaseinriskpremiawhenidio-riskishigh

Increaseinriskpremiawhenleverageishigh

• TestPrediction2:LeverageandMarketMakingActivity

Regressions(1)(3)(5)inusethefullsample,while(2)(4)(6)excludecrisis.Errorsareclusteredbyyear-assetin(1)and(2),byyearin(3)-(6).Yearfixedeffectsareincluded.

Intermediaryleveldata

Dataaggregatedbyintermediary

Consistentlynegative

(FISDData)

• TestPrediction3:Competition

• TestPrediction4:UpwardSlopingSupplyCurve

Regressions(1)(3)(5)inusethefullsample,while(2)(4)(6)excludecrisis.Errorsareclusteredbyyear.Intermediaryfixedeffectsareincluded.

Dollarvolume

Highleverageintermediariesrespond7timesmorethanlowleverageintermediariestochangesindemandshock,asshownin

• LeverageDistributionandIdiosyncraticVolatility

MarketLeverage

Year