Asset Prices and Institutional Investors: Discussion

Transcription

1 Asset Prices and nstitutional nvestors: Discussion Suleyman Basak and Anna Pavlova Ralph S.J. Koijen University of Chicago and NBER June 2011 Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

2 Delegation and Asset Pricing Lot of asset pricing theory abstracts from delegation and decentralization Quite remarkable given how important agency theory is in nance and economics more broadly This paper argues that we may need to understand the interaction between delegation and asset pricing agree mportant and transparent paper, with hopefully many followers Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

3 Size of the Mutual Fund ndustry For instance, consider the size of the mutual fund industry relative to total market cap Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

4 Model: Endowments and Preferences Two agents endowed with initial wealth shares λ and 1 λ Agents di er in terms of their preferences/objective function Retail investors: nstitutional investors (a, b > 0): These preferences imply: u R (W T ) = log W T u (W T, T ) = (a + b T ) log W T u (W T, T ) / W T = a + b T W T, and hence increasing in the benchmark, T Same in other models of preferences, for instance: just a lot more tractable in GE! u (W T, T ) = 1 1 γ (W T / T ) 1 γ, Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

5 Model: Technology N assets of which M are included in the benchmark Log-normal dividends: dd jt = D jt h µ j dt + σ j dω t i, where the last asset of the market and the index are residuals The market and index have geometric dividends too: d t = t [µ dt + σ dω t ], dd MKT,t = D MKT,t [µ MKT dt + σ MKT dω t ] Useful trick to make the problem tractable Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

6 Main nsights and Mechanism 1 For stocks in the index: Stock values are higher Volatility higher and counter-cyclical Sharpe ratios lower and counter-cyclical Stocks tend to comove "excessively" and correlation varies over time 2 No e ect for non-index stocks 3 Credit markets play an important role =) Restricticting leverage may lower index values Main mechanism: Wealth shocks determine the relative weight on the two agents objective functions Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

7 Discussion 1 Wealth e ects play central role: What drives wealth e ects? 2 How does delegation a ect asset pricing? 1 Frequency 2 Performance measurement All comments should be interpreted as a wish list paper is great as it is! Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

8 Discussion: Wealth distribution n two-agent models, the wealth distribution among agents plays an important role n this case, we are interested in t /S t, where t is the size of the fund industry and S t is the size of the equity market Note: Size MF industry as a proxy for institutional investors Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

9 Discussion: Wealth distribution To understand empirical determinants, it may be useful to start from two budget constraints: 1 Size market: S t+1 = S t R S t+1 + E t+1, where Rt S is the market return and E t net issuances minus cash dividends 2 Size mutual fund industry: t+1 = t R t+1 + F t+1 where R t is the fund industry return and F t the net ow Follows long tradition in nance and macro Campbell and Shiller (1988), Lettau and Ludvigson (2001), Gourinchas and Rey (2007), Corsetti and Konstantinou (2011) Natural application to mutual fund industry Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

10 A Valuation Equation We are interested in an expression of m t Write: where V t = S t n logs: V t+1 = (V t + E t ) Rt+1 S = V t 1 + E t R V t+1, S t E t v t v t+1 = v t + ln 1 + E t + rt+1 S V t We do the same for the mutual fund industry m t+1 = m t + ln 1 + F t + r M t+1, t where M t = t F t Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

11 A Valuation Equation t then follows: or: (m t+1 v t+1 ) (m t v t ) = rt+1 rt+1 S + ln 1 + F t M t (m 2010 v 2010 ) (m 1980 v 1980 ) = 2010 rj rj S ln 1 + F j j=1981 Valuation e ect j=1980 M j Flow e ect ln 1 + E t, V t 2009 j=1980 ln 1 + E j V j Financing e ect Hence, we can measure the importance of the wealth e ect coming from three channels! Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

12 mplication of the Valuation Equation By taking conditional expectations, we m t v t has to predict either relative returns, future ows or net issuances: m t v t lim s! E t (m s v s ) = + s=0 E t ln 1 + F t+s M t+s s=0 E t ln Flow e ect 1 + E t+s V t+s Financing e ect E t r t+s rt+s S s=1 Valuation e ect Logic as in Cochrane (2008): PD has to predict returns or dividends, or both Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

13 Derivations: Valuation equation will use the accounting equation in this discussion to interpret the history between 1980 and 2010: (m 2010 v 2010 ) (m 1980 v 1980 ) = 2010 rj rj S log 1 + F j j=1981 Valuation e ect j=1980 M j Flow e ect 2009 j=1980 log 1 + E j V j Financing e ect This paper concentrates on the rst component Could be that all terms co-move, which would provide a broader interpretation of the model Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

14 A Valuation Equation: Empirical Results Decomposition of changes in m t v t in ln (1 + E t /V t ), ln (1 + F t /M t ), and rt rt S m v ln(1+e/v) ln(1+f/m) 0.05 r r S Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

15 A Valuation Equation: Empirical Results Average change ("Trend") E r r S = 0.6% E (F /M) = 5.6% E (E /V ) = 1.9% Standard deviation of changes ("Cycle") σ r r S = 1.5% σ (F /M) = 6.5% σ (E /V ) = 6.6% Contemporaneous correlations below 10% =) Caveat: For instance ows from past returns, so correlations require more work to be conclusive Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

16 Discussion: Frequency Perhaps the most striking feature of the wealth distribution is the secular trend Model implies trends in volatilities, Sharpe ratios, index values for index versus non-index stocks: Long-term decline in risk premia Long-term increase in volatility Di erential predictability What if all was unexpected? Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

17 Discussion: Performance measurement To measure the performance of fund managers, it is common practice to regress fund returns on a benchmark: r MF = α + βr BM + ε One can imagine two benchmarks now: Aggregate stock market ndex of the institutional investor Neither of them will give a zero alpha as: There is a two-factor structure now Risk prices move over time due to the share of fund managers changing =) Benchmarks are now endogenous d be interested in understanding the implications for performance measurement Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

18 Summary Great paper on a topic that deserves a lot more attention Closed-form solutions very helpful and this model is a "benchmark" going forward Wealth distribution plays an important role in many of these models use two budget constraints to quantify some of the forces that drive the wealth distribution The interaction with ows and the nancing decisions of rms may be particularly interesting directions to extend the model Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

19 Derivations: Dynamics Aggregate Market Start from the return de nition: This implies: This results in E t : R S t+1 = N tp t+1 + N t D t+1 N t P t S t+1 = S t R S t+1 + N t+1 P t+1 N t P t+1 N t D t+1 E t+1 = N t+1 P t+1 N t P t+1 Net issuances N t D t+1 Aggregate cash dividends Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

20 Derivations: Computing the Terms We observe: Aggregate market cap, S t Total return, Rt S Capital gain, Rt CG From the de nition of the total return and the market cap, we uncover: N t P t+1 + N t D t+1 = Rt+1N S t P t = Rt+1S S t The capital gain is de ned as P t+1 /P t, and hence: which implies: N t P t+1 = Rt CG N t P t = Rt CG S t, N t+1 P t+1 N t P t+1 Net issuances N t D t+1 Aggregate cash dividends = S t+1 R CG t S t, = R S t+1 Rt CG S t Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21

21 Derivations: Dynamics Mutual Fund ndustry We observe: Size mutual fund industry, t Net ow, F t+1 This directly implies the return as: R t+1 = ( t+1 F t+1 ) / t We then have: t+1 F t+1 = M t+1 = ( t F t + F t ) Rt+1 = (M t + F t ) Rt+1 = M t 1 + F t M t R t+1 Koijen (U. of Chicago and NBER) Asset Prices and nstitutional nvestors June / 21