P s =(0,W 0 R) safe; P r =(W 0 σ,w 0 µ) risky; Beyond P r possible if leveraged borrowing OK Objective function Mean a (Std.Dev.

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1 ECO 305 FALL 2003 December 2 ORTFOLIO CHOICE One Riskless, One Risky Asset Safe asset: gross return rate R (1 plus interest rate) Risky asset: random gross return rate r Mean µ = E[r] >R,Varianceσ 2 = V[r] Initial wealth W 0.Ifxin risky asset, final wealth W =(W 0 x) R + xr = RW 0 +(r R) x E[W ] = W 0 R + x (µ R) V[W ] = x 2 σ 2 ; Std. Dev. = x σ As x varies, straight line in (Mean,Std.Dev.) figure. expected wealth * r s standard deviation s =(0,W 0 R) safe; r =(W 0 σ,w 0 µ) risky; Beyond r possible if leveraged borrowing OK Objective function Mean a (Std.Dev.) 2 ;so optimal 1

2 Two Risky Assets W 0 =1; Random gross return rates r 1, r 2 Means µ 1 >µ 2 ;Std.Devs.σ 1, σ 2, Correl. Coefft. ρ ortfolio (x, 1 x). FinalW = xr 1 +(1 x) r 2 E[W ]=xµ 1 +(1 x) µ 2 = µ 2 + x (µ 1 µ 2 ) V[W ]=x 2 (σ 1 ) 2 +(1 x) 2 (σ 2 ) 2 +2x (1 x) ρσ 1 σ 2 =(σ 2 ) 2 2 x σ 2 (σ 2 ρσ 1 )+x 2 [(σ 1 ) 2 2 ρσ 1 σ 2 +(σ 2 ) 2 ] expected wealth * 1 m 2 standard deviation Diversification can reduce variance if ρ < min [σ 1 /σ 2, σ 2 /σ 1 ] 1, 2 points for the two individual assets m minimum-variance portfolio ortion 2 m dominated; m 1 efficient frontier Continuation past 1 if short sales of 2 OK Optimum when preferences as shown 2

3 One Riskless, Two Risky Assets First combine two riskies; then mix with riskless expected wealth * F 1 r s h m 2 standard deviation This gets all points like h on all lines like s r Efficient frontier s F tangential to risky combination curve Then along curve segment F 1 if no leveraged borrowing; continue straight line s F if leveraged borrowing OK With preferences as shown, optimum mixes safe asset with particular risky combination F Mutual fund F is the same for all investors regardless of risk-aversion (so long as optimum in s F ) Even less risk-averse people may go beyond F including corner solution at 1 or tangency past 1 if can sell 2 short to buy more 1 3

4 CAITAL ASSET RICING MODEL Individual investors take the rates of return as given but these must be determined in equilibrium Add supply side firms issue equities Take production, profit-max as exogenous Two firms, profits Π 1 and Π 2.MeansE[Π 1 ],E[Π 2 ]; Variances V[Π 1 ],V[Π 2 ]; Covariance Cov[Π 1, Π 2 ] Safe asset (government bond) sure gross return rate R Market values of firms F 1, F 2 ; to be solved for (endogenous) (Random) rates of return r 1 = Π 1 /F 1 and r 2 = Π 2 /F 2, and for whole market, r m =(Π 1 + Π 2 )/(F 1 + F 2 ) After a lot of algebra, important results: (1) E[r 1 ] R = Cov[r 1,r m ] { E[r m ] R } V[r m ] Risk premium on firm-1 stock depends on its systematic risk (correlation with whole market) only, not idiosyncratic risk (part uncorrelated with market) Coefficient is beta of firm-1 stock (2) F 1 = E[Π 1] A Cov[Π 1, Π 1 + Π 2 ] R where A is the market s aggregate risk-aversion (usually small) Value of firm = present value of its profits adjusted for systematic risk, and discounted at riskless rate of interest 4

5 ROCKET-SCIENCE FINANCE Equity, debt etc - complex pattern of payoffs in different scenarios: vector S =(S 1,S 2,...) Owning security S is full equivalent to owning portfolio of Arrow-Debreu securities (ADS): S 1 of ADS 1, S 2 of ADS 2,... In equilibrium, no riskless arbitrage profit available So relation bet. price S of S and ADS prices p i : S = S 1 p 1 + S 2 p Converse example: Two scenarios, two firms s shares payoff MicTel (M 1,M 2 ),BioWiz(B 1,B 2 ). If X M of MicTel + X B of BioWiz 1ofADS 1, X M M 1 + X B B 1 =1, X M M 2 + X B B 2 =0 B 2 M 2 X M =, X B = M 1 B 2 B 1 M 2 M 1 B 2 B 1 M 2 One of these may be negative: need short sales 5

6 ADS s can be constructed from available securities Then no-arbitrage-in-equilibrium condition: 1 = X M MicTel + X B BioWiz Similarly 2. So the constructed ADS s can be priced. Every financial asset is defined by its vector of payoffs in all scenarios. Therefore it can be priced using these prices of all ADS s ( pricing kernel ) Examples options and other derivatives General idea: Markets for risks are complete, and achieve areto-efficient allocation of risks if enough securities exist that their payoff vectors span the space of wealths in all scenarios Rocket-science finance extends this idea to infinite-dimensional spaces of scenarios If sequence of periods, need enough markets to span the scenarios one-period ahead, and then rebalance portfolio by trade (dynamic hedging) Finance = General equilibrium + Linear algebra! Recent research: (1) Asset pricing with incomplete markets (2) Strategic trading with / against asymmetric info 6