This paper provides a dynamic rational expectations equilibrium model in which investors have heterogeneous information and investment opportunities. Informed investors privately receive advance information about future earnings that is unrelated to current earnings. In response to good advance information, stock prices increase and informed investors act as trend chasers, increasing their inve...

In this paper, we apply Markowitz’s approach of portfolio selection to government bond portfolios. As a main feature of our analysis, we use term structure models to estimate expected returns, return variances, and covariances of different bonds. Our empirical study for the German market shows that a small number of risky bonds is sufficient to reach very promising predicted risk-return profile...

In this companion paper to “Optimal Investment with Transaction Costs and Stochastic Volatility Part I: Infinite Horizon”, we give an accuracy proof for the finite time optimal investment and consumption problem under fast mean-reverting stochastic volatility of a joint asymptotic expansion in a time scale parameter and the small transaction cost. AMS subject classification 91G80, 60H30. JEL su...

Stochastic optimization identifies the asset allocation that minimizes the probability of exhausting the retirement portfolio, thereby minimizing risk, from unmanaged (constant) and optimally managed withdrawals over the retirement life span. Optimal equity compositions and minimized probabilities of prematurely exhausting the portfolio increase with higher withdrawal rates and earlier retireme...

Portfolio optimization inputs differ widely from their subsequent out-of-sample (OOS) values. As a result, optimized portfolios have 2 to 28 times more risk OOS than their ex-ante estimates suggest. I propose a simple solution to this problem: let the data speak for itself and pick, in real time, the correction that most reduces past OOS errors. The resulting optimized portfolios consistently o...

There exist two separate branches of finance that require advanced quantitative techniques: the "Q" area of derivatives pricing, whose task is to "extrapolate the present"; and the "P" area of quantitative risk and portfolio management, whose task is to "model the future". We briefly trace the history of these two branches of quantitative finance, highlighting their different goals and challeng...

The comparative statics of the optimal portfolios across individuals is carried out for a continuous-time complete market model, where the risky assets price process follows a joint geometric Brownian motion with time-dependent and deterministic coefficients. It turns out that the indirect utility functions inherit the order of risk aversion (in the Arrow-Pratt sense) from the von Neumann-Morge...

We consider a continuous time dynamic pension funding model in a defined benefit plan of an employment system. The benefits liabilities are random, given by a geometric Brownian process. Three different situations are studied regarding the investment decisions taken by the sponsoring employer: in the first, the fund is invested at a constant, risk-free rate of interest; in the second, the promo...

this research aims to use var as a risk measure to find the optimum portfolio in tehran stock exchange. in this research var which is calculated with parametric method by using the 15 daily returns of 100 companies from march 21, 2001 to november 22, 2007 was added to the markowitz model of portfolio optimization as additional constraint. by changing the accepted var and accepted confidence lev...

This paper analyses the portfolio problem of an investor maximizing the expected exponential utility of his terminal real wealth. The investor must cope with both a set of stochastic investment opportunities and a set of background risks. If the market is complete we are able to find an exact solution. If the market is incomplete, we suggest an approximated general solution. Contrary to other e...