Delegated portfolio management and optimal allocation of portfolio managers

2015 ◽  
Vol 47 (21) ◽  
pp. 2142-2153 ◽  
Author(s):  
Michael Christensen ◽  
Michael Vangsgaard Christensen ◽  
Ken Gamskjaer
2011 ◽  
Vol 01 (02) ◽  
pp. 265-292 ◽  
Author(s):  
Ernst Maug ◽  
Narayan Naik

This paper investigates the effect of fund managers' performance evaluation on their asset allocation decisions. We derive optimal contracts for delegated portfolio management and show that they always contain relative performance elements. We then show that this biases fund managers to deviate from return-maximizing portfolio allocations and follow those of their benchmark (herding). In many cases, the trustees of the fund who employ the fund manager prefer such a policy. We also show that fund managers in some situations ignore their own superior information and "go with the flow" in order to reduce deviations from their benchmark. We conclude that incentive provisions for portfolio managers are an important factor in their asset allocation decisions.


2016 ◽  
Vol 1 (1) ◽  
pp. 20
Author(s):  
Elli Kraizberg

<p dir="LTR">In many countries around the globe, portfolio managers utilize well accepted models, assuming that a partial stake of ownership is proportionally valued. This assumption is incorrect  in markets in which traded firms or publicly held firms are controlled by major owners who would take any possible measure to protect and maintain a 'lock' on control, so they can secure a sellable asset to another control seeker. In this case, estimation of key parameters such as, volatility, expected returns and diversification effect, may be grossly distorted.</p><p dir="LTR">We would argue that a major trigger for the value of the benefits of control is the ability of control owners to transfer assets from their own portfolio to a controlled publicly traded firm. While it is obvious that these transfers will take place, if and only if, it is beneficial to the control owners, the impact on the minor shareholders may not necessarily be negative and may vary depending on several parameters. Thus, the benefits of control are not entirely "private", i.e. appropriation and diversion of the resources of publicly traded firms for the benefit of the control owners.     </p><p dir="LTR">This paper aims to model the effect of the benefits of control on the value of a minority held public firms. It focuses on two related issues that are discussed in the literature on the benefits of control: what drives the value of the benefits of control, given the   empirical evidence that control seekers are willing to pay a significant premium for control, and secondly, can these benefits be rationally modeled? To better understand these issues, it then models a specific drive on the part of control seekers who, in addition to their stake in a publicly traded firm, own a private portfolio. It could be argued that they may 'transfer' inferior investments to the public firms that they control exploiting less than perfect transparency. However, while they own this valuable option of 'transferring' inferior investments into the public firm, these actions may still be beneficial to the minority shareholders.</p><p dir="LTR">We establish a model and derive a simulation procedure that are applied to several cases in which transfers  are made in exchange for cash or equity, instances of full disclosure or partial transparency, the likelihood that the control owners' actions will be contested in court, level of risk, and other parameters. Then we will compare the results to empirical finding.  The final model will be greatly simplified so that the end formula can be easily used by practitioners. </p>


2019 ◽  
Vol 53 (1) ◽  
pp. 1-28
Author(s):  
Michael Dziecichowicz ◽  
Aurélie C. Thiele

We propose an approach to portfolio management over a finite time horizon that (i) does not require the precise knowledge of the underlying probability distributions, instead relying on range forecasts for the stock returns, and (ii) allows the fund manager to capture the degree of the investor’s risk aversion through a single, intuitive parameter called the budget of uncertainty. This budget represents the worst-case number of time periods with poor performance that the investor is willing to plan for. An application of this setting is target-date funds for pension fund management. We describe an efficient procedure to compute the dynamic allocation between (riskless) bonds and (riskier) stocks at each time period, and we illustrate the risk-to-time-horizon tradeoff on optimal allocation tables, which can easily be provided to fund participants to help them select their strategy. The proposed approach refines rules implemented by practitioners and provides an intuitive framework to incorporate risk in applications with end of horizon effects. In contrast with existing literature providing robust fund management approaches to mathematically sophisticated finance professionals, our goal is to provide a simple framework for less quantitative fund participants who seek to understand how stock return uncertainty and planned retirement date affect the optimal stock-vs-bond allocation in their portfolio. We extend our procedure to the case when the investor’s wealth is penalized for falling short of performance benchmarks across the time horizon. We also discuss the case where the manager can invest in multiple stocks. Numerical results are provided.


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