Total Portfolio Research Articles

A renewal theoretic result in portfolio theory under transaction costs with multiple risky assets

Abstract We consider a portfolio optimization problem in a Black-Scholes model with n stocks, in which an investor faces both fixed and proportional transaction costs. The performance of an investment strategy is measured by the average return of the corresponding portfolio over an infinite time horizon. At first, we derive a representation of the portfolio value process which only depends on the relative fractions of the total portfolio value that the investor holds in the different stocks. This representation allows us to consider these so-called risky fractions as the decision variables of the investor. We show a certain kind of stationarity (Harris recurrence) for a quite flexible class of strategies (constant boundary strategies). Then, using renewal theoretic methods, we are able to describe the asymptotic return by the behaviour of the risky fractions in a “typical” period between two trades. Our results generalize those of [irl1], who considered a financial market model with one bond and one stock, to a market with a finite number n>1 of stocks.

Managing Pension Liability Credit Risk: Maintaining a Total Portfolio Perspective

Widening corporate bond spreads have caused a dislocation between corporate-bond-based pension discount rates and the rates of commonly used interest rate hedging tools. As a result, widening spreads have brought the issue of how to manage liability credit risk to the forefront for plan sponsors. Whereas managing liability interest rate risk via interest rate swaps and/or Treasuries is relatively straightforward, managing liability credit risk is more challenging for three reasons: 1) the credit component of liability returns are not investable, 2) no capital-efficient risk management tool exists to hedge liability credit risk, and 3) the connection between credit spreads and the returns of common risky assets (i.e., equities) is relatively reliable, especially during periods of economic stress when the values of risky assets typically fall as credit spreads widen. In order to construct efficient liability-driven solutions and avoid poor funding ratio outcomes, it is thus essential to view liability credit spread risk from a total portfolio perspective inclusive of risky assets. Meder recommends that, from a long-term policy perspective, plan sponsors should generally avoid credit risk in the liability hedge. From a tactical perspective, however, adding credit risk to the liability hedge when credit spreads are wide and expected to narrow can improve funding ratio outcomes, but the amount of credit risk taken must be appropriately scaled to the total portfolio.

Comparison of different copula assumptions and their application in portfolio construction

The paper deals with modeling of mutual dependencies among financial assets. Its aim is to investigate the impact of different copula assumptions on optimal portfolios, when CVaR optimization is used. Strategic asset allocation perspective is supposed. It is demonstrated that copula functions enable us to separate the modeling of dependency features of financial assets from the modeling of marginal distribution characteristics, in the context of practical portfolio construction tasks. The difference between portfolios constructed using normal copula and student t copula is shown when mutual or pension fund exposed to long-only constrain is assumed. The fund is considered to invest solely into equity and fixed-income instruments. As expected, the exclusive use of linear correlation coefficients leads to underestimation of total portfolio risk. The superiority of student t copula portfolios intensifies as the confidence level of CVaR rises and/or as the CVaR target increases.

Portfolio Construction and Uncertainty

Traditional mean variance optimization assumes that future returns and covariances of all the assets in the universe are known exactly. In practice, these input parameters are subject to estimation errors that may render the output of the optimization algorithm essentially useless. Here we present three alternative ways to deal with parameter uncertainty when constructing optimal portfolio allocations. The portfolio resampling is a heuristic method to achieve less concentrated portfolios that deliver stable results out-of-sample. Bayesian estimators provide a mathematical framework to update prior beliefs with estimation uncertainty to derive more stable portfolios. The naive equal weighted portfolio assumes that there is no knowledge about the future. We show that these portfolios outperform the traditional mean variance efficient portfolios and recommend using such techniques or a combination of these techniques to construct passive investment benchmarks. Furthermore we recommend using a more active approach to portfolio investing in order to profit from the generally smaller estimation errors of near term forecasts than long term forecasts. This approach results in allocating more than half the total portfolio risk to tactical asset allocation. At the same time the freedom of the active manager needs to be controlled by an asymmetric tracking error resulting in asymmetric payoff structures through active management.

Portfolio Risk Consequences of Fixed-Income Exposures

Interest rate and credit exposures can have quite different consequences for risk when viewed from a total portfolio perspective and from the perspective of a fixed-income portfolio in isolation. Within a fixed-income portfolio, interest rate exposure enhances volatility, whereas credit exposure can play a diversifying role. Conversely, at the total portfolio level, credit exposure tends to augment risk, while interest rate exposure may impact only modestly, or possibly even reduce, overall portfolio volatility. This dichotomy can give rise to agency problems when management of fixed-income portfolios is delegated. The author suggests various approaches for designing fixed-income mandates to better align them with investor objectives.

Risk contributions, information and reverse stress testing

In this paper we describe methods of decomposing risk into subcomponents such as contributing instruments, subportfolios or underlying risk factors e.g., equity, foreign exchange, economy-wide systematic and interest rate risk factors. The Euler allocation principle for allocation of instrument and subportfolio risk contributions to the total portfolio risk is widely applied in practice for portfolio managers risk budgeting and economic capital allocations. However, the decomposition of risk factors into summable contributions is in general not possible and we describe a non-parametric method of extracting relative information of risk factors that is valid for general non-linear portfolios. The measure is based on the Kullback information theory and while it does not constitute a decomposition it can be used to judge the relative importance of risk factors in determining profit and loss. The measure is also useful for understanding the relevance of so-called reverse stress tests where a certain loss level is identified with certain risk factor values. The use of the information measure is illustrated with an application to a portfolio of derivatives.

The Efficiency of Greek Public Pension Fund Portfolios

Greek public pension funds can invest up to 23% into risky assets and are not allowed to invest outside Greece. This paper seeks to investigate the costs of investment constraints on pension fund portfolios. In particular we try to quantify the losses that portfolios suffer due to under-diversification and sub-optimal asset allocation. We find that the high concentration of Greek equity portfolios imposes a substantial return and utility loss which is further increased when the lack of international diversification is taken into account. Restricting the weight of equities to 23% of the total portfolio, leads to sub-optimal asset allocation that costs as much as 2% (3%) per annum compared to a balanced domestic (global) benchmark.

A Multi-Portfolio Model for Bespoke CDO Pricing Part I: Methodology

This paper presents a dynamic multi-portfolio default model for consistent and arbitrage-free pricing synthetic CDO tranches that reference a bespoke portfolio. In order to incorporate standard tranche price information, we assume that the bespoke portfolio has name overlapping with some index portfolios.Dividing the total portfolio (parent) into non-overlapping sub-portfolios (children), and assuming homogeneity for both the parent and the children, we use a top-down dynamic default intensity model for the parent, and specify the conditional probability of default in the children given imminent default in the parent. We consider two fundamental cases which are building blocks of more complex applications: (a) the parent is an index and the bespoke is a child; and (b) the bespoke is the parent that contains one or more indices as children.When the parent is the index, the parent default process is uniquely determined independent of the children, and the child conditional default probability distribution is calibrated to the spreads of the children. When the bespoke is the parent and one or more children are indexes, we simultaneously calibrate the parent default intensity model and the child default probability to the standard tranches and child portfolio spreads. The model is designed to establish consistency between the pricing of standard tranches and the pricing of bespoke tranches. Application may include:• Portfolio enlargement where the bespoke tranche references a “global” portfolio that contains “regional” indexes as sub-portfolio. For example, tranches referencing CDX.NA.IG and iTraxx Europe.• Portfolio thinning where the bespoke tranche references a sub-portfolio of an index.• Combination of portfolio enlargement and thinning. For example, tranche referencing a subset of CDX and a subset of iTraxx.

Optimization Model of Incremental Loan Portfolio based on Risks Overlap of Incremental and Existing Portfolio

Abstract This paper establishes the non-linear functional relationship of risk overlap of incremental and existing portfolios. The decision-making model for incremental loan portfolio is based on how total loan portfolio optimization is built. The contributions and characteristics lie in three aspects. The first contribution is to put forward the scientific problem of controlling total portfolio risk based on risk overlapping of incremental and existing portfolios while putting out an incremental portfolio. The whole control of incremental and existing portfolios is the top issue, which not only exploits new idea about optimal allocation and control of financial assets but also alters traditional idea merely considering the risk of incremental portfolios. The second contribution is to establish the non-linear function relation of overlap between incremental and existing portfolios. Based on the theory of non-linear overlap of total portfolio, the function expression connecting total portfolio with incremental and existing portfolios is built. The third contribution is the controlling of total risk after overlapping between the existing and incremental portfolios risk. It solves the problem of how to control and optimize total portfolio risk while allocating an incremental portfolio.

International Diversification Strategies for Direct Real Estate

This paper will disentangle the performance of international real estate into property type performance and region selection. This helps to create an international diversification strategy for direct real estate. We use constrained cross-section regression with dummy variables for regions and property types to measure the best risk reducer. We analyze the impact of currency changes on total returns by looking at a hedged and un-hedged portfolio, both stock and equally weighted. The findings show that geographic factors have the largest influence on the volatility of international real estate returns. The average variance of the regional effects is higher than the property type effects and therefore the regional effects have a higher influence on the variation of the total portfolio. However, the regional effects are less stable through time, compared with the variance and correlation of the property type effects. Also the property type effect seems to become a more important factor for the return over time, especially when the return is expressed in local currency.

Trading Dynamics in the Foreign Exchange Market: A Latent Factor Panel Intensity Approach

We develop a panel intensity framework for the analysis of complex trading activity datasets containing detailed information on individual trading actions in different securities for a set of investors. A feature of the model is the presence of a time varying latent factor, which captures the influence of unobserved time effects and allows for correlation across individuals. We show how to estimate the model parameters using a simulated maximum likelihood technique adopting the efficient importance sampling approach of Richard & Zhang (2007).Apart from the innovative methodology enabling detailed characterization of a complex dynamic trading process, we contribute to the literature on behavioral finance by providing new results on behavioral biases such as the disposition effect and investor overconfidence. These new insights are made possible by the joint characterization of not only the decision to close (exit) a position, usually considered in isolation in the behavioral finance literature, but also the decision to open (enter) a position, which together describe the trading process in its entirety. While the disposition effect is defined with respect to the willingness to realize profits/losses with respect to the performance of the position under consideration, we find that the performance of the total portfolio of positions is an additional factor influencing trading decisions and can reinforce or dampen the standard disposition effect. Moreover, the proposed methodology allows the investigation of the severity of various behavioral biases for different groups of investors ranging from small retail investors to professional and institutional investors.

Pursuing Genuinely Successful e-Government Projects: Mission Impossible?

Genuinely successful, high-yield e-government projects are still difficult to find and even more difficult to measure, even five years after Richard Heeks’ classic paper, “Most g-Government-for-Development Projects Fail” (1). Heeks claimed that 85% of e-government projects in developing countries don’t achieve promised goals, of which 35% are total failures, 50% are partial failures, and only 15% are successes. Soon thereafter, the World Bank reported that its sectoral based projects with information and communication technology (ICT) components had an “alarmingly high failure rate” with 50% suffering disputes and 80% requiring contract amendments (2). With a total ICT component portfolio estimated currently at US$7.3 billion and less than half of the projects rated “satisfactory” by the Bank’s own evaluation system, it would seem that many ICT projects can waste precious resources that could be devoted to competing development needs. Our best guess is that things have not improved for two reasons. First, today’s e-government systems are increasingly dependent upon inter-agency cooperation. “Agency-centric,” or “silo” approaches to systems reform, and “supply and install” projects seldom work. For example, vehicle licensing systems often require the interoperation and cross-agency cooperation of transport, tax, and finance systems, perhaps with links to private sector financial institutions, insurance, motor agencies and the police. Second, many projects depend on trade facilitation systems that involve interoperation between customs and traders for all government agencies and permit-issuing authorities, border control, airports etc. In some countries there may be over 20 agencies involved in permit-issuing and over 30 stakeholder systems involved in implementing an ICT-based “single window” trade facilitation initiative. Increasingly, e-government projects are bumping up against technology policy issues that need to be addressed at the national level. For instance, interoperability policies often need to be addressed in order for proprietary systems at local and national level government units to “talk to each other.” Secondly, e-government boils down to people using computer-aided business systems in ways that make government more accessible, effective and accountable. Every stakeholder eventually asks either “What’s in it for me?” or “Why should I be involved in this e-government project?” In this article we present three examples of successful e-government deployments that have succeeded because they have addressed policy issues upfront and/or can easily answer the crucial cui bono question. The three cases include: Nangi Village Wireless Outreach (Nepal), Nemmadi, (Karnataka, India), and MK Connects (Macedonia).

Stress Testing German Banks in a Downturn in the Automobile Industry

In this paper we stress-test credit portfolios of 28 German banks based on a Mertontype multi-factor credit risk model. The ad-hoc stress scenario is an economic downturn in the automobile industry that constitutes an exceptional but plausible event suggested by historical data. Rather than on a particular stress forecast, the focus of the paper is on the main drivers of the stress impact on banks' credit portfolios. Although the percentage of loans in the automobile sector is relatively low for all banks in the sample, the expected loss conditional on the stress event increases substantially by 70%-80% for the total portfolio. This result confirms the need to account for hidden sectoral concentration risk because the increase in expected loss is driven mainly by correlation effects with related industry sectors. Therefore, credit risk dependencies between sectors have to be adequately captured even if the trigger event is confined to a single sector. Finally, we calculate the impact on banks' own funds ratios. The main results are robust against various robustness checks, namely those concerning the granularity of the credit portfolio, the level of inter-sector asset correlations, and a cross-sectional variation of intra-sector asset correlations.

AN ANALYSIS OF MUTUAL FUND PERFORMANCE, BY APPLYING Z-SCORE

Selecting a mutual fund is not an easy task as there are nearly 38Asset Management companies (AMC) offering many funds. The first step for investors is decided has how to select a fund. With the 38 active players the mutual fund industry has mopped up nearly $8 billion through equity mutual fund schemes alone. This is due to the attributes of the indifferent performance player in the equity market. As an investor we wants a return on our investment, most investors tend to evaluate fund performance on a short-term basis. There is a need to educate investor about risk-adjusted return and also the total portfolio return. The key to investors return will be the funds ability to outperform the benchmark index on a consistent basis without taking lot of risks. Here's I prepared a blueprint for a structured approach to fund selection that is Z-Score. It is used on the based on the statistics on the group with smaller sample size, which means that almost surely stocks with better trailing 12 months performance experience higher net % change in number of shares, higher net raw change in number of shares, and higher net individual weight change compare to the worst performing stocks.

Linking Reduced Deforestation and a Global Carbon Market: Impacts on Costs, Financial Flows, and Technological Innovation

Discussions over tropical deforestation are currently at the forefront of climate change policy negotiations at national, regional, and international levels. This paper analyzes the effects of linking Reduced Emissions from Deforestation and Forest Degradation (REDD) to a global market for greenhouse gas emission reductions. We supplement a global climate-energy-economy model with alternative cost estimates for reducing deforestation emissions in order to examine a global program for stabilizing greenhouse gas concentrations at 550 ppmv of CO2 equivalent. Introducing REDD reduces global forestry emissions through 2050 by 20-22% in the Brazil-only case and by 64-88% in the global REDD scenarios. At the same time, REDD lowers the total costs of the climate policy by an estimated 10-25% depending on which tropical countries participate and whether the “banking” of excess credits for use in future periods is allowed. As a result, REDD could enable additional reductions of at least 20 ppmv of CO2-equivalent concentrations with no added costs compared to an energy-sector only policy. The cost savings from REDD are magnified if banking is allowed and there is a need to increase the stringency of global climate policy in the future in response, for example, to new scientific information. Results also indicate that REDD decreases carbon prices in 2050 by 8-23% with banking and 11-26% without banking. While developing regions, particularly Latin America, gain the value of REDD opportunities, the decrease in the carbon price keeps the value of international carbon market flows relatively stable despite an increase in volumes transacted. We also estimate that REDD generally reduces the total portfolio of investments and research and development of new energy technologies by 1-10%. However, due to impacts on the relative prices of different fossil fuels, REDD has a slight positive estimated effect on investments in coal-related technologies (IGCC and CCS) as well as, in some cases, non-electric energy R&D. This research confirms that integrating REDD into global carbon markets can provide powerful incentives for the preservation of tropical forests while lowering the costs of global climate change protection and providing valuable policy flexibility.

Decentralized Downside Risk Management

The process of risk management for institutional investors faces two challenges. First, since most institutions are decentralized as opposed to being direct investors in assets, it is difficult to separate the risks of the assets in the portfolio from the risks generated by the investment decisions by the fund management to construct the portfolio. To address this issue, we propose a risk measurement methodology which calculates the risk contributions of individual securities and investment decisions simultaneously. This decomposition is applicable to any decentralized investor as long as its relevant risk measurement statistic can be additively decomposed. Second, statistics used to measure risk may not coincide with institution-specific investment risks, in the sense that the utility employed in asset allocation may be unrelated to the risk measure utilized. For example, an institution may do mean-variance asset allocation, but inconsistently measure the risk of the portfolio using Value at Risk. We apply this methodology to a particular type of decentralized investor, specifically, endowment funds where the relevant risk statistic is the downside risk of returns relative to actual payout levels, plus inflation. We show how downside risk can be decomposed and apply our simultaneous downside risk decomposition empirically on a sample of U.S. endowment funds. We find that an endowment's asset allocation to U.S. Equity, consistent with having the largest weight in the average endowment portfolio, generates about 50% of total endowment returns but almost 100% of total portfolio downside risk. We further find that tactical allocations (or timing) have economically small contributions to both returns and risk. Finally, we find that the allocations to U.S. Fixed Income and to Hedge Funds as well as active investment decisions (except for tactical) contribute positively to returns, while reducing portfolio downside risk. The risk contributions are sensitive to changes in payout levels and an increase in the latter may offset the risk reducing power of active investing.

Port and terminal selection by deep-sea container operators

This paper deals with the importance of port choice and container terminal selection for deep-sea container carriers. The paper focuses on the research question: on what basis do deep-sea container operators select container ports (strategy) and container terminals (financial reasons) in the Hamburg–Le Havre range over others? In answering this research question, three dimensions are addressed in detail: the buying decision characteristics; port choice strategy; and terminal selection. The results show that strategic considerations at company level are important. For port choice the most important criteria from a carrier's perspective are: availability of hinterland connections; reasonable tariffs; and immediacy of consumers (large hinterland). In addition to these criteria, shipping lines attach great value to often neglected factors, such as feeder connectivity, environmental issues and the total portfolio of the port. The study reveals that port selection and terminal selection are not the same with terminal selection criteria mainly depending on: handling speed; handling costs; reliability; and hinterland connections. The analysis also brought forward that the decision making is different per container carrier, per trade and per port type, implying that a one size fits all approach is not relevant.

Prologis

Abstract“Property, Real Estate & Development” (MIC: SIC: 6798 NAIC: 525930)ProLogis owns, manages and develops industrial distribution facilities. Co.'s business is organized into three segments: property operations, for direct ownership of distribution and retail properties; fund management, for investing management of property funds and the properties; and CDFS business, for development or acquisition of real estate properties. As of Dec 31 2007, Co.'s total portfolio of properties owned, managed and under development, including direct‐owned properties and properties owned by property funds and CDFS joint ventures, consisted of 2,773 properties aggregating 510.2 million square feet and serving 4,912 customers in 118 markets in North America, Europe and Asia.

Another Look at Portfolio Optimization under Tracking-Error Constraints

Today, the use of a benchmark portfolio is common practice in the financial management industry. This setup allows the investor to evaluate the added value in line with the risks undertaken. But the relevant concept of risk is relative risk as defined by tracking-error volatility. The problem of minimizing the volatility of tracking error was originally solved by Roll (1992). He noticed that the optimal portfolios obtained have several undesirable properties and then suggested introducing an additional constraint on the beta of the portfolio. More recently, Jorion (2003) elegantly tackled this problem again, pointing out that constant-TEV portfolios are described by an ellipse. He showed that because of the flat shape of this ellipse, adding a constraint on total portfolio volatility can substantially improve the performance of the managed portfolio. This paper looks at the problem from another angle. Instead of considering constant TEV frontiers as Jorion does, we allow tracking error to vary but we fix the risk aversion. It is shown that the resulting optimal portfolios have several desirable properties.

Prologis

Abstract“Property, Real Estate & Development” (MIC: SIC: 6798 NAIC: 525930)ProLogis owns, manages and develops industrial distribution facilities. Co.'s business is organized into three segments: property operations, for direct ownership of distribution and retail properties; fund management, for investing management of property funds and the properties; and CDFS business, for development or acquisition of real estate properties. As of Dec 31 2007, Co.'s total portfolio of properties owned, managed and under development, including direct‐owned properties and properties owned by property funds and CDFS joint ventures, consisted of 2,773 properties aggregating 510.2 million square feet and serving 4,912 customers in 118 markets in North America, Europe and Asia.