Institutional Portfolio Managers Research Articles

Buy, Sell or Hold? The Information in Institutional Real Estate Investor Consensus

We investigate whether the consensus of institutional investors to buy, sell, or hold a particular property type in a particular quarter can improve the information environment in commercial real estate markets. In particular, we analyze the drivers of investor consensus as well as the informative value of buy and sell consensus for future returns. For the period of 1996 to 2018 and for eight sub-property types, we find that private leasing (space market) information predominantly drives the buy and hold consensus, while private asset market information is more important for the sell consensus. Publicly available equity and debt capital market information has the highest explanatory power for the sell and hold consensus. Furthermore, buy and sell consensus has informative value for future returns. The component of buy consensus that is explained by private information has the highest informative value for future returns, particularly in periods of financial crisis and poorly performing real estate markets. On the other hand, the component of sell consensus that is explained by public information has the highest informative value for future returns. Our findings have implications for institutional investors and portfolio managers as they suggest that the survey-based consensus of institutional investors contains valuable information to formulate return expectations, identify trends, and make investment decisions.

Crossing boundaries beyond the investment grade: Induced trading by rating-contingent investment constraints

Institutional portfolio managers face rating-based constraints established by investment policy statements (IPS) in their delegated management which, similar to formal regulations, restrict investment in bonds below certain rating levels. We analyze how prices and liquidity of corporate bonds traded by institutional investors react to downgrades crossing these internal limits. Consistent with the existence of a non-regulatory transmission channel, downgrades through regular IPS ratings have a greater impact on the market than downgrades crossing regulatory boundaries, such as the investment-speculative frontier and the NAIC's risk-based capital system thresholds. Our results reveal the existence of other source of rating-related frictions that should be considered.

Institutional investors' stocks portfolio strategies and commodity prices: a cross-correlation analysis in a financialisation context

New institutional players entered the futures markets with additional important capital inflows from 2000s onwards. Generally, labelled by the term financialisation of commodity markets, integration between traditional financial assets and futures markets raised several concerns for potential spill-over effects on commodity price levels and return volatilities. The aim of this paper is to empirically investigate the plausibility of a lead-lag relationship ignited by institutional investors portfolio management strategies. In order to pursue this goal, a cross-correlation function (ccf) is applied to stock exchange indexes and main international commodity spot prices. The key findings are that the overall effects of such an increased integration/participation appear quite controversial. Oil seem to support (with weak signals detected) this reaction mechanism. Substantially, not significant results are observable for industrial and agricultural commodities.

J. M. Keynes’ influence on institutional portfolio management

ABSTRACTIn the earlier part of his portfolio management career, J. M. Keynes pursued a short-term, asset allocation-based speculative approach to portfolio management, only to abandon it in the early 1930s in favor of a long-term, security selection approach based on identifying intrinsic value. It was the earlier Keynes who endorsed E. L. Smith’s 1924 U.S. monograph, Common Stocks as Long Term Investments, encouraging his insurance company contacts to conduct a similar study in the United Kingdom. This suggestion was taken up in the 1920s and 1930s by U.K. insurance actuaries, whose lead was followed post-1945 by pension fund actuaries. Among the latter, George Ross Goobey is the most well-known, his name being closely associated with the Cult of the Equity, which, with the increasing formalization of institutional portfolio management over the last two or three decades, has transmuted into the Cult of the Benchmark. Underlying this latter cult is the emphasis on asset allocation, which can be traced back to Smith’s monograph. It is ironic that Keynes’ enduring influence is more likely to be felt through his endorsement of Smith rather than by the adoption of the genuine investment approach of his later career.

Minimum sum regression as the optimum robust algorithm in the computation of financial beta

In the world of finance and portfolio management, “beta” refers to the sensitivity of a security’s return, to the sensitivity of the “market” portfolio and is an indication of the level of systematic risk, i.e., the amount of risk that a company’s equity shares with the entire market. Correct values for beta are crucial for institutional portfolio managers, as the client contract almost always calls for a portfolio beta approximately equal to 1.0. Typically, beta is estimated using Ordinary Least Squares, but OLS is reliant on some very stringent assumptions. Here, betas are computed and compared using OLS and four robust regression algorithms. Minimum sum regression is identified as the superior robust regression algorithm to estimate beta. Keywords: Financial Beta, Ordinary Least Squares, Robust Regression, Portfolio Management. JEL Classification: C21, G11

Do Global Oil Price Changes Affect Indian Stock Market Returns?

The present research work is conducted to analyze whether changes in oil prices at global level affect the stock market returns in Indian market. Daily closing stock market price data from National Stock Exchange (NSE) and daily oil prices, for the period beginning from January 2010 to December 2014, are taken into consideration. VAR model of co-integration is used to test the relation between the two variables. It is found that there is no long term integration between oil price and Indian stock index series. Apart from long term, these series do not even cause each other in short run. Very weak correlation, about 3.21 percent, was observed in the series that may be due to recent fall in crude oil prices at global level. Individual/ institutional investors, portfolio managers, corporate executives, policy makers and practitioners may draw meaningful conclusions from the findings of the present study while operating in stock markets. Research like this may help diverse stakeholders in management of their existing portfolios as their portfolio management strategies may be, up to some extent, dependent upon such research work.This paper is an attempt to fill the research gap that exists for Indian stock market in terms of its relationship with global oil prices.

Practical Applications of The Drivers of Predicted Beta

Do portfolio managers know what’s really driving beta? While institutional portfolio managers understand the concept of beta from a practical standpoint, little work has been done on what actually drives beta in a stock portfolio, says Jackson Wang , Executive Director at MSCI in San Francisco. In The Drivers of Predicted Beta , published in the Fall 2014 issue of The Journal of Portfolio Management , Wang and co-author Jose Menchero , until recently Managing Director at MSCI, explain their theory of factor beta. In this report, Wang describes their approach and how it can be used to study cross-sectional variations in beta and to identify which factors are most responsible for the variations.

Practical Applications of Portfolio Concentration and the Geometry of Co-Movement

Imagine a new visually appealing, intuitive tool for institutional portfolio managers to understand the changing correlations between stocks over time, so they can limit concentration risk. This <b>Practical Applications</b> report shows how <b>Wesley Phoa</b>, author of <b><i>Portfolio Concentration and the Geometry of Co-Movement</i></b>, achieved this using a diffusion map method and 3-D gaming technology to visualize correlations of S&amp;P 500 and S&amp;P 100 stocks. “A lot of equity managers are not very quantitative, ” he states in an interview for this report. Phoa set out to find a visual way of representing a mass of information about stock correlations that was both easy to understand and had precise quantitative meaning in its representations. The result is a visually compelling and robust way of looking at correlations between stocks and stock sectors. Phoa is Senior Vice President at <b>The Capital Group Companies</b> in Los Angeles. His article appeared in the Summer 2013 issue of <b><i>The Journal of Portfolio Management</i></b>.

Head and Shoulders Above the Rest? The Performance of Institutional Portfolio Managers Who Use Technical Analysis

Abstract This study takes a novel approach to testing the efficacy of technical analysis. Rather than testing specific trading rules as is typically done in the literature, we rely on institutional portfolio managers’ statements about whether and how intensely they use technical analysis, irrespective of the form in which they implement it. In our sample of more than 10,000 portfolios, about one-third of actively managed equity and balanced funds use technical analysis. We compare the investment performance of funds that use technical analysis versus those that do not, using five metrics. Mean and median (3 and 4-factor) alpha values are generally slightly higher for a cross section of funds using technical analysis, but performance volatility is also higher. Benchmark-adjusted returns are also higher, particularly when market prices are declining. The most remarkable finding is that portfolios with greater reliance on technical analysis have elevated skewness and kurtosis levels relative to portfolios that do not use technical analysis. Funds using technical analysis appear to have provided a meaningful advantage to their investors, albeit in an unexpected way.

Structuring global Property Portfolios: A Cointegration Approach

We create globally diversified real estate portfolios using cointegration methods over 1992-2009. Cointegration is robust to intertemporal correlation instability, identifies markets that share common factors and long-term trends, and identifies leading markets that do not respond to deviations from equilibrium within each cointegrated region. Our cointegrationinspired model portfolios outperform the mean-variance optimized portfolio by 575-725 basis points annually. Differences in performance remain significant over separate time periods, and after controlling for various risk factors. Collectively, the results help clarify property portfolio selection and allocation policy vital for institutional investors and global real estate portfolio managers.

Modeling coherent trading risk parameters under illiquid market perspective

PurposeThe purpose of this paper is to originate a proactive approach for the quantification and analysis of liquidity risk for trading portfolios that consist of multiple equity assets.Design/methodology/approachThe paper presents a coherent modeling method whereby the holding periods are adjusted according to the specific needs of each trading portfolio. This adjustment can be attained for the entire portfolio or for any specific asset within the equity trading portfolio. This paper extends previous approaches by explicitly modeling the liquidation of trading portfolios, over the holding period, with the aid of an appropriate scaling of the multiple‐assets' liquidity‐adjusted value‐at‐risk matrix. The key methodological contribution is a different and less conservative liquidity scaling factor than the conventional root‐t multiplier.FindingsThe proposed coherent liquidity multiplier is a function of a predetermined liquidity threshold, defined as the maximum position which can be unwound without disturbing market prices during one trading day, and is quite straightforward to put into practice even by very large financial institutions and institutional portfolio managers. Furthermore, it is designed to accommodate all types of trading assets held and its simplicity stems from the fact that it focuses on the time‐volatility dimension of liquidity risk instead of the cost spread (bid‐ask margin) as most researchers have done heretofore.Practical implicationsUsing more than six years of daily return data, for the period 2004‐2009, of emerging Gulf Cooperation Council (GCC) stock markets, the paper analyzes different structured and optimum trading portfolios and determine coherent risk exposure and liquidity risk premium under different illiquid and adverse market conditions and under the notion of different correlation factors.Originality/valueThis paper fills a main gap in market and liquidity risk management literatures by putting forward a thorough modeling of liquidity risk under the supposition of illiquid and adverse market settings. The empirical results are interesting in terms of theory as well as practical applications to trading units, asset management service entities and other financial institutions. This coherent modeling technique and empirical tests can aid the GCC financial markets and other emerging economies in devising contemporary internal risk models, particularly in light of the aftermaths of the recent sub‐prime financial crisis.

Economic Capital Allocation under Coherent Market Liquidity Constraints

Asset liquidity trading risk arises from the failure to recognize or address changes in market conditions that affect the ability to liquidate trading assets quickly and with minimal loss in value. Yet despite this universal recognition of the phenomena, there exist no precise mathematical definition of liquidity risk and traditional Value at Risk (VaR) models fail to recognize the impact of liquidity trading risk. In this work we do not offer a definitive one either, but we develop measures of certain kinds of liquidity trading risk that is useful for completing the definition of market risk and for predicting liquidity-adjusted VaR (L-VaR) under illiquid market conditions and within a multivariate context. We argue that asset liquidity risk associated with the uncertainty of liquidating multiple-assets over a given holding period, particularly for thinly traded or emerging markets securities under adverse market conditions, is a key factor in formalizing and measuring overall trading risk and is therefore an important component to model. This paper proposes a practical framework for the quantification of asset liquidity risk, and its impact on economic capital allocations, for multiple assets，portfolios. We present a method whereby the holding periods are adjusted according to the particular needs of each trading portfolio; and this can be attained for the entire portfolio or for specific assets within the trading portfolio. This paper extends previous approaches by explicitly modeling the liquidation of trading portfolios, over the holding period, with the aid of an appropriate scaling of the multiple-assets，L-VaR matrix along with GARCH-M technique to forecast conditional volatility and expected return. The key methodological contribution is a different and a less conservative liquidity scaling factor than the conventional root-t multiplier. The proposed liquidity multiplier is a function of a predetermined liquidity threshold, defined as the maximum position which can be unwound without disturbing market prices during one trading day, and is quite straightforward to implement even by very large financial institutions and institutional portfolio managers. Using more than six years of daily return data of emerging Gulf Cooperation Council (GCC) stock markets, we analyze different trading portfolios (of both long and short-sales trading positions) and determine asset liquidity risk exposure and coherent annual economic capital allocations under different illiquid and adverse market conditions and under the notion of different correlation factors and unwinding periods.

What Explains the Growth in Commodity Derivatives?

This article documents the massive increase in trading in commodity derivatives over the past decade—growth which far outstrips the growth in commodity production and the need for derivatives to hedge risk by commercial producers and users of commodities. During the past decade, many institutional portfolio managers added commodity derivatives as an asset class to their portfolios. This addition was part of a larger shift in portfolio strategy away from traditional equity investment and toward derivatives based on assets such as real estate and commodities. Institu­tional investors’ use of commodity futures to hedge against stock market risk is a relatively recent phenomenon. Trading in commodity derivatives also increased along with the rapid expansion of trading in all derivative markets. This trading was directly related to the search for higher yields in a low interest rate environment. The growth was both in organized exchanges and over-the-counter (OTC) trading, but the gross market value of OTC trading was an order of magnitude greater. This growth is important to note because a critical factor in the recent crisis was counterparty failure in OTC trading of mortgage derivatives.

Performance of monthly multivariate filtered historical simulation value-at-risk

This study examines the performance of 16 value-at-risk (VaR) models in the context of institutional portfolio management. The paper focuses on multivariate versus univariate approaches of asset modelling, estimated with monthly or daily data, and filtered historical simulation (FHS) versus Monte Carlo simulation (MCS) techniques. Tests on VaR violations show that the best-performing models are generally the univariate FHS and MCS models with daily asymmetric GARCH specification. A comparative analysis reveals that the asymmetric impact of positive versus negative shocks in the conditional volatility is the most important feature of the models.

Comovement and Return Predictability

In this paper, we investigate whether comovement can generate predictability in returns. Barberis and Shleifer (2003) argue that style investing causes comovement of stocks within a style to be larger than that warranted by fundamentals. This naturally suggests that comovement may measure investor sentiment, a construct that both academics and practitioners would like to measure with precision. The former are interested in measuring sentiment for scientific reasons and the latter for mercenary ones. Unfortunately, instruments to measure sentiment are either sparse or of poor quality (Baker and Wurgler (2007)). But since our interest is not in aggregate sentiment but comovement with respect to a particular style, we can use an extraordinarily simple and yet precise measure: the R2 of a regression of the stock on the returns of style it belongs to. We measure comovement with respect to size and book-to-market based portfolios because of their ubiquitous role in both retail and institutional portfolio management. We find that between 1970 and 2006, a long-short portfolio strategy based on low and high comovement stocks generates gross returns of 0.9% per month for up to 3 months and 0.7% per month up to 12 months. The excess returns (alpha) after controlling for size, book-to-market and momentum effects are up to 0.86% per month. Although comovement is correlated with trading volume, our results withstand the incorporation of volume in to the trading strategy (Lee and Swaminathan (2000)). As we complete our analysis over the next few months, we expect to (a) use an alternative measure of comovement, (b) examine measures of investment style beyond the traditional size and value-growth grid, (c) examine time variation in excess returns, and (d) determine if changes in comovement can explain the reversal in returns over long-horizons (DeBondt and Thaler (1985)).

From Delivering to Packaging of Alpha

The hedge fund industry typically takes a producer (manager) rather than a consumer (investor) perspective. There ought to be new types of hedge fund offerings better suited to the needs of institutional investors. In the case of active bond portfolios, the authors present evidence that managers can use fixed-income derivatives not only to generate and deliver abnormal performance, but also to package such performance in a form that is consistent with the modern core-satellite approach to institutional portfolio management. A dynamic extension allows for asymmetric control of active management risk. <b>TOPICS:</b>Real assets/alternative investments/private equity, derivatives, portfolio management/multi-asset allocation

Institutional Portfolio Management

Institutional portfolio management has two main goals: 1) to implement the policy risk of the institutional fund as efficiently as possible, and 2) to add value. While these two goals may be accomplished by beta drivers and alpha drivers, asset managers often attempt to extract alpha from beta drivers. This leads to expensive products that add more beta than alpha. To better manage institutional portfolios, beta products must be separated from alpha products, so that the two goals can be accomplished more effectively. This has implications both for the types of products produced by money managers and the types of products purchased by the institutional investor's staff.

"With Friends Like These, Who Needs Enemies?" The Structure of the Investment Industry and Its Reluctance to Exercise Governance Oversight

A continuing obstacle to the success of most corporate governance initiatives is the unwillingness of the majority of institutional portfolio managers to co-operate with governance activists even to the extent of merely voting in cases where clear benefits would flow to all shareholders from a positive result. Portfolio managers have given many excuses for their lack of participation in such efforts, but upon examination, most turn out to be facile rationalisations. Institutional investors’ negative attitudes towards governance may be attributed to scepticism on the part of some individuals, but there also seem to be structural factors at work. Some are integral to corporate governance itself: the difficulty of quantifying governance information, and the longer time horizon necessary for the realisation of most governance initiatives. Others are, however, a function of the structure of the investment industry: the different backgrounds and aptitudes of most corporate governance specialists from most investment managers, reliance upon third-party consultants, a different orientation towards investment, short-termism, differing career paths and perceptions, fear of bureaucratic intervention and competition for performance compensation. It is proposed that some internal readjustment of investment management companies, coupled with a clearer commitment by senior executives at those companies to exploit governance initiatives, would be beneficial both to the cause of better corporate governance and to portfolio returns.

Does Soft Dollar Brokerage Benefit Portfolio Investors: Agency Problem or Solution?

With soft dollar brokerage, institutional portfolio managers pay brokers commission rates in exchange for rebates they use to buy third-party research. One hypothesis views this practice as a reflection of the agency problem in delegated portfolio management; another views it as a contractual solution to the agency problem that aligns the incentives of investors, managers, and brokers where direct monitoring mechanisms are inadequate. Using a database of institutional money managers, we find that premium commission payments are positively related to risk-adjusted performance, suggesting that soft dollar brokerage is a solution to agency problems. Moreover, premium commissions are positively related to management fees, suggesting that labor market competition does not punish managers for using soft dollars.

Rethinking Boundaries and Achieving Greater Flexibility in Implementing the Policy Portfolio

A growing number of investors has become interested in introducing greater flexibility into their policy portfolios. This flexibility can be accomplished in several ways, such as giving broader mandates or eliminating the long-only constraint. A more comprehensive approach would be to separate how investors get the return of the policy portfolio (beta) from how they seek to exploit security mispricing (alpha). For that approach to work, more large funds need to develop stronger capabilities, more institutional-quality need to offer alpha-only strategies, and managers need to enter the market. The master manager would be a hybrid of indexer, overlay manager, transition manager, master custodian, and consultant with the role of facilitating advanced forms of institutional portfolio management.