The Norway Model

Abstract:     
The Norwegian Government Pension Fund Global was recently ranked the largest fund on the planet. It is also highly rated for its professional, low-cost, transparent, and socially responsible approach to asset management. Investment professionals increasingly refer to Norway as a model for managing financial assets. We present and evaluate the strategies followed by the Fund, review long-term performance, and describe how it responded to the financial crisis. We conclude with some lessons that investors can draw from Norway’s approach to asset management, contrasting the Norway Model with the Yale Model.

Chambers, David, Dimson, Elroy and Ilmanen, Antti S., The Norway Model (October 10, 2011). Available at SSRN: http://ssrn.com/abstract=1936806 or http://dx.doi.org/10.2139/ssrn.1936806

Strategic Asset Allocation: The Global Multi-Asset Market Portfolio 1959-2011

Abstract:

The portfolio of the average investor contains important information for strategic asset allocation purposes. This portfolio shows the relative value of all assets according to the market crowd, which one could interpret as a benchmark or the optimal portfolio for the average investor. We determine the market values of equities, private equity, real estate, high yield bonds, emerging debt, non-government bonds, government bonds, inflation linked bonds, commodities, and hedge funds. For this range of assets, we estimate the invested global market portfolio for the period 1990-2011. For the main asset categories equities, real estate, non-government bonds and government bonds we extend the period to 1959-2011. To our understanding, we are the first to document the global multi-asset market portfolio at these levels of detail for such a long period of time.

Doeswijk, Ronald Q., Lam, Trevin W. and Swinkels, Laurens A. P., Strategic Asset Allocation: The Global Multi-Asset Market Portfolio 1959-2011 (November 2, 2012). Available at SSRN: http://ssrn.com/abstract=2170275 or http://dx.doi.org/10.2139/ssrn.2170275

Forecasting EREIT Returns

Forecasting EREIT Returns

Camilo Serrano, Martin Hoesli,
Volume: 13
Issue Number: 4
Year: 2007
Publication: Journal of Real Estate Portfolio Management

Executive Summary. This paper analyzes the role played by financial assets, direct real estate, and the Fama and French (1993) factors in explaining equity real estate investment trust (EREIT) returns and examines the usefulness of these variables in forecasting returns. Four models are analyzed and their predictive potential is assessed by comparing three forecasting methods: time varying coefficient (TVC) regressions, vector autoregressive (VAR) systems, and neural networks models. Trading strategies on these forecasts are compared to a passive buy-and-hold strategy. The results show that EREIT returns are better explained by models including the Fama and French factors. The VAR forecasts are better than the TVC forecasts, but the best predictions are obtained with neural networks and especially when they are applied to the model using stock, bond, real estate, size, and book-to-market factors.

Correlation, Return Gaps and the Benefits of Diversification

Correlation, Return Gaps and the Benefits of Diversification

Statman, Meir and Scheid, Jonathan, "Correlation, Return Gaps and the Benefits of Diversification" (November 2007).

Abstract:

Correlation is the common indicator for the benefits of diversification, but it is not a good indicator. This is for two reasons. First, the benefits of diversification depend not only on the correlations between returns but also on the standard deviations of returns. Second, correlation does not provide an intuitive measure of the benefits of diversification. Return gaps are better indicators. Return gaps are the difference between the returns of two assets or between two portfolios.

For example, the estimated 12-month return gap between the S&P 500 Index and the Russell 2000 Index and during February 2002 – January 2007 was 8.90%, implying that investors who concentrated their portfolios in one index or the other should have expected to lead or lag investors who diversified between the two in equal proportions by 4.45%. The realized 12-month return gaps ranged from 0.1% to 28.7%. It is hard to deduce these figure intuitively from the relatively high 0.82 correlation between the two. Similarly, it is hard to deduce intuitively from the relatively high 0.86 correlation between the S&P 500 and EAFE Indexes that their estimated 12-month return gap was 6.86% and their realized 12-month return gaps ranged from 1.8% to 23.0%. Moreover, the figures belie any claim that these assets' risk-reduction benefits have largely vanished.

Beta Based Asset Allocation: Simplicity and Transparancy

Beta Based Asset Allocation: Simplicity and Transparancy

By P. Brett Hammond, TIAA-CREF Institute (Winter 2007)

This is a companion piece to a paper titled Reverse Asset Allocation: Alternatives at the Core, written in the second quarter of 2007. As discussed in that paper, the challenges and potential benefits of alternative assets include portfolio instability and counterintuitive results on the one hand, and superior return and risk expectations on the other — characteristics that become strikingly evident through asset allocation exercises involving alternatives

International Price and Earnings Momentum

International Price and Earnings Momentum

Leippold, Markus and Lohre, Harald, (March 4, 2008)

Abstract:

We find that price and earnings momentum are pervasive features of developed equity markets when controlling for multiple testing issues. Having ruled out data snooping as possible explanation for both phenomena, the evidence becomes even more startling. Recently, Chordia and Shivakumar (2006) argue that U.S. price momentum is subsumed by earnings momentum. We replicate their empirical finding for the U.S. and show that it does carry over to Europe on an aggregate level, but it does not apply to each and every European country. While the above explanation seems to be confined to certain time periods, earnings momentum nevertheless appears to be a crucial factor in explaining the price momentum anomaly in many developed markets. Since we cannot establish a decent relation between the earnings momentum phenomenon and macroeconomic risks we suspect a behavioral-based explanation to be at work. Narrowing the search for such a behavioral explanation we provide evidence that the anomaly is most likely not related to dispersion in analysts' earnings forecast.

S&P Global Index Review

S&P Global Index Review

The Global Index Review is designed for money managers and derivative traders to help them assess the performance and correlations of the S&P indices against other popular indices. Published quarterly, the Global Index Review provides a graphic summary of each Standard & Poor’s equity index and compares performance, where appropriate, against other leading indices around the world. It includes data and comparative analysis on the S&P Global 1200, S&P/Citigroup Indices, regional components, as well as sector, style and domestic indices with indices from MSCI, FTSE, Russell, Wilshire, Dow Jones STOXX, and Nikkei. The Global Index Review offers comparative performance, portfolio characteristics, sector weights, tracking statistics and correlations. For easy referencing, this publication is broken into regional chapters
including:

- Global Indices
- U.S. Indices
- European Indices
- Japanese Indices
- Canadian Indices
- Australian Indices
- Asia and Latin America
- Alternative Indices

S&P Alternate Assets Report

S&P Alternate Assets Report

The quarterly S&P Global Alternative Assets Report provides institutional investors with comprehensive performance analysis across a number of alternative asset classes.

Global alternative assets included in this issue:

S&P Listed Private Equity
S&P Global Infrastructure
S&P MLP
S&P U.S. Preferred Stock
S&P/TSX Preferred Share
S&P Global Timber & Forestry
S&P Select Frontier
S&P Global Property 40