Does the diversification potential of securitized real estate vary over time and should investors care?

Liang Peng, Rainer Schulz

    Research output: Contribution to journalArticle

    7 Citations (Scopus)

    Abstract

    This paper examines the dynamics of the covariance matrix of return rates for securitized real estate, other company stocks, and government bonds for a cross-section of eight countries. In-sample analysis establishes that in all countries the covariance matrix is time-varying and reacts stronger to bad than to good news. Using a realistic out-of-sample exercise, we find that portfolios selected with a forecasted dynamic covariance matrix are less risky than portfolios constructed with the static matrix. However, benefits of using the dynamic covariance matrix for active portfolio management are mostly offset by rebalancing cost. Passive buy-and-hold investors benefit, because the forecasted dynamic covariance matrix provides better risk assessment.
    Original languageEnglish
    Pages (from-to)310-340
    Number of pages31
    JournalThe Journal of Real Estate Finance and Economics
    Volume47
    Issue number2
    Early online date8 Feb 2012
    DOIs
    Publication statusPublished - Aug 2013

    Fingerprint

    real estate
    diversification
    investor
    government bonds
    portfolio management
    matrix
    risk assessment
    news
    costs
    time
    Covariance matrix
    Investors
    Real estate
    Diversification
    cross section
    cost

    Keywords

    • dynamic conditional correlation
    • portfolio allocation
    • forecast evaluation

    Cite this

    @article{62d4be87d21f4c688c7f2e720523b7c6,
    title = "Does the diversification potential of securitized real estate vary over time and should investors care?",
    abstract = "This paper examines the dynamics of the covariance matrix of return rates for securitized real estate, other company stocks, and government bonds for a cross-section of eight countries. In-sample analysis establishes that in all countries the covariance matrix is time-varying and reacts stronger to bad than to good news. Using a realistic out-of-sample exercise, we find that portfolios selected with a forecasted dynamic covariance matrix are less risky than portfolios constructed with the static matrix. However, benefits of using the dynamic covariance matrix for active portfolio management are mostly offset by rebalancing cost. Passive buy-and-hold investors benefit, because the forecasted dynamic covariance matrix provides better risk assessment.",
    keywords = "dynamic conditional correlation, portfolio allocation, forecast evaluation",
    author = "Liang Peng and Rainer Schulz",
    year = "2013",
    month = "8",
    doi = "10.1007/s11146-011-9357-5",
    language = "English",
    volume = "47",
    pages = "310--340",
    journal = "The Journal of Real Estate Finance and Economics",
    issn = "0895-5638",
    publisher = "Springer Netherlands",
    number = "2",

    }

    TY - JOUR

    T1 - Does the diversification potential of securitized real estate vary over time and should investors care?

    AU - Peng, Liang

    AU - Schulz, Rainer

    PY - 2013/8

    Y1 - 2013/8

    N2 - This paper examines the dynamics of the covariance matrix of return rates for securitized real estate, other company stocks, and government bonds for a cross-section of eight countries. In-sample analysis establishes that in all countries the covariance matrix is time-varying and reacts stronger to bad than to good news. Using a realistic out-of-sample exercise, we find that portfolios selected with a forecasted dynamic covariance matrix are less risky than portfolios constructed with the static matrix. However, benefits of using the dynamic covariance matrix for active portfolio management are mostly offset by rebalancing cost. Passive buy-and-hold investors benefit, because the forecasted dynamic covariance matrix provides better risk assessment.

    AB - This paper examines the dynamics of the covariance matrix of return rates for securitized real estate, other company stocks, and government bonds for a cross-section of eight countries. In-sample analysis establishes that in all countries the covariance matrix is time-varying and reacts stronger to bad than to good news. Using a realistic out-of-sample exercise, we find that portfolios selected with a forecasted dynamic covariance matrix are less risky than portfolios constructed with the static matrix. However, benefits of using the dynamic covariance matrix for active portfolio management are mostly offset by rebalancing cost. Passive buy-and-hold investors benefit, because the forecasted dynamic covariance matrix provides better risk assessment.

    KW - dynamic conditional correlation

    KW - portfolio allocation

    KW - forecast evaluation

    U2 - 10.1007/s11146-011-9357-5

    DO - 10.1007/s11146-011-9357-5

    M3 - Article

    VL - 47

    SP - 310

    EP - 340

    JO - The Journal of Real Estate Finance and Economics

    JF - The Journal of Real Estate Finance and Economics

    SN - 0895-5638

    IS - 2

    ER -