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    Empirical Analysis of Regime-Focused Asset Allocation Strategies within a Markov Switching Framework

    O'Sullivan, Alan (2022) Empirical Analysis of Regime-Focused Asset Allocation Strategies within a Markov Switching Framework. PhD thesis, National University of Ireland Maynooth.

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    This thesis consists of three papers examining the relationship between key macro-economic variables and optimal asset allocation strategies. We find evidence that asset prices behave differently depending upon the underlying economic regime. A regime-based asset allocation strategy seeks to integrate a full suite of securities across the full business cycle. We find additional evidence supporting the linkages in the literature between dynamic portfolio optimization and tactical rebalancing across unique state spaces. Paper 1 seeks to test and confirm whether the joint distribution of equity, fixed income and gold returns pursue a dynamic, non-linear pattern. We illustrate the benefits of utilising a time-varying, Markov-switching regime-based framework to forecast expected returns. Long-run historical monthly returns dating back to 1968 were used to assess return predictability. We adopt a unique approach for our empirical analysis amongst the existing regime-shifting literature by segmenting our full 50-year sample period (1968-2019) into three specific regimes (1968-1983), (1984-2007) & (2008-2019). We find evidence that supports the presence of a low-volatility premium. Economic regimes appear to be ordered by the intrinsic nature of their volatility. We have produced robust evidence supporting the negative risk-reward relationship between international equity markets and volatility. Our findings support the theories that exposures to gold offer attractive diversification benefits, particularly to equity investors. Across all four of the individual study sample periods monthly gold returns outperform during periods of excess volatility. Regime classification is structured upon a combination of empirical evidence and proven economic principles. Regimes are ordered in terms of factor exposures to economic growth, inflation and volatility. We construct a 2 x 2 factor model of growth and inflation characterised by a four-quadrant internal system. These internal regimes are classified by a combination of factors. The first order effects relate to the inter-relationship or covariance between growth and inflation. The second order effects constitute the policy response to this environment. Multiple linear modelling equations are used to identify causal relationships between dependent financial assets and our predictor variables. These were split between regime-agnostic, contiguous data sampling methods and regime-specific, non-contiguous data sampling. The findings appear consistent with the prevailing macroeconomic theory that broader equity market returns outperform gold, fixed income and commodity assets during specific market regimes and that gold should outperform the S&P500 across inflationary regimes. In paper 3 there was a focus on whether dynamic asset allocation strategies can capture enhanced portfolio opportunities through profitable sector pivots, factor exposures and optimization. We developed a unique leading indicator framework utilising statistically significant predictor variables to inform the regime-based asset allocation process. Furthermore, robustness checks were conducted across a diverse range of assets including individual equity sectors, mutual funds, tradeable assets and investment factors. This study is distinctive in its approach of utilising this Bayesian grounded leading indicator framework and in the scope of the assets used to test its robustness.

    Item Type: Thesis (PhD)
    Keywords: Empirical Analysis; Regime-Focused; Asset Allocation; Strategies; Markov; Switching Framework;
    Academic Unit: Faculty of Social Sciences > School of Business
    Item ID: 16915
    Depositing User: IR eTheses
    Date Deposited: 07 Feb 2023 10:12
      Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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