Browsing by Author "Mandal, Anandadeep"

Now showing 1 - 6 of 6
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    Determinants of asymmetric return comovements of gold and other financial assets
    (Elsevier, 2016-08-18) Poshakwale, Sunil S.; Mandal, Anandadeep
    Using conditional time-varying copula models, we characterize the dependence structure of return comovements of gold and other financial assets (stocks, bonds, real estate and oil) during economic expansion and contraction regimes. We also investigate which key macroeconomic and non-macroeconomic variables significantly impact the asset return comovements using a two stage Markov Switching Stochastic Volatility (MSSV) framework. Our results show that the non-macro variables have significant influence on the return comovements. We find that gold is an inappropriate hedge against interest rate changes for real-estate and oil-based portfolios, while for bond portfolios, gold offers a good hedge against inflation uncertainty. We also provide evidence that the “flight to safety” phenomenon is due to the implied volatility of the stock market, rather than the observed stock market uncertainty. Finally, we forecast the asset return comovements and examine their economic significance. We show that a dynamic MSSV model which includes the macroeconomic and non-macroeconomic variables yields superior forecast of future asset return comovements when compared with a multivariate conditional covariance model.
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    Do investors gain from forecasting the asymmetric return co‐movements of financial and real assets?
    (Wiley, 2020-08-10) Mandal, Anandadeep; Poshakwale, Sunil S.; Power, Gabriel J.
    Recent research on asset allocation emphasizes the importance of considering non‐traditional asset classes such as commodities and real estate—the former for their diversification properties, and the latter due to its importance in the average investor's portfolio. However, modelling and forecasting asset return co‐movements is challenging because the dependence structure is dynamic, regime‐specific, and non‐elliptical. Moreover, little is known about the economic source of this time‐varying dependence or how to use this information to improve investor portfolios. We use a flexible framework to assess the economic value to investors of incorporating better forecasting information about return co‐movements between equities, bonds, commodities, and real estate. The dependence structure is allowed to be dynamic and non‐elliptical, while the state variables follow Markov‐switching stochastic volatility processes. We find that the predictability of return co‐movements is significantly improved by incorporating macro and non‐macroeconomic variables, in particular inflation uncertainty and bond illiquidity. The economic value added to investors is significant across levels of risk aversion, and the model outperforms traditional multivariate GARCH frameworks.
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    An empirical investigation of the determinants of asset return comovements
    (Cranfield University, 2015-10) Mandal, Anandadeep; Poshakwale, Sunil S.
    Understanding financial asset return correlation is a key facet in asset allocation and investor’s portfolio optimization strategy. For the last decades, several studies have investigated this relationship between stock and bond returns. But, fewer studies have dealt with multi-asset return dynamics. While initial literature attempted to understand the fundamental pattern of comovements, later studies model the economic state variables influencing such time-varying comovements of primarily stock and bond returns. Research widely acknowledges that return distributions of financial assets are non-normal. When the joint distributions of the asset returns follow a non-elliptical structure, linear correlation fails to provide sufficient information of their dependence structure. In particular two issues arise from this existing empirical evidence. The first is to propose a more reliable alternative density specification for a higher-dimensional case. The second is to formulate a measure of the variables’ dependence structure which is more instructive than linear correlation. In this work I use a time-varying conditional multivariate elliptical and non-elliptical copula to examine the return comovements of three different asset classes: financial assets, commodities and real estate in the US market. I establish the following stylized facts about asset return comovements. First, the static measures of asset return comovements overestimate the asset return comovements in the economic expansion phase, while underestimating it in the periods of economic contraction. Second, Student t-copulas outperform both elliptical and non-elliptical copula models, thus confirming the ii dominance of Student t-distribution. Third, findings show a significant increase in asset return comovements post August 2007 subprime crisis ... [cont.].
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    The governing dynamics of stock-bond return co-movements: a systematic literature review
    (Cranfield University, 2012-08) Mandal, Anandadeep; Poshakwale, Sunil S.
    Understanding stock-bond return correlation is a key facet in asset mix, asset allocation and in an investor’s portfolio optimisation strategy. For the last couple of decades, several studies have probed this cardinal relationship. While initial literature tries to understand the fundamental pattern of co-movements, later studies aim to model the economic state variables influencing such time-varying volatility behaviour of stock-bond returns. This study provides a systematic literature review in the field of stock and bond return correlation. The review investigates the existing literature in three key dimensions. First, it examines the effect of macro-economic variables on SB return co-movements. Second, it illustrates the effect of financial integration on the asset correlation dynamics. Third, it reviews the existing models that are employed to estimate the dynamic relationship. In addition to the systematic review, I conduct an empirical analysis of stock-bond return co-movements on U.S. capital market. Both the literature and the empirical investigation substantiate my claims on existing research gaps and respective scope for further research. Evidence shows that existing models impose strong restrictions on past stock-bond return variance dynamics and yield inconclusive results. I, therefore, propose an alternative method, i.e. copula function approach, to model stock and bond time-varying co-movements. Since the previous studies largely focus on developed economies, I suggest an empirically investigation of emerging economies as well. This will allow me to examine the effect of financial integration on the dynamic asset return correlation. Apart from this academic contribution, the study provides an illustration of the economic implications which relate to portfolio optimization and minimal-risk hedge ratio.
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    Lower tick sizes and futures pricing efficiency: evidence from the emerging Malaysian market
    (2018-11-16) Poshakwale, Sunil S.; Taunson, Jude W.; Mandal, Anandadeep; Theobald, Michael
    We provide robust evidence of the impact on spot market liquidity and the pricing efficiency of FBM-FKLI index futures following the introduction of lower tick sizes for the stocks listed in the Bursa Malaysia. Our findings show a significant increase in unexpected trading volume and the speed of mean reversion of the futures mispricing. We find that the increase in the unexpected trading volume of the underlying stocks helps in reducing inter-market price discrepancies. The findings offer new evidence that lowering of tick sizes improves pricing efficiency in the Malaysian futures market.
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    Sources of time varying return comovements during different economic regimes: evidence from the emerging Indian equity market
    (Springer, 2016-05-18) Poshakwale, Sunil S.; Mandal, Anandadeep
    We study the economic and non-economic sources of stock return comovements of the emerging Indian equity market and the developed equity markets of the US, UK, Germany, France, Canada and Japan. Our findings show that the probability of extreme comovements in the economic contraction regime is relatively higher than in the economic expansion regime. We show that international interest rates, inflation uncertainty and dividend yields are the main drivers of the asymmetric return comovements. Findings reported in the paper imply that the impact of interest rates and inflation on return comovements could be used for anticipating financial contagion and/or spillover effects. This is particularly critical since during extreme market conditions, the tail return comovements can potentially reveal critical information for active portfolio management.