Covariance complexity and rates of return on assets

This paper considers the estimation of the expected rate of return on a set of risky assets. The approach to estimation focuses on the covariance matrix for the returns. The structure in the covariance matrix determines shared information which is useful in estimating the mean return for each asset. An empirical Bayes estimator is developed using the covariance structure of the returns distribution. The estimator is an improvement on the maximum likelihood and Bayes–Stein estimators in terms of mean squared error. The effect of reduced estimation error on accumulated wealth is analyzed for the portfolio choice model with constant relative risk aversion utility.     

Consumption smoothing channels in open economies

Many intertemporal open economy macro models imply a theory of consumption smoothing channels; thus we build an empirical model to analyze the intertemporal smoothing role of saving components (fixed investments, inventories and trade balance) through the use of VAR impulse responses to different types of shocks. We find that for the OECD countries the bulk of intertemporal smoothing has been carried out domestically, via gross fixed investments and inventories, but the trade balance has also played a relevant – albeit volatile – smoothing role. We also characterize the dynamic behavior of each component: the trade balance and inventories are mostly used as short-run smoothing tools while fixed investment provides more and more smoothing over time. We can also address some empirical puzzles, such as the “excess sensitivity of investment” anomaly (Glick, R., Rogoff, K., 1995. Global versus country-specific productivity shocks and the current account. Journal of Monetary Economics, 35, 159–192) and the “saving-investment correlation puzzle” (Feldstein, M., Horioka, C., 1980. Domestic saving and international capital flows. Economic Journal, 90, 314–329).     

Gaussian Estimation and Forecasting of Multi-Factor Term Structure Models with an Application to Japan and the United Kingdom

In this paper we extend the exact discrete model of Bergstrom (1966) first used in empirical finance by Brennan and Schwartz (1979) to estimate their two-factor term structure model to estimate other two-factor term structure models using the recent assumption in Nowman (1997) for single factor models. Following Nowman (1997) we use the exact Gaussian estimation methods of Bergstrom (1983–1986, 1990) to estimate two-factor CKLS, Vasicek and CIR models. We estimate the models using monthly UK and Japanese interest rate data and our results indicate that the estimation method works well in practice.     

Forecasting asymmetries in aggregate stock market returns: Evidence from conditional skewness

This paper provides a time-series test for the Differences-of-Opinion theory proposed by Hong and Stein (2003) [Hong, H., Stein, J.C., 2003. Differences of opinion, short-sales constraints and market crashes. Review of Financial Studies 16, 487–525.] in the aggregate market, thus extending the cross-sectional test of Chen et al. (2001) [Chen, J., Hong, H., Stein, J.C.. 2001. Forecasting crashes: trading volume, past returns and conditional skewness in stock prices. Journal of Financial Economics 61, 345–381.] for this theory across individual stocks. An autoregressive conditional density model with a skewed-t distribution is used to estimate the effects of past trading volume on return asymmetry. Using NYSE and AMEX data from 1962 to 2000, we find that the prediction of the Hong–Stein model that negative skewness will be most pronounced under high trading volume conditions is not supported in our time-series analysis with market data.     

A Note on Gaussian Estimation of the CKLS and CIR Models with Feedback Effects for Japan

In this note we extend the Gaussian estimation of two factor CKLS and CIR models recently considered in Nowman, K. B. (2001, Gaussian estimation and forecasting of multi-factor term structure models with an application to Japan and the United Kingdom, Asia Pacif. Financ. Markets 8, 23–34) to include feedback effects in the conditional mean as was originally formulated in general continuous time models by Bergstrom, A. R. (1966, Non-recursive models as discrete approximations to systems of stochastic differential equations, Econometrica 34, 173–182) with constant volatility. We use the exact discrete model of Bergstrom, A. R. (1966, Non-recursive models as discrete approximations to systems of stochastic differential equations, Econometrica 34, 173–182) to estimate the parameters which was first used by Brennan, M. J. and Schwartz, E. S. (1979, A continuous time approach to the pricing of bonds, J. Bank. Financ. 3, 133–155) to estimate their two factor interest model but incorporating the assumption of Nowman, K. B. (1997, Gaussian estimation of single-factor continuous time models of the term structure of interest rates, J. Financ. 52, 1695–1706; 2001, Gaussian estimation and forecasting of multi-factor term structure models with an application to Japan and the United Kingdom, Asia Pacif. Financ. Markets 8, 23–34). An application to monthly Japanese Euro currency rates indicates some evidence of feedback from the 1-year rate to the 1-month rate in both the CKLS and CIR models. We also find a low level-volatility effect supporting Nowman, K. B. (2001, Gaussian estimation and forecasting of multi-factor term structure models with an application to Japan and the United Kingdom, Asia Pacif. Financ. Markets 8, 23–34).     

The saving–investment correlation puzzle is still a puzzle

A number of simulation studies claim to have solved the Feldstein–Horioka puzzle by demonstrating that a high time-series correlation between saving and investment naturally arises from business cycle shocks. This paper uses panel data of saving and investment controlled for business cycle shocks to empirically test the significance of cyclical shocks — productivity, fiscal and the terms of trade shocks — in explaining a high saving–investment correlation. The estimation results reveal that conventional aggregate shocks only partially explain the high saving–investment correlation. Moreover, country differences in the size of the GNP and the non-traded sector do not significantly affect the saving–investment correlation. The saving–investment correlation puzzle remains a puzzle after all.     

Equity markets and growth: Cross-country evidence on timing and outcomes, 1980–1995

The rapid expansion of organized equity exchanges in both emerging and developed markets has prompted policymakers to raise important questions about their macroeconomic impact, yet the need to focus on recent data poses implementation difficulties for econometric studies of dynamic interactions between stock markets and economic performance in individual countries. This paper overcomes some of these difficulties by applying recent developments in the analysis of panels with a small time dimension to estimate vector autoregressions for a set of 47 countries with annual data for 1980–1995. After describing recent theories on the role of stock markets in growth and considering a pure cross-sectional empirical approach, our panel VARs show leading roles for stock market liquidity and the intensity of activity in traditional financial intermediaries on per capita output. The findings underscore the potential gains associated with developing deep and liquid financial markets in an increasingly global economy.     

Costly external financing, investment timing, and investment–cash flow sensitivity

This paper examines the effects of costly external financing on the optimal timing of a firm's investment. By altering the optimal investment timing, costly financing affects current investment and the sensitivity of investment to internal cash flow. Importantly, the relation between the cost of external funds and investment–cash flow sensitivity is non-monotonic. Investment–cash flow sensitivity is decreasing in the cost of external financing when it is relatively low and is increasing in the financing cost when it is high. Empirical tests examining investment–cash flow sensitivities within groups of firms classified by proxies for their costs of external funds provide evidence consistent with the model. The model and the empirical results complement recent studies by Cleary, Povel and Raith [Cleary, S., Povel, P. and Raith, M., 2007. The U-shaped investment curve: theory and evidence, Journal of Financial and Quantitative Analysis 42, 1–39.] and Almeida and Campello [Almeida, H. and Campello, M., in press, Financial constraints, asset tangibility and corporate investment, Review of Financial Studies.] that show a non-monotonic relation between firms' investment and the availability of internal funds.     

Cross-impact analysis and classical probability: The question of consistency

A great deal of confusion has surrounded the basic definitions and concepts in the various versions of cross-impact analysis. The purpose of this article is to clarify the meaning of one of the fundamental concepts-conditional probability-as used in a cross-impact analysis. The authors begin by illustrating two versions of conditional probability, one based on correlation and one based on causation, and show that the latter is much better suited to the study of alternative futures. One of the main sources of past misunderstanding is the attempt to apply the correlative conditions of Bayes' theorem to a causative cross-impact analysis. They demonstrate that there is no inconsistency between Bayes' theorem and cross-impact analysis; the confusion results from the use of Bayes' theorem when the basic analysis involves causation.     

Asset–liability modelling and pension schemes: the application of robust optimization to USS

This paper uses a novel numerical optimization technique – robust optimization – that is well suited to solving the asset–liability management (ALM) problem for pension schemes. It requires the estimation of fewer stochastic parameters, reduces estimation risk and adopts a prudent approach to asset allocation. This study is the first to apply it to a real-world pension scheme, and the first ALM model of a pension scheme to maximize the Sharpe ratio. We disaggregate pension liabilities into three components – active members, deferred members and pensioners, and transform the optimal asset allocation into the scheme's projected contribution rate. The robust optimization model is extended to include liabilities and used to derive optimal investment policies for the Universities Superannuation Scheme (USS), benchmarked against the Sharpe and Tint, Bayes–Stein and Black–Litterman models as well as the actual USS investment decisions. Over a 144-month out-of-sample period, robust optimization is superior to the four benchmarks across 20 performance criteria and has a remarkably stable asset allocation – essentially fix-mix. These conclusions are supported by six robustness checks.     

The estimation and determinants of emerging market country risk and the dynamic conditional correlation GARCH model

Country risk assessment is central to the international investment, which recently has increasingly focused on emerging markets (EM). In this paper we proxy for country risk in EM by using time-varying beta. We extend existing literature by applying a dynamic conditional correlation GARCH model. After confirming beta is time varying in twenty EM over the period January 1995 to December 2008 we investigate the GARCH (1,1) model and find the t-distribution generates the lowest forecast errors compared to the normal error distribution and a generalised error distribution. In a comparison of previous modelling techniques the results of our modified Diebold-Mariano test statistics suggest that the Kalman Filter model outperforms the GARCH model and the Schwert and Seguin (1990) model. Using a DCC-GARCH model our evidence suggests that considering dynamic betas can improve beta out-of-sample predicting ability and therefore offers potential gains for investors. Finally, we find dynamic betas across EM are strongly associated with each nation's interest rates, US interest rates and the Consumer Price Index (CPI) and to a lesser extent the exchange rates. Our results have some similarities to those in previous studies of developed markets in the economic determinants of time-varying beta but differences exist in the results on best model to forecast time-varying beta. These findings have implications for estimating country risk for investment and risk management purposes in EM.     

An empirical examination of the benefits of international diversification

We examine the benefits of international portfolio diversification for U.K. investors between January 1985 and December 2000 using the approach of Wang [Wang, Z., 1998. Efficiency loss and constraints on portfolio holdings. Journal of Financial Economics 48, 359–375] and Li et al. [Li, K., Sarkar, A., Wang, Z., 2003. Diversification benefits of emerging markets subject to portfolio constraints. Journal of Empirical Finance 10, 57–80]. We find significant increases in the Sharpe [Sharpe, W.F., 1966. Mutual fund performance. Journal of Business 39, 119–138] and certainty equivalent return (CER) performance in moving from a domestic strategy to an international strategy that includes either global industry or country equity portfolios, even in the presence of short selling restrictions. We also find significant diversification benefits using U.K. unit trusts with international equity objectives. However, U.K. international unit trusts do not capture all the diversification benefits provided by either global industry or country equity portfolios.     

基于SVECM的我国经济增长动态效应的实证研究

本文应用结构向量误差修正模型(SVECM),实证分析1990-2008年我国投资、消费、进出口对经济增长的动态效应.实证结果显示:消费对经济的短期和长期冲击均高于投资和进出口,消费对投资冲击大于投资对消费冲击,消费和投资未产生相互挤出效应;经济波动以消费为主,世界经济波动对我国经济波动显著增强.     

Dynamic factor long memory volatility

In this paper, we develop a long memory orthogonal factor (LMOF) multivariate volatility model for forecasting the covariance matrix of financial asset returns. We evaluate the LMOF model using the volatility timing framework of Fleming et al. [J. Finance, 2001, 56, 329–352] and compare its performance with that of both a static investment strategy based on the unconditional covariance matrix and a range of dynamic investment strategies based on existing short memory and long memory multivariate conditional volatility models. We show that investors should be willing to pay to switch from the static strategy to a dynamic volatility timing strategy and that, among the dynamic strategies, the LMOF model consistently produces forecasts of the covariance matrix that are economically more useful than those produced by the other multivariate conditional volatility models, both short memory and long memory. Moreover, we show that combining long memory volatility with the factor structure yields better results than employing either long memory volatility or the factor structure alone. The factor structure also significantly reduces transaction costs, thus increasing the feasibility of dynamic volatility timing strategies in practice. Our results are robust to estimation error in expected returns, the choice of risk aversion coefficient, the estimation window length and sub-period analysis.     

A dynamic model of active portfolio management with benchmark orientation

This paper studies optimal dynamic portfolios for investors concerned with the performance of their portfolios relative to a benchmark. Assuming that asset returns follow a multi-linear factor model similar to the structure of Ross (1976) [Ross, S., 1976. The arbitrage theory of the capital asset pricing model. Journal of Economic Theory, 13, 342–360] and that portfolio managers adopt a mean tracking error analysis similar to that of Roll (1992) [Roll, R., 1992. A mean/variance analysis of tracking error. Journal of Portfolio Management, 18, 13–22], we develop a dynamic model of active portfolio management maximizing risk adjusted excess return over a selected benchmark. Unlike the case of constant proportional portfolios for standard utility maximization, our optimal portfolio policy is state dependent, being a function of time to investment horizon, the return on the benchmark portfolio, and the return on the investment portfolio. We define a dynamic performance measure which relates portfolio’s return to its risk sensitivity. Abnormal returns at each point in time are quantified as the difference between the realized and the model-fitted returns. Risk sensitivity is estimated through a dynamic matching that minimizes the total fitted error of portfolio returns. For illustration, we analyze eight representative mutual funds in the U.S. market and show how this model can be used in practice.     

Modest policy interventions

We present a theoretical and empirical framework for computing and evaluating linear projections conditional on hypothetical paths of monetary policy. A modest policy intervention does not significantly shift agents’ beliefs about policy regime and does not induce the changes in behavior that Lucas (Carnegie–Rochester Conference Series on Public Policy, Vol. 1, Amsterdam, North-Holland, 1976, pp. 104–130) emphasizes. Applied to an econometric model of U.S. monetary policy, we find that a rich class of interventions routinely considered by the Federal Reserve is modest and their impacts can be reliably forecasted by an identified linear model. Modest interventions can shift projected paths and probability distributions of macro variables in economically meaningful ways.     

The Performance,Asset Allocation,and Investment Style of International Equity Managers

This paper evaluates the performance of 114 international equity managers over the January 1988–December 1997 period. Performance tests are conducted using Sharpe (1966) and Jensen (1968) performance methodologies. The managers are divided into mutual fund (n=54) and separately managed fund (n=60) investment management categories. Each management category is further divided by foreign and world (global) investment objectives. Three major findings are reported. First, international equity managers, on average, were unable to outperform the MSCI World market proxy during the sample period. However, world managers did perform better than their foreign counterparts. Second, geographic asset allocation and equity style allocation decisions enhanced the performance of international managers during the sample period. Third, separately managed funds outperformed mutual funds during the period studied when mutual fund returns are measured net of management fees. The apparent managed performance advantage abates, however, when mutual fund returns are adjusted to include management fees. Thus, we find no significant difference in the performance of the management categories when returns are measured gross of fees.     

Dealing with financial instability under a DSGE modeling approach with banking intermediation: A predictability analysis versus TVP-VARs

In the dynamic stochastic general equilibrium (DSGE) literature there has been an increasing awareness on the role that the banking sector can play in macroeconomic activity. We present a DSGE model with financial intermediation as in Gertler and Karadi (2011). The estimation of shocks and of the structural parameters shows that time-variation should be crucial in any attempted empirical analysis. Since DSGE modelling usually fails to take into account inherent nonlinearities of the economy, we propose a novel time-varying parameter (TVP) state-space estimation method for VAR processes both for homoskedastic and heteroskedastic error structures. We conduct an exhaustive empirical exercise to compare the out-of-sample predictive performance of the estimated DSGE model with that of standard ARs, VARs, Bayesian VARs and TVP-VARs. We find that the TVP-VAR provides the best forecasting performance for the series of GDP and net worth of financial intermediaries for all steps-ahead, while the DSGE model outperforms the other specifications in forecasting inflation and the federal funds rate at shorter horizons.     

Time to wealth goals in capital accumulation

This paper considers the problem of investment of capital in risky assets in a dynamic capital market in continuous time. The model controls risk, and in particular the risk associated with errors in the estimation of asset returns. The framework for investment risk is a geometric Brownian motion model for asset prices, with random rates of return. The information filtration process and the capital allocation decisions are considered separately. The filtration is based on a Bayesian model for asset prices, and an (empirical) Bayes estimator for current price dynamics is developed from the price history. Given the conditional price dynamics, investors allocate wealth to achieve their financial goals efficiently over time. The price updating and wealth reallocations occur when control limits on the wealth process are attained. A Bayesian fractional Kelly strategy is optimal at each rebalancing, assuming that the risky assets are jointly lognormal distributed. The strategy minimizes the expected time to the upper wealth limit while maintaining a high probability of reaching that goal before falling to a lower wealth limit. The fractional Kelly strategy is a blend of the log-optimal portfolio and cash and is equivalently represented by a negative power utility function, under the multivariate lognormal distribution assumption. By rebalancing when control limits are reached, the wealth goals approach provides greater control over downside risk and upside growth. The wealth goals approach with random rebalancing times is compared to the expected utility approach with fixed rebalancing times in an asset allocation problem involving stocks, bonds, and cash.