Diversification Meltdown or the Impact of Fat tails on Conditional Correlation?

A perceived increase in correlation during turbulent market conditions implies a reduction in the benefits arising from portfolio diversification. Unfortunately, it is exactly then that these benefits are most needed. To determine whether diversification truly breaks down, we investigate the robustness of a popular conditional correlation estimator against alternative distributional assumptions. Analytical results show that the apparent meltdown in the benefits from diversification could be a consequence of assuming normally distributed returns. A more realistic assumption - the bivariate Student-t distribution - suggests that constant correlation may be sustained over the full support of the multivariate return distributionConditional correlation, Truncated correlation, Bivariate Student-t correlation.

Fat-tailed models for risk estimation

In the post-crisis era, financial institutions seem to be more aware of the risks posed by extreme events. Even though there are attempts to adapt methodologies drawing from the vast academic literature on the topic, there is also skepticism that fat-tailed models are needed. In this paper, we address the common criticism and discuss three popular methods for extreme risk modeling based on full distribution modeling and and extreme value theory. --

Does Portfolio Optimization Pay?

All HARA-utility investors with the same exponent invest in a single risky fund and the risk-free asset. In a continuous time-model stock proportions are proportional to the inverse local relative risk aversion of the investor (1/γ-rule). This paper analyses the conditions under which the optimal buy and holdportfolio of a HARA-investor can be approximated by the optimal portfolio of an investor with some low level of constant relative risk aversion using the 1/γ-rule. It turns out that the approximation works very well in markets without approximate arbitrage opportunities. In markets with high equity premiums this approximation may be of low quality.HARA-utility, portfolio choice, certainty equivalent, approximated choice

Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Open accessThis paper reports a new methodology and results on the forecast of the numerical value of the fat tail(s) in asset returns distributions using the irrational fractional Brownian motion model. Optimal model parameter values are obtained from fits to consecutive daily 2-year period returns of S&P500 index over [1950–2016], generating 33-time series estimations. Through an econometric model,the kurtosis of returns distributions is modelled as a function of these parameters. Subsequently an auto-regressive analysis on these parameters advances the modelling and forecasting of kurtosis and returns distributions, providing the accurate shape of returns distributions and measurement of Value at Risk

Portfolio Choice for HARA Investors: When Does 1/γ (not) Work?

In the continuous time-Merton-model the instantaneous stock proportions are inversely proportional to the investorâs local relative risk aversion γ. This paper analyses the conditions under which a HARA-investor can use this 1/γ-rule to approximate her optimal portfolio in a finite time setting without material effects on the certainty equivalent of the portfolio payoff. The approximation is of high quality if approximate arbitrage opportunities do not exist and if the investorâs relative risk aversion is higher than that used for deriving the approximation portfolio. Otherwise, the approximation quality may be bad.HARA-utility, portfolio choice, certainty equivalent, approximated choice

The Nobel Memorial Prize for Robert F. Engle

I review and interpret two of Robert Engle's most important contributions: the theory and application of cointegration, and the theory and application of dynamic volatility models. I treat the latter much more extensively, de-emphasizing technical aspects and focusing instead on the intuition, nuances and importance of the work.

The Impact of Fat Tails on Equilibrium Rates of Return and Term Premia

We investigate the impact of ignoring fat tails observed in the empirical distributions of macroeconomic time series on the equilibrium implications of the consumption-based asset-pricing model with habit formation. Fat tails in the empirical distributions of consumption growth rates are modeled as a dampened power law process that nevertheless guarantees finiteness of moments of all orders. This renders model-implied mean equilibrium rates of return and equity and term premia finite. Comparison with a benchmark Gaussian process reveals that accounting for fat tails lowers the model-implied mean risk-free rate by 20 percent, raises the mean equity premium by 80 percent and the term premium by 20 percent, bringing the model implications closer to their empirically observed counterparts.pricing model, habit formation, term premium, equity premium, fat tails, dampened power law