Measuring financial risk and portfolio reversion with time changed tempered stable Lévy processes

Given that underlying assets in financial markets exhibit stylized facts such as leptokurtosis, asymmetry, clustering properties and heteroskedasticity effect, this paper applies the stochastic volatility models driven by tempered stable Lévy processes to construct time changed tempered stable Lévy processes (TSSV) for financial risk measurement and portfolio reversion. The TSSV model framework permits infinite activity jump behaviors of returns dynamics and time varying volatility consistently observed in financial markets by introducing time changing volatility into tempered stable processes which specially refer to normal tempered stable (NTS) distribution as well as classical tempered stable (CTS) distribution, capturing leptokurtosis, fat tailedness and asymmetry features of returns in addition to volatility clustering effect in stochastic volatility. Through employing the analytical characteristic function and fast Fourier transform (FFT) technique, the closed form formulas for probability density function (PDF) of returns, value at risk (VaR) and conditional value at risk (CVaR) can be derived. Finally, in order to forecast extreme events and volatile market, we perform empirical researches on Hangseng index to measure risks and construct portfolio based on risk adjusted reward risk stock selection criteria employing TSSV models, with the stochastic volatility normal tempered stable (NTSSV) model producing superior performances relative to others.     

Two-Sided Bounds for Ruin Probabilities when the Adjustment Coefficient does not Exist

In this paper, we derive two-sided bounds for the ruin probability in the compound Poisson risk model when the adjustment coefficient of the individual claim size distribution does not exist. These bounds also apply directly to the tails of compound geometric distributions. The upper bound is tighter than that of Dickson (1994). The corresponding lower bound, which holds under the same conditions, is tighter than that of De Vylder and Goovaerts (1984). Even when the adjustment coefficient exists, the upper bound is, in some cases, tighter than Lundberg's bound. These bounds are applicable for any positive distribution function with a finite mean. Examples are given and numerical comparisons with asymptotic formulae for the ruin probability are also considered.     

Conditions Ensuring the Decomposition of Asset Demand for All Risk-Averse Investors

Abstract

The paper explores how the demand for a risky asset can be decomposed into an investment effect and a hedging effect by all risk-averse investors. This question has been shown to be complex when considered outside of the mean-variance framework. Dependence among returns on the risky assets is restricted to quadrant dependence and it is found that the demand for one risky asset can be decomposed into an investment component based on the risk premium offered by the asset and a hedging component used against the fluctuations in the return on the other risky asset. The paper also discusses how the class of quadrant-dependent distributions is related to that of two-fund separating distributions. This contribution opens up the search for broader distributional hypotheses suitable to asset demand models. Examples are discussed.     

Changes in volatility of credit spread and market efficiency during rapid growth of credit-related securities

This paper investigates the changes in credit spread volatility during 1993–2001. We find that the credit spreads between junk-grade corporate bonds and Treasury bonds were significantly more volatile in the second half of this period when credit-related securities became popular. In contrast, investment-grade bonds exhibited no significant change in volatility. The junk bonds variance ratios changed from being less than one to greater than one. Using the GJR-Garch model, the conditional volatilities of junk bonds increased in the second half of the period and the mean reversion speeds slowed, suggesting a longer time for mean reversion to occur. Our analysis rules out treasury volatility, credit spread level, equity market return, T-bill rate, curvature of the Treasury curve, financial crisis, quantity of defaults and standard deviation of defaults as explanations for the increase in junk bond volatility. In contrast, volatility of equity returns provides a partial explanation of junk bond spread volatility in the later period.     

Monotonicity in asset returns: New tests with applications to the term structure,the CAPM,and portfolio sorts

Many theories in finance imply monotonic patterns in expected returns and other financial variables. The liquidity preference hypothesis predicts higher expected returns for bonds with longer times to maturity; the Capital Asset Pricing Model (CAPM) implies higher expected returns for stocks with higher betas; and standard asset pricing models imply that the pricing kernel is declining in market returns. The full set of implications of monotonicity is generally not exploited in empirical work, however. This paper proposes new and simple ways to test for monotonicity in financial variables and compares the proposed tests with extant alternatives such as t-tests, Bonferroni bounds, and multivariate inequality tests through empirical applications and simulations.     

Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models

We extend the recently introduced latent threshold dynamic models to include dependencies among the dynamic latent factors which underlie multivariate volatility. With an ability to induce time-varying sparsity in factor loadings, these models now also allow time-varying correlations among factors, which may be exploited in order to improve volatility forecasts. We couple multi-period, out-of-sample forecasting with portfolio analysis using standard and novel benchmark neutral portfolios. Detailed studies of stock index and FX time series include: multi-period, out-of-sample forecasting, statistical model comparisons, and portfolio performance testing using raw returns, risk-adjusted returns and portfolio volatility. We find uniform improvements on all measures relative to standard dynamic factor models. This is due to the parsimony of latent threshold models and their ability to exploit between-factor correlations so as to improve the characterization and prediction of volatility. These advances will be of interest to financial analysts, investors and practitioners, as well as to modeling researchers.     

Asset allocation in markets with contagion: The interplay between volatilities,jump intensities,and correlations

We study the impact of financial contagion on the dynamic asset allocation problem of a CRRA investor facing an incomplete market with two risky assets. We apply a Markov chain regime-switching framework with state-dependent jump intensities, diffusion volatilities and diffusion correlations. The key model feature that a switch to the bad contagion regime is triggered by a loss in one of the risky assets allows for the implementation of a hedging demand against contagion risk. Moreover, a state-dependent diffusion correlation combined with heterogeneity in jump intensities and volatilities can, e.g., generate a flight to quality effect upon a systemic jump.     

居民金融资产结构变化与国债认购空间分析

国债是居民持有的重要金融资产,居民对其金融资产结构的调整会影响国债的发行规模,本文通过国际比较分析总结了居民金融资产结构变化的规律。并考察了我国居民金融资产流量结构的变化趋势和国债在居民金融资产结构中的地位,为此为基础,对“十五”期间政府面向居民可以发生国债的规模进行了预测。     

GDP growth and currency valuation: The case of the dollar

One popular view on the strength of the US dollar around the turn of the century is that the higher growth in the US compared to Europe had stimulated foreigners to buy American assets, thereby driving up the exchange rate. In this paper a modified portfolio balance model is presented, in which it is shown that the impact of output growth on the exchange rate depends crucially on the origin of this growth. An improvement of the output gap is shown to actually depress the exchange rate whereas an increase in potential output growth leads to an appreciation, especially if this improvement is likely to be persistent. In an empirical example, it is shown that the equilibrium real dollar rate is indeed positively affected by high trend growth in the US, whereas it is negatively affected by a positive output gap. The model outperforms the random walk in forecasting future real dollar rates one to eight quarters ahead.