A comprehensive portfolio construction under stochastic environment

Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. ^ A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: (a) increase the efficiency of the portfolio optimization process, (b) implement large-scale optimizations, and (c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. ^ The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. ^ The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH). ^

A Comprehensive Portfolio Construction Under Stochastic Environment

Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: a) increase the efficiency of the portfolio optimization process, b) implement large-scale optimizations, and c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH).

The correlation of structure and electronic properties near the surface of transition metal oxides

The strong couplings between different degrees of freedom are believed to be responsible for novel and complex phenomena discovered in transition metal oxides (TMOs). The physical complexity is directly responsible for their tunability. Creating surfaces/interfaces add an additional ' man-made' twist, approaching the quantum phenomena of correlated materials. ^ The dissertation focused on the structural and electronic properties in proximity of surface of three prototype TMO compounds by using three complementary techniques: scanning tunneling microscopy, angle-resolved photoelectron spectroscopy and low energy electron diffraction, particularly emphasized the effects of broken symmetry and imperfections like defects on the coupling between charge and lattice degrees of freedom. ^ Ca1.5Sr0.5RuO4 is a layered ruthenate with square lattice and at the boundary of magnetic/orbital instability in Ca2-xSrxRuO4. That the substitution of Sr 2+ with Ca2+ causing RuO6 rotation narrows the dxy band width and changes the Fermi surface topology. Particularly, the γ(dxy) Fermi surface sheet exhibited hole-like in Ca1.5Sr0.5RuO4 in contrast to electron-like in Sr2RuO4, showing a strong charge-lattice coupling. ^ Na0.75CoO2 is a layered cobaltite with triangular lattice exhibiting extraordinary thermoelectric properties. The well-ordered CoO2-terminated surface with random Na distribution was observed. However, lattice constants of the surface are smaller than that in bulk. The surface density of states (DOS) showed strong temperature dependence. Especially, an unusual shift of the minimum DOS occurs below 230 K, clearly indicating a local charging effect on the surface. ^ Cd2Re2O7 is the first known pyrochlore oxide superconductor (Tc ∼ 1K). It exhibited an unusual second-order phase transition occurring at TS1 = 200 K and a controversial first-order transition at TS2 = 120 K. While bulk properties display large anomalies at TS1 but rather subtle and sample-dependent changes at TS2, the surface DOS near the EF show no change at T s1 but a substantial increase below TS2---a complete reversal as the signature for the transitions. We argued that crystal imperfections, mainly defects, which were considerably enhanced at the surface, resulted in the transition at TS2. ^