The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and nonellipticity. It introduces a so-called...

We report strong evidence that changes of momentum, i.e. "acceleration", defined as the first difference of successive returns, provide better performance and higher explanatory power than momentum. The corresponding Γ-factor explains the momentum-sorted portfolios entirely but not the reverse....

We investigate the impact of high-frequency trading (HFT) on market quality and investor welfare using a general limit order book model. We find that while the presence of HFT always improves market quality under symmetric information, under asymmetric information this is the case only if...

We construct mean-variance portfolios using a factor model approach. We show the importance of portfolio allocation for large unbalanced equity data sets using the full CRSP database. We compare the performance of our portfolio construction methodology to the 1/N naive diversification strategy,...

We study how short-term informational advantages can be monetized in a high-frequency setting, when large inventories are explicitly penalized. We find that if most of the additional information is revealed regardless of the high-frequency traders' actions, then fast inventory management allows...

We study optimal investment with multiple assets in the presence of small proportional transaction costs. Rather than computing an asymptotically optimal no-trade region, we optimize over suitable trading frequencies. We derive explicit formulas for these and the associated welfare losses due to...

We introduce a simulation method for dynamic portfolio valuation and risk management building on machine learning with kernels. We learn the dynamic value process of a portfolio from a finite sample of its cumulative cash flow. The learned value process is given in closed form thanks to a...

Covariance matrix forecasts for portfolio optimization have to balance sensitivity to new data points with stability in order to avoid excessive rebalancing. To achieve this, a new robust orthogonal GARCH model for a multivariate set of non-Gaussian asset returns is proposed. The conditional...

Monetary risk measures classify a financial position by the minimal amount of external capital that must be added to the position to make it acceptable.We propose a new concept: intrinsic risk measures. The definition via external capital is avoided and only internal resources appear. An...

We consider the problem of hedging a European contingent claim in a Bachelier model with transient price impact as proposed by Almgren and Chriss. Following the approach of Rogers and Singh [24] and Naujokat and Westray, the hedging problem can be regarded as a cost optimal tracking problem of...