In this article, we examine how model selection in neural networks can be guided by
statistical procedures such as hypothesis tests, information criteria and cross validation. The …

In this paper we empirically analyze the permanent price impact of trades by investigating
the relation between unexpected net order flow and price changes. We use intraday data on …

In this paper we apply statistical inference techniques to build neural network models which
are able to explain the prices of call options written on the German stock index DAX. By …

We develop a new family of estimators of the covariance matrix that relies solely on forward-looking
information. It uses only current prices of plain-vanilla options. In an out-of-sample …

In this paper, we apply Markowitz's approach of portfolio selection to government bond
portfolios. As a main feature of our analysis, we use term structure models to estimate expected …

We investigate the term structure of bond market illiquidity premia and show that the term
structure varies greatly over time. Short and long end are strictly separated suggesting that …

Providing a framework to integrate regret as an additional decision criterion in Markowitz’s
model of portfolio selection, we propose two different views on regret: An investor might feel …

Food price volatility has re‐emerged as an important topic of political discussion since the
food price crisis of 2007–2008. Different volatility drivers have been identified for different …

In this chapter, we present a literature review of the agricultural and food price volatility patterns
observed over the last decade. We focus on studies published in peer-reviewed journals…

Option‐implied betas are a promising alternative to historical beta estimators, because they
are inherently forward‐looking and can incorporate new information immediately and fully. …