We propose an iterative procedure to efficiently estimate models with complex log-likelihood functions and the number of parameters relative to the observations being potentially high. Given consistent but inefficient estimates of sub-vectors of the parameter vector, the procedure yields...

We study the accuracy and usefulness of automated (i.e., machine-generated) valuations for illiquid and heterogeneous real assets. We assemble a database of 1.1 million paintings auctioned between 2008 and 2015. We use a popular machine-learning technique - neural networks - to develop a pricing...

We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and non-visual object characteristics. We find that higher automated valuations relative to auction house pre-sale estimates are associated with substantially higher...

This paper considers a trading game in which sequentially arriving liquidity traders either opt for a market order or for a limit order. One class of traders is considered to have an extended trading horizon, implying their impatience is linked to their trading orientation. More specifically,...

We report evidence that the presence of hidden liquidity is associated with greater liquidity in the order books, greater trading volume, and smaller price impact. Limit and market order submission behavior changes when hidden liquidity is present consistent with at least some traders being able...

Innovative automated execution strategies like Algorithmic Trading gain significant market share on electronic market venues worldwide, although their impact on market outcome has not been investigated in depth yet. In order to assess the impact of such concepts, e.g. effects on the price...

This paper analyzes liquidity in an order driven market. We only investigate the best limits in the limit order book, but also take into account the book behind these inside prices. When subsequent prices are close to the best ones and depth at them is substantial, larger orders can be executed...

This paper provides theory as well as empirical results for pre-averaging estimators of the daily quadratic variation of asset prices. We derive jump robust inference for pre-averaging estimators, corresponding feasible central limit theorems and an explicit test on serial dependence in...

This paper studies the market quality of an internalization system which is designed as part of an open limit order book (the Xetra system operated by Deutsche Börse AG). The internalization sys-tem (Xetra BEST) guarantees a price improvement over the inside spread in the Xetra order book. We...

We revisit the role of time in measuring the price impact of trades using a new empirical method that combines spread decomposition and dynamic duration modeling. Previous studies which have addressed the issue in a vector-autoregressive framework conclude that times when markets are most active...