This paper analyses the co-movements between the US stock market and several commodity futures between 1998 and 2011. It computes dynamic conditional correlations at (i) 1-hour, (ii) 5-minute, (iii) 10-second, and (iv) 1-second frequencies and documents a synchronized structural break,...

This paper examines a popular stock message board and finds slight daily predictability using supervised learning algorithms when combining daily sentiment with historical price information. Additionally, with the profit potential in trading stocks, it is of no surprise that a number of popular...

The problem of capital allocation to a set of strategies could be partially avoided or at least greatly simplified with an appropriate strategy approval decision process. This paper proposes such a procedure. We begin by splitting the capital allocation problem into two sequential stages:...

We propose and study a stylization of high frequency trading (HFT). Our interest is an order book which consists of orders from slow liquidity traders and orders from high-frequency traders. We would like to frame a model which is amenable to the (seemingly natural) mathematical toolkit of...

Using data from world stock exchange indices prior to and during periods of global financial crises, clusters and networks of indices are built for asset graphs based on distance thresholds and diverse periods of time, so that it is then possible to analyze how clusters are formed according to...

This paper provides a “non-extensive” information theoretic perspective on the relationship between risk and incomplete states uncertainty. Theoretically and empirically, we demonstrate that a substitution effect between the latter two may take place. Theoretically, the “non-extensive”...

In this paper we investigate trading with optimal mean reverting portfolios subject to cardinality constraints. First, we identify the parameters of the underlying VAR(1) model of asset prices and then the quantities of the corresponding Ornstein-Uhlenbeck (OU) process are estimated by pattern...

Intraday volatility and market impact models in volume time are proposed. We build an intraday volatility profile to capture non-stationarity of intraday price returns and utilize a fractional Brownian motion process to measure deviations from square root scaling rule of volatility. <p> We propose...</p>

This paper investigates the profitability of a trading strategy based on training a model to identify stocks with high or low predicted returns. A tail set is defined to be a group of stocks whose volatility-adjusted price change is in the highest or lowest quantile, for example the highest or...

Interview with Andrei Kirilenko