This paper presents an innovative new approach to investment portfolio design, which applies a discrete, state-based methodology to defining market states and making asset allocation decisions with respect to both current and future state membership. State membership is based on attributes taken...

Quantifiable, measurable risk is of critical importance when making data-driven decisions in finance and investment management, but what if the generally accepted practice of the investment industry for calculating risk possessed incorrect mathematical assumptions and embedded biases? This piece...

This paper presents an innovative new approach to investment portfolio design, which applies a discrete, state-based methodology to defining market states and making asset allocation decisions with respect to both current and future state membership. State membership is based on attributes taken...

Market participants often invoke the concept of discrete state when discussing financial markets. Bull market, bear market, depression, and recession are all terms that map to discrete market states. Mental models of how markets behave in each state and transition between states are then applied...

We propose a novel asset allocation model using a Markov process of states defined by clustered efficient frontier coefficients. While most research in Markov models of the market characterize regimes using return and volatility, we instead propose characterizing these states using efficient...

Quantifiable, measurable risk is of critical importance when making data-driven decisions in finance and investment management, but what if the generally accepted practice of the investment industry for calculating risk possessed incorrect mathematical assumptions and embedded biases? This piece...

The increasing pace and cost associated with the development and exploitation of new technologies is making it prohibitive for organizations to work on their own. Supply chain companies are expected to share the risks of developing technologies, without necessarily being offered long-term...

We measure the incidence of latency arbitrage for cross-listed stocks around the time of an exogenous shock that made the markets faster. Our sample is from NASDAQ Nordic and consists of Nordic blue chip firms listed and traded in multiple markets. We document a sharp decline in the incidence of...

We propose a near zero-intelligence agent-based model of the E-Mini S&P 500 futures market that allows for a close examination of market microstructure in the context of a flash crash. Several classes of agents are characterized by how fast they trade and where they place trades in the limit...

Electronic markets have emerged as popular venues for the trading of a wide variety of financial assets, and computer based algorithmic trading has also asserted itself as a dominant force in financial markets across the world. Identifying and understanding the impact of algorithmic trading on...