We present Algorithmic Adjoint Differentiation (AAD), also known as Automatic Adjoint Differentiation, which computes the derivative(s) of computer code. In finance this leads to a relatively new and novel approach, pioneered by (Giles and Glasserman, 2006), to compute financial risks. When...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

This paper derives a robust online equity trading algorithm that achieves the greatest possible percentage of the final wealth of the best pairs rebalancing rule in hindsight. A pairs rebalancing rule chooses some pair of stocks in the market and then perpetually executes rebalancing trades so...

This paper examines the proportion of wealth invested in stock and bond portfolios as a function of the investors' age, i.e., investment horizon. It has become increasingly popular to advice investors to relocate their funds from a primarily stock portfolio to a primarily bond portfolio as they...

A concise look in three unrelated, yet complex environments reveals a strong human dependence on the recognition heuristic. Its marketability to the mind as a good decision making tool (over other complex approaches), is shown to be almost innate and ultimately successful. The three...

For a market with m assets and T discrete trading sessions, Cover and Ordentlich (1998) found that the “Cost of Achieving the Best Rebalancing Rule in Hindsight” is p(T, m) = _{n₁ ···^Σ n_m=T} (n₁,^T...,n_m)(n₁/T)(n₁ · · · (n_m/T)^n_m. Their super-replicating strategy is impossible to compute...

This paper derives a robust online equity trading algorithm that achieves the greatest possible percentage of the final wealth of the best pairs rebalancing rule in hindsight. A pairs rebalancing rule chooses some pair of stocks in the market and then perpetually executes rebalancing trades so...

We study the impact of liquidity in optimal portfolio choice under leveraging to improve risk-adjusted and absolute returns. We consider a quasi-elastic market with continuous trading where temporary liquidity costs are sufficiently large relative to permanent impact. We show analytically that...

We develop scenario-based stochastic programming models for hedging the risks of international portfolios using options. The models provide an increasing level of integration in managing market and foreign exchange (FX) risks. We start with a single-stage model with currency options for...

All the financial practitioners are working in incomplete markets full of unhedgeable risk-factors. Making the situation worse, they are only equipped with the imperfect information on the relevant processes. In addition to the market risk, fund and insurance managers have to be prepared for...