We introduce a new deep learning architecture for predicting price movements from limit order books. This architecture uses a causal convolutional network for feature extraction in combination with masked self-attention to update features based on relevant contextual information. This...

Hedging of illiquid financial instruments is carried out with liquid instruments that, as a rule, have simpler payoff functions. For example, hedging of Asian or long-dated put options is carried out with vanilla puts, hedging of Bermuda swaptions is done with vanilla swaptions, etc. This kind...

Macroeconomic data is often noisy, contradictory and lagging. These limitations render the data difficult to integrate into a robust quantitative investment strategy that generates excess returns. This paper outlines a new approach to macro investing that removes these inherent limitations in...

This work presents an asset pricing model that under rational expectation equilibrium perspective shows how, depending on risk aversion and noise volatility, a risky-asset has one equilibrium price that differs in term of efficiency: an informational efficient one (similar to Campbell and Kyle...

ARFIMA models, as advocated by Jiang and Tian for use in long-term volatility forecasting, are found in a follow-up empirical study to be dominated by a certain simple historical predictor of stock price volatility at a five-year horizon. (This particular historical predictor is not recommended...

Hedge Fund returns are often highly serially correlated mainly due to illiquidity exposures given that investments in such securities tend to be inactively traded and associated market prices are not always readily available. Following that, observed returns of such alternative investments tend...

An impulse response function is derived for a vector autogressive model with a multivariate GARCH-in-Mean process. The multivariate GARCH volatility speci cation is based on Tsiaplias and Chua (2009) and accommodates both direct and indirect volatility spillovers. The impulse response function...

Traditional portfolio optimization models specify placement of capital as rather irrevocably and fully at risk through investment horizon(s) or continuously. Under this constraint, asset class allocation typically serves as primary mode of diversification, pursuing risk moderation by seeking to...

In recent years both equity and bond markets have been afflicted by high volatility. In order to build up a portfolio on a quantitative basis, several models may be used, such as minimum variance portfolio or equally weighted portfolio. In 2008/09 another way to deal with diversification came...

In finance, decision making and choice requires that we assume that asset prices tend to trend. This assumption also logically enables us to construct exits to limit losses and protect capital. But investors have good reason to be uneasy regarding the potential for significant loss when using a...