We report strong evidence that changes of momentum, i.e. "acceleration", defined as the first difference of successive returns, provide better performance and higher explanatory power than momentum. The corresponding Γ-factor explains the momentum-sorted portfolios entirely but not the reverse....

We introduce a new class of momentum strategies, the risk-adjusted time series momentum (RAMOM) strategies, which are based on averages of past futures returns, normalized by their volatility. We test these strategies on a universe of 64 liquid futures contracts and show that RAMOM strategies...

We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second...

We propose a dynamic Rational Expectations (RE) bubble model of prices with the intention to exploit it for and evaluate it on optimal investment strategies. Our bubble model is defined as a geometric Brownian motion combined with separate crash (and rally) discrete jump distributions associated...

A new model class for univariate asset returns is proposed which involves the use of mixtures of stable Paretian distributions, and readily lends itself to use in a multivariate context for portfolio selection. The model nests numerous ones currently in use, and is shown to outperform all its...

The use of mixture distributions for modeling asset returns has a long history in finance. New methods of demonstrating support for the presence of mixtures in the multivariate case are provided. The use of a two-component multivariate normal mixture distribution, coupled with shrinkage via a...

We classify the sentiment of a large sample of StockTwits messages as bullish,bearish or neutral, and create a stock-aggregate daily sentiment polarity measure.Polarity is positively associated with contemporaneous stock returns. On average,polarity is not able to predict next-day stock returns....

Standard strategic asset allocation procedures usually neglect market interaction. However, returns are not generated in a vacuum but are the result of the market's price discovery mechanism which is driven by investors' investment strategies. Evolutionary finance accounts for this and...

Average skewness, which is defined as the average of monthly skewness values across firms, performs well at predicting future market returns. This result still holds after controlling for the size or liquidity of the firms or for current business cycle conditions. We also find that average...

We build a macroeconomic model for Switzerland, the Euro Area, and the USA that drives the dynamics of several asset classes and the liabilities of a representative Swiss (defined-contribution) pension fund. This encompassing approach allows us to generate correlations between returns on assets...