A prominent factor used in most models predicting stock returns is firm size. Yet no consensus has emerged on the magnitude and stability of the size premium, with some researchers even questioning the usefulness of the factor. To take stock of the voluminous academic literature on the size...

We examine in this paper the training and test set performance of several equity factor models with a dataset of 20 years of data, 1,200 stocks and 100 factors. First, we examine several models to forecast expected returns, which can be used as baselines for more complex models: linear...

Three concepts: stochastic discount factors, multi-beta pricing and mean-variance efficiency, are at the core of modern empirical asset pricing. This chapter reviews these paradigms and the relations among them, concentrating on conditional asset-pricing models where lagged variables serve as...

For years, research has been conducted to correctly model and predict the risk and return structures of Private Equity (PE) funds. Although past research has revealed valuable insight into the features of those funds, most risk and return model struggle with the dispersion of PE funds' returns,...

A time-series basis decomposition and trend extraction technique known as Empirical Mode Decomposition (EMD), designed for multi-scale time-frequency decomposition in non-stationary time-series settings, will be combined with Regularised Covariance Regression (RCR) methods to produce a framework...

The paper discusses the lower partial moments for the return of the investment portfolio which consists of the assets whose random incomes are modeled by variance-gamma, gamma distributions and constants.The formulas depend on values of generalized hypergeometric functions. As a corollary, the...

We introduce a methodology for dynamic modelling and forecasting of realized covariance matrices based on generalization of the heterogeneous autoregressive model (HAR) for realized volatility. Multivariate extensions of popular HAR framework leave substantial information unmodeled in residuals....

Asset allocation strategies which utilize stop-loss and stop-gain rules may dramatically decrease risk and even increase long-term return relative to passive investing. I introduce an asset allocation strategy which shifts portfolio weights based on simplistic stop rules. The two-asset (S&P...

In the past 20 years, momentum or trend following strategies have become an established part of the investor toolbox. We introduce a new way of analyzing momentum strategies by looking at the information ratio (IR, average return divided by standard deviation). We calculate the theoretical IR of...