We consider dynamic sublinear expectations (i.e., time-consistent coherent risk measures) whose scenario sets consist … of singular measures corresponding to a general form of volatility uncertainty. We derive a càdlàg nonlinear martingale …

how these volatility measures can be used for risk management. We find that momentum risk management significantly …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 …

Undiversifiable (or systematic risk) has long been an enemy of investors. Many countercyclical strategies have been … technique, founded on the premise of physiological bias and risk-aversion. We take a behavioral discussion in order to … negative betas to the S&P 500, while exhibiting similar risk-adjusted excess returns over both bull and bear markets. Further …

volatility jump diffusion model …

-especially volatility and illiquidity shocks-over the subprime crisis in order to investigate their market timing activities. In a … systematic risk is highly nonlinear in extreme scenarios-especially during the subprime crisis. We find that countercyclical …-traditional risk premia by deliberately increasing their systematic risk while the later focus more on minimizing risk. Our results …

We test the existence of a time-series relationship between the aggregate idiosyncratic volatility and the market index … return at the global level by introducing various global measures of aggregate idiosyncratic volatility. We offer four … definitions of aggregate global idiosyncratic volatility (GIVOL) based on factor models and two other definitions, which are free …

One of the main explanations for the idiosyncratic volatility (IVOL) puzzle (i.e., the negative relation between lagged … IVOL and returns) is a missing risk factor. We show analytically that if IVOL proxies for a missing risk factor, then the … risk factors. Overall, our results suggest that both diversifiable (i.e., true idiosyncratic risk) and non …

significantly, when an inter-temporal risk parity strategy is applied. Volatility clustering and fat tails are behind this …Inter-temporal risk parity is a strategy that rebalances risky assets and cash in order to target a constant level of … ex-ante risk over time. When applied to equities and compared to a buy-and-hold portfolio it is known to improve the …

We discuss how to build ETF risk models. Our approach anchors on i) first building a multilevel (non …-)binary classification/taxonomy for ETFs, which is utilized in order to define the risk factors, and ii) then building the risk models based … on these risk factors by utilizing the heterotic risk model construction of https://ssrn.com/abstract=2600798 (for binary …