This is a summary of links featured on Quantocracy on Monday, 05/27/2019. To see our most recent links, visit the Quant Mashup. Read on readers!
-
Volatility vs Risk [Two Centuries Investments]Much has been written on this topic, but for what its worth, here is my take. Volatility is how much something moves up and down. The stock market is more volatile than the bond market, on average. Yet, a black-box hedge fund might be less volatile than S&P500, but is it less risky? Risk = Unexpected Outcomes + Unrecoverable Consequences In my view, Risk is an unexpected outcome that
-
Cheap versus Expensive Countries [Factor Research]A global value portfolio on country level features structural country biases Returns were positive since 1990, but lacked consistency Value on country and single stock level exhibit the same trends, highlighting common performance drivers INTRODUCTION Holding Value stocks is emotionally challenging as cheap valuations are usually due to companies experiencing temporary or structural issues such as
-
Extended Kalman Filter [Dekalog Blog]In the code box below I provide code for an Extended Kalman filter to model a sine wave. This is a mashup of code from a couple of toolboxes I have found online, namely learning-the-extended-kalman-filter and EKF/UKF Tollbox for Matlab/Octave. The modelled states are the phase, angular frequency and amplitude of the sine wave and the measurement is the ( noisy ) sine wave value itself.
-
An Updated Look At Memorial Week Historical $SPX Performance [Quantifiable Edges]The week of Memorial Day has shown some interesting seasonal tendencies over the years. But it has been less consistent recently. The chart below is one I have shown in the past, and have now updated. It examines SPX performance from the Friday before Memorial Day to the Friday after it. 2019-05-24 There was no substantial edge apparent throughout the 70s, but starting in 1983 through 2009 there
-
Alternatives To Correlation For Quantifying Diversification [Capital Spectator]Diversification is famously described as the only free lunch in investing and so its no surprise that modeling, analyzing and otherwise dissecting the concept is a core part of portfolio design and management. The correlation coefficient is often the go-to metric in this corner of finance. But like any one statistical measure, there are pros and cons with correlation and so relying on it
-
Risk-Factor Identification: A Critique [Alex Chinco]In standard cross-sectional asset-pricing models, expected returns are governed by exposure to aggregate risk factors in a market populated by fully rational investors. Heres how these models work. Because investors are fully rational, they correctly anticipate which assets are most likely to have low returns in especially inconvenient future states of the worldi.e., returns that are highly
-
U.S. Treasuries: decomposing the yield curve and predicting returns [SR SV]A new paper proposes to decompose the U.S. government bond yield curve by applying a bootstrapping method that resamples observed return differences across maturities. The advantage of this method over the classical principal components approach would be greater robustness to misspecification of the underlying factor model. Hence, the method should be suitable for bond return predictions