Momentum in individual stock returns emanates from momentum in factor returns. Most factors are positively autocorrelated: the average factor earns a monthly return of 1 basis point following a year of losses and 53 basis points following a positive year. Factor momentum explains all forms of...

We propose a discrete-time stochastic volatility model in which regime switching serves three purposes. First, changes in regimes capture low frequency variations, which is their traditional role. Second, they specify intermediate frequency dynamics that are usually assigned to smooth...

The returns to hedge funds and other alternative investments are often highly serially correlated in sharp contrast to the returns of more traditional investment vehicles such as long-only equity portfolios and mutual funds. In this paper, we explore several sources of such serial correlation...

This paper investigates the relationship between stock market trading volume and the autocorrelations of daily stock index returns. The paper finds that stock return autocorrelations tend to decline with trading volume. The paper explains this phenomenon using a model in which risk-averse...

We analyze the prices of owner-occupied housing in 97 metropolitan areas between 1980 and 2011. Our tests indicate that price changes exhibit positive serial correlation at the one year intervals, with subsequent reversals of price changes over longer intervals. Consistent with our simple model,...

We propose a Bayesian procedure for exploiting small, possibly long-lag linear predictability in the innovations of a finite order autoregression. We model the innovations as having a log-spectral density that is a continuous mean-zero Gaussian process of order 1/√T. This local embedding makes...

The SVAR and narrative approaches to estimating tax multipliers deliver significantly different results. The former yields multipliers of about 1 percent, whereas the latter produces much larger multipliers of about 3 percent. The SVAR and narrative approaches differ along two important...

In the early 1940s, Haavelmo proposed a probabilistic structure for econometric modeling, aiming to make econometrics useful for public decision making. His fundamental contribution has become thoroughly embedded in subsequent econometric research, yet it could not fully answer all the deep...