Asset Pricing

April 11, 2014
Lauren Cohen and Christopher Malloy, Harvard Business School, Organizers

Lubos Pastor, University of Chicago and NBER; Robert Stambaugh, University of Pennsylvania and NBER; and Lucian Taylor, University of Pennsylvania

Scale and Skill in Active Management

Pastor, Stambaugh, and Taylor empirically analyze the nature of returns to scale in active mutual fund management. They find strong evidence of decreasing returns at the industry level: as the size of the active mutual fund industry increases, a fund's ability to outperform passive benchmarks declines. At the fund level, all methods considered indicate decreasing returns, but estimates that avoid econometric biases are insignificant. The authors also find that the active management industry has become more skilled over time. This upward trend in skill coincides with industry growth, which precludes the skill improvement boosting fund performance. Finally, the authors find that performance deteriorates over a typical fund's lifetime. This result can also be explained by industry-level decreasing returns to scale.

Ralph Koijen, London Business School, and Motohiro Yogo, Federal Reserve Bank of Minneapolis

Shadow Insurance

Liabilities ceded by life insurers to shadow reinsurers (that is, affiliated and less regulated off-balance-sheet entities) grew from $11 billion in 2002 to $364 billion in 2012. Koijen and Yogo show that companies using shadow insurance, which capture half of the market share, ceded 25 cents of every dollar insured to shadow reinsurers in 2012, up from 2 cents in 2002. The authors' adjustment for shadow insurance reduces risk-based capital by 53 percentage points (or 3 rating notches) and raises impairment probabilities by a factor of four. They develop a structural model of the life insurance industry to estimate the impact of current policy proposals to curtail shadow insurance. Without shadow insurance, marginal cost would rise by 18 percent, and annual life insurance underwritten would fall by 23 percent.

Matthew Baron, Princeton University, and Wei Xiong, Princeton University and NBER

Credit Expansion and Financial Instability: Evidence from Stock Prices

Baron and Xiong examine financial instability associated with bank credit expansion in a set of 23 developed countries during the years 1920 to 2012. They find that credit expansion, measured by the three-year change in bank-credit-to-GDP ratio, predicts a significantly increased crash risk in the returns of the bank equity index and the equity market index in the subsequent one to eight quarters. Despite the increased crash risk, credit expansion predicts both lower mean and median returns of these indices in the subsequent quarters, even after controlling for a host of variables known to predict the equity premium. Furthermore, conditional on credit expansion of a country exceeding a modest threshold of 1.5 standard deviations, the predicted excess return for the bank equity index in the subsequent four quarters is significantly negative, with a magnitude of nearly –20 percent, while the positive predicted excess return subsequent to a credit contraction of the same size is substantially more modest. These findings present a challenge to the views that credit expansions are caused either by banks acting against the will of shareholders or by elevated risk appetites of shareholders, and instead suggest a role for the optimism of bankers and stock investors.

Marcin Kacperczyk, Imperial College and NBER; Jaromir Nosal, Columbia University; and Luminita Stevens, University of Maryland

Investor Sophistication and Capital Income Inequality

What contributes to the growing income inequality across U.S. households? Kacperczyk, Nosal, and Stevens develop an information-based general equilibrium model that links capital income derived from financial assets to a level of investor sophistication. Their model implies income inequality between sophisticated and unsophisticated investors that is growing in investors' aggregate and relative sophistication in the market. They show that their model is quantitatively consistent with the data from the U.S. market. In addition, they provide supporting evidence for their mechanism using a unique set of cross-sectional and time-series predictions on asset ownership and stock turnover.

Tarun Ramadorai and Cristian Badarinza, University of Oxford

Preferred Habitats and Safe-Haven Effects: Evidence from the London Housing Market

The infrequent nature of economic and political crises means that using pure time-series methods to distinguish safe haven demand effects on asset prices from a wide range of alternative drivers can be problematic. Badarinza and Ramadorai present a new cross-sectional approach motivated by the insight that investors may have different "preferred habitats" within a broad asset class. The authors employ this strategy using large databases of historical housing transactions in London and find that economic and political risk in southern Europe, China, the Middle East, Russia, and South Asia helps explain price and volume dynamics in the London housing market over the past two decades. Safe haven effects on the London housing market are long-lasting and significant, but temporary. The method also uncovers intriguing insights about cross-country variation in preferred habitats within London.

Stefano Giglio, University of Chicago and NBER; Matteo Maggiori, New York University and NBER; and Johannes Stroebel, New York University

Very Long-Run Discount Rates

Giglio, Maggiori, and Stroebel provide the first direct estimates of how agents trade off immediate costs and uncertain future benefits that occur in the very long run, 100 or more years away. They exploit a unique feature of housing markets in England, Wales, and Singapore where residential property ownership takes the form of either leaseholds or freeholds. Leaseholds are temporary, pre-paid, and tradable ownership contracts with maturities between 50 and 999 years, while freeholds are perpetual ownership contracts. The difference between leasehold and freehold prices represents the present value of perpetual rental income starting at leasehold expiry. The authors estimate the price discounts for varying leasehold maturities compared to freeholds and extremely long run leaseholds via hedonic regressions using proprietary datasets of the universe of transactions in each country. Agents discount very long run cash flows at low rates, assigning high present values to cash flows hundreds of years in the future. For example, 100-year leaseholds are valued up to 15 percent less than otherwise identical freeholds. Given the riskiness of rents, this suggests that both long-term risk-free discount rates and long-term risk premiums are low. Together with the relatively high average return to housing, this also implies a downward-sloping term structure of discount rates. The authors' results provide a new testing ground for asset pricing theories, including the analysis of bubbles, and have direct implications for climate change policy, long-run fiscal policy, and the conduct of cost benefit analyses. The authors find that households are relatively more willing to pay today to ensure reduced climate costs in the distant future, but relatively less willing to pay to only reduce the risk of bad climate outcomes compared to the leading environmental models.

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