A recent literature shows how an increase in volatility reduces leverage. However, in order to explain pro-cyclical leverage it assumes that bad news increases volatility, that is, it assumes an inverse relationship between first and second moments of asset returns. This paper suggests a reason why bad news is more often than not associated with higher future volatility. We show that, in a model with endogenous leverage and heterogeneous beliefs, agents have the incentive to invest mostly in technologies that become more volatile in bad times. Agents choose these technologies because they can be leveraged more during normal times. Together with the existing literature this explains procyclical leverage. The result also gives a rationale to the pattern of volatility smiles observed in the stock options since 1987. Finally, the paper presents for the first time a dynamic model in which an asset is endogenously traded simultaneously at different margin requirements in equilibrium.
The literature on leverage until now shows how an increase in volatility reduces leverage. However, in order to explain pro-cyclical leverage it assumes that bad news increases volatility. This paper suggests a reason why bad news is more often than not associated with higher future volatility. We show that, in a model with endogenous leverage and heterogeneous beliefs, agents have the incentive to invest mostly in technologies that become volatile in bad times. Together with the old literature this explains pro-cyclical leverage. The result also gives rationale to the pattern of volatility smiles observed in the stock options since 1987. Finally, the paper presents for the first time a dynamic model in which an asset is endogenously traded simultaneously at different margin requirements in equilibrium.
We build a simple model of leveraged asset purchases with margin calls. Investment funds use what is perhaps the most basic financial strategy, called “value investing,” i.e. systematically attempting to buy underpriced assets. When funds do not borrow, the price fluctuations of the asset are normally distributed and uncorrelated across time. All this changes when the funds are allowed to leverage, i. e. borrow from a bank, to purchase more assets than their wealth would otherwise permit. During good times competition drives investors to funds that use more leverage, because they have higher profits. As leverage increases price fluctuations become heavy tailed and display clustered volatility, similar to what is observed in real markets. Previous explanations of fat tails and clustered volatility depended on “irrational behavior,” such as trend following. Here instead this comes from the fact that leverage limits cause funds to sell into a falling market: A prudent bank makes itself locally safer by putting a limit to leverage, so when a fund exceeds its leverage limit, it must partially repay its loan by selling the asset. Unfortunately this sometimes happens to all the funds simultaneously when the price is already falling. The resulting nonlinear feedback amplifies large downward price movements. At the extreme this causes crashes, but the effect is seen at every time scale, producing a power law of price disturbances. A standard (supposedly more sophisticated) risk control policy in which individual banks base leverage limits on volatility causes leverage to rise during periods of low volatility, and to contract more quickly when volatility gets high, making these extreme fluctuations even worse.
The present crisis is the bottom of a recurring problem that I call the leverage cycle, in which leverage gradually rises too high then suddenly falls much too low. The government must manage the leverage cycle in normal times by monitoring and regulating leverage to keep it from getting too high. In the crisis stage the government must stem the scary bad news that brought on the crisis, which often will entail coordinated write downs of principal; it must restore sane leverage by going around the banks and lending at lower collateral rates (not lower interest rates), and when necessary it must inject optimistic capital into firms and markets than cannot be allowed to fail. Economists and the Fed have for too long focused on interest rates and ignored collateral.
Equilibrium determines leverage, not just interest rates. Variations in leverage cause fluctuations in asset prices. This leverage cycle can be damaging to the economy, and should be regulated.
The introduction and widespread use of credit cards increases trading efficiency but, by also increasing the velocity of money, it causes inflation, in the absence of monetary intervention.
If the monetary authority attempts to restore pre-credit card price levels by reducing the money supply, it might have to sacrifice the efficiency gains.
When there is default on credit cards, there is even more inflation, and less efficiency gains. The monetary authority might then have to accept less than pre-credit card efficiency in order to restore pre-credit card price levels, or else it will have to accept inflation if it is unwilling to cut efficiency below pre-credit card levels. This could be a source of stagflation.
One measure of the health of the Social Security system is the difference between the market value of the trust fund and the present value of benefits accrued to date. How should present values be computed for this calculation in light of future uncertainties? We think it is important to use market value. Since claims on accrued benefits are not currently traded in financial markets, we cannot directly observe a market value. In this paper, we use a model to estimate what the market price for these claims would be if they were traded.
In valuing such claims, the key issue is properly adjusting for risk. The traditional actuarial approach — the approach currently used by the Social Security Administration in generating its most widely cited numbers — ignores risk and instead simply discounts “expected” future flows back to the present using a risk-free rate. If benefits are risky and this risk is priced by the market, then actuarial estimates will differ from market value. Effectively, market valuation uses a discount rate that incorporates a risk premium.
Developing the proper adjustment for risk requires a careful examination of the stream of future benefits. The U.S. Social Security system is “wage-indexed”: future benefits depend directly on future realizations of the economy-wide average wage index. We assume that there is a positive long-run correlation between average labor earnings and the stock market. We then use derivative pricing methods standard in the finance literature to compute the market price of individual claims on future benefits, which depend on age and macro state variables. Finally, we aggregate the market value of benefits across all cohorts to arrive at an overall value of accrued benefits.
We find that the difference between market valuation and “actuarial” valuation is large, especially when valuing the benefits of younger cohorts. Overall, the market value of accrued benefits is only 4/5 of that implied by the actuarial approach. Ignoring cohorts over age 60 (for whom the valuations are the same), market value is only 70% as large as that implied by the actuarial approach.
Equilibrium determines leverage, not just interest rates. Variations in leverage cause fluctuations in asset prices. This leverage cycle can be damaging to the economy, and should be regulated.
We argue that even when macroeconomic variables are constant, underlying microeconomic uncertainty and borrowing constraints generate inflation.
We study stochastic economies with fiat money, a central bank, one nondurable commodity, countably many time periods, and a continuum of agents. The aggregate amount of the commodity remains constant, but the endowments of individual agents fluctuate “independently” in a random fashion from period to period. Agents hold money and, prior to bidding in the commodity market each period, can either borrow from or deposit in a central bank at a fixed rate of interest. If the interest rate is strictly positive, then typically there will not exist an equilibrium with a stationary wealth distribution and a fixed price for the commodity. Consequently, we investigate stationary equilibria with inflation, in which aggregate wealth and prices rise deterministically and at the same rate. Such an equilibrium does exist under appropriate bounds on the interest rate set by the central bank and on the amount of borrowing by the agents.
If there is no uncertainty, or if the stationary strategies of the agents select actions in the interior of their action sets in equilibrium, then the classical Fisher equation for the rate of inflation continues to hold and the real rate of interest is equal to the common discount rate of the agents. However, with genuine uncertainty in the endowments and with convex marginal utilities, no interior equilibrium can exist. The equilibrium inflation must then be higher than that predicted by the Fisher equation, and the equilibrium real rate of interest underestimates the discount rate of the agents.