PURPOSE: The purpose of this paper is to analyse regulatory reform in the wake of the financial crisis of 2007-2008.

DESIGN/METHODOLOGY/APPROACH: The paper proposes a framework for regulatory reform that begins with the observation that financial manias and panics cannot be legislated away, and may bean unavoidable aspect of modern capitalism.

FINDINGS: Financial crises are unavoidable when hardwired human behavior—fear and greed, or“animal spirits”—is combined with free enterprise, and cannot be legislated or regulated away. Like hurricanes and other forces of nature, market bubbles, and crashes cannot be entirely eliminated, but their most destructive consequences can be greatly mitigated with proper preparation. In fact, the most damaging effects of financial crisis come not from loss of wealth, but rather from those who are unprepared for such losses and panic in response. This perspective has several implications for the types of regulatory reform needed in the wake of the financial crisis of 2007-2008, all centered around the need for greater transparency, improved measures of systemic risk, more adaptive regulations,including counter-cyclical leverage constraints, and more emphasis on financial literacy starting in high school, including certifications for expertise in financial engineering for the senior management and directors of all financial institutions.

ORIGINALITY/VALUE: The paper stresses how we must resist the temptation to react too hastily to market events, and deliberate thoughtfully and broadly, instead, craft new regulations for the financial system of the twenty-first century. Financial markets do not need more regulation; they need smarter and more effective regulation

This document is the written testimony submitted to the US House of Representatives Financial Services Committee for its hearing on systemic risk regulation, held October 29, 2009, and it is not a formal academic research paper, but is intended for a broader audience of policymakers and regulators. Academic readers may be alarmed by the lack of comprehensive citations and literature review, the imprecise and qualitative nature of certain arguments, and the abundance of illustrative examples, analogies, and metaphors. Accordingly, such readers are hereby forewarned—this paper is not research, but is instead a summary of the policy implications that I have drawn from my interpretation of that research. This testimony focuses on three themes: (1) Establishing the means to measure and monitor systemic risk on an ongoing basis is the single-highest priority for financial regulation reform; (2) Systemic risk measurement and regulation will likely require new legislation compelling systemically important entities to provide more transparency on a confidential basis to regulators, e.g., information regarding their assets, liabilities, holdings, leverage, collateral, liquidity, counterparties, and aggregate exposures to key financial variables and other risks; and (3) Because systemic risk cuts across multiple regulatory bodies that do not necessarily share the same objectives and constraints, it may be more efficient to create an independent agency patterned after the National Transportation Safety Board (NTSB), solely devoted to measuring, tracking, and investigating systemic risk events in support of—not in competition with—all regulatory agencies.

In this guest post, MIT Sloan Prof. Andrew Lo provides an insightful look at how "extended periods of prosperity act as an anesthetic in the human brain," lulling everyone involved into "a drug-induced stupor that causes us to take risks that we know we should avoid."

The push for financial regulatory reform has highlighted an important debate surrounding the Efficient Markets Hypothesis, the idea that market prices are rationally determined and fully reflect all available information. If true, the EMH implies that regulation is largely unnecessary because markets allocate resources and risks efficiently via the "invisible hand". However, critics of the EMH argue that human behaviour is hardly rational but is driven by "animal spirits" that generate market bubbles and busts, and regulation is essential for reining in misbehavior.

In this opinion piece, MIT Sloan Prof. Andrew Lo writes, “The world has become more complex over the past 20 years, and we need to update our investment paradigm to incorporate these new complexities... To achieve true diversification, investors must now have a broader set of asset classes and risk exposures, long and short, in their portfolios.”

The recent proposal by the Fed to regulate bankers’ compensation practices is understandable given the events of the past two years, but setting caps on salaries and bonuses misses the fundamental problem of compensation on Wall Street. Despite the public resentment surrounding finance-industry payouts, the fact is that no one objects to paying for performance. We just want to make sure we’re not getting fleeced or paying for pure dumb luck, and this is where the problem lies.

In response to the current financial crisis, a number of hedge funds have implemented "gates" on their funds that restrict withdrawals when the sum of redemption requests exceeds a certain percentage of the fund's total assets. To reduce the investor's risk exposures during these periods, we propose a futures overlay strategy designed to hedge out or control the common factor exposures of gated assets. By taking countervailing positions in stock, bond, currency, and commodity exposures, an investor can greatly reduce the systematic risks of their gated assets while still enjoying the benefits of manager-specific alpha. Such overlay strategies can also be used to reposition the betas of an investor's entire portfolio, effectively rebalancing asset-class exposures without having to trade the less liquid underlying assets during periods of market dislocation. To illustrate the costs and benefits of such overlay, we simulate the impact of a simple beta-hedging strategy applied to long/short equity hedge funds in the TASS database.

Written testimony of Andrew W. Lo, prepared for the U.S. House of Representatives Committee on Oversight and Government Reform.

Our topic is corporate risk management, with perhaps a look at the implications for the current financial crisis. And I’d like to start by saying a few things that might help set the stage for our four panelists, who are all very interesting and accomplished people. When we think about risk and risk management, everybody says it’s very important. When a firm or an institution goes down, a lot of people lose their jobs, assets change hands, and a lot of franchise value can be destroyed in the process. So risk management is important in the sense of protecting on the downside. But there’s also a common perception that risk management has very little to do with creating growth and value—that you’ll never get to the Fortune 100 just by having good risk management. And I think that’s a serious misunderstanding of what risk management is really all about.

The Efficient Markets Hypothesis (EMH) refers to the notion that market prices fully reflects all available information. Developed independently by Paul A. Samuelson and Eugene F. Fama in the 1960's, this idea has been applied extensively to theoretical models and empirical studies of financial securities prices, generating considerable controversy as well as fundamental insights into the price-discovery process. The most enduring critique comes from psychologists and behavioral economists who argue that the EMH is based on counterfactual assumptions regarding human behavior, i.e., rationality. Recent advances in evolutionary psychology and the cognitive neurosciences may be able to reconcile the EMH with behavioral anomalies.

The value of active investment management is traditionally measured by alpha, beta, tracking error, and the Sharpe and information ratios. These are essentially static characteristics of the marginal distributions of returns at a single point in time, and do not incorporate dynamic aspects of a manager's investment process. In this paper, I propose a new measure of the value of active investment management that captures both static and dynamic contributions of a portfolio manager's decisions. The measure is based on a decomposition of a portfolio's expected return into two distinct components: a static weighted-average of the individual securities' expected returns, and the sum of covariances between returns and portfolio weights. The former component measures the portion of the manager's expected return due to static investments in the underlying securities, while the latter component captures the forecast power implicit in the manager's dynamic investment choices. This measure can be computed for long-only investments, long/short portfolios, and asset allocation rules, and is particularly relevant for hedge-fund strategies where both components are significant contributors to their expected returns, but only one should garner the high fees that hedge funds typically charge. Several analytical and empirical examples are provided to illustrate the practical relevance of these new measures.

Long-only portfolio managers and investors have acknowledged that the long-only constraint is a potentially costly drag on performance, and loosening this constraint can add value. However, the magnitude of the performance drag is difficult to measure without a proper benchmark for a 130/30 portfolio. In this paper, we provide a passive but dynamic benchmark consisting of a 'plain-vanilla' 130/30 strategy using simple factors to rank stocks and standard methods for constructing portfolios based on these rankings. Based on this strategy, we produce two types of indexes: investable and 'look ahead' indexes, in which the former uses only prior information and the latter uses realized returns to produce an upper bound on performance. We provide historical simulations of our 130/30 benchmarks that illustrate their advantages and disadvantages under various market conditions.

This major collection presents a careful selection of the most important published articles in the field of financial econometrics. Starting with a review of the philosophical background, the collection covers such topics as the random walk hypothesis, long-memory processes, asset pricing, arbitrage pricing theory, variance bounds tests, term structure models, market microstructure, Bayesian methods and other statistical tools.

Read Andrew Lo's Introduction to the International Library of Financial Econometrics

Systemic risk is commonly used to describe the possibility of a series of correlated defaults among financial institutions—typically banks—that occur over a short period of time, often caused by a single major event. However, since the collapse of Long Term Capital Management in 1998, it has become clear that hedge funds are also involved in systemic risk exposures. The hedge-fund industry has a symbiotic relationship with the banking sector, and many banks now operate proprietary trading units that are organized much like hedge funds. As a result, the risk exposures of the hedge-fund industry may have a material impact on the banking sector, resulting in new sources of systemic risks. In this paper, we attempt to quantify the potential impact of hedge funds on systemic risk by developing a number of new risk measures for hedge funds and applying them to individual and aggregate hedge-fund returns data. These measures include: illiquidity risk exposure, nonlinear factor models for hedge-fund and banking-sector indexes, logistic regression analysis of hedge-fund liquidation probabilities, and aggregate measures of volatility and distress based on regime-switching models. Our preliminary findings suggest that the hedge-fund industry may be heading into a challenging period of lower expected returns, and that systemic risk is currently on the rise.

In contrast to traditional investments such as stocks and bonds, hedge-fund returns have more complex risk exposures that yield additional and complementary sources of risk premia. This raises the possibility of creating passive replicating portfolios or "clones" using liquid exchange-traded instruments that provide similar risk exposures at lower cost and with greater transparency. Using monthly returns data for 1,610 hedge funds in the TASS database from 1986 to 2005, we estimate linear factor models for individual hedge funds using six common factors, and measure the proportion of the funds' expected returns and volatility that are attributable to such factors. For certain hedge-fund style categories, we find that a significant fraction of both can be captured by common factors corresponding to liquid exchange-traded instruments. While the performance of linear clones is often inferior to their hedge-fund counterparts, they perform well enough to warrant serious consideration as passive, transparent, scalable, and lower-cost alternatives to hedge funds.