Financing Drug Discovery via Dynamic Leverage2016
We extend the megafund concept for funding drug discovery to enable dynamic leverage in which the portfolio of candidate therapeutic assets is predominantly financed initially by equity, and debt is introduced gradually as assets mature and begin generating cash flows. Leverage is adjusted so as to maintain an approximately constant level of default risk throughout the life of the fund. Numerical simulations show that applying dynamic leverage to a small portfolio of orphan drug candidates can boost the return on equity almost twofold compared with securitization with a static capital structure. Dynamic leverage can also add significant value to comparable all-equity-financed portfolios, enhancing the return on equity without jeopardizing debt performance or increasing risk to equity investors.
Lessons From Hollywood: A New Approach To Funding R&D2016
In this article, we suggest an alternative structure for undertaking the long-term, high-risk, highly capital-intensive R&D programs that typify science-based settings. We refer to this structure as a project-focused organization (PFO). PFOs are entities that are created with the sole purpose of conducting a specific R&D project. When the project is completed, the PFO is disbanded, residual returns (if there are any) are distributed to investors, and intellectual property and other assets are sold off. We think PFOs are an attractive alternative to both the traditional vertical integration model and the traditional venture capital/entrepreneurial startup model. We discuss how such PFOs could work in practice, using the example of biopharmaceutical R&D, although we argue that the structure has much broader applicability.
What Is An Index?2016
Technological advances in telecommunications, securities exchanges, and algorithmic trading have facilitated a host of new investment products that resemble theme-based passive indexes but which depart from traditional market-cap-weighted portfolios. I propose broadening the definition of an index using a functional perspective—any portfolio strategy that satisfies three properties should be considered an index: (1) it is completely transparent; (2) it is investable; and (3) it is systematic, i.e., it is entirely rules-based and contains no judgment or unique investment skill. Portfolios satisfying these properties that are not market-cap-weighted are given a new name: “dynamic indexes.” This functional definition widens the universe of possibilities and, most importantly, decouples risk management from alpha generation. Passive strategies can and should be actively risk managed, and I provide a simple example of how this can be achieved. Dynamic indexes also create new challenges of which the most significant is backtest bias, and I conclude with a proposal for managing this risk.
Risk and Risk Management in the Credit Card Industry2016
Using account level credit-card data from six major commercial banks from January 2009 to December 2013, we apply machine-learning techniques to combined consumer-tradeline, credit-bureau, and macroeconomic variables to predict delinquency. In addition to providing accurate measures of loss probabilities and credit risk, our models can also be used to analyze and compare risk management practices and the drivers of delinquency across the banks. We find substantial heterogeneity in risk factors, sensitivities, and predictability of delinquency across banks, implying that no single model applies to all six institutions. We measure the efficacy of a bank’s risk-management process by the percentage of delinquent accounts that a bank manages effectively, and find that efficacy also varies widely across institutions. These results suggest the need for a more customized approached to the supervision and regulation of financial institutions, in which capital ratios, loss reserves, and other parameters are specified individually for each institution according to its credit-risk model exposures and forecasts.
The Gordon Gekko Effect: The Role of Culture in the Financial Industry2016
Culture is a potent force in shaping individual and group behavior, yet it has received scant attention in the context of financial risk management and the recent financial crisis. I present a brief overview of the role of culture according to psychologists, sociologists, and economists, and then present a specific framework for analyzing culture in the context of financial practices and institutions in which three questions are answered: (1) What is culture?; (2) Does it matter?; and (3) Can it be changed? I illustrate the utility of this framework by applying it to five concrete situations—Long Term Capital Management; AIG Financial Products; Lehman Brothers and Repo 105; Société Générale’s rogue trader; and the SEC and the Madoff Ponzi scheme—and conclude with a proposal to change culture via “behavioral risk management.”
Where to From Here?2015
Ever since the Great Recession, the global financial regulatory system has undergone significant changes. But have these changes been sufficient? Have they created a new problem of over-regulation? Is the system currently in a better position than in the pre-Recession years, or have we not adequately addressed the basic causes of the financial crisis and resulting Great Recession These were the questions and issues addressed in the seventeenth annual international banking conference held at the Federal Reserve Bank of Chicago in November 2014. In collaboration with the Bank of England, the theme of the conference was to examine the state of the new global financial system as it has evolved in response to significant market changes and regulatory reforms triggered by the global financial crisis. The papers from that conference are collected in this volume, with contributions from an international array of government officials, regulators, industry practitioners and academics.
The Wisdom of Crowds Vs. the Madness of Mobs2015
Intelligence does not arise only in individual brains; it also arises in groups of individuals. This is collective intelligence: groups of individuals acting collectively in ways that seem intelligent. In recent years, a new kind of collective intelligence has emerged: interconnected groups of people and computers, collectively doing intelligent things. Today these groups are engaged in tasks that range from writing software to predicting the results of presidential elections. This volume reports on the latest research in the study of collective intelligence, laying out a shared set of research challenges from a variety of disciplinary and methodological perspectives. Taken together, these essays—by leading researchers from such fields as computer science, biology, economics, and psychology—lay the foundation for a new multidisciplinary field.
Pioneered by the Nobel Prize–winning economist Harry Markowitz over half a century ago, portfolio theory is one of the oldest branches of modern financial economics. It addresses the fundamental question faced by an investor: how should money best be allocated across a number of possible investment choices? That is, what collection or portfolio of financial assets should be chosen? In this article, we describe the fundamentals of portfolio theory and methods for its practical implementation. We focus on a fixed time horizon for investment, which we generally take to be a year, but the period may be as short as days or as long as several years. We summarize many important innovations over the past several decades, including techniques for better understanding how financial prices behave, robust methods for estimating input parameters, Bayesian methods, and resampling techniques.
Spectral Analysis of Stock-Return Volatility, Correlation, and Beta2015
We apply spectral techniques to analyze the volatility and correlation of U.S. common-stock returns across multiple time horizons at the aggregate-market and individual-firm level. Using the cross-periodogram to construct frequency bandlimited measures of variance, correlation and beta, we find that volatilities and correlations change not only in magnitude over time, but also in frequency. Factors that may be responsible for these trends are proposed and their implications for portfolio construction are explored.
Megafunding Drug Research2015
As price-gouging practices by a handful of drug companies attract headlines, one troubling aspect of the story remains underplayed. Exorbitant increases in the prices of existing drugs, including generics, are motivated not just by crass profiteering but by a deep skepticism about the economic feasibility of developing new drugs. That skepticism is justified.
Traditional models for funding drug development are faltering. In the US and many other developed countries, the average cost of bringing a new drug to market has skyrocketed, even as patents on some of the industry’s most profitable drugs have expired. Venture capital has pulled back from early-stage life-sciences companies, and big pharmaceutical companies have seen fewer drugs reach the market per dollar spent on research and development...
Opinion: A New Approach to Financial Regulation2015
In this Op-Ed Piece, MIT Sloan Professor Andrew Lo and Princeton Professor Simon Levin write, "We propose that the financial system has crossed a threshold of complexity where the system is evolving faster than regulators and regulations can keep pace. For example, the system is now truly globally connected, but coordination across sovereign jurisdictions is difficult to achieve. This new situation calls for a new perspective, one based on a different paradigm than the ones on which financial regulation is currently based, such as efficient markets, rational expectations, and models patterned after the physical sciences."
FAQs for Megafund Financing2015
A document answering frequently asked questions about the megafund idea.
Law Is Code: A Software Engineering Approach to Analyzing the United States Code2015
The agglomeration of rules and regulations over time has produced a body of legal code that no single individual can fully comprehend. This complexity produces inefficiencies, makes the processes of understanding and changing the law difficult,and frustrates the fundamental principle that the law should provide fair notice to the governed. In this Article, we take a quantitative, unbiased, and software-engineering approach to analyze the evolution of the United States Code from 1926 to today. Software engineers frequently face the challenge of understanding and managing large, structured collections of instructions, directives, and conditional statements, and we adapt and apply their techniques to the U.S. Code over time. Our work produces insights into the structure of the U.S. Code as a whole, its strengths and vulnerabilities, and new ways of thinking about individual laws. For example, we identify the first appearance and spread of important terms in the U.S. Code like “whistleblower” and “privacy.” We also analyze and visualize the network structure of certain substantial reforms,including the Patient Protection and Affordable Care Act and the Dodd-Frank Wall Street Reform and Consumer Protection Act, and show how the interconnections of references can increase complexity and create the potential for unintended consequences. Our work is a timely illustration of computational approaches to law as the legal profession embraces technology for scholarship in order to increase efficiency and to improve access to justice.
Reply to “(Im)Possible Frontiers: A Comment”2015
In Brennan and Lo (2010), a mean-variance efficient frontier is defined as “impossible” if every portfolio on that frontier has negative weights, which is incompatible with the Capital Asset Pricing Model (CAPM) requirement that the market portfolio is mean-variance efficient. We prove that as the number of assets n grows, the probability that a randomly chosen frontier is impossible tends to one at a geometric rate, implying that the set of parameters for which the CAPM holds is extremely rare. Levy and Roll (2014) argue that while such “possible”frontiers are rare, they are ubiquitous. In this reply, we show that this is not the case; possible frontiers are not only rare,but they occupy an isolated region of mean-variance parameter space that becomes increasingly remote as n increases. Ingersoll (2014) observes that parameter restrictions can rule out impossible frontiers, but in many cases these restrictions contradict empirical fact and must be questioned rather than blindly imposed.
Funding Translational Medicine via Public Markets: The Business Development Company2015
A business development company (BDC) is a type of closed-end investment fund with certain relaxed requirements that allow it to raise money in the public equity and debt markets, and can be used to fund multiple early-stage biomedical ventures, using financial diversification to de-risk translational medicine. By electing to be a “Regulated Investment Company” for tax purposes, a BDC can avoid double taxation on income and net capital gains distributed to its shareholders. BDCs are ideally suited for long-term investors in biomedical innovation, including: (i) investors with biomedical expertise who understand the risks of the FDA approval process, (ii) “banking entities,” now prohibited from investing in hedge funds and private equity funds by the Volcker Rule, but who are permitted to invest in BDCs, subject to certain restrictions, and (iii) retail investors, who traditionally have had to invest in large pharmaceutical companies to gain exposure to similar assets. We describe the history of BDCs, summarize the requirements for creating and managing them, and conclude with a discussion of the advantages and disadvantages of the BDC structure for funding biomedical innovation.