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The SEC has proposed rules governing offerings of asset‐backed securities (ABS) that will impose extensive new requirements for disclosure and periodic reporting, including substantial additional information regarding various parties involved in securitization transactions. When final rules are adopted, probably by the end of this year, ABS issuers will need to have the necessary information available to them to permit them to comply with the new rules. This article summarizes the proposed rules, with emphasis on provisions that have caused particular concern in the asset‐backed securities markets. The article suggests steps that ABS issuers and their counsel should take time now to ensure that they are in a position to comply with the new rules regarding disclosure and reporting about originators, servicers, credit enhancers, and others, so as to avoid finding themselves unable to securitize portfolio assets in a public offering.

Security design of asset-backed securities (ABS) could affect the value of the ABS and that of the issuing firm as well when there exists an information asymmetry between insiders and outsiders of the firm, depending on the size of the assets sold. If the size is relatively small, the optimal security design will be such that the firm sells the risk-free, senior security (backed by the asset sold) to outsiders at a minimum size and retains the risky, subordinate security. If the size is large, the firm should sell outsiders both the risk-free security at a maximum size and the risky tranche at a minimum size. Meanwhile, if the firm has to sell an asset portfolio rather than an asset, the firm is better off by selling the portfolio through bundling the assets of the portfolio. It turns out that the bundling into senior and subordinate tranches is preferred to the bundling and selling to outsiders.

The purpose of this summary is to provide excerpts of selected Financial Industry Regulatory Authority (FINRA) Regulatory Notices and Disciplinary Actions issued in April, May, and June 2010.

The paper provides excerpts from FINRA Regulatory Notice 10‐18, Master Accounts and Sub‐Accounts; 10‐22, Regulation D Offerings; 10‐23, Trade Reporting and Compliance Engine (TRACE); 10‐24, Trade Reporting; 10‐27, Customer Complaint Reporting; and 10‐30, Trading‐Pause Pilot Program; provides summaries of selected disciplinary actions.

(10‐18) If a firm has notice that the sub‐accounts of a master account have different beneficial ownership (but does not know the identities of the beneficial owners) or the firm is privy to facts and/or circumstances that would reasonably raise the issue as to whether the sub‐accounts, in fact, may have separate beneficial owners, then the firm must inquire further and satisfy itself as to the beneficial ownership of each such sub‐account. (10‐22) A broker‐dealer has a duty – enforceable under federal securities laws and FINRA rules – to conduct a reasonable investigation of securities that it recommends, including those sold in a Regulation D offering. (10‐23) On February 22, 2010, the SEC approved the second major proposed expansion of TRACE to include Asset‐backed Securities as TRACE‐Eligible Securities, to require the reporting of Asset‐backed Securities transactions and to establish reporting fees. (10‐27) Starting on July 1, 2010, the beginning of the third calendar quarter, firms must use revised and new product codes to report statistical information regarding written customer complaints relating to annuities and life settlement products. (10‐30) On June 10, 2010, FINRA began a pilot program in which it will halt trading otherwise than on an exchange with respect to securities included in the S&P 500® Index where the primary listing market has issued a trading pause due to extraordinary market volatility. Selected disciplinary actions: FINRA announced that it has settled charges with two additional firms relating to the sale of auction rate securities (ARS) that became illiquid when auctions froze in February 2008. FINRA announced that it has fined five broker‐dealers a total of $385,000 for the illegal sale of more than 8 billion shares of penny stock on behalf of their customers.

These are direct excerpts designed to provide a useful digest for the reader and an indication of regulatory trends. The FINRA staff is aware of this summary but has neither reviewed nor edited it. For further detail as well as other useful information, the reader should visit www.finra.org.

Social scientists have long been interested in how political institutions affect economic performance. Nowhere are these effects more apparent today than in the current U.S. financial meltdown. This article offers an analysis of the meltdown by showing how government regulation among other things helped cause it. Specifically, the article shows how regulatory reforms closely associated with neoliberalism created perverse incentives that contributed significantly to the increased lending in the mortgage market and increased speculation in other financial markets even as such behavior was becoming increasingly risky. The result was the failure of mortgage firms, banks, a major insurance company, and eventually the market for short-term business loans, which triggered a general liquidity crisis thereby thrusting the entire economy into a severe recession. Implications for future research are explored. The article also offers a few policy prescriptions and an assessment of their political viability going forward.

In August 2007 the Mainsail II SIV-Lite was frozen by its trustee as a result of the ongoing credit crisis. The state of Maine held $20 million of Mainsail commercial paper in its Cash Pool portfolio, a short-term portfolio that puts temporary, excess state revenues to work. When word of the potential loss became public, the Treasurer came under attack. The case introduces the functions of a state Treasury department, with particular emphasis on the investment objectives and guidelines for the cash pool as well as its composition. The case reviews the events leading up to and including August 2007, the month when the credit markets first began to seize and when the financial crisis effectively began. It examines securitization, structured finance, and the Mainsail SIV-Lite structure in some detail.

In the search for alternative income-generating assets, the paper addresses the following question, one that the literature has yet to answer: what is a reasonable allocation, if any, to asset-backed securities within a 60–40% stock-bond balanced portfolio of mutual funds?

The authors apply the Black–Litterman model of Modern Portfolio Theory to test the efficacy of adding asset-backed securities to the classic 60–40% stock-bond portfolio of mutual funds. The authors use out-of-sample tests of one, three, five, and ten years to determine a reasonable asset allocation. The data are monthly and range from January 2000 through September 2021.

The statistical evidence indicates a modest reward-risk added value from the addition of asset-backed securities, as measured by the Sharpe “reward-to-variability” ratio, in holding periods of three, five, and ten years. Based on the findings, the authors conclude that a reasonable asset allocation for income-seeking, risk-averse investors who follow the classic 60%–40% stock-bond allocation is 8%–10%.

The findings apply to a stock-bond balanced portfolio of mutual funds. Other fund combinations could produce different results.

Investors and money managers can use the findings to improve portfolio performance.

For investors seeking higher income-generating securities in the current record-low interest rate environment, the authors determine a reasonable asset allocation range on asset-backed securities. This study is the first to provide such direction to these investors.

This paper provides a comprehensive overview of the gradual evolution of the supervisory policy adopted by the Basel Committee for the regulatory treatment of asset securitisation. The pathology of the new “securitisation framework” is carefully highlighted to facilitate a general understanding of what constitutes the current state of computing adequate capital requirements for securitised credit exposures. Although a simplified sensitivity analysis of the varying levels of capital charges depending on the security design of asset securitisation transactions is incorporated, the author does not engage in a profound analysis of the benefits and drawbacks implicated in the new securitisation framework.

Studies of Depression-era financial remediation have generally focused on federal deposit insurance and the provision of equity to banks by the Reconstruction Finance Corporation (RFC). This paper broadens the concept of financial remediation to include other programs – RFC lending, federal guarantees of farm and home mortgages, and the elimination of interest on demand deposits – and other intermediaries – savings and loans, mutual savings banks, and life insurance companies. The benefits of remediation or the amounts potentially at risk to the government in these programs are calculated annually and allocated to the various intermediaries. The slow remediation of real estate loans (two-thirds of these intermediaries' loans) needs further study with respect to the slow economic recovery. The paper compares Depression-era remediation with efforts during the 2008–2009 crisis. Today's remediation contrasts with the 1930s in its speed, magnitude relative to GDP or private sector nonfinancial debt, the share of remediation going to nonbanks, and emphasis on securities markets.

The advent of derivatives and structured products has coincided with a proliferation of fixed income models used to analyze hedging, pricing, forecasting, and estimation for the term structure of interest rates. This article evaluates five models Ho‐Lee (HL); Black‐Derman‐Toy (BDT); Vasicek; Cox‐Ingersoll‐Ross (CIR); and Heath‐Jarrow‐Morton (HJM) (see Exhibit 1) that are currently used by structured finance practitioners. We suggest which models are most appropriate for assets with different time horizons, interest rate sensitivities and cashflow properties. The authors link model selection to structured financial instruments with the singular focus on the trade‐off between model precision/complexity and calculation costs.