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Sustainable (also known as environmental, social, and corporate governance [ESG]) investing is currently of intense interest in the investment world. In this article, the authors consider the salient challenges associated with ESG investing and how quantitative approaches may address them. Compared to fundamental methods of sustainable investing, the authors see quantitative methods as having several advantages: These methods can build on and extend the vast analytical toolbox of modern portfolio theory to incorporate investor preference in portfolio construction; they can leverage the recent data explosion to obtain insights on many intangible sustainability metrics; and they do not have the black box label. Instead, subjective judgment applied to building the quantitative system is essential. A thoughtful analytical system can be applied to a large universe of stocks, and quantitative methods may also be leveraged to predict popular ESG vendor ratings. Although these are the early days of quantitative sustainable investing, the authors believe these advantages will prove the quantitative method’s worth in sustainable investing. TOPICS:ESG investing, portfolio theory, portfolio construction, statistical methods Key Findings ▪ Quantitative methods have unique advantages for sustainable investing in the areas of portfolio construction, data application, and scaling domain knowledge. ▪ The skillful quantitative practitioner can create the optimal blend of human insight and computing power to extract sustainability insights from data.

This article examines the behavior of the small-capitalization stock return cycle. The authors compare the period 1980–2020 with a study for the period 1960–1995. They find that in the earlier period small-cap stocks earned a return premium when the economy was rising, long-term rates were rising, the US dollar was rising, and market volatility was falling. During the last decade, a strong move in large-cap stocks dwarfed the small-cap premium. The authors conjecture that a change in the character of economic growth, rising long-term rates, and oversold small-cap conditions may reverse this. TOPICS:Portfolio theory, portfolio construction, wealth management Key Findings • The small-cap premium appears to have waned in the last 20 years. • The premium is, however, still related to economic cycles. • Economic conditions and valuations now favor a small-stock premium.

Throughout the past 45 years, the crux of quantitative portfolio management has evolved through advances in three spheres: (1) domain expertise (market savvy), (2) data superiority (smart not just big), and (3) digital (econometric models). The data and digital of the 1970s and 1980s now appear rather primitive. Quantitative practitioners have survived (and at times thrived) through creative innovation. The author briefly discusses some examples of evolution identified with relation to these three circles. As in the past, successful managers will prosper with creative discovery and positioning at the intersection of these elements—domain, data, and digital. TOPICS:Statistical methods, simulations, big data/machine learning Key Findings • Successful investing in quantitative equites dates back to the time of the E-model in the 1980s and has had a golden evolution. • The passion for research discovery and creativity will continue to advance the practice in the future. • Future leaders will position themselves at the intersection of the three ever-present spheres: (1) domain expertise (market savvy), (2) data superiority (smart, not just big), and (3) digital (econometric models).

Approaches to quantitative equity investing have evolved markedly. Thirty years ago, the focus was on alpha generation, but with the recent decade’s acceptance of smart (alternative) beta, the focus is turning to transparent methods of construction for factor investing. In this article, the authors present an approach for evaluating various methods of portfolio construction that lead to the same factor exposures. Four portfolios are of interest: factor weighted, cap weighted, equal weighted, and risk parity weighted. The authors compare these portfolios based on standard performance statistics as well as new metrics of value-added, such as performance participation rates and portfolio sector concentrations. The results indicate that once the desired factor exposure is achieved, it is beneficial to build the portfolio with the most desirable characteristics in terms of diversification.

In Small-Cap Allocations: Timing the Entry, in the September 2020 edition of The Journal of Portfolio Management, Eric Sorensen and Sebastian Lancetti, both of PanAgora Asset Management, assert that economic conditions now may favor a small-stock premium. They analyze the performance of small-cap stocks since 1965 and identify connections between small-cap stocks and moves in interest rates, market volatility, and the broader economy. They speculate that although large-cap stocks have outperformed small-caps during the past decade, conditions are ripe for small-caps to reassert themselves. The key factors include: 1) the very low level of long-term interest rates and the potential for interest rates to rise; 2) the anticipated economic recovery following the Covid-induced recession; and 3) the current relatively cheap valuations of small-cap stocks. TOPICS:Portfolio theory, portfolio construction, wealth management

This article examines the application of risk parity to fully diversify an equity portfolio. It presents wealth accumulation in a stochastic dominance framework, tested over increasing investment horizons. The portfolio construction algorithms consider sector, country, and stocks in achieving an alternative to capitalization-weighted approaches. Risk parity is dominant over 75% of the historical periods for any two-year horizon and is dominant in all cases after six-year horizons. It achieves dominance over capitalization-weighted indices over shorter horizons during periods of higher market volatility, periods of higher inflation, and periods with steep yield curves.

Practical Applications Summary In Not All Factor Exposures Are Created Equal, from the 2018 Quantitative Special Issue of The Journal of Portfolio Management, authors Eric Sorensen, Mark Barnes, Nick Alonso, and Edward Qian (all of PanAgora Asset Management in Boston, MA) evaluate the use of different portfolio construction methodologies for managing factor portfolios. They consider four types of portfolios that hold the factor exposure constant and have varying security weighting schemes: factor weighted (FW), cap weighted (CW), equal weighted (EW), and risk parity weighted (RP). The find that using a risk-aware weighting scheme exemplified by their RP portfolios generally achieves both strong upside participation and an advantageous defensive posture when a factor underperforms. They ascribe the advantage of the RP approach to sector positions, particularly in emphasizing exposure to defensive sectors such as consumer staples, healthcare, and utilities.

Today, managers who are labeled quantitative are painted with a rather broad brush that references security breadth and formulaic empirical factor modeling, and managers who are labeled fundamental are marked by depth of analysis and human insight. Despite divergent styles, the basic differentiator is information—information sources, information processing, and information implementation. Sorensen argues that the evolution of quantitative equity investing will be marked by small, diversified, and additive elements of innovative information analysis (expert systems). As with earlier generations of quantitative equity modeling (value, quality, and so forth), the raw material will be fundamental and the goal will be to more efficiently mimic the best fundamental investors.

Not all value strategies are created equal; that is, correlations among different value strategies and among similar value strategies across markets are, in general, low. Thus, to preserve market neutrality and reduce exposure to volatility, investors need to augment value strategies and adopt a multi-strategy approach. Some exposures, however, are common to value strategies and are not diversified away. Among these exposures are value premiums and volatility jumps. The authors present their findings of value-based strategies in several markets, including top-down country allocation in equities, bonds, and currencies, and bottom up stock selection in the U.S., Japan, and Germany. The focus of the authors’ research is on the correlations among these strategies and their exposures to select market factors.

The net value-added of an investment strategy has two parts: the expected value of the alpha skill, and the cost of implementation. The first part is positive and depends on the efficacy of a return forecasting model; the second is negative and depends on portfolio turnover and trading skills. The higher the former, and the lower the latter, the happier the investor. Typically, managers give little consideration to turnover, but throw an alpha model into an optimizer, setting turnover constraints to handle transaction costs. The explicit framework here instead integrates alpha models with portfolio turnover and transaction costs. The result allows evaluation of factors in terms of net return and then optimization of multiple factors to achieve the best net information ratio. Optimal multifactor models change as portfolio turnover constraints change, providing a potential solution for model evolution as assets under management grow.

Fiduciary institutions are forging ahead to remove the traditional long-only handcuffs that constrain the delivery of maximum net alpha by their equity managers. The proliferation of 130/30 managers (long 130% and short 30%, with beta 1.0) prompts a question as to the optimal ratio for these constrained long-short strategies. Analysis of the range from long-only to fully unconstrained will help find the optimal solution that maximizes the risk-adjusted return. The ratio that maximizes net information ratio (IR after leakages) depends largely on the risk budget, the chosen benchmark, leveraging costs, and the transaction costs associated with turnover. In the case of normal active risk (3%-5%), more alpha leverage is better than less. That is, despite the declining marginal benefit of higher leverage, 150/50 may be better than 120/20, approximating a pure market-neutral strategy.

Active portfolio managers often see themselves as assemblers of efficient portfolios that maximize information ratios through the value-added of their proprietary investment insights (alphas), but approaches to reconciling often-contradicting investment insights differ widely. A linear combination of different investment insights can be used to support an analytical framework that maximizes the information from one single source. Simulations based on this framework reveal the impact of varying two key variables the cross-sectional correlation of alpha signals and the time series correlations of the information coefficients related to alpha signals. The latter plays a more important role, providing diversification benefit to strategy risk over time. This analytical foundation has applications in sensitivity analysis and improving active performance.

A frequent question regarding quantitative investing is: What are good variables for stock selection? Traditional quantitative strategies are variations of screening techniques. Quantitative investment managers seek to narrow the investable universe to a manageable number of stocks that have desirable characteristics. The authors introduce an alternative approach to traditional methods of stock screening based on a statistical technique known as classification and regression tree (CART). CART allows screening factors to interact on a conditional basis. The end result is a hierarchical (tree) structure that assigns a probability of outperformance (or underperformance) for each stock. The authors apply two alternative CART strategies to the selection of technology stocks, and evaluate their performance. The models demonstrate significant improvement over the more ad hoc stock ranking techniques.

With the growth in the market for interest rate swaps has come a growing need to understand the potential default risks of these instruments. In general, swap participants can deal with default risk by seeking to mitigate it (by dealing only with AAA-rated counterparties, for example). Alternatively, potential counterparties can attempt to come to some agreement about the degree of default risk and use that knowledge to "price" their positions. A model of swap default risk evaluates jointly the probability of the swap counterparty defaulting and the cost (or impact) of the default for the solvent party. The model helps to establish the correct level for a swap between risky (or potentially risky) parties. The key considerations are the swap parties' credit conditions and the shape and volatility of the yield curve.

(1992). The Use and Misuse of Value Investing. Financial Analysts Journal: Vol. 48, No. 2, pp. 51-58.

One of the common delineations across the spectrum of active equity management continues to be the growth style versus the value style. Pension funds, for example, routinely allocate capital to both styles within the larger scheme of asset (strategy) allocation. There are strong philosophical differences between active managers that adopt these styles. Growth managers discriminate between companies on their future growth prospects, presuming that the market has underacted to positive growth potential and/or underestimated this growth. Valuation criterion, such as price-to-earnings, becomes a secondary consideration. In contrast, value managers are bargain hunters, and seek companies for which the market has overacted to dull or weak fundamentals and/or underestimated potential for future improvement. Pension consultants have sophisticated methods of categorizing growth versus value managers. The two groups of style managers tend to use radically different factors in ranking stocks. In addition, these factors also contribute to a number of available (and investable) indices that allow money managers to achieve a growth or value investment passively, and to assess their performances that are incremental to a passive benchmark. In the long-run, it is debatable where either a growth or value style delivers more wealth creation, once an adjustment is made for risk. (Value has lower beta and earns lower averages returns, but also has lower volatility, rendering the Sharpe ratio similar to that of growth in the long run.) However, during shorter periods (quarters or years), value and growth returns often alternate in substantially higher performance over the cycle. Some managers seek to dynamically allocate to growth versus value to have the best of both worlds over time. This timing strategy, however, requires considerable skill and discipline. Keywords: equity investment style; style indices growth stocks; value stocks; small-cap stocks; large-cap stocks; style drift; contrarian investor; consistent growth manager

Pension funds should use risk parity as an alternative to actively managed cap-weighted indices, according to Eric Sorensen and Nicholas Alonso . Though the strategy is typically applied as an approach to balance risk across asset classes, the authors of this research demonstrate its flexibility and outperformance versus traditional cap-weighted indices. Risk parity can help investors resist horizon bias, say the authors. They also note is that risk-parity portfolios suffer less in declining markets, while gaining most of the upside of rising markets, as compared with cap-weighted indices. Sorensen, who is President and CEO of PanAgora Asset Management , and co-author Alonso, who is a Portfolio Manager at the Boston-based firm, present their findings in The Resale Value of Risk Parity Portfolios , in the Winter 2015 issue of The Journal of Portfolio Management .

Applying a multifactor alpha model across a diverse range of stocks is a popular approach to forecast securities' expected returns. This approach assumes that one single return-generating equation provides adequate alpha forecasts - that is, one-size-fits-all. In this paper, we extend prior empirical research by introducing an alternative alpha-modeling approach. Our approach presents a parsimonious way of modeling securities individually in order to capture the idiosyncratic return behavior pertaining to different security contexts. Our investment objective is information ratio maximization, through optimal alpha factor weights. Our modeling technique demonstrates the importance of different factor categories (cheapness, quality, and sentiment) that vary significantly across various security contexts. These contexts span typical dimensions of risk characteristics (value, growth, or earnings variability). We illustrate how practitioners can apply our technique in their security selection process, and document to what extent our approach improves the ex post information ratio when compared with a one-size-fits-all approach.

IN THE 1970S THERE was a noticeable increase in the amount of preferred stock issued by utility companies. During this period the historically positive yield differential between high grade preferred stocks and high grade corporate bonds turned negative. A substantial fraction of the demand for preferred stock has come from casualty and stock life insurance companies [10]. Much of the corporate demand for preferred stock may be attributed to the 85 percent exclusion of preferred dividends from net income for federal income tax purposes. Insurance companies must follow the valuation rules of the National Association of Insurance Commissioners (NAIC). For example, bonds may be carried at amortized original cost (book value) if they are investment grade (equivalent to Moody's Baa or higher), but they have to be carried at a lower value if they have lower ratings. Common stock is carried at market price. The NAIC recently adopted a rule permitting insurance companies to carry sinking fund preferreds at book value rather than marking them to the market. The 1979 edition of the Valuation of Securities: Procedures and Instructions booklet published by the NAIC allows preferred stock held by property and casualty companies to: "Commencing with the December 31, 1978 Annual Statement, be valued for statement purposes at cost, providing the issue is subject to a 100% mandatory sinking fund ... over a period not longer than 40 years from the date of issue" [11]. Holding assets which are accounted for at book value rather than market value reduces the variance of reported equity. The benefit of this provision for insurance companies is that during a period of rising interest rates, sinking fund preferred stock held by insurance companies will not contribute to erosion of reported asset base and balance sheet equity. It is likely that in some instances the provision would enable insurance companies to continue to write new policies at a growth rate that would not otherwise be possible due to state statutes which limit the maximum value of policies written in relation to balance sheet asset value. Whether or not bookkeeping rules have a significant impact on security prices has long been an interesting question [4] [6]. This paper examines the impact of the change in NAIC rules upon the pricing of preferred stock.1

(1986). Portfolio Returns from Active Industry Group Rotation. Financial Analysts Journal: Vol. 42, No. 5, pp. 43-50.

THIS STUDY OF NEW issues of corporate bonds has two objectives. The first objective is to compare interest costs of corporate bonds sold by competitive bid with comparable bonds sold by negotiation. Previous studies investigating the question of competitive versus negotiated sales of corporate bonds dwell primarily on underwriter spread, which typically constitutes about 1% of corporate bond interest cost.' Results presented here demonstrate that interest costs for negotiated sales are significantly greater than are interest costs for competitive sales, ceteris paribus. A second objective is to determine which market participants are beneficiaries of higher interest costs in negotiated sales. The analysis shows that interest cost differentials due to underwriting method and bidder competition primarily accrue to investors in the form of higher or lower yields. Section I discusses the determinants of corporate bond interest cost. Section II presents and analyzes observed differences in borrowing costs. Section III offers concluding remarks.

(1989). A Total Differential Approach to Equity Duration. Financial Analysts Journal: Vol. 45, No. 5, pp. 30-37.

(1983). Pricing of Municipal Bond Underwritings: It May Pay to Invest When Underwriters Don’t. Financial Analysts Journal: Vol. 39, No. 2, pp. 58-64.

Systematic use of dividend discount models has the potential to add value to the portfolio management process. Using consensus forecasts of earnings growth, the authors tested four valuation models ranging in complexity from a simple price-earnings ratio model to a threeperiod dividend discount model. Each model was used to rank 150 stocks from the SP this difference increased to 35.63 per cent when the three-period model was used for ranking. Adjustment for risk improved model performance, especially when used in conjunction with the more complex models.

Historically, preferred stock ranks well below common stock and bond issues as a source of financing in the private capital market. Relative to issuance of bonds, the issuance of preferred stock burdens the issuer with a fixed financing cost without benefitingthe issuer with the tax deductability associated with interest payments.

In recent years, there have been a number of studies investigating the yield spread phenomena between new and seasoned bonds ([1], [2], [3], [4], [8], [10], [13]). This literature focuses upon two aspects of the equilibrium pricing of new versus seasoned bonds: (l) analysis of the microeconomic determinants of new issue/seasoned issue yield spreads such as specific differences in coupon rates, call features, maturity features, and the like; and (2) analysis of macroeconomic determinants of yield spreads such as economic growth, interest rate cycles, changing marginal tax rates, and the like.

In the last several years, there has been increased theoretical emphasis on the agent-principal problem as it applies to corporate finance. This paper is an attempt to empirically test for the presence of the agency costs and their relation to the debt policy of corporations. We find that firms with higher insider ownership have greater debt ratios than firms with lower insider ownership, which may be explained by the agency costs of debt and/or the agency costs of equity. Other regression results tend to confirm the theoretically optimal relationships put forth by Myers. We find that high-growth firms use less debt rather than more debt, high-operating-risk firms use more debt rather than less debt, and firm size appears to be uncorrelated to the level of debt.

Recent empirical research has demonstrated that increased bidder competition lowers borrowing costs for issuers of municipal bonds [4, 5, 7, 12, 13, 14]. Consequently, the accepted position of many economists is that new issues should be offered by competitive bid. However, this conclusion is unwarranted in the case of lower-quality bonds receiving only one or two bids. The purpose of this paper is to investigate the economic consequences of municipalities selling bonds by negotiation. More specifically, it investigates the hypothesis that in instances when issuers face relatively high demand uncertainty for their new bonds, it is potentially more efficient to sell bonds by negotiation than by competitive bidding. It is shown that, for lower rated bonds having only one or two bids, cost savings are possible by using negotiation.

Received monetary theory supports the existence of a strong relationship between monetary activity and stock prices. Following the work of Friedman and Schwartz [8], relating money supply to aggregate economic activity, some researchers have examined the more specific connection between changes in the rate of growth of money supply and associated movements in stock prices (see [6], [10], [11], [14], [17], [18], [19], [20], [22], and [28]). These studies use a variety of monetary aggregate measures to functionally relate the level of stock market indices to contemporaneous and lagged monetary growth rates. In general, the findings indicate a direct relationship between money supply and stock returns.

Virtually all new state and local governmental bond issues are purchased initially by an underwriter, or syndicate of underwriters, who in turn resells the bonds to investors. The underwriter attempts to sell the bonds for an amount which exceeds his purchase price. The difference is underwriter spread. Of course the probability that the underwriter will actually receive the planned spread is directly related to the yields at which the reoffering is attempted. The purpose of this study is to test and analyze the relationship between reoffering yields for new municipal bond issues and the spread which the underwriter plans to receive. This study differs from previous studies in method of analysis, and in being the first such study to examine underwriter behavior in the bond market.

This paper examines the demand for municipal bond insurance in the context of a competitive signaling equilibrium model. The study compares the pricing of new bond issues that are insured to similar issues that are not insured. The results indicate that issuers who purchase bond insurance, on average, are able to reduce their new issue borrowing cost more than enough to offset the cost of the insurance premium. Furthermore, the net benefit to the issuer increases as the underlying credit quality of the bond declines.