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The US bond market had over $42.39 trillion of outstanding debt at the end of the third quarter of 2018, eclipsing the US stock market’s approximately $30 trillion in market capitalization. The sheer size of the bond market provides ample opportunities, as well as risks, for institutional investors. Some of these risks escape investors’ radar because of the nature of fixed-income securities: low transparency, illiquidity, and over-the-counter (OTC) trading. In this paper, we present our concerns regarding five secular changes brought up by the over-regulation of the marketplace after the financial crisis of 2008 and investors’ persistent thirst for yield. Further, while painful lessons were gleaned after the punishing 2008 financial crisis, we present empirical evidence that suggests that many sectors, such as the auto loans and collateralized loan obligations, that were largely unscathed by this crisis may be at risk in the next downturn. This paper is based on original data sources and academic research. The authors are in continuing dialogue with other experts that may further the research, and welcome interested parties to get in contact.

Private equity has traditionally been thought to provide diversi cation bene ts. However, these benefi ts may be lower than anticipated. We find that private equity suffers from signifi cant exposure to the same liquidity risk factor as public equity and other alternative asset classes. The unconditional liquidity risk premium is close to 3% annually and, in a four-factor model, the inclusion of this liquidity risk premium reduces alpha to zero. In addition, we provide evidence that the link between private equity returns and overall market liquidity occurs via a funding liquidity channel.

The traditional investment paradigm is based on several key assumptions including rational investors, stationary probability laws, and a positive linear relationship between risk and expected return with parameters that are constant over time and which can be accurately estimated. These assumptions were plausible during the “Great Modulation” — the seven decades spanning the mid-1930s to the mid-2000s in which equity markets exhibited relatively stable risk and expected returns — but have broken down during the past decade, implying temporary but significant violations of rational pricing relationships. This tension between rational and behavioral market conditions is captured by the Adaptive Markets Hypothesis (AMH), an evolutionary perspective on market dynamics in which intelligent but fallible investors learn from and adapt to changing environments. Under the AMH, markets are not always efficient, but they are highly competitive and adaptive, and can vary in their degree of efficiency as the economic environment and investor population change over time. The AMH has several new implications for financial analysis, including the possibility of negative risk premia, the transformation of alpha into beta, and the importance of macro factors and risk budgeting in asset-allocation policies.

In this paper we present a mean-reverting jump diffusion model for the electricity spot price. We obtain a closed-form solution for forward contracts and calibrate it to market data from England and Wales. Finally, based on the calibrated forward curve we present months, quarters, and seasons-ahead forward surfaces.

We review theory and evidence relating to herd behavior, payoff and reputational interactions, social learning, and informational cascades in capital markets. We offer a simple taxonomy of effects, and evaluate how alternative theories may help explain evidence on the behavior of investors, firms, and analysts. We consider both incentives for parties to engage in herding or cascading, and the incentives for parties to protect against or take advantage of herding or cascading by others.

We argue that active management's popularity is not puzzling despite the industry's poor track record. Our explanation features decreasing returns to scale: As the industry's size increases, every manager's ability to outperform passive benchmarks declines. The poor track record occurred before the growth of indexing modestly reduced the share of active management to its current size. At this size, better performance is expected by investors who believe in decreasing returns to scale. Such beliefs persist because persistence in industry size causes learning about returns to scale to be slow. The industry should shrink only moderately if its underperformance continues.

I review the recent high-frequency trader (HFT) literature to single out the economic channels by which HFTs affect market quality. I first group the various theoretical studies according to common denominators and discuss the economic costs and benefits they identify. I then, for each group, review the empirical literature that either speaks to the models' assumptions or their predictions. This enables me to come to a "data-weighted" judgement on the economic value of HFTs.

We study whether exposure to market-wide correlation shocks affects expected option returns, using data on S&P100 index options, options on all components, and stock returns. We present evidence of priced correlation risk based on prices of index and individual variance risk. A trading strategy exploiting priced correlation risk generates a high alpha and is attractive for CRRA investors without frictions. Correlation risk exposure explains the cross-section of index and individual option returns well. The correlation risk premium cannot be exploited with realistic trading frictions, providing a limits to arbitrage interpretation of our ýndings of a high price of correlation risk.

We exploit the merger between BlackRock and Barclays Global Investors to study how changes in expected ownership concentration affect the investment behavior of funds and the cross-section of stocks worldwide. We find that funds with open-end structures and a large exposure to commonly-held stocks begin avoiding these stocks following the merger announcement. This leads to a permanent change in the composition of institutional ownership and a negative price and liquidity impact. We confirm these results in a large sample of global asset management mergers. Our findings suggest that market participants act strategically in response to changes in expected financial fragility.

Abstract_Content: Brownian motion and normal distribution have been widely used in the Black-Scholes option pricing framework to model the return of assets. However, two puzzles emerge from many empirical investigations: the leptokurtic feature that the return distribution of assets may have a higher peak and two (asymmetric) heavier tails than those of the normal distribution, and an empirical abnormity called "volatility smile'' in option pricing. To incorporate both of them, this paper proposes, for the purpose of option pricing, a double exponential jump diffusion model. The main attraction of the model is its simplicity. In particular, it is simple enough to derive analytical solutions for a variety of option pricing problems, including call and put options, interest rate derivatives and path-dependent options; it seems impossible for many other alternative models to do this. Equilibrium analysis and a psychological interpretation of the model are also presented.

We survey 509 equity portfolio managers from both traditional and sustainable funds on whether, why, and how they incorporate firms’ environmental and social (“ES”) performance into investment decisions. ES performance influences stock selection, engagement, and voting for over three quarters of investors, including nearly two thirds of traditional investors. The primary motivation is financial, even among funds marketed as sustainable. Few are willing to sacrifice financial returns for ES performance, largely due to fiduciary duty concerns. A second driver is constraints, such as fund mandates, firmwide policies, and client wishes, which led 72% to make stock selection, voting, or engagement decisions they otherwise would not have. Achieving ES impact is seen as much less important, even among sustainable funds.

In this paper a stochastic volatility model is presented that directly prescribes the stochastic development of the implied Black-Scholes volatilities of a set of given standard options. Thus the model is able to capture the stochastic movements of a full term structure of implied volatilities. The conditions are derived that have to be satisfied to ensure absence of arbitrage in the model and its numerical implementation is discussed.

Paired-switching refers to investing in one of a pair of negatively correlated equities/ETFs/Funds and periodic switching of the position on the basis of either the relative performance of the two equities/ETFs/Funds over a period immediately prior to the switching or some other criterion. It is based upon the idea that if the returns of two equities are negatively correlated, the overlapping of the periods during which the equities individually yield returns greater than their mean values will be infrequent. Consequently, if the criterion for switching is even minimally accurate in its ability to identify the boundaries of such periods, there is a possibility of improving the performance of the portfolio consisting of the two equities over the portfolio wherein the two equities are statically weighted on the basis of traditional methods such as, for example, variance minimization. In this paper we present some results that indicate that some very simple criteria for paired-switching can lead to lower volatility without any significant penalty in terms of lower returns.

In this paper a new credit risk model for credit derivatives is presented. The model is based upon the "Libor market" modelling framework for default-free interest rates. We model effective default-free forward rates and effective forward credit spreads as lognormal diffusion processes, and recovery is modelled as a fraction of the par value of the defaulted claim. The newly introduced survival-based pricing measures are a valuable tool in the pricing of defaultable payoffs and allow a straightforward derivation of the no-arbitrage dynamics of forward rates and forward credit spreads. The model can be calibrated to the prices of defaultable coupon bonds, asset swap rates and default swap rates for which closed-form solutions are given. For options on default swaps and caps on credit spreads, approximate solutions of high accuracy exist. This pricing formula for options on default swaps is made exact in a modified modelling framework using an analogy to the swap measure, the default swap measure.

We estimate the risk premium for firm-level climate change exposure among S\&P 500 stocks and its time-series evolution between 2005 to 2020. Exposure reflects the attention paid by market participants in earnings calls to a firm's climate-related risks and opportunities. When extracted from realized returns, the unconditional risk premium is insignificant but exhibits a period with a positive risk premium before the financial crisis and a steady increase thereafter. Forward-looking expected return proxies deliver an unconditionally positive risk premium, with maximum values of 0.5% to 1% p.a., depending on the proxy, between 2011 and 2014. The risk premium has been lower since 2015, especially when the expected return proxy explicitly accounts for the higher opportunities and the lower crash risks that characterize high-exposure stocks. This finding arises as the priced part of the risk premium primarily originates from uncertainty about climate-related upside opportunities. In the time series, the risk premium is negatively associated with green innovation, Big Three holdings, and ESG fund flows, and positively associated with climate change adaptation programs.

By calculating an estimated measure of undetected insider trading, this paper shows that profits made by informed corporate insiders prior to tender offer announcements increase after the first enforcement of insider trading laws. I analyze the effects of Insider Trading regulation on a sample of 5,099 acquisitions in 56 different countries, and estimate the profits due to insider trading from the abnormal volume in the weeks prior to the announcement, under the assumption that insiders purchase those shares at the prevailing price and hold them until the public announcement. I find that laws that prosecute insider trading fail to eliminate profits made by insiders, and make acquisitions more expensive. Therefore, by increasing the market reaction to an acquisition, insider trading laws make it profitable to violate them.

This paper aims to identify the likely source(s) of value that cryptocurrencies exhibit in the marketplace using cross sectional empirical data examining 66 of the most used such 'coins'. A regression model was estimated that points to three main drivers of cryptocurrency value: the difficulty in 'mining' for coins; the rate of unit production; and the cryptologic algorithm employed. Bitcoin-denominated relative prices were used, avoiding much of the price volatility associated with the dollar exchange rate. The resulting model can be used to better understand the drivers of relative value observed in the emergent area of cryptocurrencies.

In this article we examine the backfill bias or instant history bias for hedge funds using additional information from the Tass database. This is information about the exact date a hedge fund starts reporting to Tass. Using this information we are able to reveal the length of the instant histories. We find these to be just over 3 years on average. This number is far greater than previously documented. More than half of the recorded returns in the database are backfilled. The magnitude of the overall backfill bias is about 4 percent per annum on average. Again this number exceeds all previous estimates of the backfill bias we are aware of. We elaborate further across different time periods styles. Next, we eliminate backfilled returns and use survivorship free data to create a universe in which we could invest in real time. We introduce an investor who invests an equal amount in each fund that is in the universe. Conditional on this investment strategy our results indicate that the backfill bias is underestimated, and has a substantial downward effect on the returns across most hedge fund styles and is consistent over time for the whole sample. We have no reason to believe that our conclusions are limited to the Tass database.

Credit rating agencies (CRAs) bear some responsibility for the financial crisis that started in 2007 and remains ongoing. This is acknowledged by policymakers, market participants, and by the agencies themselves. It soon became clear that, given the depth of the crisis, CRAs would not be able to satisfy policymakers by eliminating flaws in their rating methods and improving corporate governance. Although the CRAs were more or less unregulated before the outbreak of the financial crisis, after the crisis started, politicians became increasingly vocal in demanding regulation. Initially, these demands were confined to a more binding form of self-regulation. But as the crisis progressed, the calls for state regulation grew ever louder. It became apparent after the November 2008 G-20 summit in Washington that state regulation could no longer be avoided. In Europe, the course had been set in this direction even before then. Since European policymakers saw the crisis as evidence that the Anglo-Saxon approach to the financial markets had failed, they believed they were now strongly placed to have a decisive influence on shaping a new international financial order. It is remarkable to note the shift in European policy from a self-regulatory approach, which was comparatively liberal in international terms, to quite rigorous state regulation of CRAs. Both the European Commission and the European Parliament drew up far-reaching plans. Although European policymakers knew that only globally consistent regulation would be appropriate for a new world financial order, their initial draft legislation was geared more toward stand-alone European regulation. While the final version of the European Union Regulation on Credit Rating Agencies focuses firmly on the European arena, the key point for all market participants is that this is unlikely to have an adverse effect on the global ratings market. It must nevertheless be recognized that the scope of the selected regulatory approach is extremely narrow. Certainly, it has the potential to improve the corporate governance of CRAs and prevent conflicts of interests. But it can do nothing to address the repeated calls for greater competition or for CRAs to be made liable for their ratings.

How can we report returns for a swap that has zero value? How can we perform return optimization for a zero-value long-short portfolio? By introducing a suitable "basis", it is possible to extend the definition of returns to leveraged products in such a way that performance attribution and portfolio optimization are feasible. Risk-adjusted performance attribution and connections of performance attribution with probability theory are also discussed.

We investigate the relation between two market anomalies to provide insights into analysts' role as information intermediaries. Prior research finds that accruals and analyst earnings forecast revisions predict future returns. We find that the accrual and forecast revision strategies generate returns of 15.5% and 5.5% when implemented independently. Strikingly, a combined strategy that uses forecast revisions to refine the accrual strategy generates a return of 28.5%. Firms with consistent accrual and forecast revision signals have less persistent accruals and earnings. We also find that accruals can be used to refine the forecast revision strategy - high accruals are associated with overoptimism in analyst forecasts. Our findings indicate that although forecast revisions reflect information about accrual and earnings persistence beyond that reflected in the level of current year accruals, investors do not fully incorporate this information into their valuation assessments.

We document and explain the sharp performance deterioration of smart beta indexes after the corresponding smart beta ETFs are launched for investment. While smart beta is purported to deliver excess returns through factor exposures, the market-adjusted return of smart beta indexes drops from about 3% “on paper” before ETF listings to about -0.50% to -1% after ETF listings. This performance decline cannot be explained by variation in factor premia, strategic timing, or diminishing returns to scale. Instead, we find strong evidence of data mining in the construction of smart beta indexes, which helps ETFs attract flows, as investors respond positively to backtests.

When annual earnings are regressed on annual returns, the returns coefficient is higher when returns are negative. The difference between the coefficients of earnings on positive and negative returns is called asymmetric timeliness of earnings and, in the accounting literature, is used extensively as a conservatism measure. The objective of this paper is to investigate the relation between asymmetric timeliness and the market-to-book ratio (MTB), using a theory of accounting conservatism that reflects the role of accounting as observed in practice. Recent literature has focused on the negative relation between the two measures. Using our theory of conservatism, we predict and observe empirically that the relation between asymmetric timeliness over a period and MTB at the end of the period is positive when asymmetric timeliness is measured cumulatively over long horizons. Our paper further highlights that when asymmetric timeliness is measured over short periods not including the firm's IPO, it is dependent on the composition of equity value at the beginning of that period. This dependence is responsible for the negative association observed between asymmetric timeliness estimated over short periods and MTB at the end of the period. Our theory and empirical results further suggest that asymmetric timeliness is a better measure of total conservatism at a point in time when it is estimated cumulatively over multiple years preceding that time. Overall, our results are consistent with our theory that accounting does not record changes in rents and is asymmetrically timely in recording changes in separable asset values.

We construct a robust stochastic discount factor (SDF) that summarizes the joint explanatory power of a large number of cross-sectional stock return predictors. Our method achieves robust out-of-sample performance in this high-dimensional setting by imposing an economically motivated prior on SDF coefficients that shrinks the contributions of low-variance principal components of the candidate factors. While empirical asset pricing research has focused on SDFs with a small number of characteristics-based factors --- e.g., the four- or five-factor models discussed in the recent literature --- we find that such a characteristics-sparse SDF cannot adequately summarize the cross-section of expected stock returns. However, a relatively small number of principal components of the universe of potential characteristics-based factors can approximate the SDF quite well.

This paper examines the effect of accounting conservatism on firm-level investment during the 2007-2008 global financial crisis. Using a differences-in-differences design, we find that firms with less conservative financial reporting experienced a sharper decline in investment activity following the onset of the crisis compared to firms with more conservative financial reporting. This relation was stronger for firms that were financially constrained, faced greater external financing needs, or had higher information asymmetry. We also find that more conservative firms experienced lower declines in both debt raising activity and stock performance. The evidence suggests that accounting conservatism reduces underinvestment in the presence of information frictions.