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Our analytical description of how banks’ responses to asset price changes can result in procyclical leverage reveals that for banks with a binding regulatory leverage constraint, absent differences in regulatory risk weights across assets, leverage is not procyclical. For banks without a binding constraint, fair value and bank regulation both can contribute to procyclical leverage. Empirical findings based on a large sample of US commercial banks reveal that bank regulation explains procyclical leverage for banks relatively close to the regulatory leverage constraint and contributes to procyclical leverage for those that are not. Fair value accounting does not contribute to procyclical leverage.
Using survey data from a sample of senior investment professionals from mainstream (i.e. not SRI funds) investment organizations we provide insights into why and how investors use reported environmental, social and governance (ESG) information. The primary reason survey respondents consider ESG information in investment decisions is because they consider it financially material to investment performance. ESG information is perceived to provide information primarily about risk rather than a company’s competitive positioning. There is no one size fits all, with the financial materiality of different ESG issues varying across sectors. Lack of comparability due to the lack of reporting standards is the primary impediment to the use of ESG information. Most frequently, the information is used to screen companies with the most often used method being negative screening. However, negative screening is perceived as the least investment beneficial while full integration into stock valuation and positive screening considered more beneficial. Respondents expect negative screening to be used less in the future, while positive screening and active ownership to be used more.
In this paper we characterise the propensity of big capital investments to systematically deliver poor outcomes as "fragility," a notion suggested by Nassim Taleb. A thing or system that is easily harmed by randomness is fragile. We argue that, contrary to their appearance, big capital investments break easily — i.e. deliver negative net present value — due to various sources of uncertainty that impact them during their long gestation, implementation, and operation periods. We do not refute the existence of economies of scale and scope. Instead we argue that big capital investments have a disproportionate (non-linear) exposure to uncertainties that deliver poor or negative returns above and beyond their economies of scale and scope. We further argue that to succeed, leaders of capital projects need to carefully consider where scaling pays off and where it does not. To automatically assume that "bigger is better," which is common in megaproject management, is a recipe for failure.
The persistence of returns is a critical issue for investors in their choice of private equity managers. In this paper we analyse buyout performance persistence in new ways, using a unique database containing cash-flow data on 13,523 portfolio company investments by 865 buyout funds. We focus on unique realized deals and find that persistence of fund managers has substantially declined as the private equity sector has matured and become more competitive. Private equity has, therefore, largely conformed to the pattern found in most other asset classes in which past performance is a poor predictor of the future.
This paper studies the properties of bond risk premia in the cross-section of subjective expectations. We exploit an extensive dataset of yield curve forecasts from financial institutions and document a number of novel findings. First, contrary to evidence presented for stock markets but consistent with rational expectations, the relation between subjective expectations and future realizations is positive, and this result holds for the entire cross-section of beliefs. Second, when predicting short term interest rates, primary dealers display superior forecasting ability when compared to non-primary dealers. Third, we reject the null hypothesis that subjective expected bond returns are constant. When predicting long term rates, however, primary dealers have no information advantage. This suggests that a key source of variation in long-term bonds are risk premia and not short-term rate variation. Fourth, we show that consensus beliefs are not a sufficient statistics to describe the cross-section of beliefs. Moreover, the beliefs of the most accurate agents are those most spanned by a contemporaneous cross-section of bond prices. This supports equilibrium models and Friedman's market selection hypothesis. Finally, we use ex-ante spanned subjective beliefs to study predictions of several reduced-form and structural models and uncover a number of statistically significant relationships in favour of rational expectations.
Governments across the globe are eager to foster entrepreneurial ecosystems, yet there is no consensus on what policies to use. We develop a theory about the equilibrium consequences of two canonical types of entrepreneurship policies: policies that encourage entrepreneurs to found new ventures, and policies that encourage investors to fund new ventures. We distinguish between a short-term impact on current market activity, versus a long-term impact on future activity. Investing in entrepreneurial ventures requires tacit knowledge that is mainly acquired through prior entrepreneurial experience, implying that the supply of capital depends on successful entrepreneurs from prior generations. Recognizing this intergenerational linkage has a profound impact on the market equilibrium, and the effect of entrepreneurship policies. Our analysis identifies a rationale for using funding polices.
We provide evidence that open-end structures undermine asset managers’ incentives to attack long-term mispricing. First, we compare open-end funds with closed-end funds. Closed-end funds purchase more underpriced stocks than open-end funds, especially if the stocks involve high arbitrage risk. We then show that hedge funds with high share restrictions, having a lower degree of open-ending, also trade against long-term mispricing to a larger extent than other hedge funds. Our analysis suggests that open-end organizational structures are not conducive to long-term risky arbitrage.
This article addresses the question of how competition for investments among firms in a certain industry impacts their capital structure. We develop a new modelling framework, which simulates financial variables of a set of firms in a given sector. We use it to analyse how firms are competing for new investments. The leverage of the firm impacts its flexibility to react upon investment opportunities, and we show how it can be optimised to maximise the firm’s growth. As an illustration, we then apply the model on a set of European airlines and global pharmaceutical companies. The novelty that this paper introduces is the explicit modelling of the interaction among several companies. Invariably, the literature on optimal capital structure focuses on a single company optimising its capital structure in a world where the actions of its competitors are exogenous. Corporate Finance theory states that the optimisation of investment opportunities is one of three drivers of optimal leverage (together with reduction of the distress costs or tax expenditures). Our results suggest that the optimal capital structure should incorporate the competitive position of the firm as well as the availability of investment opportunities. Our framework allows corporate decision makers (CEOs and CFOs) to incorporate these aspects in their decision making.
Our main conclusion is that the leverage of the company impacts its ability to capture investment opportunities in a world where such opportunities are scarce. Companies with very low or very high leverage have reduced flexibility to invest, due to a high hurdle rate. Reducing the volatility of cash flows via hedging generally improves the ability to invest. The ability to invest in random growth opportunities is particularly important in mature industries, where investment opportunities are limited. Finally, if more flexible companies exploit investment opportunities this reduces the investment options for their less flexible competitors.
We study the effect that internal information systems have upon a firm’s leverage and corporate governance choices. Information systems lower governance costs by facilitating more targeted interventions. But they also generate asymmetric information between firms and their investors. As a result, firms may attempt to signal their superior quality by assuming more leverage. In some circumstances, this can reduce governance incentives and result in inferior outcomes. Investors anticipate this effect, and it renders information systems inefficient.
The post-2008 period focused attention on "twin-crises". Banking crises may lead to sovereign crises where fiscal vulnerabilities are exacerbated by the extension of support for the banking system. We develop a model that describes private sector generated capital inflow that is used to finance investment and consumption expenditure. In the event of an economic contraction, the (convex) haircut on outstanding debt is negotiated, or bargained, centrally by the sovereign. Two results arise: the volume of debt and haircut rate are inefficient. In this setting the accumulation of capital achieves two goals. First, it generates sufficient optimism about future income to allow the debt market to function. Second, and counter-intuitively, it increases expected haircuts by raising the value of the outside option of complete default. These competing forces characterize the optimal balanced-budget macroprudential policy targeting capital investment.
In this paper I study the relationship between aggregate money balances and subsequent stock and bond returns. I find that levels of broad money multipliers (the ratios of broad money to narrow money) forecast future returns with a negative sign, while changes in these multipliers forecast returns with a positive sign. These findings indicate that levels of multipliers are pro-cyclical: like the P/D ratio, they tend to be high at times of low expected returns. The dynamics of these multipliers may also indicate changes in the volume of financial intermediation and the level of net leverage, consistent with credit-cycle theories of macroeconomic fluctuations.
People share billions of pieces of content such as news, videos, and photos through social media every day. Marketers are interested in the extent to which such content propagates and, importantly, which factors make widespread propagation more likely. Extant research considers various factors, such as content attributes (e.g., newness), source traits (e.g., expertise), and network structure (e.g., connectivity). This research builds on prior work by introducing a novel behavior-focused transmitter characteristic that is positively associated with content propagation in social media: activity, or how frequently a person transmits content. Evidence for this effect comes from five studies and different paradigms. First, two studies using data from large social media platforms (Twitter and LiveJournal) show that content posted by higher-activity transmitters—whom we refer to as “social pumps”—propagates more than content posted by lower-activity transmitters. Second, three experiments explore the mechanism driving this effect, showing that social media users receiving content from a social pump are more likely to retransmit it (a necessary behavior for achieving aggregate-level propagation) because they infer that content from a social pump is more likely to be current, and therefore more attractive as something to pass along through retransmission.
Value at Risk (VaR) forecasts can be produced from conditional autoregressive VaR models, estimated using quantile regression. Quantile modeling avoids a distributional assumption, and allows the dynamics of the quantiles to differ for each probability level. However, by focusing on a quantile, these models provide no information regarding Expected Shortfall (ES), which is the expectation of the exceedances beyond the quantile. We introduce a method for predicting ES corresponding to VaR forecasts produced by quantile regression models. It is well known that quantile regression is equivalent to maximum likelihood based on an asymmetric Laplace (AL) density. We allow the density’s scale to be time-varying, and show that it can be used to estimate conditional ES. This enables a joint model of conditional VaR and ES to be estimated by maximizing an AL log-likelihood. Although this estimation framework uses an AL density, it does not rely on an assumption for the returns distribution. We also use the AL log-likelihood for forecast evaluation, and show that it is strictly consistent for the joint evaluation of VaR and ES. Empirical illustration is provided using stock index data.