# Research articles for the 2020-07-15

arXiv

Generalizing earlier works of Delbaen & Haezendonck [5] as well as of [18] and [16] for given compound mixed renewal process S under a probability measure P, we characterize all those probability measures Q on the domain of P such that Q and P are progressively equivalent and S remains a compound mixed renewal process under Q with improved properties. As a consequence, we prove that any compound mixed renewal process can be converted into a compound mixed Poisson process through a change of measures. Applications related to the ruin problem and to the computation of premium calculation principles in an insurance market without arbitrage opportunities are discussed in [26] and [27], respectively.

SSRN

Analyze the components of administrative expenses and find that some expenditure in administrative expenses, such as employee training expenses, employee education expenses, technology development expenses, etc., which have a long-term positive effect on improving the relationship between enterprises and the government or banks, enhancing employee satisfaction, improving corporate technology, and enhancing corporate competitiveness, so as to create future benets for the enterprise. Based on the empirical analysis, we prove that the previous administrative expenses are positively related to the current operating profit. Through data analysis and empirical research, it shows that: (1) administrative expenses are positively associated with future operating performance; (2) the capital market can partially recognize the future value creation ability of administrative expenditure so that the administrative expense future value has significantly positive pricing coefficient; (3) the capital market fails to fully recognize the future value created by administrative expenditure so that the highest portfolio can experience significantly positive future excess return.

arXiv

We propose an adaptive and explicit fourth-order Runge-Kutta-Fehlberg method coupled with a fourth-order compact scheme to solve the American put options problem. First, the free boundary problem is converted into a system of partial differential equations with a fixed domain by using logarithm transformation and taking additional derivatives. With the addition of an intermediate function with a fixed free boundary, a quadratic formula is derived to compute the velocity of the optimal exercise boundary analytically. As such, it enables us to employ fourth-order spatial and temporal discretization with Dirichlet boundary conditions for obtaining the numerical solution of the asset option, option Greeks, and the optimal exercise boundary. The advantage of the Runge-Kutta-Fehlberg method is based on error control and the adjustment of the time step to maintain the error at a certain threshold. By comparing with some existing methods in numerical experiments, it shows that the present method has a better performance in terms of computational speed and provides a more accurate solution.

SSRN

Relationship between IPOs and Local political turnover has been disputed and studied (Piotroski and Zhang (2014)). In this paper, we further focus on the anti-corruption and IPOs, since 2012 Chairman Xi announced and conducted a series of action of "hit the tiger" in order to reduce the anti-corruption and pure discipline in CPC. By examining and testing provincial panel data, we found the demotion of provincial officials can affect IPO decisions of Chinese companies that are eligible to list, those who take advantage of the window where companies lose political connections can lead to certain resource allocation inefficiencies. Additionally, firms performance and ownership could also be influenced by such demotion and anti-corruption.

arXiv

We consider the problem of computing the Value Adjustment of European contingent claims when default of either party is considered, possibly including also funding and collateralization requirements. As shown in Brigo et al. (\cite{BLPS}, \cite{BFP}), this leads to a more articulate variety of Value Adjustments ({XVA}) that introduce some nonlinear features. When exploiting a reduced-form approach for the default times, the adjusted price can be characterized as the solution to a possibly nonlinear Backward Stochastic Differential Equation (BSDE). The expectation representing the solution of the BSDE is usually quite hard to compute even in a Markovian setting, and one might resort either to the discretization of the Partial Differential Equation characterizing it or to Monte Carlo Simulations. Both choices are computationally very expensive and in this paper we suggest an approximation method based on an appropriate change of numeraire and on a Taylor's polynomial expansion when intensities are represented by means of affine processes correlated with the asset's price. The numerical discussion at the end of this work shows that, at least in the case of the CIR intensity model, even the simple first-order approximation has a remarkable computational efficiency.

SSRN

We test whether the unconventional monetary policy (UMP) announcements by the Federal Reserve and the European Central Bank represent a risk factor for the hedge fund industry as a whole and for ten commonly used strategies in particular. Using modified event studies and Markov switching models, we find that UMP announcements represent a risk factor for Convertible Arbitrage, Dedicated Short Bias, Emerging Markets, Equity Market Neutral, Fixed Income Arbitrage strategies as well as the Multi-Strategy type. We further test whether UMP announcements have an indirect effect on hedge fundsâ€™ performance through breaks in the parameters of the conventional risk factors. Using Chow and Bai-Perron tests, we find that for the industry as a whole and for all strategies, most and Bai-Perron tests, we find that for the industry as a whole and for all strategies, most of the UMP announcements correspond to break dates for the traditional factor loadings.

SSRN

In light of recent announcements of the Ministry of Finance about the emission of the so-called national bonds, this paper deals with the problems related to bonds as the most widely accepted financial instrument on the Croatian secondary market. Although the meaning of the bond as a debt security financial instrument is probably clear to everyone, trading and utilization of all the advantage this financial instrument offers is still insufficiently developed. Moreover, since bonds appear to be a possible alternative to bank deposits, it is necessary to determine the basic concepts of the difference in the calculation of yield between these two potential investments. Considering these facts, the contribution of this paper is aimed at taking a closer look and simplifying the overall understanding of this significant financial instrument. On top of that, the purpose of this paper is to raise the awareness of the broader public with respect to understanding of the basic characteristics of bonds, their advantages and disadvantages and ultimately to elaborate in detail the investment possibilities offered by bonds, as one of the most popular debt security financial instrument in Croatia. The first chapter describes the general problems related to bonds, their basic characteristics and current divisions. The paper then elaborates current dynamics of bonds in the secondary capital market in the Republic of Croatia, providing a comparative presentation of purchase and sale trade channels in the secondary market. The final chapter shows a practical example of price and yield calculation until maturity of the bond issued by the Ministry of Finance of RoC, being traded on Zagreb Stock Exchange.

SSRN

Cryptocurrencies represent a new type of digital asset that cannot be linked to the framework of fundamental and systematic factors of existing financial instruments of the traditional capital market. Due to the lack of strictly defined fundamental indicators, supported by the results of research by the academic community, considering cryptocurrencies as investment opportunities can put investors in a subordinate position, a situation of complete uncertainty. Cryptocurrencies and their entire technical infrastructure are still a kind of unknown to the general public. Due to this, but also the lack of a regulatory framework, investors have to rely on sometimes uncertain information gathered through various media platforms. However, regardless of the type of assets and the mentioned shortcomings, when constructing a portfolio, investors should consider the dynamics of returns of potential components of the portfolio in order to identify and quantify the assumed investment risk and define the expected return. Cryptocurrencies are based on the idea of decentralization initially introduced by bitcoin blockchain technology and as such have their own historical sequence of origin. Since bitcoin is the first digital currency based on asymmetric cryptography, the change in its value can serve as a leading indicator of the movement of the cryptocurrency market as a whole. Accordingly, this paper will formally identify and describe the performance of the cryptocurrency portfolio with different optimization goals taking into account the assumption of a significant systematic impact of bitcoin cryptocurrency on the dynamics of the value of the aggregate secondary cryptocurrency market. For this purpose, six optimization targets will be formed: MinVar, MinCVaR, MaxSR, MaxSTARR, MaxUT and MaxMean. The results of the formed portfolios will be compared with the results of portfolios with the same allocation objectives, but which include a limitation on the impact of BTC as a systematic factor. The results suggest that by controlling the exposure by factor, better overall portfolio performance can be achieved through higher returns and Sharpe Ratio in four of the six implemented optimization strategies, while in terms of absolute risk measure five out of six portfolios achieved lower overall risk. Also, the obtained results confirm that the bitcoin transaction system plays a major role in defining the future movement of the value of the secondary cryptocurrency market.

arXiv

The purpose of this study is to investigate the effects of the COVID-19 pandemic on economic policy uncertainty in the US and the UK. The impact of the increase in COVID-19 cases and deaths in the country, and the increase in the number of cases and deaths outside the country may vary. To examine this, the study employs bootstrap ARDL cointegration approach from March 8, 2020 to May 24, 2020. According to the bootstrap ARDL results, a long-run equilibrium relationship is confirmed for five out of the 10 models. The long-term coefficients obtained from the ARDL models suggest that an increase in COVID-19 cases and deaths outside of the UK and the US has a significant effect on economic policy uncertainty. The US is more affected by the increase in the number of COVID-19 cases. The UK, on the other hand, is more negatively affected by the increase in the number of COVID-19 deaths outside the country than the increase in the number of cases. Moreover, another important finding from the study demonstrates that COVID-19 is a factor of great uncertainty for both countries in the short-term.

arXiv

Geometric Arbitrage Theory reformulates a generic asset model possibly allowing for arbitrage by packaging all assets and their forwards dynamics into a stochastic principal fibre bundle, with a connection whose parallel transport encodes discounting and portfolio rebalancing, and whose curvature measures, in this geometric language, the 'instantaneous arbitrage capability' generated by the market itself. The cashflow bundle is the vector bundle associated to this stochastic principal fibre bundle for the natural choice of the vector space fibre. The cashflow bundle carries a stochastic covariant differentiation induced by the connection on the principal fibre bundle. The link between arbitrage theory and spectral theory of the connection Laplacian on the vector bundle is given by the zero eigenspace resulting in a parametrization of all risk neutral measures equivalent to the statistical one. This indicates that a market satisfies the (NFLVR) condition if and only if $0$ is in the discrete spectrum of the connection Laplacian on the cash flow bundle or of the Dirac Laplacian of the twisted cash flow bundle with the exterior algebra bundle. We apply this result by extending Jarrow-Protter-Shimbo theory of asset bubbles for complete arbitrage free markets to markets not satisfying the (NFLVR). Moreover, by means of the Atiyah-Singer index theorem, we prove that the Euler characteristic of the asset nominal space is a topological obstruction to the the (NFLVR) condition, and, by means of the Bochner-Weitzenb\"ock formula, the non vanishing of the homology group of the cash flow bundle is revealed to be a topological obstruction to (NFLVR), too. Asset bubbles are defined, classified and decomposed for markets allowing arbitrage.

SSRN

We study how investorâ€™s persistent preference to invest more in the home market â€" â€œhome biasâ€ â€" is affecting investorâ€™s efforts to mitigate risks associated with climate change. When investors have a tendency to tilt their portfolio towards domestic assets, the carbon intensity in the home market may well affect the carbon exposures of their portfolios and hence climate risk. This paper analyzes the carbon exposure and home bias of stock portfolios across a wide range of different investors from the euro area using a unique stock-level holdings data. We find that at the stock-level, carbon-intensive firms have higher ownership when the stocks are from the EU-home market. At the portfolio level, higher carbon footprints of euro area investors are related to home bias. The bias to invest more in carbon-intensive firms from the domestic and EU-home market is associated with higher stocks returns.

arXiv

In this paper, we investigate the mesoscale structure of the World Trade Network. In this framework, a specific role is assumed by short and long-range interactions, and hence by the distance, between countries. Therefore, we identify clusters through a new procedure that exploits Estrada communicability distance and the vibrational communicability distance, which turn out to be particularly suitable for catching the inner structure of the economic network. The proposed methodology aims at finding the distance threshold that maximizes a specific modularity function defined for general metric spaces. Main advantages regard the computational efficiency of the procedure as well as the possibility to inspect intercluster and intracluster properties of the resulting communities. The numerical analysis highlights peculiar relationships between countries and provides a rich set of information that can hardly be achieved within alternative clustering approaches.

SSRN

Crash risk has been a hot dispute since financial crisis (2008) and the Chinese stock market crash (2015). Many literature including features of managers have been discussed to connect them with crash risk. However, fewer literatures focus on the channel between innovation and crash risk. In this paper, two different channels of innovation input and output have been constructed to explain the crash risk. Innovation input, R&D activities under earnings management, increase the information asymmetry and crash risk, while innovation output, patent quality for its public availability for datum, decrease the information asymmetry, and crash risk. Sample selection for innovative firms and non-innovative firms have been examined to be robust. The financial crisis has also been tested to verify the crash risk. We hope to build two mechanisms for conduction between innovation and crash risk in China.

SSRN

Our paper presents a crude oil price model in which the price is confined in a wide moving band. A price crash occurs when the price breaches the lower boundary where a smooth-pasting condition is imposed. Using an asymmetric mean-reverting fundamental (supply/demand) shock, the solution derived from the oil price equation for the model shows the oil price follows a mean-reverting square-root process, which is quasi-bounded at the boundary. The oil price dynamics generates left-skewed price distributions consistent with empirical observations. A weakened mean-reverting force for the price increases the probability leakage for the price across the boundary and the risk of a price crash. The empirical results show the oil price dynamics can be calibrated according to the model, where the mean reversion of the price dynamics is positively co-integrated with the oil production reaction to negative demand shocks, and with the risk reversals of the commodity currencies, the Canadian dollar and the Australian dollar in currency option markets. The results are consistent with an increased price crash risk with negative demand shocks and negative risk reversals. The forecasting performance of the oil price model is better than the futures-spread models and random walk models during the crash periods. While the price of oil was above the lower boundary for most of the time, the conditions for breaching the boundary were met in 2008 and 2014 when the price fell sharply.

arXiv

The present work addresses theoretical and practical questions in the domain of Deep Learning for High Frequency Trading, with a thorough review and analysis of the literature and state-of-the-art models. Random models, Logistic Regressions, LSTMs, LSTMs equipped with an Attention mask, CNN-LSTMs and MLPs are compared on the same tasks, feature space, and dataset and clustered according to pairwise similarity and performance metrics. The underlying dimensions of the modeling techniques are hence investigated to understand whether these are intrinsic to the Limit Order Book's dynamics. It is possible to observe that the Multilayer Perceptron performs comparably to or better than state-of-the-art CNN-LSTM architectures indicating that dynamic spatial and temporal dimensions are a good approximation of the LOB's dynamics, but not necessarily the true underlying dimensions.

SSRN

Using a forward-looking measure of climate risk exposure based on textual analysis of firms' 10-K reports, we assess whether climate risks â€" as disclosed to the regulator â€" are priced in the credit default swap (CDS) market. We construct a novel climate risk measure based on BERT, an advanced context-based language understanding algorithm, and we adapt it for our purposes. Differentiating between physical and transition risks, we find that transition risk increases CDS spreads, especially after the Paris Climate Agreement of 2015. These increases are statistically and economically highly significant. However, we do not find such an effect for physical risk.

SSRN

We document significant spreads in style factors â€" value, size, quality, momentum, and low volatility â€" in each of the style box categories. This is also true even for the value and small size factors, which are reflected in the original definition of the style box framework. Some single factors stay within a given style box, like quality in Core, while other factors drift across style boxes, like momentum and even the size factor! We build multifactor portfolios within each style box, giving access to five style factors that can stay within a style category which have exhibited information ratios over 1.0 over June 2003 to March 2019.

arXiv

Using the carefully selected industry classification standard, we divide 102 industry securities indices in China's stock market into four demand-oriented sector groups and identify demand-oriented industry-specific volatility spillover networks. The "deman-oriented" is a new idea of reconstructing the structure of the networks considering the relationship between industry sectors and the economic demand their outputs meeting. Networks with the new structure help us improve the understanding of the economic demand change, especially when the macroeconomic is dramatically influenced by exogenous shocks like the outbreak of COVID-19. At the beginning of the outbreak of COVID-19, in China's stock market, spillover effects from industry indices of sectors meeting the investment demand to those meeting the consumption demands rose significantly. However, these spillover effects fell after the outbreak containment in China appeared to be effective. Besides, some services sectors including utility, transportation and information services have played increasingly important roles in the networks of industry-specific volatility spillovers as of the COVID-19 out broke. By implication, firstly, being led by Chinese government, the COVID-19 is successfully contained and the work resumption is organized with a high efficiency in China. The risk of the investment demand therefore was controlled and eliminated relatively fast. Secondly, the intensive using of non-pharmaceutical interventions (NPIs) led to supply restriction in services in China. It will still be a potential threat for the Chinese economic recovery in the next stage.

SSRN

Using four different asset pricing models to estimate the residual returns, I show empirically that there are no material differences in the statistical and economic significance between idiosyncratic momentum strategies based on different asset-pricing models. I also show that idiosyncratic momentum is priced in the cross-section of returns, but spanned by a combination of risk factors when the combination includes price momentum. Despite being explained by common risk factors, the results suggest that idiosyncratic momentum is a stronger factor than price momentum and has a lower exposure to earnings momentum than price momentum.

SSRN

This paper studies the relation between immediate market response to corporate earnings announcements and subsequent stock price movement. By adapting an information signal model from Holthausen and Verrecchia (1988), we develop a new measure â€" the immediate earnings response coefficient (IERC) â€" to capture immediate market response. We find that a smaller immediate market reaction to earnings surprise, or a lower IERC, leads to a larger subsequent market response. A trading strategy based on our findings can generate an average abnormal return of 5.21% per quarter.

SSRN

This paper draws upon several distinct contributions to improve the out-of- sample forecasting performance of realized volatility models. More specifically, we retain the rolling-sample idea of Andreou and Ghysels (2002) to propose a new approach we call the Rolling Realized Volatility (RRV ), which samples consecutive high-frequency squared returns regardless of whether they originate from the same trading session like in the traditional approach. This new approach yields a sample approximately M times larger than the traditional approach, where M is the intraday sampling frequency. The new approach has at least two advantages. First, having more observations increases the informational dynamics of the OLS regression. Second, the Rolling method accounts for the serial correlation between the last returns in day t âˆ' 1 and the first returns in day t. We test competing out-of-sample forecast losses from the new approach against those of the traditional method for the S&P 500 and 26 Dow Jones Industrial Average stocks. Using several state-of-the-art realized volatility models, both a simulation and an empirical exercise strongly suggest the Rolling approach yields superior out-of-sample performance over the traditional approach.

SSRN

Croatian Abstract: Cilj rada je provoÄ'enje empirijskog testiranja teorije hijerarhijske financijskih izbora (pecking order theory) na hrvatskom trÅ¾iÅ¡tu kapitala. IstraÅ¾ivanje je obuhvatilo 17 nefinancijskih druÅ¡tava uvrÅ¡tenih na ZagrebaÄkoj burzi za razdoblje od 2008. - 2016. godine, odnosno za sva uvrÅ¡tena druÅ¡tva za koja su bili raspoloÅ¾ivi svi podatci za navedeno razdoblje. Iz uzorka su iskljuÄena druÅ¡tva iz financijskog sektora. Ispitivanje postojanja hijerarhije financijskih izbora provedeno je prema postavkama regresijskog modela Shyam-Sundersa i Myersa (1999). Rezultati indiciraju odbacivanje hipoteze o postojanju jakog oblika hijerarhije financijskih izbora i sugeriraju prihvaÄ‡anje postojanja slabog oblika hijerarhije financijskih izbora, Å¡to je u korelaciji s prijaÅ¡njim istraÅ¾ivanjima provedenim na drugim trÅ¾iÅ¡tima.English Abstract: The purpose of this paper is empirical testing of the pecking order theory of the capital structure on Croatian capital market. The survey included 17 non-Ãž nancial corporations listed on the Zagreb Stock Exchange for the period 2008 - 2016, i.e. all the listed companies for which all the required data were available. Companies from Ãž nancial sector were excluded from the sample. The existence of the pecking order theory was carried out according to the regression model of Shyam-Sunders and Myers (1999). The results indicate the rejection of the hypothesis of the existence of a strong form of pecking order theory and suggest acceptance of the weak form of pecking order theory. The result is in accordance with other certain studies for the other markets.

arXiv

The objective of this work is twofold: to expand the depression models proposed by Tobin and analyse a supply shock, such as the Covid-19 pandemic, in this Keynesian conceptual environment. The expansion allows us to propose the evolution of all endogenous macroeconomic variables. The result obtained is relevant due to its theoretical and practical implications. A quantity or Keynesian adjustment to the shock produces a depression through the effect on aggregate demand. This depression worsens in the medium/long-term. It is accompanied by increases in inflation, inflation expectations and the real interest rate. A stimulus tax policy is also recommended, as well as an active monetary policy to reduce real interest rates. On the other hand, the pricing or Marshallian adjustment foresees a more severe and rapid depression in the short-term. There would be a reduction in inflation and inflation expectations, and an increase in the real interest rates. The tax or monetary stimulus measures would only impact inflation. This result makes it possible to clarify and assess the resulting depression, as well as propose policies. Finally, it offers conflicting predictions that allow one of the two models to be falsified.

arXiv

Geometric mean market makers (G3Ms), such as Uniswap and Balancer, comprise a popular class of automated market makers (AMMs) defined by the following rule: the reserves of the AMM before and after each trade must have the same (weighted) geometric mean. This paper extends several results known for constant-weight G3Ms to the general case of G3Ms with time-varying and potentially stochastic weights. These results include the returns and no-arbitrage prices of liquidity pool (LP) shares that investors receive for supplying liquidity to G3Ms. Using these expressions, we show how to create G3Ms whose LP shares replicate the payoffs of financial derivatives. The resulting hedges are model-independent and exact for derivative contracts whose payoff functions satisfy an elasticity constraint. These strategies allow LP shares to replicate various trading strategies and financial contracts, including standard options. G3Ms are thus shown to be capable of recreating a variety of active trading strategies through passive positions in LP shares.

SSRN

Central banks' macro-prudential supervisory activities have to fulfill three distinct tasks: (i) assessing banking system's vulnerability to exogenous adverse turbulence, (ii) evaluating the risk of systemic crisis originating from idiosyncratic shocks and (iii) measuring financial markets' sensitivity to policy stimuli. Being macro-prudential stress tests the centerpiece of this policy approach a question arises: are they up to the task? Studying how 2011 to 2018 EBA stress tests affected market risk perception, we show that they provided agents with valuable information on the policy stance and on the vulnerability of the banking system, serving their function especially under the second and third dimensions.

SSRN

In business research, firm size is both ubiquitous and readily measured. In contrast, complexity, another firm-related construct, is frequently relevant, but difficult to measure and not well defined. As a result, complexity is seldom incorporated in empirical designs. Measures such as the number of firm segments or the readability of a firmâ€™s financial filings are often used as proxies for some aspect of complexity. We argue that most extant measures of complexity are misspecified, one-dimensional, and/or not widely available. We propose a text-based solution as a widely available, omnibus measure of this multidimensional concept and use audit feesâ€"which are well established as being largely driven by size and complexityâ€"as the primary empirical framework for evaluation. Because this is a new measure, we also consider alternative contexts, including returns around 10-K filings, initial public offerings, unexpected earnings, and the COVID-19 crisis.

SSRN

Using data on international, on-line media coverage and tone of the Brexit referendum, we test whether it is media coverage or tone to provide the largest forecasting performance improvements in the prediction of the conditional variance of weekly FTSE 100 stock returns. We find that versions of standard symmetric and asymmetric Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models augmented to include media coverage and especially media tone scores outperforme traditional GARCH models both in-and-out-of-sample.

SSRN

We examine the effect of pay discrimination on corporate innovation and inventor productivity using difference-in-differences regressions based on the staggered passage of state-level pay secrecy laws that mitigate pay discrimination. We find significant increases in the quantity and quality of patents produced by firms and inventors in states that have passed such laws. Moreover, the effects of this legislation are more pronounced for firms in states with greater existing pay gaps. Further mechanism tests indicate that the passage of pay secrecy laws promotes innovation by motivating inventors (especially minority ones) to exert more effort, enhancing teamwork, and attracting talented minority inventors.

SSRN

Microfinance contracts have enormous economic and welfare significance. We study, theoretically and empirically, the problem of effort choice under individual liability (IL) and joint liability (JL) contracts when loan repayments are made either privately, or publicly in front of one's social group. Our theoretical model identifies guilt from letting down the expectations of partners in a JL contract, and shame from falling short of normatively inadequate effort, under public repayment of loans, as the main psychological drivers of effort choice. Evidence from our lab-in-the-field experiment in Pakistan reveals large treatment effects and confirms the central roles of guilt and shame. Under private repayment, a JL contract increases effort by almost 100% relative to an IL contract. Under public repayment, effort levels are comparable under IL and JL contracts, which is consistent with recent empirical results. This indicates that shame-aversion plays a more important role as compared to guilt-aversion. Under IL, repayment in public relative to private repayment increases effort by 60%, confirming our shame-aversion hypothesis. Under JL, a comparison of private and public repayment shows that shame trumps guilt in explaining effort choices of borrowers.

SSRN

Activist short sellers identify and publicize allegations of overvaluation, and frequently fraud, to induce long shareholders to sell and thereby to profit from the resulting price decline. We provide descriptive evidence that firms make several distinct types of disclosures in response to activist short seller campaigns and are more likely to respond publicly to ex ante more credible reports. Firms that announce internal investigations launched by the board are significantly more likely to be delisted, face enforcement action, and are less likely to become an acquisition target. Our analysis provides important new evidence on the role of activist short selling and the information revealed in target firm responses.

SSRN

Diverging beliefs about the impact of climate policy on the value of fossil fuel assets can lead investors to different valuations of fossil fuel companies. This paper models the share price formation in a market where one group of investors systematically overestimate future prices, and explores how firms can maximise firm value through share repurchases by responding to changing investor beliefs. We find that the optimal buyback strategy reduces the impact of price volatility on share prices, i.e. the optimal response of the firm is to counteract price variations. When expectations to future prices drop, the optimal response is to buy back shares. Furthermore, we show that the optimal buyback strategy can lead to a persistent and higher share of investors who overestimate future share value compared to the case where the supply of shares are fixed. The result implies that buybacks can dampen price signals originating from fossil fuel divestment. In the light of substantial engagement in buyback programs observed in the US oil sector, divestment is unlikely to have had any significant effect on share prices or firm valuations in this sector.

SSRN

Using a large sample of U.S. firms and their major customers, we find that customersâ€™ social performance has a positive impact on suppliersâ€™ intangible investment, but only a marginal effect on their physical investment. When suppliers gain a new major customer who has better social performance than existing customers, suppliers invest more intangible assets. The results are robust with controls for industry and year fixed effects, customer-base concentration, and firm characteristics of both suppliers and customers. Our findings are consistent with the implicit contract theory that customersâ€™ social performance affects the trustworthiness of their implicit commitments to suppliers.

SSRN

The paper describes and analyzes the application of the capital asset pricing model (CAPM) and the single-index model on the Zagreb stock exchange during the drop in the total trade turnover, and mostly in the trade of equity securities. This model shows through the analysis techniques used to estimate the systematic risk per share compared to the market portfolio. Also, the model quantifies the environment in which a company and its stocks exist, expressing it as risk, or a beta coefficient. Furthermore, with respect to the market stagnation, one can also discuss the usefulness of the model, especially if the quality of the input data is questionable. In this regard, the importance of the proper application and interpretation of the results obtained based on the model during the stagnation of the market, and especially during the stagnation of the trade of equity securities, is gaining even greater importance and significance. On the other hand, the results obtained through the analysis of data point to problems arising during the application of the model. It turns out the main problem of applying the CAPM model is the market index with negative returns during the observation period.

arXiv

We apply Geometric Arbitrage Theory to obtain results in Mathematical Finance, which do not need stochastic differential geometry in their formulation. First, for a generic market dynamics given by a multidimensional It\^o's process we specify and prove the equivalence between (NFLVR) and expected utility maximization. As a by-product we provide a geometric characterization of the (NUPBR) condition given by the zero curvature (ZC) condition. Finally, we extend the Black-Scholes PDE to markets allowing arbitrage.

SSRN

This paper studies how stock markets perceive and price cyber risk. We estimate the ex-ante likelihood for a firm to experience a data breach using logistic LASSO regressions combined with cross-validation. Ranking firms based on this proxy for cyber risk, we find that it influences both investor portfolio choices and stock prices. In particular, institutional investors tend to sell stocks with high cyber risk and buy those with low cyber risk; this tendency is stronger during periods with higher data breach concerns. We show that a one-standard deviation increase in cyber risk is associated with a premium of 3.41% per annum.

SSRN

Many research showed a high degree of correlation between the US and European capital markets, partly due to industrialâ€'financial linkages of the United States and Europe, and partly due to the influence of psychological factors on the behavior of individuals, and the concept of behavioral finance. However, it can be assumed that the movement of the value of an observed index does not depend solely on the change of values of the S & P 500 index. Accordingly and in line with rational economic theory, this paper examines the link between changes in the value of selected macroeconomic indicators and the value of the main share Croatian capital market index CROBEX. The results indicate that of the nine initially observed variables, movement of CROBEX can be described and further explained by changes in the value of average wages, parity rate and dollar, the kuna and the euro and the kuna and the Swiss franc.

SSRN

Systematic violations of the no-arbitrage conditions via cash-derivatives bases appeared during and persisted ever since the Global Financial Crisis (GFC). One such fundamental violation is the Covered Interest Rate Parity (CIP) measured by the cross currency basis ("xccy basis"). The literature offers divergent reasons for this violation for the GFC-2014 period (e.g., cost of borrowing, counter party risk, finite capital) versus the post-2014 period (e.g., balance sheet constraints, market segmentation). This paper reconciles the divergent reasons by offering an unified, no-arbitrage framework consistent, explanation for both the occurrence (GFC-2014) and the persistence of this violation post-2014. I introduce collateralization to the valuation of the no-arbitrage conditions. By adjusting for an opportunity cost of collateral, I create (collateralized) "effective" risk-free discount rates to test the CIP conditions. I find that the xccy basis typically follows this introduced opportunity cost of collateral, which is consistent with a narrative that the no-arbitrage framework is not persistently violated. This evidence is supported by two empirical approaches - (1) A panel regression model using a proxy for the cost of collateral composed of General Collateral (GC) repo rates less OIS rates, and (2) A formal multi-currency and multi-curve xccy pricing model that extracts the cost of collateral from multiple swap instruments.

SSRN

This paper attempts to estimate and study the role of 'other information', as posited in the residual income valuation model of Ohlson (1995), for tracking and predicting future returns of the S&P 500. 'Other information' is an unobserved variable and defined as a summary of value-relevant information about events and their effect on future profitability, which is captured in a company's current stock price and returns, but not yet reflected in a company's current financial statements. This suggests a potential to predict subsequent returns. Previous literature has found that traditional valuation metrics (e.g. B/P, E/P, and D/P ratios) have poor predictive power. In this study, we apply a factor augmented vector autoregression (FAVAR) to estimate this value-relevant latent variable and assess its predictive performance. The FAVAR is a suitable model because it enables us to analyze and quantify the linkages of stock market value, profitability, and unobserved factors that are broadly captured by big data. We use a two-step principal components estimation approach to extract the unobserved factors of 78 informational variables from financial market, accounting, investor and consumer sentiment, and macroeconomic data. Our analysis shows that, in comparison to competing measures, the estimated latent value-relevant variable can track contemporaneous stock returns and has statistically reliable power to predict both future real stock returns and excess returns over a Treasury Bill rate, both in- and out-of-sample.

SSRN

We find significantly greater first round Payroll Protection Program (PPP) lending to small businesses in areas in which community banks have a greater market share. One explanation for this pattern is that community banks are less hierarchical which enables branch managers to make faster lending decisions. Consistent with this argument we find distance is a much more important determinant of loan performance for community banks than for large banks. We also find that interest rates on SBA loans are increasing in distance but much less so for loans made by community banks.

SSRN

Using data on 1,312 US equity active mutual funds with $3.9 trillion in AUM, we analyze the link between fundsâ€™ â€œbottoms upâ€ holdings-based environmental, social, and governance (â€œESGâ€) scores and fundsâ€™ active returns, style factor loadings, and alphas. We find that funds with high ESG scores do have different profiles of factor loadings than low-scoring ESG funds. In particular, funds with high Environmental scores tend to have high quality and momentum factor loadings. In partitioning the ESG scores into components that are related to factors (Factor ESG) and idiosyncratic components (Idiosyncratic ESG), we find strong positive relations between fund alphas and Factor ESG scores.

SSRN

Demand and supply uncertainty lead to market models setting prices to levels of acceptable risk for excess supplies and net revenues. The result is a two price equilibrium. Equilibrium solutions applied to financial market data infer demand and supply elasticities and log normal volatilities. Demand elasticities are observed to be higher than supply elasticities as are the volatilities. Normalizing observed volatilities to the volatility of the daily traded volume allows for the inference of a market implied duration of the equilibrium. The median duration is around a minute and half with an interquartile range from 37 seconds to three minutes.

arXiv

On a periodic basis, publicly traded companies report fundamentals, financial data including revenue, earnings, debt, among others. Quantitative finance research has identified several factors, functions of the reported data that historically correlate with stock market performance. In this paper, we first show through simulation that if we could select stocks via factors calculated on future fundamentals (via oracle), that our portfolios would far outperform standard factor models. Motivated by this insight, we train deep nets to forecast future fundamentals from a trailing 5-year history. We propose lookahead factor models which plug these predicted future fundamentals into traditional factors. Finally, we incorporate uncertainty estimates from both neural heteroscedastic regression and a dropout-based heuristic, improving performance by adjusting our portfolios to avert risk. In retrospective analysis, we leverage an industry-grade portfolio simulator (backtester) to show simultaneous improvement in annualized return and Sharpe ratio. Specifically, the simulated annualized return for the uncertainty-aware model is 17.7% (vs 14.0% for a standard factor model) and the Sharpe ratio is 0.84 (vs 0.52).

SSRN

It is puzzling that the single most important explanatory variable for municipal reserves is the state in which a municipality is located. In this paper we leverage a broad panel of US municipalities to show that a pair of behavioral heuristics: anchoring and the bandwagon effect, are an excellent explanation for the state effect, and for municipal reserves. It appears that when it comes to deciding on how much to save, cities target the levels of savings they held in the past, adjusting for the savings levels of their neighbors.

SSRN

This paper uses a natural experiment in Japan to provide evidence of the feedback loop between corporate borrowing and commercial real estate investment emphasized in macro-finance models with collateral constraints. Japan enacted a series of reforms in the early 1980s which relaxed national regulatory constraints on the height and size of buildings. Combining originally-constructed local commercial land price indices for over 400 localities with geocoded firm balance sheets, I show that these land use deregulations generated a boom-bust cycle in corporate real estate values, borrowing, and real estate investment. Firms located in more ex ante land use constrained areas both issued more debt and invested more heavily in real estate, thus amplifying the initial positive shock to commercial real estate prices. I develop a multi-city spatial sorting model with production externalities and real estate collateral which uses the estimated reduced form effects of my local regulatory instruments on firm outcomes to assess aggregate effects of the reform. I find that the deregulatory shock to commercial real estate markets and corporate borrowing environment amplified the real estate cycle in the 1980s and led to an increased incidence of zombie lending in the 1990s.

SSRN

Chinese Abstract: åœ¨è¯åˆ¸æ³•ä¿®è®¢è¿‡ç¨‹ä¸ï¼Œä¸€ä¸ªé‡è¦é—®é¢˜æ˜¯æˆ'å›½æ˜¯å¦åº"å¼•è¿›ç¾Žå›½è"é‚¦è¯åˆ¸æ³•è§„å®šå¹¶è¢«è"é‚¦æœ€é«˜æ³•é™¢å¤šæ¬¡ç•Œå®šçš„â€œæŠ•èµ„åˆåŒâ€ç‰å…œåº•æ¡æ¬¾ã€‚é€šè¿‡ç³»ç»Ÿæ¢³ç†æˆ'å›½ã€Šè¯åˆ¸æ³•ã€‹ä¸è¯åˆ¸æ¦‚å¿µçš„å'å±•è½¨è¿¹ï¼Œæ·±å…¥è€ƒå¯Ÿç¾Žå›½ç»éªŒï¼Œå¹¶ç»"åˆæˆ'å›½å›½æƒ…ï¼ŒåŒ…æ‹¬ç«‹æ³•å'Œå¸æ³•æœºå…³èƒ½åŠ›ã€åˆ†ä¸šç›'ç®¡ä½"åˆ¶å'Œé‡'èžä½"ç³»ç‰¹å¾ç‰ï¼Œå»ºè®®æˆ'å›½çŽ°é˜¶æ®µè¯åˆ¸ç«‹æ³•åº"æ²¿è¢åˆ—ä¸¾æ¨¡å¼ï¼Œå¾ªåºæ¸è¿›å¢žåŠ æ–°åž‹è¯åˆ¸ç±»åž‹ï¼Œä¸å®œç…§æ¬ç¾Žå›½ç»éªŒï¼Œæ€¥åˆ‡å¼•å…¥â€œæŠ•èµ„åˆåŒâ€ç‰æ¡æ¬¾å'Œå¤§ä¸€ç»Ÿè¯åˆ¸å®šä¹‰ã€‚ä½†ä½œä¸ºè¿‡æ¸¡æ€§æŽªæ–½ï¼Œå…¶ä»–æœªåˆ—ä¸¾è¯åˆ¸çš„äºŒçº§å¸‚åœºç›'ç®¡å¯ä»¥é€æ¥äº¤ç"±è¯ç›'ä¼šç»Ÿä¸€è´Ÿè´£ï¼Œä»¥è§£å†³ç›'ç®¡å¥—åˆ©ç‰é—®é¢˜ï¼Œå¹¶ä¸ºå°†æ¥é‡'èžç›'ç®¡ä½"åˆ¶çš„æ·±åŒ–æ"¹é©å¥ å®šåŸºç¡€ã€‚English Abstract: During the recent reform of Chinaâ€™s Securities Law, an important issue is whether China should introduce the catch-all notion of investment contract which is stipulated in the securities law and has been discussed in many court cases in the U.S.. This paper provides a systematic account of the development of the concept of securities in China, conducts an in-depth discussion of the U.S. experiences, and considers Chinaâ€™s local conditions, including the capacity of the legislature and the judiciary, its sectors-based financial regulatory regime, and the characteristics of the current stage of development of the Chinese financial markets. The paper suggests that at the moment, China should continue to enumerate the types of securities to gradually expand the scope of the concept of securities, rather than simply adopt the U.S. experience to introduce a catch-all provision of investment contract. However, as a transition measure, the various types of securities not enumerated under the securities law could be gradually transferred to the jurisdiction of the securities regulator to address the problem of regulatory arbitrage and pave the way for a structural reform of the financial regulation in the future.