Research articles for the 2019-06-12
SSRN
We propose a novel early warning system for detecting financial market crashes that utilizes the information extracted from the shape of financial market movement. Our system incorporates Topological Data Analysis (TDA), a new set of data analytics techniques specialised in profiling the shape of data, into a more traditional machine learning framework. Incorporating TDA leads to substantial improvements in timely detecting the onset of a sharp market decline. Our framework is both able to generate new features and also unlock more value from existing factors. Our results illustrate the importance of understanding the shape of financial market data and suggest that incorporating TDA into a machine learning framework could be beneficial in a number of financial market settings.
SSRN
We present an arbitrage-free affine term structure model that jointly prices U.S. Treasury bonds, S&P 500 dividend strips and the S&P 500 equity index as a function of the economy. Our model allows us to extract new insights on how short- and long-duration dividends and their discount rates respond to changes in the economy. Within the affine model, we obtain accurate decompositions of discount rates into risk free rates, inter est rate and dividend risk premiums. Our model is able to price bond and equity claims with high precision and predict economic variables and returns in bonds and short-horizon dividends.
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Merger announcements cause upward revisions in the market value of target firms' technology peers, whether targets and their peers belong to the same industry or not. Firms having deeper technology overlaps with the targets experience more dramatic price revisions. Consistent with the acquisition probability theory, a firm is more likely to be taken over if at least one of its technology peers has been acquired recently, and peers more vulnerable to acquisitions have greater upward price revisions. Our findings demonstrate that the market for corporate control is an important information source to resolve the uncertainties in technology valuation.
SSRN
With data on 739 European IPOs raising $248 billion, we examine the links between underpricing and adviser monitoring intensity. We compare first-day return impacts of the marketâs three leading advisers with their contractual terms and IPO specialization. We find evidence consistent with monitoring and contracting theories, but also of collusion: rents for unobserved pre-IPO corporate finance advice are collected via higher underpricing and directed to favoured banks. The effects remain when introducing controls and across sub-samples. Our findings suggest unsophisticated issuers, who experience increased underpricing in advised deals, would benefit from greater transparency of advisersâ contracts and bank revenue relationships.
SSRN
This paper studies the link between banks' geographic concentration and the growth in mortgage lending during the boom and bust cycle. Concentrated banks increase their lending relatively less during the boom, and they experience lower reduction in their loans through the ensuing bust. In the aggregate, bank concentration has an impact on the overall credit supply rather than a mere reallocation of lending between concentrated and diversified banks: MSAs with greater exposure to concentrated banks experience less excessive expansion and contraction in mortgage supply during the boom and following bust. As a result, higher bank concentration is associated with less severe boom and bust cycle in house prices.
SSRN
We analyze the effect of CEO food culture on corporate innovation using a sample of Chinese listed firms from 2000 to 2016. We extend benign masochism and behavioral consistency theories to determine that a CEO with Szechuan cuisine food culture is positively associated with corporate innovation. The influence of CEOsâ food culture and overseas experience on firm innovation are substitutes to each other. CEO food culture matters in state-owned enterprises (SOEs) than in non-SOEs. CEOsâ Szechuan cuisine food culture also increases the volatility of firm performance.
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
The choice of how business activities are financed is vital to every firm. This is because optimal or balanced capital mix between debt and equity impacts on the firmâs value as well as its market valuation. However, optimal capital mix has over the years attracted attention due to its aforementioned impacts with previous studies finding mixed results. The study examined the effect of capital structure on financial performance of 40 selected firms listed on the Nigeria Stock Exchange. Secondary data were obtained from annual reports and accounts of the sample firms for a ten year period (2007-2016), and were analysed using descriptive and inferential statistics; panel least regression technique. Hausman test was also conducted which favoured fixed-effect model. The study found a statistically significant positive relationship between proxies of financial performance (ROE and ROA) and capital structure. The study recommended that top management of listed firms in Nigeria should judiciously mix capital structure components to enhance the productivity and profitability of their companies.
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We compared performance of Pearsonâs correlations based (PeMVPs) and partial correlations based (PaMVPs) mean variance portfolios (MVPs) with equal-weight portfolios (EWPs) for several US equity indexes. We found that performance of MVPs and EWPs depends on two factors: the constituents of the underlying equity index and its holding period. When a market-wide index contained super-high growth technology stocks, such as FAANNG in the S&P 500, PeMVP being a concentrated growth portfolio unsurprisingly outperformed more diversified PaMVP and EWP. However, when FAANNG were dropped from the S&P 500, and even in the case of the S&P 500 Growth (that lacks relatively low-performing value stocks), PeMVP did not outperform PaMVP at the three- and six-month holding periods. Moreover, at a shorter, one-month holding period, PaMVP was statistically superior. For other equity indexes considered in this work, PaMVP always outperformed PeMVP, and EWP could outperform PeMVP at shorter holding periods.
SSRN
We study empirically how competition among high-frequency traders (HFTs) affects their trading behavior and market quality. Our analysis exploits a unique dataset, which allows us to compare environments with and without high-frequency competition, and contains an exogenous event - a tick size reform - which we use to disentangle the effects of the rising share of high-frequency trading in the market from the effects of high-frequency competition. We find that when HFTs compete, their speculative trading increases. As a result, market liquidity deteriorates and short-term volatility rises. Our findings hold for a variety of market quality and high-frequency trading behavior measures.
SSRN
Do credit ratings affect the quality of firms' disclosure? We examine this question by testing for the effect of ratings on earnings management. Using novel data on rating analysts to obtain exogenous variation in ratings, we find that earnings quality improves as ratings become more optimistic. Additionally, we show firms manage earnings in a direction consistent with the financial state implied by the rating, which suggests ratings contain credible private information. Our paper implies a complementary relation between ratings and disclosure, and our results suggest a unique channel through which improving rating quality can improve other sources of public information.
arXiv
We present an artificial neural network (ANN) approach to value financial derivatives. Atypically to standard ANN applications, practitioners equally use option pricing models to validate market prices and to infer unobserved prices. Importantly, models need to generate realistic arbitrage-free prices, meaning that no option portfolio can lead to risk-free profits. The absence of arbitrage opportunities is guaranteed by penalizing the loss using soft constraints on an extended grid of input values. ANNs can be pre-trained by first calibrating a standard option pricing model, and then training an ANN to a larger synthetic dataset generated from the calibrated model. The parameters transfer as well as the non-arbitrage constraints appear to be particularly useful when only sparse or erroneous data are available. We also explore how deeper ANNs improve over shallower ones, as well as other properties of the network architecture. We benchmark our method against standard option pricing models, such as Heston with and without jumps. We validate our method both on training sets, and testing sets, namely, highlighting both their capacity to reproduce observed prices and predict new ones.
SSRN
I study whether banksâ loan loss provisioning contributed to economic downturns by examining the U.S. housing market. Specifically, I examine the influence of delayed loan loss recognition (DLR) on bank lending and risk-taking in the U.S. mortgage market and the aggregate effects of DLR on house prices and household consumption during the Great Recession. I first examine the effects of DLR on individual banksâ behavior. Then I construct ZIP code-level exposure to banksâ DLR to examine the aggregate effects of banksâ DLR on the housing market. I find high DLR banks reduced mortgage supply, leading high exposure ZIP codes to experience larger decreases in mortgage supply during the crisis. Mortgages from high DLR banks were also more likely to become distressed, leading to more foreclosures and short sales in high exposure ZIP codes during the crisis. Consequently, banksâ DLR negatively affected house prices during the crisis, implying a significant decrease in household consumption. These findings suggest banksâ loan loss provisioning affected loan supply and risk-taking, exacerbating the economic downturn via the household channel.
SSRN
Recent empirical research shows that both financial and value-related considerations prevail for an individualâs decision to invest in companies or products deemed sustainable or socially responsible. This paper investigates how different investor motivations vary across forms of sustainable investment strategies, in particular between broad sustainable investments and targeted impact investments. We use a unique dataset of retail investors engaged in a development oriented microfinance investment vehicle to analyze how different motives affect the demand for distinct sustainable investments. Our results show that different motives trigger different types of sustainable investments. While decisions to engage in general sustainable investments are mainly linked to return and risk expectations, the investment decision for the impact investment vehicle is connected more strongly to value attributes. In line with previous findings on general sustainable investments, we find that the decision to invest is driven more by value-related criteria while the amount invested is driven by financial motivations. Our analysis furthermore shows that distrust in the financial markets is a major driver for the share invested in general sustainable investments, but not in impact investments.
SSRN
Financial statements are one of the most important sources of information which aid stakeholders in taking various economic decisions. Accounting measures like earnings present in these statements assist in decision-making. However, this requires high quality of earnings. It has an impact on the firmâs market risk which further influences investment decision of the investors as well as the cost of raising funds by the firms. The present study addresses this issue and attempts to investigate the impact of earnings quality (EAQ) on market risk (SMR) of companies listed on the S&P BSE 100 Index for the period 2013-14 to 2017-18. A panel data analysis revealed that EAQ has a significant negative impact on firm excess returns (RRf). However, EAQ is not significantly related to firmâs SMR and hence EAQ doesnât interact with market excess returns (MTRf) for affecting the RRf. Among control variables, only firm size is found to have a significant and negative impact on RRf as well as SMR. This study contributes to the literature by exploring the EAQ-SMR relationship in Indian context since the empirical evidence on other economies cannot be applied to India.
SSRN
This research uses an indirect methodology to examine the effects of health insurance mergers and acquisitions by analyzing the impact of insurersâ scale of operations and group affiliation status on benefits, costs, and efficiency from the perspective of various stakeholders. The analysis can provide insights related to federal and state governmentsâ antitrust scrutiny and regulations, and inform the public debate over mergers and acquisitions in the health insurance industry. We find that stakeholders to this process (consumers, regulators, health care providers, society at large) are inconsistent regarding the assessment of what constitutes efficiency with respect to scale of operations and group affiliation status depending upon their viewpoint (choice) of most appropriate inputs and outputs to the health care market dynamics. In this study big-sized insurers (those in the top 20% of insurers by member month enrollment) and small groups (those affiliated with a group with fewer than 10 member insurers) are the most efficient from the societal input-output perspective, From a composite perspective that combines the input-output choices relevant from the societal perspective and from the insurersâ perspective big-sized insurers and big groups (those affiliated with a group with 10 or more member insurers) are found to be the most efficient. Additionally, we find most insurers are scale inefficient. The analysis of scale (dis)economies provides some guidelines regarding the appropriate scale of operations for the scale efficiency, and informs discussion of mergers and acquisitions among health insurers.
arXiv
Ergodicity describes an equivalence between the expectation value and the time average of observables. Applied to human behaviour, ergodic theory reveals how individuals should tolerate risk in different environments. To optimise wealth over time, agents should adapt their utility function according to the dynamical setting they face. Linear utility is optimal for additive dynamics, whereas logarithmic utility is optimal for multiplicative dynamics. Whether humans approximate time optimal behavior across different dynamics is unknown. Here we compare the effects of additive versus multiplicative gamble dynamics on risky choice. We show that utility functions are modulated by gamble dynamics in ways not explained by prevailing economic theory. Instead, as predicted by time optimality, risk aversion increases under multiplicative dynamics, distributing close to the values that maximise the time average growth of wealth. We suggest that our findings motivate a need for explicitly grounding theories of decision-making on ergodic considerations.
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This paper emphasizes the economic importance of the civil society sector in the national socio-economic context. There is a systematic neglect of the economic and financial components of civil society organizations and non-profit sector in Croatia even though a significant volume of civil society organizationsâ activities is funded from public sources and there is a high possibility of exploitation of their relatively privileged tax position. The purpose of this paper is to present research results of the funding sources, the financial potential and the elements of economic performance of citizensâ associations in the Republic of Croatia. The survey sample includes over 20,000 citizensâ associations which have submitted financial reports to the Registry of Non-profit Organizations in accordance with the statutory obligation. The research is based on aggregated data reported in the Balance Sheet and Performance Report for 2015 and 2016. The scientific contribution of the paper is reflected in the assessment of the financial performance and financial transparency of the activities of civil society organizations in the Republic of Croatia and their sustainability in comparison with Serbia and Slovenia.
SSRN
The development of an economyâs financial sector facilitates improved access to capital. This study focuses on firm growth in terms of how much assets it controls and BRICS is chosen as the empirical medium of investigation. The impact financial sector development on firm growth amongst 3353 listed firms in BRICS countries is investigated using a GMM estimation technique. Firmâs investment in assets increases the organizational resources and productive capacity needed to achieve growth in the market. Financial sector development improves access to capital and firms with higher access to external finance pursue growth opportunities using debt. Financial sector development helps firms to adjust their capital structures quickly thereby minimizing the costs of staying off target. The speed of adjustment of firms towards their target capital structure facilitates financing of firm growth. The study found that listed firms in Brazil, Russia India, China and South Africa have a target total liabilities-to-total assets ratio and financial sector development helps firms to partially adjust towards target levels and pursue growth opportunities.
SSRN
We examine the effect of firm-level political risk on debt markets. While prior research relies mainly on economy-wide proxies for political risk (such as the economic policy uncertainty index), Hassan et al. [2019] suggests that a substantial part of political risk plays out at the firm-level. We use their measure of political risk to show that borrower-level political risk is reflected in the pricing and liquidity of public debt, the cost of private debt, and credit default swap spreads and recovery rates. We also document the strength of pricing effects for persistent versus temporary variation in firm-level political risk.Furthermore, we show that lender-level political risk influences the supply of credit and has a significant effect on loan pricing. Taking advantage of the granularity of our measure, we also show that firm-specific changes in political risk propagate across firms and lenders, suggesting the importance of network effects in amplifying the effects of political uncertainty. Finally, we show that borrowers and lenders can mitigate the effect of political risk via political activism and through changes to contractual terms.
arXiv
We argue that a stochastic model of economic exchange, whose steady-state distribution is a Generalized Beta Prime (also known as GB2), and some unique properties of the latter, are the reason for GB2's success in describing wealth/income distributions. We use housing sale prices as a proxy to wealth/income distribution to numerically illustrate this point. We also explore parametric limits of the distribution to do so analytically. We discuss parametric properties of the inequality indices -- Gini, Hoover, Theil T and Theil L -- vis-a-vis those of GB2 and introduce a new inequality index, which serves a similar purpose. We argue that Hoover and Theil L are more appropriate measures for distributions with power-law dependencies, especially fat tails, such as GB2.
SSRN
The only retirement contract that both insures against longevity risk and hedges against inflation is a life annuity that is linked to the consumer price index (CPI). It is denominated in the same units of account as Social Security benefits. We call it a âreal annuity,â although it is also referred to as an inflation-indexed single-premium immediate annuity (SPIA). In computing a personâs replacement ratio of preretirement income, we can add Social Security benefits and the income produced by a real annuity to arrive at a meaningful number. An annuity that is not linked to the CPI we call a ânominal annuity.â It is measured in units that are different from Social Security, so it would be a mistake to add the two in computing a replacement ratio. Despite those obvious facts, real annuities are largely ignored in practice and they comprise a tiny portion of the annuities market. The vast majority of income annuities sold are fixed in nominal dollars. From the perspective of rational economic decision-making, this is a puzzle. Letâs call it the ânominal annuity puzzle.â The purpose of this article is to explore the reasons behind this puzzle and to suggest ways to solve it. The lack of interest in real annuities can be explained by a lack of recognition that the purchase of a nominal annuity constitutes a speculative bet on future inflation rates and that the real annuity is the risk-free asset.
SSRN
This research provides the theoretical foundations for introducing hysteresis, the historic memory or path dependency, into the banking and financial industry. This is done by generalizing the popular Monti-Klein model of banking competition, to allow for both fixed entry and per-period cost/subsidy. However, the empirically relevant case of zero per-period fixed costs is considered as well. As will be shown, such a model implies multiple path dependent equilibria of banks' activities or in other words Hysteresis. The implications of the theory of hysteresis developed herein are tested by applying a breakpoint unit root tests to the historical U.S. data on banking. These tests find evidence for hysteresis in the commercial banking sector in most but not all U.S. states.
SSRN
The only retirement contract that both insures against longevity risk and hedges against inflation is a life annuity that is linked to the consumer price index (CPI). It is denominated in the same units of account as Social Security benefits. We call it a âreal annuity,â although it is also referred to as an inflation-indexed single-premium immediate annuity (SPIA). In computing a personâs replacement ratio of preretirement income, we can add Social Security benefits and the income produced by a real annuity to arrive at a meaningful number. An annuity that is not linked to the CPI we call a ânominal annuity.â It is measured in units that are different from Social Security, so it would be a mistake to add the two in computing a replacement ratio. Despite those obvious facts, real annuities are largely ignored in practice and they comprise a tiny portion of the annuities market. The vast majority of income annuities sold are fixed in nominal dollars. From the perspective of rational economic decision-making, this is a puzzle. Letâs call it the ânominal annuity puzzle.â The purpose of this article is to explore the reasons behind this puzzle and to suggest ways to solve it.
SSRN
This paper addresses the inconsistency of downturn definition adopted by the conditional PD under the IRB approach and the downturn LGD (latent variable based versus macroeconomic based). This will potentially result in risk underestimation and inadequate capital coverage. We confirm this underestimation by Monte Carlo simulation based on 18 years default database of over 50 international large banks. The simulation shows that the current regulatory downturn LGD does not pass the minimum survival probability of 99.9% as traditionally required in the IRB approach. Our developed method incorporates latent variables to address the aforementioned inconsistency and performs with a survival rate of 99.9%. Further, it also outperforms the Foundation IRB approach in terms of accuracy. In contrast to other conditional LGD models in the literature, our method is applicable not only to market-based LGD but to workout LGD as well.
SSRN
Using survey data gathered from grantees of the non-profit Breast Cancer Research Foundation (BCRF), we investigated the commercial and non-commercial impact of their research funding. We found significant impact in both domains. Commercially, 19.5% of BCRF grantees filed patents, 35.9% had a project that has reached clinical development, and 12 companies have or will be spun off from existing projects, thus creating 127 new jobs. Non-commercially, 441 graduate students have been trained by 116 grantees, 767 post-doctoral fellows have been trained by 137 grantees, 66% of grantees have used funding for faculty salaries, 93% have achieved collaboration with other researchers, and 42.7% have enacted process improvements in research methodology. Econometric analysis identifies BCRF funding and associated process improvements as key factors driving the likelihood to file patents. However, we also found that the involvement of more than one institution in a collaborative project had a negative impact on subsequent development. This may point to frictions introduced by multi-university interactions.
SSRN
In this paper we extend the existing literature on xVA along three directions. First, we extend existing BSDE-based xVA frameworks to include initial margin by following the approach of Crépey (2015a) and Crépey (2015b). Next, we solve the consistency problem that arises when the front- office desk of the bank uses trade-specific discount curves that differ from the discount curve adopted by the xVA desk. Finally, we address the existence of multiple aggregation levels for contingent claims in the portfolio between the bank and the counterparty by providing suitable extensions of our proposed single-claim xVA framework.
SSRN
This study applies Fama-French-style factor loading analysis to cryptocurrency financial performance data to determine the originality of 32 reportedly novel consensus algorithms (âproofsâ) and 20 hybrid consensus mechanisms as compared to conventional proof-of-work and proof-of-stake using a sample of 302 cryptocurrencies. Only 14 out of 32 new consensus algorithms and 12 out of 20 hybrid mechanisms are found to be truly original. Innovative consensus protocols are not associated with superior returns while original hybrid solutions are. The findings allow investors to select coins with original âproofsâ and to explore performance implications of consensus algorithms. For future research, the applicability of market, size, proof and age factors for risk and attribution analysis of cryptocurrency markets is evidenced.
arXiv
Pairs Trading is carried out in the financial market to earn huge profits from known equilibrium relation between pairs of stock. In financial markets, seldom it is seen that stock pairs are correlated at particular lead or lag. This lead-lag relationship has been empirically studied in various financial markets. Earlier research works have suggested various measures for identifying the best pairs for pairs trading, but they do not consider this lead-lag effect. The present study proposes a new distance measure which incorporates the lead-lag relationship between the stocks while selecting the best pairs for pairs trading. Further, the lead-lag value between the stocks is allowed to vary continuously over time. The proposed measures importance has been show-cased through experimentation on two different datasets, one corresponding to Indian companies and another corresponding to American companies. When the proposed measure is clubbed with SSD measure, i.e., when pairs are identified through optimising both these measures, then the selected pairs consistently generate the best profit, as compared to all other measures. Finally, possible generalisation and extension of the proposed distance measure have been discussed.
SSRN
Full paper is available at: https://ssrn.com/abstract=3015582Identifying firm connections by shared analyst coverage, we find that a connected-firm (CF) momentum factor generates a monthly alpha of 1.68% (t = 9.67). In spanning regressions, the alphas of industry, geographic, customer, customer/supplier industry, single- to multi-segment, and technology momentum factors are insignificant/negative after controlling for CF momentum. Similar results hold in cross-sectional regressions and in developed international markets. Sell-side analysts incorporate news about linked firms sluggishly. These effects are stronger for complex and indirect linkages. Consistent with limited investor attention, these results indicate that momentum spillover effects are a unified phenomenon that is captured by shared analyst coverage.
SSRN
The financial foundation of Germanyâs manufacturing success, according to the comparative capitalism literature, is an ample supply of long-term capital, provided to firms by a three-pillar banking system and âpatientâ domestic shareholders. This premise also informs the recent literature on growth models, which documents a shift towards a purely exportled growth model in Germany since the 1990s. We challenge this common assumption of continuity in the German financial system. Export-led growth, characterized by aggregate wage suppression and high corporate profits, has allowed non-financial corporations to increasingly finance investment out of retained earnings, thus lowering their dependence on external finance. This paper documents this trend and shows that business lending by banks has increasingly been constrained on the demand side, reducing the power â" and relevance â" of banks vis-Ã -vis German industry. The case study suggests a need for students of growth models to pay greater attention to the dynamic interaction between institutional sectors in general, and between the financial and the non-financial sectors in particular.
SSRN
The architecture of supervision â" how we define the allocation of supervisory powers to different policy institutions â" can have implications for policy conduct and for the economic and financial environment in which these policies are implemented. Theoretically, an integrated structure for monetary policy and supervision brings important benefits arising from better information flow and policy coordination. Aggregate supervisory information may significantly improve the conduct of monetary policy and the effectiveness of the lender of last resort function. As long as the process towards an integrated structure does not shrink the set of available tools, monetary policy and supervision are no less effective in pursuing their objectives than a separated structure. Additionally, an integrated structure does not seem to be correlated with more price and/or financial instability, as suggested by analysing a large global set of countries with different supervisory set-ups. A centralised structure for supervision entails significant benefits in terms of fewer opportunities for supervisory arbitrage by banks and less informational asymmetry. A large central supervisor can take advantage of economies of scale and scope in supervision and gain a broader perspective on the stability of the entire banking sector, which should result in improved financial stability. Potential drawbacks of a centralised supervisory structure are the possible lack of specialisation relative to local supervisors and the increased distance between the supervisor and the supervised institutions. We discuss the implications of our findings in the euro area context and in relation to the design of the Single Supervisory Mechanism (SSM).
arXiv
We advocate the use of Agnostic Allocation for the construction of long-only portfolios of stocks. We show that Agnostic Allocation Portfolios (AAPs) are a special member of a family of risk-based portfolios that are able to mitigate certain extreme features (excess concentration, high turnover, strong exposure to low-risk factors) of classical portfolio construction methods, while achieving similar performance. AAPs thus represent a very attractive alternative risk-based portfolio construction framework that can be implemented in different situations, with or without an active trading signal.
SSRN
This paper studies the impact of higher bank capital requirements on corporate lending spreads. We conduct an empirical analysis using granular bank- and loan-level data for Switzerland. Overall, we find a positive relationship between capital ratios, actual and required, and lending spreads. The relationship is statistically significant but economically small. According to our results, a one-percentage point increase of capital ratios (risk- weighted) leads to an increase in lending spreads between 0 and 5 basis points. This figure is higher - between 5 and 20 basis points - for unweighted capital ratios (leverage ratios), partly but not only reflecting scaling effects. We find support in favor of gradual phasing-in of new requirements as banks with capital shortfalls relative to their short-run regulatory requirements charge higher spreads relative to institutions with surpluses while the effects are weaker for look-through capital shortfalls. Holding additional capital when requirements are raised is associated with lower spreads vis-a-vis peers.
SSRN
Loan loss provisions in the euro area are negatively related to GDP growth, i.e., they are procyclical. Loan loss provisions tend to be more procyclical at larger and better capitalized banks. The procyclicality of loan loss provisions can explain about two-thirds of the variation of bank capitalization over the business cycle. We estimate that provisioning procyclicality in the euro area is about twice as large as in other advanced economies. This difference reflects a larger procyclicality of provisioning in euro area countries already prior to euro adoption, and the divergent growth experiences of euro area countries following the global financial crisis.
arXiv
Existing research argues that countries increase their production baskets based on the available capabilities, adding products which require similar capabilities to those already produced, a process referred to as path dependency. Expansions to include goods that use divergent capabilities from those currently in the economy requires a structural change in available capabilities. Structural changes in existing capabilities contributes to countries economic growth and development. Economic development increases environmental risks from higher consumption of energy and natural resources. Managing that risk is critical and a transition to a green economy can help. The main objective of this research is to determine if structural changes or path dependency drives the expansion in production of green economy products. We consider a dataset with 138 countries over the period of 2008 to 2017, with a focus on specific case study examples, including all countries in the world and China. The results of this research show countries increased their green production baskets based on their available capabilities following path dependency as well as by expanding to products that path dependency does not predict. This suggests that, while path dependency may explain some expansion in green economies, additional theories are needed to fully explain observed green economic expansion.
arXiv
Multi-agent learning is a promising method to simulate aggregate competitive behaviour in finance. Learning expert agents' reward functions through their external demonstrations is hence particularly relevant for subsequent design of realistic agent-based simulations. Inverse Reinforcement Learning (IRL) aims at acquiring such reward functions through inference, allowing to generalize the resulting policy to states not observed in the past. This paper investigates whether IRL can infer such rewards from agents within real financial stochastic environments: limit order books (LOB). We introduce a simple one-level LOB, where the interactions of a number of stochastic agents and an expert trading agent are modelled as a Markov decision process. We consider two cases for the expert's reward: either a simple linear function of state features; or a complex, more realistic non-linear function. Given the expert agent's demonstrations, we attempt to discover their strategy by modelling their latent reward function using linear and Gaussian process (GP) regressors from previous literature, and our own approach through Bayesian neural networks (BNN). While the three methods can learn the linear case, only the GP-based and our proposed BNN methods are able to discover the non-linear reward case. Our BNN IRL algorithm outperforms the other two approaches as the number of samples increases. These results illustrate that complex behaviours, induced by non-linear reward functions amid agent-based stochastic scenarios, can be deduced through inference, encouraging the use of inverse reinforcement learning for opponent-modelling in multi-agent systems.
SSRN
We uncover a link between U.S. monetary policy and liquidity risk premia in stock markets around the world. Liquidity risk premia vary considerably over time and strongly co-move across countries. They are significantly lower when U.S. monetary policy tightens. A positive shock to the Federal Funds futures rate of 10 basis points is associated with a 41 basis points decline in the liquidity risk premium. This effect is concentrated among high liquidity risk stocks and is more acute when the foreign claims by U.S. banks on the country of interest are unusually high. Overall, our results indicate that U.S. monetary policy shocks affect the pricing of liquidity risk around the world and highlight the importance of a âbank channelâ in the transmission of these shocks.
SSRN
This article provides a brief introduction to risk premia strategies and notes how commodity risk premia strategies are an extension of ideas that were originally developed for the equity markets. The paper considers how to manage the risks of these strategies and discusses the importance of a modicum of fundamental analysis. The article further covers the active management of risk premia strategies and includes a number of techniques that attempt to minimize the inevitable losses that can arise from such strategies. The paper concludes with providing several hypotheses, based on recent academic research, on why a number of commodity risk premia strategies have historically earned high average returns.