Research articles for the 2020-09-16
SSRN
This paper proposes a novel state-space approach to explain stock market dynamics driven by different types of trading, which leads to a new promising scheme for proactive risk management in financial investment. Particularly, it is assumed that the current price changes are formulated through daily trading by multiple types of traders, each of whom follows a specific investment strategy based on technical indicators and a fuzzy logic using past data of stock prices, volumes and yield curves. Moreover, the current price changes are represented by a linear combination of those multiple trading types, where the coefficients corresponding with the size of impact on the price changes are regarded as time-varying state variables to be sequentially estimated under a state-space framework. Thereby, this work develops a new factor decomposition method on price changes from a perspective of different traders' demand and supply to analyze the current situations and potential risks in financial markets. In empirical experiments, it is shown that the implementation of particle filtering algorithm makes it possible to replicate market price changes. Further, new signals based on the estimated states are developed, which are applied to proactive risk management in financial investment. Especially, it has been found that the demands of yield curve-based traders subtracting those of trend-followers could be a promising signal of stock market crashes, which has successfully enhanced simple buy-and-hold strategy of SP, as well as constant proportion strategies.
arXiv
This paper introduces a theory of equivalent expectation measures, such as the R measure and the RT1 measure, generalizing the martingale pricing theory of Harrison and Kreps (1979) for deriving analytical solutions of expected prices - both the expected current price and the expected future price - of contingent claims. We also present new R-transforms which extend the Q-transforms of Bakshi and Madan (2000) and Duffie et al. (2000), for computing the expected prices of a variety of standard and exotic claims under a broad range of stochastic processes. Finally, as a generalization of Breeden and Litzenberger (1978), we propose a new concept of the expected future state price density which allows the estimation of the expected future prices of complex European contingent claims as well as the physical density of the underlying asset's future price, using the current prices and only the first return moment of standard European OTM call and put options.
SSRN
Using customer-supplier networks, we document a strong increase in stock return comovement between customer and supplier after the establishment of their relationship. This increase in comovement is mainly associated with cash flow news and firm-specific information. We find that the idiosyncratic shocks to customers diffuse through the customer-supplier network and aggregate into a systematic risk, which affects suppliers' expected returns. Using a long-short portfolio based on exposure to aggregated customer risk, we realize annual excess returns of 3.1% (value-weighted) and 6.11% (equal-weighted), respectively. The customer risk factor cannot be explained by market, size, book-to-market, or momentum factor. Consistently, we also find a positive relationship between exposure to the customer risk factor and cost of equity capital.
SSRN
This paper analyzes the relation between demographic structure and real asset returns on treasury bills, bonds and stocks for the G7-countries (United States, Canada, Japan, Italy, France, the United Kingdom and Germany). A macroeconomic multifactor model is used to examine a variety of different demographic factors from 1951 to 2002. There was no robust relationship found between shocks in demographic variables and asset returns in the framework of these models, which suggests that Asset Meltdown is rather fiction than fact.
SSRN
This paper uses a novel and direct retail investor attention proxy and provide evidence that retail investor attention is important for information efficiency around earnings announcements. I also uncover asymmetric patterns in subsequent responses to good and bad earnings surprises when retail investors are the most attentive. If earnings news is bad, a strong reversal is present, which I find to be consistent with an attention-induced buying pressure. If the news is good, then even though the announcement must also have been attention-grabbing, no subsequent buying pressure is observed, consistent with the immediate response being complete. The effects are intensified for stocks with higher limits to arbitrage, and when institutional investors are the least attentive.
SSRN
Bitcoin blockchain possesses immense potential for future opportunities, well beyond its current use in financial services underpinning cryptocurrencies, i.e. replacing traditional trusted third parties with trusted machines. Despite over a decade has passed since Nakamoto Satoshi launched Bitcoin in January 2009, it still continues to face barriers, challenges as well as a major regulatory hurdle in the U.S. and Europe. This paper looked into three hypothetical scenarios where the price of bitcoin surges over $50,000 (scenario 1), $100,000 (scenario 2), and $1,000,000 (scenario 3). Although new path-breaking technologies and inventions (i.e. Bitcoin) will continue to forge ahead unabated regardless of doubters, doomsayers, skeptics, pessimists, disbelievers, and short-sighted politicians (President Trump); however, these scenarios can only become a reality if the Trump administration and law makers stop constantly running headlong into backlash to cryptocurrencies (Bitcoin and Libra coin in particular). For future price growth of Bitcoin and altcoins, cryptocurrency markets need more people like Christine Lagarde, the former Managing Director of the IMF (currently, president of the European Central Bank), who urged central banks not to ignore “winds of change†and consider looking into the case of central bank digital currency.
SSRN
We study how plan sponsors choose investment management firms from their opportunity set when delegating $1.6 trillion in assets between 2002 and 2017. Two factors play an influential role in choice: pre-hiring returns, and pre-existing personal connections between personnel at the plan (or consultant advising the plan), and the investment management firm. Post-hiring returns for chosen firms are significantly lower than those for unchosen firms. The post-hiring returns of firms with relationships are, at best, indistinguishable from those without relationships, and often significantly worse. While relationships are conducive to asset gathering by investment managers, they do not appear to generate commensurate benefits for plan sponsors via higher gross returns or lower fees.
SSRN
The back and forth negotiation of Argentina’s most recent efforts to restructure its sovereign debt has given rise to novel issues of interpretation and use of collective action clauses (CACs), accompanied by charges and countercharges of abuse by Argentina of this important addition to the international financial architecture, on the one hand, and an alleged desire on the creditor side to walk back advances in the orderly restructuring of sovereign debt for narrow reasons of self-interest. Beneath the noise, however, there are important, previously unexamined issues of the policies underlying CACs and a need to improve the drafting of these clauses in order to ensure that they in fact further the policies that inspired them.
arXiv
In economic literature, economic complexity is typically approximated on the basis of an economy's gross export structure. However, in times of ever increasingly integrated global value chains, gross exports may convey an inaccurate image of a country's economic performance since they also incorporate foreign value-added and double-counted exports. Thus, I introduce a new empirical approach approximating economic complexity based on a country's value-added export structure. This approach leads to substantially different complexity rankings compared to the established metrics. Moreover, the explanatory power of GDP per capita growth rates for a sample of 40 lower-middle- to high-income countries is considerably higher, even if controlling for typical growth regression covariates.
arXiv
We propose forecast encompassing tests for the Expected Shortfall (ES) jointly with the Value at Risk (VaR) based on flexible link (or combination) functions. Our setup allows testing encompassing for convex forecast combinations and for link functions which preclude crossings of the combined VaR and ES forecasts. As the tests based on these link functions involve parameters which are on the boundary of the parameter space under the null hypothesis, we derive and base our tests on nonstandard asymptotic theory on the boundary. Our simulation study shows that the encompassing tests based on our new link functions outperform tests based on unrestricted linear link functions for one-step and multi-step forecasts. We further illustrate the potential of the proposed tests in a real data analysis for forecasting VaR and ES of the S&P 500 index.
arXiv
In this paper, we consider the problem of equal risk pricing and hedging in which the fair price of an option is the price that exposes both sides of the contract to the same level of risk. Focusing for the first time on the context where risk is measured according to convex risk measures, we establish that the problem reduces to solving independently the writer and the buyer's hedging problem with zero initial capital. By further imposing that the risk measures decompose in a way that satisfies a Markovian property, we provide dynamic programming equations that can be used to solve the hedging problems for both the case of European and American options. All of our results are general enough to accommodate situations where the risk is measured according to a worst-case risk measure as is typically done in robust optimization. Our numerical study illustrates the advantages of equal risk pricing over schemes that only account for a single party, pricing based on quadratic hedging (i.e. $\epsilon$-arbitrage pricing), or pricing based on a fixed equivalent martingale measure (i.e. Black-Scholes pricing). In particular, the numerical results confirm that when employing an equal risk price both the writer and the buyer end up being exposed to risks that are more similar and on average smaller than what they would experience with the other approaches.
SSRN
Central banks sometimes evaluate their own policies. To assess the inherent conflict of interest, we compare the research findings of central bank researchers and academic economists regarding the macroeconomic effects of quantitative easing (QE). We find that central bank papers report larger effects of QE on output and inflation. Central bankers are also more likely to report significant effects of QE on output and to use more positive language in the abstract. Central bankers who report larger QE effects on output experience more favorable career outcomes. A survey of central banks reveals substantial involvement of bank management in research production.
SSRN
In the era of diminishing power from US dollar and increasing competition among world currencies, Bitcoin, as a completely new concept as a medium of exchange, has received increasing attentions over the world. Nowadays, Bitcoin also becomes an investment vehicle, which carries attractive opportunities but also significant risks for the investment community. In this paper, we have compared the empirical performance of a newly-developed heavy-tailed distribution, the normal reciprocal inverse Gaussian (NRIG), with the most popular heavy-tailed distribution, the Student’s t distribution, under the GARCH framework in fitting the daily Bitcoin exchange rate returns. Our results indicate the heavy-tailed distribution has better performance in capture the daily Bitcoin exchange rate returns dynamics than the standard normal distribution. Our results also show the older fashioned Student’s t distribution still performs better than the new heavy-tailed distribution.
SSRN
In recent years, a liquid market for options on a broad credit default swap index (CDX) has developed. We study the extent to which these options are priced consistently with options on a broad equity index (SPX). We consider a rich structural credit risk model in which firm assets follow a jump-diffusion process with idiosyncratic and systematic risk, and we derive analytical expressions for CDX and SPX options. Calibrating the model, we find that it captures many aspects of the joint dynamics of CDX and SPX options. However, it cannot reconcile the relative levels of option implied volatilities, suggesting that credit and equity markets are not fully integrated. A strategy of selling CDX options yields significantly higher average excess returns and Sharpe ratios than selling SPX options.
SSRN
Spanish Abstract: El presente artÃculo analiza los instrumentos jurÃdicos desde una mirada múltiple. Partiendo de la definición de lo que es un instrumento, su realidad pública y privada y su condición probatoria por escrito, examinamos quién lo hace, esto es, su agente productor. El texto se sumerge en el oficio escribanil, en sus normatividades, institucionalización y estructura de su ejercicio, para examinar las caracterÃsticas, formación y calidad de quienes formalizan los instrumentos. A partir de ahÃ, analizamos el proceso de realización de estos y examinamos el conjunto de elementos y distintivos materiales y formales, desde las formas de redacción hasta el papel sellado, pasando por los aranceles y derechos de formalización y rúbricas, que preservaban y protegÃan el contenido de los instrumentos, al tiempo, que los dotaban de su fe pública. Todo lo anterior, para finalizar, nos permite entender los instrumentos como aquellas escrituras que, cimentadas en su condición probatoria y fe pública, garantizan y salvaguardan la verdad, la memoria y la trascendencia de los asuntos de los otorgantes y del reino.English Abstract:The article analyses legal instruments from a multiple perspective. Starting from the definition of what a legal instrument is, their public and private reality and their condition of written evidence, we examine who makes them, that is, their producing agent. The text immerses itself in the scribal profession, its regulations, organisation and exercise structure, in order to examine the characters, formation and qualities of who makes the instruments. From this point, we describe the process by which they were created, and review all the physical and formal aspects and signs, including writing procedures, stamped paper, fees, customs duties, and rubrics. All of this preserves and protects the instruments data, as well as provides them attestation. In conclusion, we can understand legal instruments as those scriptures that, grounded in their evidential condition and attestation, guarantee and preserve truth, memories and transcendence of grantors' and Kingdom's affairs.
SSRN
This paper investigates the intraday electricity pricing of 15-minute contracts in night hours. We tailor a recently introduced econometric model with fundamental impacts, which is successful in describing the pricing of day contracts. Our estimation results show that mean reversion and the positive price effect of neighboring contracts are generic features of the price formation process on the intraday market, independent of the time of day. Intraday auction prices have higher explanatory power for the pricing of night than day contracts, particularly, for the first and last 15-minute contract in a night hour. Intradaily updated forecasts of wind power infeed are the only significant fundamental factors for intraday electricity prices at night. Neither expected conventional capacities nor the slope of the merit order curve contribute to explaining price dynamics. Overall, we conclude that fundamentals lose in importance in night hours and the 15-minute intraday market is rather driven by price information.
arXiv
The international trade is one of the classic areas of study in economics. Nowadays, given the availability of data, the tools used for the analysis can be complemented and enriched with new methodologies and techniques that go beyond the traditional approach. The present paper shows the application of the Latent Dirichlet Allocation Models, a well known technique from the area of Natural Language Processing, to search for latent dimensions in the product space of international trade, and their distribution across countries over time. We apply this technique to a dataset of countries' exports of goods from 1962 to 2016. The findings show the possibility to generate higher level classifications of goods based on the empirical evidence, and also allow to study the distribution of those classifications within countries. The latter show interesting insights about countries' trade specialisation.
SSRN
This paper proposes a new parametric approach to estimate linear factor pricing mod- els with time-varying risk premia. In contrast to recent contributions to the literature, the framework presented abstains from introducing instrument variables to describe the time variation of risk prices. Instead, time-varying risk prices and exposures follow a recursive updating scheme constructed to reduce the one-step ahead prediction error from a cross-sectional factor model at the current observation. This agnostic approach is particularly useful in situations where instrument variables are unavailable or of poor quality. Estimation and inference are done by likelihood maximization. A Monte Carlo study compares the ability of the method to predict risk prices and returns to that of a regression-based method that uses noisy signals from true risk price predictors. In a realistic setting, the two approaches keep pace when the signal contains 80 percent correct information. An application to a macro-ï¬nance model of currency carry trades illustrates the novel approach.
arXiv
We investigate stochastic differential games of optimal trading comprising a finite population. There are market frictions in the present framework, which take the form of stochastic permanent and temporary price impacts. Moreover, information is asymmetric among the traders, with mild assumptions. For constant market parameters, we provide specialized results. Each player selects her parameters based not only on her informational level but also on her particular preferences. The first part of the work is where we examine the unconstrained problem, in which traders do not necessarily have to reach the end of the horizon with vanishing inventory. In the sequel, we proceed to analyze the constrained situation as an asymptotic limit of the previous one. We prove the existence and uniqueness of a Nash equilibrium in both frameworks, alongside a characterization, under suitable weak interaction assumptions. We conclude the paper by presenting an extension of the basic model to a hierarchical market, for which we establish the existence, uniqueness, and characterization of a Stackelberg-Nash equilibrium.
SSRN
A stress test assesses the value of a firm or asset in the future under an adverse counterfactual scenario. The critical points of stress tests are the valuation model and the scenario. This paper describes some of the difficulties in generating appropriate scenarios and valuing firms under these scenarios. In most cases, these difficulties can be solved if the regulator is better informed than the market. However, if this is not correct at all times and settings, then it is also sensible to carry out stress tests with market scenarios and market data. When these stress tests agree, the results gain added credibility. When they disagree, the parties can discuss whether the market has missed signals, or whether the regulators’ models are wrong or have been politically impacted.Detailed analysis of SRISK, a market based stress test, is presented from an economic, econometric and historical point of view. This is compared with alternative measures such as SES and CoVaR and with regulatory stress tests.
SSRN
We analyze the extent to which private defensive litigation insurance deters patent assertion by non-practicing entities (NPEs). We study the effect that a patent-specific defensive insurance product,offered by a leading litigation insurer, had on the litigation behavior of insured patents' owners, all of which are NPEs. We first model the impact of defensive litigation insurance on the behavior of patent enforcers and accused infringers. We show that the availability of defensive litigation insurance can have an effect on how often patent enforcers will assert their patents. We cconfirm this result empirically showing that the insurance policy had a large, negative effect on the likelihood that a patent included in the policy was subsequently asserted relative to other patents held by the same NPEs and relative to patents held by other NPEs with portfolios that were entirely excluded from the insurance product. Our findings suggest that market-based mechanisms can deter so-called "patent trolling."
SSRN
We study the impact of initial public offerings (IPOs) on corporate innovations in China. The findings suggest that going public significantly impedes corporate innovations by lowering overall innovation quality. For firms with shareholders selling or pledging less shares after IPO, the number of patents increases but the non-self-citations per patent decrease relative to matched non-IPO firms. In contrast, for firms with shareholders selling or pledging more shares after IPOs, both the number of patents and non-self-citations per patent decrease. The magnitudes of impact in the latter are stronger than those of former, supporting the initial governance force exit hypothesis.
SSRN
We utilize a novel identification strategy to analyze the impact of assets in place on firms' decisions for future projects. We exploit the context in the pharmaceutical industry, where the loss of market exclusivity for a branded drug can be used to separate the impact of cash flows generated by a firm's current assets in place from the characteristics of its future investment opportunities. We first show that around the exclusivity losses in our sample of large drugs, the affected firms' profitability drop significantly. The timing of this profitability decrease was predetermined many years ago, and therefore, arguably independent of current investment opportunities. Nevertheless, we find that R&D spending drops by approximately 25% over two years following the loss of exclusivity. We also find that stock repurchases and cash balances decline significantly. Our findings do not support the predictions of traditional capital budgeting, but are more consistent with the pecking order theory. These results further point to a lack of long-term lifecycle management that could mitigate the effect of predictable negative shocks to cash flows.
arXiv
We assess the correlation between CAP support provided to farmers and their income and use of capital and labour in the first year of the new CAP regime. This is done applying three regression models on the Italian FADN farms controlling for other farm characteristics. CAP annual payments are positively correlated with farm income and capital but are negatively correlated with labour use. Farm investment support provided by RDP measures is positively correlated to the amount of capital. Results suggest that CAP is positively affecting farm income directly but also indirectly by supporting the substitution of labour with capital
SSRN
This research focuses on Natural Language Processing (NLP) for market sentiment analysis using Valence Aware Dictionary and sEntiment Reasoner (VADER), with implementation approaches and associated limitations.VADER is a lexicon and rule-based sentiment analysis tool specifically attuned to sentiments ex- pressed in social media architectured around a list of lexical features generally labeled according to their semantic orientation as either positive or negative. VADER also considers punctuation, emojis and capitalization in order to evaluate not only the direction but also the intensity of a sentimentThe study relies on the Python vaderSentiment and sentimentClassifier libraries, also available as part of the NLTK Natural Language Toolkit package.
SSRN
This paper investigates the intergenerational mobility with regard to people’s decision to work in the U.S. financial industry over the last 47 years. I present evidence that children of fathers who worked in the financial industry during their childhood are about 8 percentage points more likely to work in finance themselves. This increase in likelihood is greater than in most other industries and is driven solely by wealthier families. In addition, I document that second-generation finance industry employees whose fathers already worked in finance enjoy a substantial income surplus compared to their industry peers.
