# Research articles for the 2020-06-25

A Data-driven Market Simulator for Small Data Environments
Hans Bühler,Blanka Horvath,Terry Lyons,Imanol Perez Arribas,Ben Wood
arXiv

Neural network based data-driven market simulation unveils a new and flexible way of modelling financial time series without imposing assumptions on the underlying stochastic dynamics. Though in this sense generative market simulation is model-free, the concrete modelling choices are nevertheless decisive for the features of the simulated paths. We give a brief overview of currently used generative modelling approaches and performance evaluation metrics for financial time series, and address some of the challenges to achieve good results in the latter. We also contrast some classical approaches of market simulation with simulation based on generative modelling and highlight some advantages and pitfalls of the new approach. While most generative models tend to rely on large amounts of training data, we present here a generative model that works reliably in environments where the amount of available training data is notoriously small. Furthermore, we show how a rough paths perspective combined with a parsimonious Variational Autoencoder framework provides a powerful way for encoding and evaluating financial time series in such environments where available training data is scarce. Finally, we also propose a suitable performance evaluation metric for financial time series and discuss some connections of our Market Generator to deep hedging.

A decomposition of general premium principles into risk and deviation
Max Nendel,Maren Diane Schmeck,Frank Riedel
arXiv

In this paper, we provide an axiomatic approach to general premium priciples giving rise to a decomposition into risk, as a generalization of the expected value, and deviation, as a generalization of the variance. We show that, for every premium priciple, there exists a maximal risk measure capturing all risky components covered by the insurance prices. In a second step, we consider dual representations of convex risk measures consistent with the premium priciple. In particular, we show that the convex conjugate of the aforementioned maximal risk measure coincides with the convex conjugate of the premium principle on the set of all finitely additive probability measures. In a last step, we consider insurance prices in the presence of a not neccesarily frictionless market, where insurance claims are traded. In this setup, we discuss premium principles that are consistent with hedging using securization products that are traded in the market.

An Economic Model of Blockchain: The Interplay between Transaction Fees and Security
He, Jiahao,ZHANG, Guangyuan,Zhang, Jiheng,Zhang, Rachel
SSRN
A blockchain system, such as Bitcoin or Ethereum, validates electronic transactions and stores them in a chain of blocks without a central authority. Miners with computing power compete for the right to create blocks according to a pre-set protocol and in return earn fees paid by users who submit transactions. Such a system essentially operates as a single server queue with batch services based on a fee-based priority discipline, albeit with distinctive features due to the security concerns caused by decentralization. That is, a transaction is confirmed only after a number of additional blocks are subsequently extended to the block containing it, which complicates the interplay between miners and users. In our study, we build a model to analyze how minersâ€™ participation decisions interact with usersâ€™ participation and fee decisions in equilibrium, and identify the optimal protocol design when the goal is to maximize total throughput or usersâ€™ utility. Our analyses show that miners and users may end up in either a vicious or virtuous cycle, depending on the initial system state. We validate our model and analytical results using data from Bitcoin.

Armageddon and the Stock Market: US, Canadian and Mexican Market Responses to the 1962 Cuban Missile Crisis
Burdekin, Richard C. K.,Siklos, Pierre L.
SSRN
The threat of nuclear annihilation has never been higher than in 1962, when US President Kennedy and Soviet Premier Khruschev engaged in brinkmanship over the placement of Soviet missiles in Cuba during October 16-28. Although the resolution of the crisis was followed by a sustained recovery in the US, Canadian and Mexican stock markets, the stock market impact of the crisis itself, at first glance, seems relatively limited. Notwithstanding the fact that empirical analysis of 1962 US market data reveal a significant break on October 23, 1962, which is the day after President Kennedyâ€™s television address about the Cuban missile crisis, the drop on this day was smaller than prior one day declines seen in the earlier part of the year. When we focus on the 1% left tail of the distribution, that is, just the very largest negative returns, a different story emerges, however. US uncertainty is now seen to have a significant negative impact on returns across each of the US, Canadian and Mexican markets. Moreover, the size of the negative response to the rise in uncertainty is comparable in all three cases notwithstanding the fact the pre-crisis Mexican stock market trajectory had been very different from that seen in the United States and Canada.

COVID-19 in Vietnam: What Happened in the Stock Market?
SSRN
The purpose of this paper is to investigate the performance of the stock market during the outbreak of the novel Coronavirus (COVID-19) in Vietnam- a frontier country that successfully tackles the outbreak of this pandemic. Employing data from 11 different industries and more than 700 firms from two main stock exchanges from January 23, 2020 (the first case reported in Vietnam), results suggest that COVID-19 exerts heterogeneous impacts on different industries. Moreover, when focusing on firm-level, results depicts that firms with a better financial background (leverage, liquidity, profitability, and cash holdings) have better stock performance.

Challenges to Economic Stability Amid Global Epidemic of COVID-19: Apposite Policy Recommendations for Economic Revival in Pakistan
SSRN
Akin to Spanish flue of 20th century, the Coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global emergency of 21st century, bequeathing a crucial impact on lives and livelihoods which triggered phenomenal policy challenges for economic revival. COVID-19 swiftly proliferated all over the globe and crumpled world economies in a short span of less than 90 days. It's beyond the imagination of all and sundry to welcome the year 2020 with such a perilous virus that will drag the world to a grievous halt-a global lockdown. This mammoth vulnerability accentuated some imperative measures by governments in public and private sectors regarding policy formulation, contextualisation and implementation in the perspective of an unparalleled global pandemic. This article dilates upon proliferation scenario of a pandemic in Pakistan with stringent combating measures by the Governments during commencement of pandemic, lockdown and soft lockdown situation. Multi-dimensional socio-economic challenges emerged out of protracted shut-down are deliberated. This startling scenario impinges upon governments to formulate policies and reforms for the wellbeing and prosperity of the nation as a renewed social contract between the citizens and the state. Some apposite policy recommendations are set forth for economic revival in respect of revisiting health sector, constitutional developments, economic boost through fiscal and monetary policies, trade-related strategies, social protection of vulnerable segments and industrial policy amidst social distancing. This paper will stipulate knowledge edifice for future researchers to combat and mainstream pandemic for the wellbeing of regional and global nations.

Climate Finance Intermediation: Interest Spread Effects in a Climate Policy Model
Lessmann, Kai,Kalkuhl, Matthias
SSRN
Interest rates are central determinants of saving and investment decisions. Costly financial intermediation distort these price signals by creating a spread between the interest rates on deposits and loans with substantial eÃ¯Â¬â‚¬ects on the supply of funds and the demand for credit. This study investigates how interest rate spreads aÃ¯Â¬â‚¬ect climate policy in its ambition to shift capital from polluting to low-carbon sectors of the economy. To this end, we introduce financial intermediation costs in a dynamic general equilibrium climate policy model. We find that costly financial intermediation aÃ¯Â¬â‚¬ects carbon emissions in various ways through a number of diÃ¯Â¬â‚¬erent channels. For low to moderate interest rate spreads, carbon emissions increase by up to 7 percent, in particular, because of lower investments into the capital intensive clean energy sector. For very high interest rate spreads, emissions fall because lower economic growth reduces carbon emissions. If a certain temperature target should be met, carbon prices have to be adjusted upwards by up to one third under the presence of capital market frictions.

Credit Rating Downgrade Risk on Equity Returns
Brakatsoulas, Periklis,Kukacka, Jiri
SSRN
We develop a four-factor model intended to capture size, value, and credit rating transition patterns in excess returns for a panel of predominantly mid- and large-cap entities. Using credit transition matrices and rating histories from 48 US issuers, we provide evidence to support a statistically significant negative downgrade risk premium in excess returns, suggesting that stocks at higher risk of failure tend to deliver lower returns. The performance of the model remains robust across several estimation methods. Panel Granger causality test results indicate that there indeed is a Granger-causal relationship from credit rating transition probabilities to excess returns. Our paper thus provides a new methodology to generate firm-level downgrade probabilities and the basis for further empirical validation and development of Fama-French-type models under financial distress.

Deeply Equal-Weighted Subset Portfolios
Sang Il Lee
arXiv

The high sensitivity of optimized portfolios to estimation errors has prevented their practical application. To mitigate this sensitivity, we propose a new portfolio model called a Deeply Equal-Weighted Subset Portfolio (DEWSP). DEWSP is a subset of top-N ranked assets in an asset universe, the members of which are selected based on the predicted returns from deep learning algorithms and are equally weighted. Herein, we evaluate the performance of DEWSPs of different sizes N in comparison with the performance of other types of portfolios such as optimized portfolios and historically equal-weighed subset portfolios (HEWSPs), which are subsets of top-N ranked assets based on the historical mean returns. We found the following advantages of DEWSPs: First, DEWSPs provides an improvement rate of 0.24% to 5.15% in terms of monthly Sharpe ratio compared to the benchmark, HEWSPs. In addition, DEWSPs are built using a purely data-driven approach rather than relying on the efforts of experts. DEWSPs can also target the relative risk and return to the baseline of the EWP of an asset universe by adjusting the size N. Finally, the DEWSP allocation mechanism is transparent and intuitive. These advantages make DEWSP competitive in practice.

Determinants of European Bank Credit Default Swap Spreads
Vogelheim, Jan
SSRN
This paper analyzes the determinants of empirical credit default swap (CDS) spreads of European banks based on two different panel regression models. Previous studies primarily focus on non-financial firms. The Expected Default Frequency (EDF) is a statistically significant and economically important credit risk factor from the KMV structural model. The panel regression attributes more than 50% of the CDS spread variation to model-based EDF. Among bank-specific CAMELS indicators, a liquidity indicator and the return on assets are significant determinants. In addition to balance sheet ratios, the market-based EDF provides a substantial contribution to increasing the modelâ€™s explanatory power. Furthermore, the stock market index is an important market-wide indicator of the macroeconomic environment explaining European bank CDS spreads. This empirical study is the first finding an explanatory content of the EURIBOR-EUREPO, TED and five-year swap spread for CDS spread levels. With rising funding and liquidity risks or general risks to financial market stability, bank CDS spreads increase. Moreover, the EURIBOR-EUREPO and TED spread are able to increase the adjusted R-squared.

Determinants of Stock Returns of Telecommunications Companies Listed on the Indonesia Stock Exchange
Endri, Endri
SSRN
This study aims to examine and analyze the effect of DER, ROA, EPS and MS on stock returns on telecommunications sector companies listed on the Indonesia Stock Exchange. This study uses annual data for the observation period from 2012 to 2016. The type of research is descriptive causality. The data used is panel data which is a combination of annual time series data and cross section processed using panel data regression analysis. The population is telecommunications companies listed on the Indonesia Stock Exchange in 2012 up to 2016 a number of 5 companies. The sampling technique used purposive sampling, found a sample of 4 companies with a 5-year observation to obtain a total observation of 20. Data were obtained from Sahamok. Data analysis in this study is panel data regression. The model used is Fixed Effect Model. The results of the analysis show that the DER variable has a significant positive effect, ROA has a significant positive effect, while EPS and MS have no significant negative effect on stock returns, namus simultaneously to the four variables DER, ROA, EPS and MS together can affect the stock return shown by data processing results that get R2 value of 82.44% of the telecommunications sector stock returns on the Indonesia Stock Exchange for the period 2012-2016.

Dynamic Effects of Persistent Shocks
Mario Alloza,Jesus Gonzalo,Carlos Sanz
arXiv

We provide evidence that many narrative shocks used by prominent literature are persistent. We show that the two leading methods to estimate impulse responses to an independently identified shock (local projections and distributed lag models) treat persistence differently, hence identifying different objects. We propose corrections to re-establish the equivalence between local projections and distributed lag models, providing applied researchers with methods and guidance to estimate their desired object of interest. We apply these methods to well-known empirical work and find that how persistence is treated has a sizable impact on the estimates of dynamic effects.

Examining the Effect of COVID-19 on Foreign Exchange Rate and Stock Market -- An Applied Insight into the Variable Effects of Lockdown on Indian Economy
Indrajit Banerjee,Atul Kumar,Rupam Bhattacharyya
arXiv

The relationship between a pandemic and the concurrent economy is quite comparable to the relation observed among health and wealth in general. Since 25th March 2020, India has been under a nation-wide lockdown. This work attempts to examine the effect of COVID-19 on the foreign exchange rates and stock market performances of India using secondary data over a span of 48 days. The study explores whether the causal relationships among the growth rate of confirmed cases (GrowthC), exchange rate (GEX) and SENSEX value (GSENSEX) are remaining the same across different pre and post-lockdown phases, attempting to capture any potential changes over time via the Vector Auto Regressive (VAR) models. A positive correlation is found between the growth rate of confirmed cases and the growth rate of exchange rate, and a negative correlation between the growth rate of confirmed cases and the growth rate of SENSEX value. A naive interpretation from this could be that with the rising growth rate of the number of confirmed cases, the economy took a toll, reflected by the Indian currency being depreciated while the stock exchange index suffered from a fall. However, on applying a VAR model, it is observed that an increase in the confirmed COVID-19 cases causes no significant change in the values of the exchange rate and SENSEX index. The result varies if the analysis is split across different time periods - before lockdown, first phase of lockdown and extension of lockdown. To compare the three periods, we had undertaken five rounds of analyses. Nuanced and sensible interpretations of the numeric results indicate significant variability across time in terms of the relation between the variables of interest. This detailed knowledge about the varying patterns of dependence could potentially help the policy makers and investors of India in order to develop their policies to cope up the situation.

How Liquidity Regulations Affect Bank Complexity: GFC vs COVID-19 Crisis
Bosshardt, Joshua,Kakhbod, Ali
SSRN
We introduce a calibrated general equilibrium model to illustrate the effect of liquidity regulations on banks' investment in complex assets and the implications for financial stability policies. Complexity, which is a form of opacity, improves bank liquidity in good times, but it also heightens vulnerability to runs during crises. Liquidity regulations support interbank lending markets during crises, but this effect is attenuated since it also encourages banks to invest in complex assets. When calibrating the model to the global financial crisis (GFC), the stabilizing benefits of liquidity regulations during crises do not compensate for the costs associated with requiring banks to hold low-return liquid assets. We consider a set of alternative policies and show that an ex-ante insurance mechanism achieves a greater improvement in welfare compared to ex-post interventions that support interbank loan prices, such as quantitative easing (QE), or asset-specific taxes that target inefficiencies in the degree of investment in complex assets. Finally, we show that the model's predictions are consistent with empirical evidence showing that the Liquidity Coverage Ratio, a novel liquidity regulation that was implemented in the time between the GFC and the COVID-19 crisis, was associated with increased investment in complex assets like mortgage-backed securities (MBSs), higher interbank loan prices during crises, and an amplified effect of QE on MBS prices.

Improvement of Organizational and Economic Mechanism of Corporate Governance in the Joint-Stock Enterprises
Ashurov, Dr. Zufar
SSRN
The aim of the research work is to develop the theoretical and methodological foundations of corporate governance, to elaborate the proposals and recommendations for improving the organizational and economic mechanism of corporate governance in the joint-stock enterprises on the basis of modern international standards.As the object of the research work there selected the joint-stock enterprises of the chemical industry incorporated in JSC â€œUzkimyosanoatâ€, and its corporate governance system. Scientific novelty of the research work is that there:- improved the normative-legal base of corporate governance system on the basis of international standard Â«G20/OECD Corporate Governance PrinciplesÂ», in terms of establishing maximum nominal value of shares in five thousand soums, increasing transparency of dividends by publishing data about them on corporate website, ensuring right for minority shareholders to participate in governance of joint-stock company through holding an extraordinary general meeting of shareholders at the written request of shareholders owning at least five percent of the shares;- improved the Corporate Governance Code in terms of applying long-term strategic planning in the activity of joint-stock companies, introducing independent member to the structure of supervisory board, determining remuneration for the members of supervisory board linking it with the performance of joint-stock company, and creating committees of supervisory board; - proposed a modern method to effectively adhere to the international principle of corporate governance Â«comply or explainÂ» in joint-stock companies, to the approaches of elaborating the long-term development strategy, to the mechanisms of internal control and to the rules for protection of shareholdersâ€™ rights; - improved the organizational and economic mechanism of corporate governance in the joint-stock enterprises of chemical industry by means of selling state blocks of shares to potential foreign investors, and by developing acceptable dividend policy ensuring the capital payback. Implementation of the research results. On the basis of scientific results obtained on improving the organizational and economic mechanism of corporate governance in the joint-stock enterprises: - the proposals on improvement of normative-legal base of corporate governance system, worked out on the basis of international standard Â«G20/OECD Corporate Governance PrinciplesÂ», in terms of establishing maximum nominal value of shares in five thousand soums, increasing transparency of dividends by publishing data about them on corporate website, ensuring right for minority shareholders to participate in governance of joint-stock company through holding an extraordinary general meeting of shareholders at the written request of shareholders owning at least five percent of the shares, were included in articles 12, 23, 62, 75, 83 of the Law of the Republic of Uzbekistan Â«On Joint-Stock Companies and Protection of Shareholdersâ€™ RightsÂ» adopted on 6 May 2014 in the new edition (a reference No.04/1-06-2-107 as of 10 September 2014 given by the Committee for Budget and Economic Reforms of the Legislative Chamber of the Oliy Majlis of the Republic of Uzbekistan). Implementation of these proposals in the norms of the law has contributed to the improvement of national corporate governance system based on requirements of the international standard; - the proposals on improvement of the Corporate Governance Code, in terms of applying long-term strategic planning in the activity of joint-stock companies, introducing independent member to the structure of supervisory board, determining remuneration for the members of supervisory board linking it with the performance of joint-stock company, and creating committees of supervisory board, were included in chapter 5, clauses 18, 19, 25 of the Corporate Governance Code adopted on 31 December 2015 (a reference as of 28 July 2016 given by the State Competition Committee of the Republic of Uzbekistan). Implementation of these proposals in the Corporate Governance Code has enabled to apply in the joint-stock companies the long-term strategic planning, to include independent members to the structure of supervisory board, to determine remuneration for the members of supervisory board linking it to the performance of joint-stock company, to create committees of supervisory board; - a modern method to effectively adhere to the international principle of corporate governance Â«comply or explainÂ» in joint-stock companies, to the approaches of elaborating the long-term development strategy, to the mechanisms of internal control and to the rules for protection of shareholdersâ€™ rights was introduced by the State Competition Committee of the Republic of Uzbekistan into the managerial activity of the joint-stock companies (a reference No.2355/02-33 as of 11 October 2018 given by the State Competition Committee of the Republic of Uzbekistan). This method has been used as a practical tool in more than 400 joint-stock companies that introduced the Corporate Governance Code; - the proposals and recommendations on improvement of organizational and economic mechanism of corporate governance in the joint-stock enterprises of chemical industry, by means of selling state blocks of shares to potential foreign investors, and by developing acceptable dividend policy ensuring the capital payback, were introduced into the managerial activity of Â«UzkimyosanoatÂ» JSC and Â«NavoiyazotÂ» JSC (a reference as of 25 January 2019 given by Â«UzkimyosanoatÂ» JSC, a reference No.01 as of 13 August 2018 given by Â«NavoiyazotÂ» JSC). Implementation of these proposals and recommendations into practice has enabled to make decision of the government on selling the state blocks of shares to potential foreign investors, to develop the effective dividend policy, to enhance the effectiveness of corporate governance system of the enterprises. As a result, at the end of 2017, the effectiveness of corporate governance system in Â«NavoiyazotÂ» JSC was evaluated as satisfactory, in Â«UzkimyosanoatÂ» JSC â€" as high; finally, the income from financial activities in Â«NavoiyazotÂ» JSC increased by 34.8 bln. soums, and in Â«UzkimyosanoatÂ» JSC â€" by 5075.0 bln. soums.

Investor Emotions and Earnings Announcements
Domonkos F. Vamossy
arXiv

Armed with a decade of social media data, I explore the impact of investor emotions on earnings announcements. In particular, I test whether the emotional content of firm-specific messages posted on social media just prior to a firm's earnings announcement explains its earnings and announcement returns. I find that investors are typically excited about firms that end up exceeding expectations, yet their enthusiasm results in lower announcement returns. Specifically, a standard deviation increase in excitement is associated with an 8.9 basis points lower announcement return, which translates into an approximately 7.2% annualized loss. Motivated by this finding, I then construct a zero-cost portfolio leveraging social media emotions and opinions around earnings announcements, and show performance exceeding the market by a factor of 1.75 over the decade. My findings confirm that emotions and market dynamics are closely related and highlight the importance of considering investor emotions when assessing a firm's short-term value.

Is Government Contracting Fair? Estimating the Value of Female Politicians for Women-Owned Firms
Gerasimova, Nataliya,Rohrer, Maximilian
SSRN
This paper provides novel evidence that female U.S. House Representatives causally increase the U.S. governmentâ€™s demand for products and services provided by female entrepreneurs. Using detailed data on individual contracts between the U.S. federal government and private firms around close U.S. congressional elections, we report that the election of a female representative increases the probability of government contracts being awarded to female entrepreneurs by 3.0 to 6.8 percentage points. Furthermore, contract performance is either improved or unaffected, which speaks against the misallocation hypothesis. We find no support for role-model effects as changes in the pool of female entrepreneurs cannot explain our findings. Thus, the evidence suggests that female politicians improve the business environment for female entrepreneurs by reducing the gender bias in the U.S. government procurement contracting system.

Model-free bounds for multi-asset options using option-implied information and their exact computation
Ariel Neufeld,Antonis Papapantoleon,Qikun Xiang
arXiv

We consider derivatives written on multiple underlyings in a one-period financial market, and we are interested in the computation of model-free upper and lower bounds for their arbitrage-free prices. We work in a completely realistic setting, in that we only assume the knowledge of traded prices for other single- and multi-asset derivatives, and even allow for the presence of bid-ask spread in these prices. We provide a fundamental theorem of asset pricing for this market model, as well as a superhedging duality result, that allows to transform the abstract maximization problem over probability measures into a more tractable minimization problem over vectors, subject to certain constraints. Then, we recast this problem into a linear semi-infinite optimization problem, and provide two algorithms for its solution. These algorithms provide upper and lower bounds for the prices that are $\varepsilon$-optimal, as well as a characterization of the optimal pricing measures. Moreover, these algorithms are efficient and allow the computation of bounds in high-dimensional scenarios (e.g. when $d=60$). Numerical experiments using synthetic data showcase the efficiency of these algorithms, while they also allow to understand the reduction of model-risk by including additional information, in the form of known derivative prices.

On the monotonicity of the eigenvector method
László Csató,Dóra Gréta Petróczy
arXiv

Pairwise comparisons are used in a wide variety of decision situations where the importance of alternatives should be measured on a numerical scale. One popular method to derive the priorities is based on the right eigenvector of a multiplicative pairwise comparison matrix. We consider two monotonicity axioms in this setting. First, increasing an arbitrary entry of a pairwise comparison matrix is not allowed to result in a counter-intuitive rank reversal, that is, the favoured alternative in the corresponding row cannot be ranked lower than any other alternative if this was not the case before the change (rank monotonicity). Second, the same modification should not decrease the normalised weight of the favoured alternative (weight monotonicity). Both properties are satisfied by the geometric mean method but violated by the eigenvector method. The axioms do not uniquely determine the geometric mean. The relationship between the two monotonicity properties and the Saaty inconsistency index are investigated for the eigenvector method via simulations. Even though their violation turns out not to be a usual problem even for heavily inconsistent matrices, all decision-makers should be informed about the possible occurrence of such unexpected consequences of increasing a matrix entry.

Option Pricing: Channels, Target Zones and Sideways Markets
arXiv

After a market downturn, especially in an uncertain economic environment such as the current state, there can be a relatively long period with a sideways market, where indexes, stocks, etc., move in channels with support and resistance levels. We discuss option pricing in such scenarios, in both cases of unattainable as well as attainable boundaries, and obtain closed-form option pricing formulas. Our results also apply to FX rates in target zones without interest rate pegging (USD/HKD, digital currencies, etc.).

Prior CEO Experience as a Predictor of Entrepreneurial IPO Success: An Analysis of VC Investment Performance
Jones, Sophie Anne
SSRN
With increasing low returns on funds, Venture Capital (VC) firms search for the holy grail of success criteria to assess entrepreneur ventures. This study investigates Initial Public Offerings (IPOs) listed on the London Stock Exchange (LSE) in the AIM market between the years 2010 and 2019, within 10 years of being founded. Findings show a large proportion of the IPOs (65%) had founders with prior CEO experience and raised more money on average (Â£21.90m compared to Â£13.28m). Hence, an implication for the VC industry for investments is that entrepreneurs with previous CEO experience will likely raise more money at IPO.

Quantum computing for Finance: state of the art and future prospects
Daniel J. Egger,Claudio Gambella,Jakub Marecek,Scott McFaddin,Martin Mevissen,Rudy Raymond,Andrea Simonetto,Stefan Woerner,Elena Yndurain
arXiv

This paper outlines our point of view regarding the applicability, state of the art, and potential of quantum computing for problems in finance. We provide an introduction to quantum computing as well as a survey on problem classes in finance that are computationally challenging classically and for which quantum computing algorithms are promising. In the main part, we describe in detail quantum algorithms for specific applications arising in financial services, such as those involving simulation, optimization, and machine learning problems. In addition, we include demonstrations of quantum algorithms on IBM Quantum back-ends and discuss the potential benefits of quantum algorithms for problems in financial services. We conclude with a summary of technical challenges and future prospects.

Real-Time Prediction of BITCOIN Price using Machine Learning Techniques and Public Sentiment Analysis
arXiv

Bitcoin is the first digital decentralized cryptocurrency that has shown a significant increase in market capitalization in recent years. The objective of this paper is to determine the predictable price direction of Bitcoin in USD by machine learning techniques and sentiment analysis. Twitter and Reddit have attracted a great deal of attention from researchers to study public sentiment. We have applied sentiment analysis and supervised machine learning principles to the extracted tweets from Twitter and Reddit posts, and we analyze the correlation between bitcoin price movements and sentiments in tweets. We explored several algorithms of machine learning using supervised learning to develop a prediction model and provide informative analysis of future market prices. Due to the difficulty of evaluating the exact nature of a Time Series(ARIMA) model, it is often very difficult to produce appropriate forecasts. Then we continue to implement Recurrent Neural Networks (RNN) with long short-term memory cells (LSTM). Thus, we analyzed the time series model prediction of bitcoin prices with greater efficiency using long short-term memory (LSTM) techniques and compared the predictability of bitcoin price and sentiment analysis of bitcoin tweets to the standard method (ARIMA). The RMSE (Root-mean-square error) of LSTM are 198.448 (single feature) and 197.515 (multi-feature) whereas the ARIMA model RMSE is 209.263 which shows that LSTM with multi feature shows the more accurate result.

Reduced-form setting under model uncertainty with non-linear affine processes
Francesca Biagini,Katharina Oberpriller
arXiv

In this paper we extend the reduced-form setting under model uncertainty introduced in [5] to include intensities following an affine process under parameter uncertainty, as defined in [15]. This framework allows to introduce a longevity bond under model uncertainty in a consistent way with the classical case under one prior, and to compute its valuation numerically. Moreover, we are able to price a contingent claim with the sublinear conditional operator such that the extended market is still arbitrage-free in the sense of "No Arbitrage of the first kind" as in [6].

Reframing Related Party Transactions in China's State-Owned Enterprises
Kang, Sang Yop
SSRN
This paper analyzes understudied aspects of related party transactions (RPTs) in Chinaâ€™s state-owned enterprises (SOEs). This paper defines the government as an â€œinstitutional controlling shareholderâ€ of SOEs. In addition, this paper examines two types of RPTs in the SOE sector: â€œcorruption-RPTsâ€ and â€œpolicy-RPTs.â€ Corruption-RPTs are those associated with tunneling for the personal greed of SOE executives and party-government officials. Thus, from the standpoint of public investors, corruption-RPTs are always detrimental and generate cash-outflow wealth-transfers. Policy-RPTs are conducted by the government as a means of enacting public policy. In contrast to corruption-RPTs, policy-RPTs are associated with two opposite conceptsâ€"â€œinstitutionalized tunnelingâ€ (in favor of the controlling shareholder of SOEs, the government) and â€œproppingâ€ (to the detriment of the government). Although it is well known that investors in China are subject to the problem of insufficient investor protection, this paper finds that investors can sometimes benefit from policy-RPTs (e.g., investors of a propped SOE). Besides, this paper demonstrates that SOEs gain a variety of additional benefits from government policies in China that favor the financial interests of SOE investors. Accordingly, this paper shows that investors in Chinese SOEs are, to some extent, compensated and protected by an informal, extra-legal investor-protection mechanism. Moreover, this paper explores an overlooked topic in Chinaâ€™s SOE sectorâ€"how the political motivations of SOE executives and party-government officials function in the context of RPTs.

Startups in the COVID-19 Funnel
Prohorovs, Anatolijs
SSRN
Venture capital (VC) investments are pro-cyclical in nature, making it much more difficult for startups to attract investments during periods of economic recession than during economic growth. To mitigate the negative effects of the coronavirus crisis on the economy, countries are being forced to invest an unprecedented amount of financial resources in the economy, which in turn requires certain priorities. Therefore, in this article, we will look at which startup categories countries should support first during this crisis and what support instruments should be used for this purpose.

Stress Test Failures and Corporate Mergers and Acquisitions
Qiu, Buhui,Wang, Teng
SSRN
This study documents that corporate borrowers of banks that failed stress tests subsequently conduct fewer mergers and acquisitions (M&A). The effect is stronger for treated firms with weaker corporate governance or more susceptible to managerial agency problems. We further document increased financial covenant usage in M&A-related bank loan contracts, as well as improved M&A deal quality, after stress test failures, suggesting that stress testing failures triggered enhanced bank screening on borrowersâ€™ M&A projects. Moreover, refrained from M&A activity that can hurt shareholders, treated firms subsequently improve their profitability. Our empirical evidence highlights a beneficial spillover effects of bank stress tests.

Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions
Andersen, Torben G.,Varneskov, Rasmus Tangsgaard
SSRN
This paper develops parameter instability and structural change tests within predictive regressions for economic systems governed by persistent vector autoregressive dynamics. Specifically, in a setting where all â€" or a subset â€" of the variables may be fractionally integrated and the predictive relation may feature cointegration, we provide sup-Wald break tests that are constructed using the Local speCtruM (LCM) approach. The new tests cover both parameter variation and multiple structural changes with unknown break dates, and the number of breaks being known or unknown. We establish asymptotic limit theory for the tests, showing it coincides with standard testing procedures, implying that existing critical values for tied-down Bessel processes may be applied, without modification. We implement the new structural change tests to explore the stability of the fractionally cointegrating relation between implied- and realized volatility (IV and RV). Moreover, we assess the relative efficiency of IV forecasts against a challenging time-series benchmark constructed from high-frequency data. Unlike existing studies, we find evidence that the IV-RV cointegrating relation is unstable, and that carefully constructed time-series forecasts are, at least, as efficient as IV in capturing low-frequency movements in RV.

The Colour of Finance Words
Garcia, Diego,Hu, Xiaowen,Rohrer, Maximilian
SSRN
We study a standard machine learning algorithm, the multinomial inverse regression (MNIR, Taddy, 2013) to measure sentiment in financial documents. We show how dictionaries constructed from such an algorithm perform much better than existing techniques in predicting stock return movements. Most of the improvement is driven by using bi-grams instead of single words. Our approach refines and expands the standard dictionaries in the literature. Our paper focuses on the transcripts from earnings calls, but we also study the release of 10-K statements (Loughran and McDonald, 2011) and general market financial news (Tetlock, 2007).

The Constitution and the Fed after the COVID-19 Crisis
SSRN
The COVID-19 financial response brought a seismic shift in the allocation of authority between Congress, the Treasury, and the Federal Reserve. According to the classic division of labor, Congress claims the â€œpower of the purseâ€ or the constitutional authority to appropriate public funds; the Treasury holds responsibility over the spending and taxing that puts those orders into effect; and the Federal Reserve engages in money creation as part of its role making monetary policy and acting as lender of last resort. Drawing on that theory of separated powers, the essay reconstructs the traditional ways of thinking that distinguished money creation by the Fed from the congressional power of the purse. Most notably, approaches to the Fed have downplayed the distributive implications of its money creation powers by casting them as merely a stabilizing force, either backstopping private lending in times of panic or maintaining the health of credit markets more generally. We then analyze the COVID-19 liquidity facilities at the heart of the Federal governmentâ€™s response to the current crisis. Established by the Fed, these facilities are shaped in non-transparent ways by the Treasuryâ€™s authority to protect the Fed from losses. With only $450 billion in congressional appropriations, the facilities are anticipated to lend$4.5 trillion, an amount the size of the 2019 federal budget. In our view, the facilities collapse the traditional narrative that distinguished Fed money creation from congressional appropriations. We conclude that that traditional narrative was problematic from the start. Congressâ€™s inability to take responsibility over Fed credit support calls for a more structural reform in our financial system- one compatible with democratic governance and distributive justice.

The Cycle of Rents: A Model of Rational Bull-and-Bear Cycles in an Efficient Market
Gracia RodrÃ­guez, Eduard
SSRN
A widespread misbelief asserts that an efficient market would arbitrage out any cyclical or otherwise partially-predictable, non-random-walk pattern on the observed market prices time series. Hence, when such patterns are observed, they are often attributed to either irrational behavior or market inefficiency. Yet, strictly speaking, the efficient markets hypothesis only rules such patterns out of the expected (i.e. mean) path, whereas, if the probability diffusion process is asymmetric (as in most economic and financial stochastic models), the observed time series will approximate the median path, which is not subject to such constraint. This paper combines a general imperfect-competition production function specification (i.e. one generating economic rents) with the concept of time-to-build to develop a rational-expectations, efficient-markets model displaying a valuation cycle along its median path. This model may therefore help to explain the bull-and-bear cycles observed in asset markets generating economic rents e.g. real estate, commodities or, for that matter, most if not all of the assets quoted in the stock exchange.

The Effect of the Central Bank Liquidity Support During Pandemics: Evidence from the 1918 Spanish Influenza Pandemic
SSRN
The coronavirus outbreak raises the question of how central bank liquidity support affects financial stability and promotes economic recovery. Using newly assembled data on cross-county flu mortality rates and state-charter bank balance sheets in New York, we investigate the effects of the 1918 Influenza Pandemic on the banking system and the role of the Federal Reserve during the pandemic. We find that banks located in more severely affected areas experienced deposit withdrawals. Banks which were members of the Federal Reserve were able to access central bank liquidity and so continue or even expand lending. Banks which were not members, however, did not borrow on the interbank market but rather curtailed lending, suggesting there was little-to-no pass-through of central bank liquidity. Further, in the counties most affected by the 1918 Influenza, even banks with direct access to the discount window liquidated assets so as to meet large deposit withdrawals, suggesting limits to the effectiveness of the liquidity provision by the Federal Reserve. Finally, we show that the pandemic caused only a short-term disruption on the financial sector. Over the long-term, deposits returned and banks restored their asset portfolios.

The Evolution of Offshore Renminbi Trading: 2016 to 2019
Cheung, Yin-Wong,Grimm, Louisa,Westermann, Frank
SSRN
We study the evolution of offshore renminbi trading between 2016 and 2019. The diffusion behaviour of offshore renminbi trading during this period is different from the one between 2013 and 2016. The geographical diffusion process displayed in the 2016-2019 period, in addition to the previously reported convergence to the geographical trading pattern of all currencies, is affected by trade intensity, bilateral swap line arrangements, and has a regional bias. Further, it is possibly affected by disputes with China, and is different from the diffusion behaviours of the offshore US dollar, euro, British pound, and Japanese yen trading.

The Evolution of Price Discovery in an Electronic Market
SSRN
We study the evolution of the price discovery process in the euro-dollar and dollar-yen currency pairs over a ten-year period on the EBS platform, a global trading venue used by both manual and automated traders. We find that the importance of market orders decreases sharply over that period, owing mainly to a decline in the information share from manual trading, while the information share of market orders from algorithmic and high-frequency traders remains fairly constant. At the same time, there is a substantial, but gradual, increase in the information share of limit orders. Price discovery also becomes faster, suggesting improvements in market efficiency. The results are consistent with theoretical predictions that in more efficient markets, informed traders tend to use more limit orders.

The Information Content of Corporate Earnings: Evidence from the Securities Exchange Act of 1934
Binz, Oliver,Graham, John R.
SSRN
We examine whether the Securities Exchange Act of 1934 increased the information provided in accounting disclosures. Prior research examining the effects of the Act generally relies on long- window tests and yields mixed results. We improve upon prior designs by examining return, return volatility, and trading volume reactions to earnings news during short earnings announcement windows, which mitigates concerns that our results are driven by confounding events. Further, we employ a difference-in-differences design to control for potential contemporaneous structural changes. We document that the informativeness of earnings announcements of treatment firms (that withheld disclosure before the Act) increases relative to control firms (that disclosed voluntarily before the Act). The results are pronounced for large firms (higher regulatory scrutiny) and firms that do not pay dividends (possibly facing higher agency costs), and are symmetric for positive and negative earnings news.

The Resilience of the Socially Responsible Investment Networks
Cerqueti, Roy,Ciciretti, Rocco,DalÃ², Ambrogio,Nicolosi, Marco
SSRN
A network model is introduced and developed to compare portfolios of funds which are high ranked in Environmental Social and Governance (ESG) aspects with those with a poor ESG compliance. The nodes in the network represent funds and the edges are weighted on the basis of the capitalization due to the common components of the connected nodes. We specifically deal with the reactions of the considered financial networks to exogenous shocks of negative financial nature. To this aim, we provide a novel definition of the resilience of a financial network in terms of stability of its community structure. We test the theoretical proposal on different networks characterized by different ESG scores. We find that the high ranked funds networks are more resilient than the corresponding networks of low ranked funds.

Time-inhomogeneous Gaussian stochastic volatility models: Large deviations and super roughness
Archil Gulisashvili
arXiv

We introduce time-inhomogeneous stochastic volatility models, in which the volatility is described by a nonnegative function of a Volterra type continuous Gaussian process that may have very rough sample paths. The main results obtained in the paper are sample path and small-noise large deviation principles for the log-price process in a time-inhomogeneous super rough Gaussian model under very mild restrictions. We use these results to study the asymptotic behavior of binary barrier options, exit time probability functions, and call options.

Towards Entrepreneurial Ecosystem Indicators : Speed and Acceleration
Théophile Carniel,Jean-Michel Dalle
arXiv

We suggest the use of indicators to analyze entrepreneurial ecosystems, in a way similar to ecological indicators: simple, measurable, and actionable characteristics, used to convey relevant information to stakeholders and policymakers. We define 3 possible such indicators: Fundraising Speed, Acceleration and nth-year speed, all related to the ability of startups to develop more or less rapidly in a given ecosystem. Results based on these 3 indicators for 6 prominent ecosystems (Berlin, Israel, London, New York, Paris, Silicon Valley) exhibit markedly different situations and trajectories. Altogether, they contribute to confirm that such indicators can help shed new and interesting light on entrepreneurial ecosystems, to the benefit of potentially more grounded policy decisions, and all the more so in otherwise blurred and somewhat cacophonic environments.

Uncertainty in Firm Valuation and a Cross-Sectional Misvaluation Measure
Bottazzi, Giulio,Cordoni, Francesco,Livieri, Giulia,Marmi, Stefano
SSRN
In all investment decisions it is important to determine the degree of uncertainty associated with the valuation of a company. We propose an original and robust methodology to company valuation which replaces the traditional point estimate of the conventional Discounted Cash Flow (DCF) with a probability distribution of fair values. It hinges on two main ingredients: an econometric model for the company revenues and a set of firm-specific balance sheet relations that are estimated using historical data. The effectiveness and scope of our methodology are explored through a series of statistical exercises on publicly traded U.S. companies. We show that an uncertainty-adjusted indicator of mispricing, derived from the fair value distribution, is capable of predicting future abnormal returns. Then, we construct a new long-short valuation factor and we test that it is not redundant for describing average returns when used to augment traditional market factor models.

Unearthing Alpha in Financial Annual Reports
Agarwal, Vinayak
SSRN
Annual Reports are the managementâ€™s way of communicating with the stakeholders of a company. It contains a plethora of information concerning the companyâ€™s historical performance for a definite period and the managementâ€™s expectations about the companyâ€™s missions, goals and future. The paper highlights that a systematic textual analysis of the annual reports to derive a sentiment coefficient can help to create an alpha-factor and make sustainable returns that are orthogonal to the market returns, A strategy of long-short equity portfolio has been advocated wherein the selection criteria is based upon the ranking of sentiment coefficient so derived from the annual reports. The results document sound evidence of an established link between the stock returns and sentiment derived from the textual analysis of such reports.

What Drives the Liquidity Premium in the Chinese Stock Market?
An, Jiyoun,Ho, Kinâ€Yip,Zhang, Zhaoyong
SSRN