Research articles for the 2019-10-29
SSRN
This paper proposes a novel approach to the portfolio management using an AutoEncoder.In particular, the features learned by an AutoEncoder with ReLU are directly exploited to the portfolio construction.Since the AutoEncoder extracts the characteristics of the data through the non-linear activation function ReLU, its realization is generally difficult due to the non-linear transformation procedure.In the current paper, we solve this problem by taking full advantage of the similarity of the ReLU and the option payoff.Especially, this paper shows that the features are successfully replicated by applying so-called the dynamic delta hedging strategy.An out of sample simulation with crypto currency dataset shows the effectiveness of our proposed strategy.Furthermore, we investigate the background of our proposed methodology, which suggests that the first principal component is quite important.
arXiv
We propose and investigate two model classes for forward power price dynamics, based on continuous branching processes with immigration, and on Hawkes processes with exponential kernel, respectively. The models proposed exhibit jumps clustering features. Models of this kind have been already proposed for the spot price dynamics, but the main purpose of the present work is to investigate the performances of such models in describing the forward dynamics. We adopt a Heath-Jarrow-Morton approach in order to capture the whole forward curve evolution. By examining daily data in the French power market, we perform a goodness-of-fit test and we present our conclusions about the adequacy of these models in describing the forward prices evolution.
SSRN
Following the last global financial crisis, efficiencies of stock markets have come to sight as a novel area of research. The question of what factors shape the efficiency of the stock market is naturally always of a curiosity in theory and practice. In line with the framework of this curiosity, this study examines the main determinants that play a crucial role in the efficiency of a certain stock market, Borsa Istanbul. Our study contributes to the literature by using five years and daily data belonging to both individual and institutional investors. We here aim to specify the ten determinants of market efficiency which are categorized under investor-based, market-based and country-based determinants. According to the three different regressions and VAR analysis, the results indicate the strong relationship between the market efficiency and the specified determinants such as turnover, market volatility, the share of foreign investors and interest rate.
SSRN
This paper develops useful theory of arbitrage and risk arbitrage. It describes a prize winning successful risk arbitrage involving Nikkei put warrants trading on the Toronto and American stock exchanges. The paper describes the various types of contracts and how the risk arbitrage was traded and executed.
SSRN
We extend the classical asset-selling problem to include debt repayment obligation, selling capacity constraint, and Markov price evolution. Specifically, we consider the problem of selling a divisible asset which is acquired through debt financing. The amount of asset that can be sold per period may be limited by physical constraints. The seller uses part of the sales revenue to repay the debt. If unable to pay off the debt, the seller must go bankrupt and liquidate the remaining asset. Our analysis reveals that in the presence of debt, the optimal asset-selling policy must take into account two opposing forces: an incentive to sell part of the asset early to secure debt payment and an incentive to delay selling the asset to capture revenue potential under limited liability. We analyze how these two forces, originating from debt financing, will distort the sellerâs optimal policy.
SSRN
I examine bank loan loss provisioning behaviour during election years - focusing on the effect of elections on banking sector loan loss provisioning. The findings reveal that the banking sectors in developed countries have higher loan loss provisions in election years. Also, income smoothing is present in election years which supports the income smoothing hypothesis. Also, banking sectors with high capital levels have higher loan loss provisions. Although there were no significant differences in bank loan loss provisioning during election years across the four bloc, the EU banking sectors and the banking sectors of BIS member-countries generally have higher loan loss provisions while the non-EU banking sectors and the banking sectors of the G7 member-countries generally have fewer loan loss provisions.
SSRN
This paper proposes a quantitative general equilibrium model with credit market frictions to explain the observed stylized facts of micro uncertainty (dispersion of re- alized firm-level outcomes) and macro uncertainty (volatility of aggregate economic variables). They are conceptually different but strongly comove and countercyclical. In my model economy, an increase in the dispersion of firm-level idiosyncratic shocks leads to more firms in the left tail of the distribution to default, which reduces the total net worth of the corporate sector. As a result, leverage increases, it magnifies the shock amplification mechanism of credit market frictions. Hence, the economy becomes more sensitive to aggregate shocks when micro uncertainty is high and the aggregate economy is more volatile. Consistent with the model predictions, I find that in the data, micro uncertainty, based on the dispersion of firm-level stock returns and sales growth, positively predicts future credit spreads.
arXiv
In corporate bond markets, which are mainly OTC markets, market makers play a central role by providing bid and ask prices for a large number of bonds to asset managers from all around the globe. Determining the optimal bid and ask quotes that a market maker should set for a given universe of bonds is a complex task. Useful models exist, most of them inspired by that of Avellaneda and Stoikov. These models describe the complex optimization problem faced by market makers: proposing bid and ask prices in an optimal way for making money out of the difference between bid and ask prices while mitigating the market risk associated with holding inventory. While most of the models only tackle one-asset market making, they can often be generalized to a multi-asset framework. However, the problem of solving numerically the equations characterizing the optimal bid and ask quotes is seldom tackled in the literature, especially in high dimension. In this paper, our goal is to propose a numerical method for approximating the optimal bid and ask quotes over a large universe of bonds in a model \`a la Avellaneda-Stoikov. Because we aim at considering a large universe of bonds, classical finite difference methods as those discussed in the literature cannot be used and we present therefore a discrete-time method inspired by reinforcement learning techniques. More precisely, the approach we propose is a model-based actor-critic-like algorithm involving deep neural networks.
SSRN
Using a machine learning approach to process 11 million tweets posted by S&P 1500 firms from 2011 through 2016, we find that poor corporate social responsibility (CSR) performance firms tweet more about CSR activities and use tweets that are shorter, and with more passive voice and extreme tone. Good CSR performance firms tweet less about CSR, yet gain twice more followers per CSR tweet than poor CSR performance firms. Good CSR performance firms also experience a greater decrease in institutional ownership along with higher increases in bid-ask spread and stock return volatility after joining Twitter than do poor CSR performance firms. Our findings suggest that poor CSR performance firms play a greenwashing strategy, but this strategy is not effective in leading to capital market consequences.
SSRN
The paper delves into the implications of the financialisation process for competition law enforcement. We consider that the recent debate over common ownership and its impact on competition law and policy integrates one of the dimensions of the financialisation of the economy. This paper offers the first attempt for a theoretical analysis of this topic, focusing on the process of financialisation in the food industry. We explore the possibility that common ownership may constitute a competition concern, raising issues of unilateral effects, horizontal collusion, vertical exclusion and vertical exploitation. This discussion is particularly important in the context of Food Value Chains, with the rise of common ownership as one of the manifestations of the broader trend of the financialisation of the food industry. Many institutional investors are passive investors in the diverse companies that are active at various segments of the Food Value Chain. Although this paper focuses solely on the seed/agro-chem sector, it is possible to identify considerable common ownership in other parts of the Food Value Chain as well, particularly in the segments with the highest levels of economic concentration. In view of the possible negative welfare effects of common ownership on competition and its prevalence in the food sector, it is contended that competition authorities need to develop adequate legal tools to deal with this issue and rely on economics but also other sources of wisdom (e.g. advanced social network analysis) that may enable a better mapping of the complexity of competitive interactions in this sector and be more adequate in the context of a complex economy. Further research will explore the latter issue.
SSRN
We propose a model to study firm relationships that endogenously determine the correlation structure of asset cash flows. Forming a relationship makes firms face the following trade-off in their valuations: On the one hand, collaboration generates an additional payoff component with a positive mean. On the other hand, a relationship makes the firms' cash flows more correlated, which lowers the investor's diversification benefit. We use our model to investigate the incentives of firms to form a relationship and to disclose their relationship to the general public. We show that disclosing relationship information can have real consequences on cash flows through affecting firm relationship at both the intensive and the extensive margins.
SSRN
Why do residential mortgages carry a fixed or an adjustable interest rate? To answer this question we study unique data from 103 banks belonging to 73 different banking groups across twelve countries in the euro area. To explain the large cross-country and time variation observed, we distinguish between the conditions that determine the local demand for credit and the characteristics of banks that supply credit. As bank funding mostly occurs at the group level, we disentangle these two sets of factors by comparing the outcomes observed for the same banking group across the different countries. Local demand conditions dominate. In particular we find that the share of new loans with a fixed rate is larger when: (1) the historical volatility of inflation is lower, (2) the correlation between unemployment and the short-term interest rate is higher, (3) households' financial literacy is lower, and (4) the use of local mortgages to back covered bonds and mortgage-backed securities is more widespread.
arXiv
Rough volatility is a well-established statistical stylised fact of financial assets. This property has lead to the design and analysis of various new rough stochastic volatility models. However, most of these developments have been carried out in the mono-asset case. In this work, we show that some specific multivariate rough volatility models arise naturally from microstructural properties of the joint dynamics of asset prices. To do so, we use Hawkes processes to build microscopic models that reproduce accurately high frequency cross-asset interactions and investigate their long term scaling limits. We emphasize the relevance of our approach by providing insights on the role of microscopic features such as momentum and mean-reversion on the multidimensional price formation process. We in particular recover classical properties of high-dimensional stock correlation matrices.
SSRN
Blockchain-based initial coin offerings (ICOs) enable start-ups to not only get funding for early-stage growth but also attract open-source contribution to assist software development. Developers who adopt the ICOs can then sell their coins (also known as tokens) at the secondary market exchanges. We investigate the impact of token exchange listing on open-source contribution to the ICO projects and the mechanisms behind the impact. Using a quasi-experimental design, we find a surge in post-exchange open-source contribution, which is mainly driven by external developers. Two mechanisms â" financial incentives and developmental incentives â" speak for the increased external contribution to the ICO projects because we find that the quality signals and token prices on exchanges positively moderate the effect of exchange listing for the token. These findings illustrate the breakthrough of token-based fundraising and software development, compared to other funding mechanisms (crowdfunding, venture capital, etc.), centers on the alignment of open-source developersâ financial and developmental incentives for increased software quality and market value. This study provides managerially relevant implications on open-source project management that is centric to blockchain-based entrepreneurship. It is also the first to unveil the synergy between open-source development and blockchain-based fundraising in the literature.
arXiv
We discuss a simple, exactly solvable model of stochastic stock dynamics that incorporates regime switching between healthy and distressed regimes. Using this model, which is analytically tractable, we discuss a way of extracting expected returns for stocks from realized CDS spreads, essentially, the CDS market sentiment about future stock returns. This alpha/signal could be useful in a cross-sectional (statistical arbitrage) context for equities trading.
arXiv
Cultural trends and popularity cycles can be observed all around us, yet our theories of social influence and identity expression do not explain what perpetuates these complex, often unpredictable social dynamics. We propose a theory of social identity expression based on the opposing, but not mutually exclusive, motives to conform and to be unique among one's neighbors in a social network. We then model the social dynamics that arise from these motives. We find that the dynamics typically enter random walks or stochastic limit cycles rather than converging to a static equilibrium. We also prove that without social network structure or, alternatively, without the uniqueness motive, reasonable adaptive dynamics would necessarily converge to equilibrium. Thus, we show that nuanced psychological assumptions (recognizing preferences for uniqueness along with conformity) and realistic social network structure are both necessary for explaining how complex, unpredictable cultural trends emerge.
SSRN
We simulate default rate (DR) distributions based on models built on crisis and tranquil time periods using U.S. mortgage loan data to explore the impact changes in model parameters between different scenarios have on stress testing results. We apply the parameter posterior distribution obtained in a Bayesian approach to stress testing to reduce the estimation risk that results from using parameter point estimates. We compute the VaRs and required capital using a model built on crisis time period data and a Bayesian coefficient posterior distribution with both the effect of macroeconomic shocks on model parameters and the estimation risk considered. The results are compared with those obtained when coefficient changes in stress testing models or coefficient uncertainty is neglected. We find that the required capital is underestimated by nearly 40% when neither parameter instability nor estimation risk is addressed.
RePEC
The paper investigates the relationship between loan quality and macroeconomic imbalance indicators. We use the local projection method to estimate the response of non-performing loans (NPL) to changes in the cyclical component of macroeconomic factors. The estimations are run for three country groups of Western European countries, Central and Eastern European countries, and Southern European countries. The results show that a rise in the output gap is followed by a rise in NPL in all country groups, while NPL responds to the unemployment rate in the Central and Eastern and Southern European countries. Inflation and real unit labour costs are positively related to NPL in all country groups, though they are estimated with large uncertainty in some country groups. The findings suggest that it is useful to monitor imbalances in the output gap, unemployment, inflation and labour costs together with credit indicators to assess the ensuing dynamics in NPL.
SSRN
We develop a model of rational bubbles based on leverage and the assumption of an imprecisely known maximum market size. In a bubble, traders push the asset price above its fundamental value in a dynamic way, driven by rational expectations about future price developments. At a previously unknown date, the bubble will endogenously burst. Householdsâ decision to lend to traders with limited liability in a bubble is endogenous. Bubbles reduce welfare of future investors. We provide general conditions for the possibility of bubbles depending on uncertainty about market size, tradersâ degree of leverage and the risk-free rate. This allows us to discuss several policy measures. Capital requirements and a correctly implemented Tobin tax can prevent bubbles. Implemented incorrectly, however, these measures may create the possibility of bubbles and can reduce welfare.
arXiv
We develop a new market-making model, from the ground up, which is tailored towards high-frequency trading under a limit order book (LOB), based on the well-known classification of order types in market microstructure. Our flexible framework allows arbitrary order volume, price jump, and bid-ask spread distributions as well as the use of market orders. It also honors the consistency of price movements upon arrivals of different order types. For example, it is apparent that prices should never go down on buy market orders. In addition, it respects the price-time priority of LOB. In contrast to the approach of regular control on diffusion as in the classical Avellaneda and Stoikov [1] market-making framework, we exploit the techniques of optimal switching and impulse control on marked point processes, which have proven to be very effective in modeling the order-book features. The Hamilton-Jacobi-Bellman quasi-variational inequality (HJBQVI) associated with the control problem can be solved numerically via finite-difference method. We illustrate our optimal trading strategy with a full numerical analysis, calibrated to the order-book statistics of a popular Exchanged-Traded Fund (ETF). Our simulation shows that the profit of market-making can be severely overstated under LOBs with inconsistent price movements.
SSRN
This Article provides an early assessment of the impact on corporate governance of the most recent wave of SOE reform announced by the CCP in 2013, officially known as the mixed-ownership reform (MOR). It offers a comprehensive and detailed account of the background, policy and regulatory frameworks, and rationale of the MOR in light of the history of ownership reform in China. It also conducts empirical studies of the change in ownership and board composition in over 30 SOEs which have recently completed their MOR experiments, as well as, several case studies including China Unicomâs MOR. We observe that MORâs impact on SOE corporate governance has been embodied in the âretreat of the stateâ, the âadvance of the (Chinese Communist) Partyâ, and a limited yet emerging separation of power between the Party and the board in SOEs. On the rationale, we argue that the MOR programme is driven by three current beliefs of the Chinese Party-state on the future of SOEs in China. First, ownership and ownership reform matter. Second, sharing control, rather than dominance by a single state shareholder, improves both the efficiency and governance of SOEs. Third, the MOR was designed to develop partnerships or alliances between the state shareholders and strategic investors in order to help the post-MOR state enterprises improve their efficiency and enhance market opportunities.
SSRN
The purpose of this paper is to study the optimal retirement and consumption/investment decisions of an infinitely lived agent who does not tolerate any decline in her consumption throughout her lifetime. The agent receives labor income but suffers disutility from working until retirement. The agentâs optimization problem combines features of both singular control and optimal stopping. We use the martingale method and study the dual problem, which can be decoupled into a singular control problem and an optimal stopping problem. We provide a closed-form solution of the optimal strategies for the time-separable von-Neumann-Morgenstern utility function. We show that the coefficient of relative risk aversion implied by the optimal portfolio (i.e., the implied coefficient of relative risk aversion, ICRRA) is a constant value smaller than 1. Moreover, we show that the ICRRA is independent of the agent's felicity utility function and depends only on the subjective discount rate and market parameters.
SSRN
We document that both the dividend yield and earnings yield can predict future inflation across advanced economies. The inflation predictability reinforces the return predictability and reduces the dividend growth predictability. We show that both discount rates and cash flows play an essential role in determining prices. We test three hypotheses related to the future growth prospect, risk aversion, and behavior bias to justify the positive correlation among inflation and dividend (earnings) yields. High expected inflation correlates with periods of lower real economic growth and higher discount rates which lead to the drop in today's prices. To rationalize the inflation predictability, we develop and estimate a long-run risk model featuring inflation non-neutrality. The estimated model can reproduce both the inflation predictability and the documented asset pricing facts.
SSRN
We propose a new stress testing method to model both macroeconomic stress and coefficient uncertainty. Based on U.S. mortgage loan data, we model the probability of default at account level using discrete time hazard analysis. We employ both the frequentist and Bayesian methods in parameter estimation and default rate (DR) stress testing. By applying the parameter posterior distribution obtained in the Bayesian approach to simulating the Bayesian estimated DR distribution, we reduce the estimation risk coming from employing point estimates in stress testing. We find that the simulated DR distribution obtained using the Bayesian approach with the parameter posterior distribution has a standard deviation 1.7 times as large as that using the frequentist approach with parameter mean estimates. Moreover, the 95% and 99% values at risk (VaR) using the Bayesian posterior distribution approach are around 2 times the VaRs at the same probability levels using the point estimate approach.
SSRN
We propose and evaluate a variety of penalized regression methods for forecasting and economic decision making in a data-rich environment under parameter uncertainty. Empirically, we explore the statistical and economic performance across different asset classes such as stocks, bonds, and currencies, and alternative strategies within an asset class (e.g., momentum and value in the space of equity). The main result shows that penalties that both shrinkage the model space and regularize the remaining regression parameters, e.g. elastic net penalty, tend to outperform competing sparse and dense methodologies, both statistically and economically.
SSRN
We are witnessing a quiet but quick transformation of corporate governance. The rise of digital technologies and social media are forcing companies to reconsider how they organize themselves and structure firm governance. What is interesting is that the corporate governance discussions haven't really changed that much. The focus is still on reducing managerial misbehavior and maximizing the value of shareholders (the stakeholders who are taking the most significant risk). And the mechanisms for achieving this are more transparency and more supervision.But framing corporate governance primarily in terms of shareholder value is incomplete and potentially misleading. It encourages box-ticking and conformity. Managers are often motivated to project an image of compliance, while continuing as before. More significantly, digital technologies are now turning the world upside down. It is a fascinating, but challenging, time for business. Industry boundaries are disappearing. Platform companies operate across multiple industries (transportation, finance, healthcare, food, etc.) and use networks to deliver new business models and disrupt incumbents. Social media empowers all the stakeholders and has transformed the meaning of transparency.We cannot think in terms of traditional corporate structures anymore. Their boundaries have become more fluid and porous. Traditional corporate organizations with their departments, business divisions, and hierarchical relationships between the different groups of stakeholders are changing as companies adapt to the digital environment. Companies are not static hierarchies anymore, but complex, dynamic ecosystems comprising diverse, interacting elements.
SSRN
This paper categorizes investors into five groups. They are: efficient markets, risk premium, genius superior traders, rejectors of efficient market theory and those who use research to make superior risk adjusted returns. Successful investment involves estimation and optimization and these are discussed.
arXiv
We present a simple uniqueness argument for a collection of McKean-Vlasov problems that have seen recent interest. Our first result shows that, in the weak feedback regime, there is global uniqueness for a very general class of random drivers. By weak feedback we mean the case where the contagion parameters are small enough to prevent blow-ups in solutions. Next, we specialise to a Brownian driver and show how the same techniques can be extended to give short-time uniqueness after blow-ups, regardless of the feedback strength. The heart of our approach is a surprisingly simple probabilistic comparison argument that is robust in the sense that it does not ask for any regularity of the solutions.
SSRN
For many firms, the value of common equity is affected by the value of two types of minority interests: equity method investments (the companyâs significant minority stakes in affiliated entities), and non-controlling interests (outside minority interests in the companyâs partially-owned subsidiaries). In most cases little information is provided on these claims, and their value is accordingly estimated using book value. This study develops an algorithm to estimate the value of minority interests using book value, earnings, and the average pricing of these fundamentals in the firmâs industry. Valuing minority interests using the algorithm instead of book value results in statistically and economically significant improvement in the accuracy of the estimated value of common equity.
arXiv
This paper focuses on the weekly idiosyncratic momentum (IMOM) as well as its risk-adjusted versions with respect to various idiosyncratic risk metrics. Using the A-share individual stocks in the Chinese market from January 1997 to December 2017, we first evaluate the performance of the weekly momentum and idiosyncratic momentum based on raw returns and idiosyncratic returns, respectively. After that the univariate portfolio analysis is conducted to investigate the return predictability with respect to various idiosyncratic risk metrics. Further, we perform a comparative study on the performance of the IMOMportfolios with respect to various risk metrics. At last, we explore the possible explanations to the IMOM as well as risk-based IMOM portfolios. We find that 1) there is a prevailing contrarian effect and a IMOM effect for the whole sample; 2) a negative relation exists between most of the idiosyncratic risk metrics and the cross-sectional returns, and better performance is found that is linked to idiosyncratic volatility (IVol) and maximum drawdowns (IMDs); 3) additionally, the IVol-based and IMD-based IMOM portfolios exhibit a better explanatory power to the IMOM portfolios with respect to other risk metrics; 4) finally, higher profitability of the IMOM as well as IVol-based and IMD-based IMOM portfolios is found to be related to upside market states, high levels of liquidity and high levels of investor sentiment.