Quantitative Finance

In this paper the dynamics of an economic system with foreign financing, of integer or fractional order, are analyzed. The symmetry of the system determines the existence of two pairs of coexisting attractors. The integer-order version of the system proves to have several combinations of coexisting hidden attractors with self-excited attractors. Because one of the system variables represents the foreign capital in ow, the presence of hidden attractors could be of a real interest in economic models. The fractional-order variant presents another interesting coexistence of attractors in the fractional order space.

In this study, we will study investor attention measurement using the Search Volume Index in the recent market. Since 2009, the popularity of mobile devices and the spread of the Internet have made the speed of information delivery faster and the investment information retrieval data for obtaining investment information has increased dramatically. In these circumstances, investor attention measurement using search volume data can be measured more accurately and faster than before mobile device popularization. To confirm this, we will compare the effect of measuring investor attention using search volume data before and after mobile device popularization. In addition, it is confirmed that the measured investor attention is that of retail traders, not institutional traders or professional traders, and the relationship between investor attention and short-term price pressure theory. Using SVI data provided by Google Trends, we will experiment with Russell 3000 stocks and IPO stocks and compare the results. In addition, the results of investigating the investor's interest using the search volume data from various angles through experiments such as the comparison of the results based on the inclusion of the noise ticker group, the comparison of the limitations of the existing investor attention measurement method, and the comparison of explanatory variables with existing IPO related studies. We would like to verify its practicality and significance.

Proof of Stake (PoS) is a burgeoning Sybil resistance mechanism that aims to have a digital asset ("token") serve as security collateral in crypto networks. However, PoS has so far eluded a comprehensive threat model that encompasses both Byzantine attacks from distributed systems and financial attacks that arise from the dual usage of the token as a means of payment and a Sybil resistance mechanism. In particular, the existence of derivatives markets makes malicious coordination among validators easier to execute than in Proof of Work systems. We demonstrate that it is also possible for on-chain lending smart contracts to cannibalize network security in PoS systems. When the yield provided by these contracts is more attractive than the inflation rate provided from staking, stakers will tend to remove their staked tokens and lend them out, thus reducing network security. In this paper, we provide a simple stochastic model that describes how rational validators with varying risk preferences react to changes in staking and lending returns. For a particular configuration of this model, we provide a formal proof of a phase transition between equilibria in which tokens are predominantly staked and those in which they are predominantly lent. We further validate this emergent adversarial behavior (e.g. reduced staked token supply) with agent-based simulations that sample transitions under more realistic conditions. Our results illustrate that rational, non-adversarial actors can dramatically reduce PoS network security if block rewards are not calibrated appropriately above the expected yields of on-chain lending.

Over-the-counter markets are at the center of the postcrisis global reform of the financial system. We show how the size and structure of such markets can undergo rapid and extensive changes when participants engage in portfolio compression, a post-trade netting technology. Tightly-knit and concentrated trading structures, as featured by many large over-the-counter markets, are especially susceptible to reductions of notional and reconfigurations of network structure resulting from compression activities. Using transaction-level data on credit-default-swaps markets, we estimate reduction levels consistent with the historical development observed in these markets since the Global Financial Crisis. Finally, we study the effect of a mandate to centrally clear over-the-counter markets. When participants engage in both central clearing and portfolio compression, we find large netting failures if clearinghouses proliferate. Allowing for compression across clearinghouses by-and-large offsets this adverse effect.

This paper acts as a collection of various trading strategies and useful pieces of market information that might help to implement such strategies. This list is meant to be comprehensive (though by no means exhaustive) and hence we only provide pointers and give further sources to explore each strategy further. To set the stage for this exploration, we consider the factors that determine good and bad trades, the notions of market efficiency, the real prospect amidst the seemingly high expectations of homogeneous expectations from human beings and the catch-22 connotations that arise while comprehending the true meaning of rational investing. We can broadly classify trading ideas and client market color material into Delta-One and Derivative strategies since this acts as a natural categorization that depends on the expertise of the various trading desks that will implement these strategies. For each strategy, we will have a core idea and we will present different flavors of this central theme to demonstrate that we can easily cater to the varying risk appetites, regional preferences, asset management styles, investment philosophies, liability constraints, investment horizons, notional trading size, trading frequency and other preferences of different market participants.

We investigate a multi-household DSGE model in which past aggregate consumption impacts the confidence, and therefore consumption propensity, of individual households. We find that such a minimal setup is extremely rich, and leads to a variety of realistic output dynamics: high output with no crises; high output with increased volatility and deep, short lived recessions; alternation of high and low output states where relatively mild drop in economic conditions can lead to a temporary confidence collapse and steep decline in economic activity. The crisis probability depends exponentially on the parameters of the model, which means that markets cannot efficiently price the associated risk premium. We conclude by stressing that within our framework, {\it narratives} become an important monetary policy tool, that can help steering the economy back on track.

Companies try to maximize their profits by recovering returned products of highly uncertain quality and quantity. In this paper, a reverse logistics network for an Original Equipment Manufacturer (OEM) is presented. Returned products are selected for remanufacturing or scrapping, based on their quality and proportional prices are offered to customers. A Mixed Integer Non-linear Programming (MINLP) model is proposed to determine the location of collection centers, the optimum price of returned products and the sorting policy. The risk in the objective function is measured using the Conditional Value at Risk (CVaR) metric. CVaR measures the risk of an investment in a conservative way by considering the maximum lost. The results are analyzed for various values of the risk parameters ({\alpha}, and {\lambda}). These parameters indicate that considering risk affects prices, the classification of returned products, the location of collection centers and, consequently, the objective function. The model performs more conservatively when the weight of the CVaR part ({\lambda}) and the value of the confidence level {\alpha} are increased. The results show that better profits are obtained when we take CVaR into account.

We study how the phenomenon of contagion can take place in the network of the world's stock exchanges due to the behavioral trait "blindeness to small changes". On large scale individual, the delay in the collective response may significantly change the dynamics of the overall system. We explicitely insert a term describing the behavioral phenomenon in a system of equations that describe the build and release of stress across the worldwide stock markets. In the mathematical formulation of the model, each stock exchange acts as an integrate-and-fire oscillator. Calibration on market data validate the model. One advantage of the integrate-and-fire dynamics is that it enables for a direct identification of cause and effect of price movements, without the need for statistical tests such as for example Granger causality tests often used in the identification of causes of contagion. Our methodology can thereby identify the most relevant nodes with respect to onset of contagion in the network of stock exchanges, as well as identify potential periods of high vulnerability of the network. The model is characterized by a separation of time scales created by a slow build up of stresses, for example due to (say monthly/yearly) macroeconomic factors, and then a fast (say hourly/daily) release of stresses through "price-quakes" of price movements across the worlds network of stock exchanges.

Poor economies not only produce less; they typically produce things that involve fewer inputs and fewer intermediate steps. Yet the supply chains of poor countries face more frequent disruptions---delivery failures, faulty parts, delays, power outages, theft, government failures---that systematically thwart the production process. To understand how these disruptions affect economic development, we model an evolving input--output network in which disruptions spread contagiously among optimizing agents. The key finding is that a poverty trap can emerge: agents adapt to frequent disruptions by producing simpler, less valuable goods, yet disruptions persist. Growing out of poverty requires that agents invest in buffers to disruptions. These buffers rise and then fall as the economy produces more complex goods, a prediction consistent with global patterns of input inventories. Large jumps in economic complexity can backfire. This result suggests why "big push" policies can fail, and it underscores the importance of reliability and of gradual increases in technological complexity.

We study the role of contingent convertible bonds (CoCos) in a network of interconnected banks. We first confirm the phase transitions documented by Acemoglu et al. (2015) in absence of CoCos, thus revealing that the structure of the interbank network is of fundamental importance for the effectiveness of CoCos as a financial stability enhancing mechanism. Furthermore, we show that in the presence of a moderate financial shock lightly interconnected financial networks are more robust than highly interconnected networks, and can possibly be the optimal choice for both CoCos issuers and buyers. Finally our results show that, under some network structures, the presence of CoCos can increase (and not reduce) financial fragility, because of the occurring of unneeded triggers and consequential suboptimal conversions that damage CoCos investors.