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arXiv2011

Optimal execution strategy in the presence of permanent price impact and fixed transaction cost

We study a single risky financial asset model subject to price impact and transaction cost over an infinite horizon. An investor needs to execute a long position in the asset affecting the price of the asset and possibly incurring in fixed transaction cost. The objective is to maximize the discounted revenue obtained by this transaction. This problem is formulated first as an impulse control problem and we characterize the value function using the viscosity solutions framework. We also analyze the case where there is no transaction cost and how this formulation relates with a singular control problem. A viscosity solution characterization is provided in this case as well. We also establish a connection between both formulations with zero fixed transaction cost. Numerical examples with different types of price impact conclude the discussion.

q-fin.TR↗

arXiv2010

How simple regulations can greatly reduce inequality

Many models of market dynamics make use of the idea of wealth exchanges among economic agents. A simple analogy compares the wealth in a society with the energy in a physical system, and the trade between agents to the energy exchange between molecules during collisions. However, while in physical systems the equipartition of energy is valid, in most exchange models for economic markets the system converges to a very unequal "condensed" state, where one or a few agents concentrate all the wealth of the society and the wide majority of agents shares zero or a very tiny fraction of the wealth. Here we present an exchange model where the goal is not only to avoid condensation but also to reduce the inequality; to carry out this objective the choice of interacting agents is not at random, but follows an extremal dynamics regulated by the wealth of the agent. The wealth of the agent with the minimum capital is changed at random and the difference between the ancient and the new wealth of this poorest agent is taken from other agents, so establishing a regulatory tool for wealth redistribution. We compare different redistribution processes and conclude that a drastic reduction of the inequality can be obtained with very simple regulations.

physics.soc-ph↗

arXiv2012

Liquidity in Credit Networks: A Little Trust Goes a Long Way

Credit networks represent a way of modeling trust between entities in a network. Nodes in the network print their own currency and trust each other for a certain amount of each other's currency. This allows the network to serve as a decentralized payment infrastructure---arbitrary payments can be routed through the network by passing IOUs between trusting nodes in their respective currencies---and obviates the need for a common currency. Nodes can repeatedly transact with each other and pay for the transaction using trusted currency. A natural question to ask in this setting is: how long can the network sustain liquidity, i.e., how long can the network support the routing of payments before credit dries up? We answer this question in terms of the long term failure probability of transactions for various network topologies and credit values. We prove that the transaction failure probability is independent of the path along which transactions are routed. We show that under symmetric transaction rates, the transaction failure probability in a number of well-known graph families goes to zero as the size, density or credit capacity of the network increases. We also show via simulations that even networks of small size and credit capacity can route transactions with high probability if they are well-connected. Further, we characterize a centralized currency system as a special type of a star network (one where edges to the root have infinite credit capacity, and transactions occur only between leaf nodes) and compute the steady-state transaction failure probability in a centralized system. We show that liquidity in star networks, complete graphs and Erdös-Rényi networks is comparable to that in equivalent centralized currency systems; thus we do not lose much liquidity in return for their robustness and decentralized properties.

q-fin.TR↗

arXiv2010

Price dynamics in financial markets: a kinetic approach

The use of kinetic modelling based on partial differential equations for the dynamics of stock price formation in financial markets is briefly reviewed. The importance of behavioral aspects in market booms and crashes and the role of agents' heterogeneity in emerging power laws for price distributions is emphasized and discussed.

q-fin.TR↗

arXiv2010

Automated Liquidity Provision and the Demise of Traditional Market Making

Traditional market makers are losing their importance as automated systems have largely assumed the role of liquidity provision in markets. We update the model of Glosten and Milgrom (1985) to analyze this new world: we add multiple securities and introduce an automated market maker who uses the relationships between securities to price order flow. This new automated participant transacts the majority of orders, sets prices that are more efficient, and increases informed and decreases uninformed traders' transaction costs. These results can explain the recent dominance of high frequency trading in US markets and the corresponding increase in trading volume and decrease in transaction costs for US stocks.

q-fin.TR↗

arXiv2010

Empirical Limitations on High Frequency Trading Profitability

Addressing the ongoing examination of high-frequency trading practices in financial markets, we report the results of an extensive empirical study estimating the maximum possible profitability of the most aggressive such practices, and arrive at figures that are surprisingly modest. By "aggressive" we mean any trading strategy exclusively employing market orders and relatively short holding periods. Our findings highlight the tension between execution costs and trading horizon confronted by high-frequency traders, and provide a controlled and large-scale empirical perspective on the high-frequency debate that has heretofore been absent. Our study employs a number of novel empirical methods, including the simulation of an "omniscient" high-frequency trader who can see the future and act accordingly.

q-fin.TR↗

arXiv2010

Lowest Unique Bid Auctions

We consider a class of auctions (Lowest Unique Bid Auctions) that have achieved a considerable success on the Internet. Bids are made in cents (of euro) and every bidder can bid as many numbers as she wants. The lowest unique bid wins the auction. Every bid has a fixed cost, and once a participant makes a bid, she gets to know whether her bid was unique and whether it was the lowest unique. Information is updated in real time, but every bidder sees only what's relevant to the bids she made. We show that the observed behavior in these auctions differs considerably from what theory would prescribe if all bidders were fully rational. We show that the seller makes money, which would not be the case with rational bidders, and some bidders win the auctions quite often. We describe a possible strategy for these bidders.

math.PR↗

arXiv2010

A Chaotic Approach to Market Dynamics

Economy is demanding new models, able to understand and predict the evolution of markets. To this respect, Econophysics is offering models of markets as complex systems, such as the gas-like model, able to predict money distributions observed in real economies. However, this model reveals some technical hitches to explain the power law (Pareto) distribution, observed in individuals with high incomes. Here, non linear dynamics is introduced in the gas-like model. The results obtained demonstrate that a chaotic gas-like model can reproduce the two money distributions observed in real economies (Exponential and Pareto). Moreover, it is able to control the transition between them. This may give some insight of the micro-level causes that originate unfair distributions of money in a global society. Ultimately, the chaotic model makes obvious the inherent instability of asymmetric scenarios, where sinks of wealth appear in the market and doom it to complete inequality.

nlin.CD↗

arXiv2010

An algorithmic information-theoretic approach to the behaviour of financial markets

Using frequency distributions of daily closing price time series of several financial market indexes, we investigate whether the bias away from an equiprobable sequence distribution found in the data, predicted by algorithmic information theory, may account for some of the deviation of financial markets from log-normal, and if so for how much of said deviation and over what sequence lengths. We do so by comparing the distributions of binary sequences from actual time series of financial markets and series built up from purely algorithmic means. Our discussion is a starting point for a further investigation of the market as a rule-based system with an 'algorithmic' component, despite its apparent randomness, and the use of the theory of algorithmic probability with new tools that can be applied to the study of the market price phenomenon. The main discussion is cast in terms of assumptions common to areas of economics in agreement with an algorithmic view of the market.

q-fin.TR↗

arXiv2010

Chaos and Unraveling in Matching Markets

We study how information perturbations can destabilize two-sided matching markets. In our model, agents arrive on the market over two periods, while agents in the first period do not know the types of those arriving later. Agents already present in the market may match early or wait for the small group of new entrants. Despite the lack of discounting or risk aversion, this perturbation creates incentives to match early and leave the market before the new agents arrive. These incentives do not disappear as the market gets large. Moreover, we identify a new adverse phenomenon in this setting: as markets get large the probability of \emph{chaos} -- where no early matching scheme for existing agents is robust to pairwise deviations -- approaches 1. These results are independent of the distribution of agents' types and robust to asymmetries between the two sides of the market. Our findings thus suggest that matching markets are extremely sensitive to institutional details and uncertainty.

q-fin.TR↗

arXiv2010

Comparing Prediction Market Structures, With an Application to Market Making

Ensuring sufficient liquidity is one of the key challenges for designers of prediction markets. Various market making algorithms have been proposed in the literature and deployed in practice, but there has been little effort to evaluate their benefits and disadvantages in a systematic manner. We introduce a novel experimental design for comparing market structures in live trading that ensures fair comparison between two different microstructures with the same trading population. Participants trade on outcomes related to a two-dimensional random walk that they observe on their computer screens. They can simultaneously trade in two markets, corresponding to the independent horizontal and vertical random walks. We use this experimental design to compare the popular inventory-based logarithmic market scoring rule (LMSR) market maker and a new information based Bayesian market maker (BMM). Our experiments reveal that BMM can offer significant benefits in terms of price stability and expected loss when controlling for liquidity; the caveat is that, unlike LMSR, BMM does not guarantee bounded loss. Our investigation also elucidates some general properties of market makers in prediction markets. In particular, there is an inherent tradeoff between adaptability to market shocks and convergence during market equilibrium.

q-fin.TR↗

arXiv2010

Convergence of Income Growth Rates in Evolutionary Agent-Based Economics

We consider a heterogeneous agent-based economic model where economic agents have strictly bounded rationality and where income allocation strategies evolve through selective imitation. Income is calculated by a Cobb-Douglas type production function, and selection of strategies for imitation depends on the income growth rate they generate. We show that under these conditions, when an agent adopts a new strategy, the effect on its income growth rate is immediately visible to other agents, which allows a group of imitating agents to quickly adapt their strategies when needed.

q-fin.TR↗

arXiv2010

Kinetic models for socio-economic dynamics of speculative markets

In this paper we introduce a simple model for a financial market characterized by a single stock or good and an interplay between two different traders populations, chartists and fundamentalists, which determine the price dynamic of the stock. The model has been inspired by the microscopic Lux-Marchesi model (T.Lux, M.Marchesi, Nature 397, (1999), 498--500). The introduction of kinetic equations permits to study the asymptotic behavior of the investments and the price distributions and to characterize the regimes of lognormal behavior and the formation of power law tails.

q-fin.TR↗

arXiv2010

Statistical causes for the Epps effect in microstructure noise

We present two statistical causes for the distortion of correlations on high-frequency financial data. We demonstrate that the asynchrony of trades as well as the decimalization of stock prices has a large impact on the decline of the correlation coefficients towards smaller return intervals (Epps effect). These distortions depend on the properties of the time series and are of purely statistical origin. We are able to present parameter-free compensation methods, which we validate in a model setup. Furthermore, the compensation methods are applied to high-frequency empirical data from the NYSE's TAQ database. A major fraction of the Epps effect can be compensated. The contribution of the presented causes is particularly high for stocks that are traded at low prices.

q-fin.ST↗

arXiv2010

How sensitive are equilibrium pricing models to real-world distortions?

In both finance and economics, quantitative models are usually studied as isolated mathematical objects --- most often defined by very strong simplifying assumptions concerning rationality, efficiency and the existence of disequilibrium adjustment mechanisms. This raises the important question of how sensitive such models might be to real-world effects that violate the assumptions. We show how the consequences of rational behavior caused by perverse incentives, as well as various irrational tendencies identified by behavioral economists, can be systematically and consistently introduced into an agent-based model for a financial asset. This generates a class of models which, in the special case where such effects are absent, reduces to geometric Brownian motion --- the usual equilibrium pricing model. Thus we are able to numerically perturb a widely-used equilibrium pricing model market and investigate its stability. The magnitude of such perturbations in real markets can be estimated and the simulations imply that this is far outside the stability region of the equilibrium solution, which is no longer observed. Indeed the price fluctuations generated by endogenous dynamics, are in good general agreement with the excess kurtosis and heteroskedasticity of actual asset prices. The methodology is presented within the context of a financial market. However, there are close links to concepts and theories from both micro- and macro-economics including rational expectations, Soros' theory of reflexivity, and Minsky's theory of financial instability.

q-fin.GN↗

arXiv2010

The nature of price returns during periods of high market activity

By studying all the trades and best bids/asks of ultra high frequency snapshots recorded from the order books of a basket of 10 futures assets, we bring qualitative empirical evidence that the impact of a single trade depends on the intertrade time lags. We find that when the trading rate becomes faster, the return variance per trade or the impact, as measured by the price variation in the direction of the trade, strongly increases. We provide evidence that these properties persist at coarser time scales. We also show that the spread value is an increasing function of the activity. This suggests that order books are more likely empty when the trading rate is high.

q-fin.TR↗

arXiv2013

A Mathematical Approach to Order Book Modeling

Motivated by the desire to bridge the gap between the microscopic description of price formation (agent-based modeling) and the stochastic differential equations approach used classically to describe price evolution at macroscopic time scales, we present a mathematical study of the order book as a multidimensional continuous-time Markov chain and derive several mathematical results in the case of independent Poissonian arrival times. In particular, we show that the cancellation structure is an important factor ensuring the existence of a stationary distribution and the exponential convergence towards it. We also prove, by means of the functional central limit theorem (FCLT), that the rescaled-centered price process converges to a Brownian motion. We illustrate the analysis with numerical simulation and comparison against market data.

q-fin.TR↗

arXiv2011

Response of double-auction markets to instantaneous Selling-Buying signals with stochastic Bid-Ask spread

Statistical properties of order-driven double-auction markets with Bid-Ask spread are investigated through the dynamical quantities such as response function. We first attempt to utilize the so-called {\it Madhavan-Richardson-Roomans model} (MRR for short) to simulate the stochastic process of the price-change in empirical data sets (say, EUR/JPY or USD/JPY exchange rates) in which the Bid-Ask spread fluctuates in time. We find that the MRR theory apparently fails to simulate so much as the qualitative behaviour ('non-monotonic' behaviour) of the response function $R(l)$ ($l$ denotes the difference of times at which the response function is evaluated) calculated from the data. Especially, we confirm that the stochastic nature of the Bid-Ask spread causes apparent deviations from a linear relationship between the $R(l)$ and the auto-correlation function $C(l)$, namely, $R(l) \propto -C(l)$. To make the microscopic model of double-auction markets having stochastic Bid-Ask spread, we use the minority game with a finite market history length and find numerically that appropriate extension of the game shows quite similar behaviour of the response function to the empirical evidence. We also reveal that the minority game modeling with the adaptive ('annealed') look-up table reproduces the non-linear relationship $R(l) \propto -f(C(l))$ ($f(x)$ stands for a non-linear function leading to '$λ$-shapes') more effectively than the fixed (`quenched') look-up table does.

q-fin.TR↗