Optimal Trading Strategies in a Limit Order Market with Imperfect Liquidity

We study the optimal execution strategy of selling a security. In a continuous time diffusion framework, a risk-averse trader faces the choice of selling the security promptly or placing a limit order and hence delaying the transaction in order to sell at a more favorable price. We introduce a random delay parameter, which defers limit order execution and characterizes market liquidity. The distribution of expected time-to-fill of limit orders conforms to the empirically observed exponential distribution of trading times, and its variance decreases with liquidity. We obtain a closed-form solution and demonstrate that the presence of the lag factor linearizes the impact of other market parameters on the optimal limit price. Finally, two more stylized facts are rationalized in our model: the equilibrium bid-ask spread decreases with liquidity, but increases with agents risk aversion

Implications for liquidity from innovation and transparency in the European corporate bond market

This paper offers a new framework for the assessment of financial market liquidity and identifies two types: search liquidity and systemic liquidity. Search liquidity, i.e. liquidity in “normal” times, is driven by search costs required for a trader to find a willing buyer for an asset he/she is trying to sell or vice versa. Search liquidity is asset specific. Systemic liquidity, i.e. liquidity in “stressed” times, is driven by the homogeneity of investors - the degree to which one’s decision to sell is related to the decision to sell made by other market players at the same time. Systemic liquidity is specific to market participants’ behaviour. This framework proves fairly powerful in identifying the role of credit derivatives and transparency for liquidity of corporate bond markets. We have applied it to the illiquid segments of the European credit market and found that credit derivatives are likely to improve search liquidity as well as systemic liquidity. However, it is possible that in their popular use today, credit derivatives reinforce a concentration of positions that can worsen systemic liquidity. We also found that post-trade transparency has surprisingly little bearing on liquidity in that where it improves liquidity it is merely acting as a proxy for pre-trade transparency or transparency of holdings. We conclude that if liquidity is the objective, pre-trade transparency, as well as some delayed transparency on net exposures and concentrations, is likely to be more supportive of both search and systemic liquidity than post-trade transparency. JEL Classification: G14, G15, G18.Financial market functioning, liquidity, transparency, credit markets and financial innovation.

The Impact of Reduced Pre-Trade Transparency Regimes on Market Quality

This paper studies the effects of pre-trade quote transparency on spread, price discovery and liquidity in an artificial limit order market with heterogeneous trading rules. Our agent-based numerical experiments suggest that full quote transparency incurs substantial transaction costs to traders and dampens trading activity in an order-driven market. Our finding reveals that exogenous restriction of displayed depth, up to several best quotes, does not benefit market performance. On the contrary, endogenous restriction of displayed quote depth, by means of iceberg orders, improves market quality in multiple dimensions: it reduces average transaction costs, maintains higher liquidity and moderate volatility, balances the limit order book, and enhances price discovery

An empirical behavioral model of price formation

Although behavioral economics has demonstrated that there are many situations where rational choice is a poor empirical model, it has so far failed to provide quantitative models of economic problems such as price formation. We make a step in this direction by developing empirical models that capture behavioral regularities in trading order placement and cancellation using data from the London Stock Exchange. For order placement we show that the probability of placing an order at a given price is well approximated by a Student distribution with less than two degrees of freedom, centered on the best quoted price. This result is surprising because it implies that trading order placement is symmetric, independent of the bid-ask spread, and the same for buying and selling. We also develop a crude but simple cancellation model that depends on the position of an order relative to the best price and the imbalance between buying and selling orders in the limit order book. These results are combined to construct a stochastic representative agent model, in which the orders and cancellations are described in terms of conditional probability distributions. This model is used to simulate price formation and the results are compared to real data from the London Stock Exchange. Without adjusting any parameters based on price data, the model produces good predictions for the magnitude and functional form of the distribution of returns and the bid-ask spread

Pricing-to-market and the failure of absolute PPP

The authors show that deviations from the law of one price in tradable goods are an important source of violations of absolute PPP across countries. Using highly disaggregated export data, they document systematic international price discrimination: at the U.S. dock, U.S. exporters ship the same good to low-income countries at lower prices. This pricing-to-market is about twice as important as any local non-traded inputs, such as distribution costs, in explaining the differences in tradable prices across countries. The authors propose a model of consumer search that generates pricing-to-market. In this model, consumers in low-income countries have a comparative advantage in producing non-traded, non-market search activities and therefore are more price sensitive than consumers in high-income countries. They present cross-country time use evidence and evidence from U.S. export prices that are consistent with the model.

SIZE AND HETEROGENEITY MATTER. A MICROSTRUCTURE-BASED ANALYSIS OF REGULATION OF SECONDARY MARKETS FOR GOVERNMENT BONDS.

This paper deals with the economics of secondary markets for government bonds. Ultimately, the analysis is shaped by a public policy goal: assessing the elements of a regulatory framework for these markets. In that regard, the decisive role of market structure leads to a critical review of microstructure conclusions relevant specifically for government debt markets. It is argued that the nature of information asymmetries and matching costs in government debt markets determines a bias towards a fragmented microstructure at odds both with exchange-like arrangements and with ordinary regulatory approaches. Hence, a generic conclusion highlights the risks of blindly transposing regulatory principles from the equity markets area without due regard to the specifics of the bond market. As a specific application of this idea, the paper critically reviews electronic trading platforms that emulate exchange-like order execution solutions. More specifically, the paper opposes the hybrid microstructure (pure limit order book plus affirmative quoting obligation) faced by European primary dealers and the arbitrage-based approach to market-making found in US inter-dealer markets. The Citigroup disruptive trade in August 2004 is analyzed from this perspective. Government bond regulation is argued to necessarily depart from ordinary approaches also because it captures the diverse interests of various governmental agencies. As an application of this principle, the paper discusses repo and short-selling regulation in government bond markets. The atypical market structure and the multi- agency endeavour around government bond markets raise the chances of regulatory failures. Nevertheless, it is argued that a reliance on competition, integrative infrastructure and basic systemic protections as over-arching principles for regulation is consistent with recommendations from relevant economic theory. Finally, political economy issues arising in implementation of transparency, disclosure or retail investor protection will be addressed in the context of selected country cases.government bonds, microstructure, regulation

FORECASTING OF THE STOCK RATE OF LEADING WORLD COMPANIES USING ECONOMETRIC METHODS AND DCF ANALYSIS

In this article, we will cover various models for forecasting the stock price of global companies, namely the DCF model, with well-reasoned financial analysis and the ARIMA model, an integrated model of autoregression − moving average, as an econometric mechanism for point and interval forecasting. The main goal is to compare the obtained forecasting results and evaluate their real accuracy. The article is based on forecasting stock prices of two companies: Coca-Cola HBC AG (CCHGY) and Nestle S.A. (NSRGF). At the moment, it is not determined which approach is better for predicting the stock price − the analysis of financial indicators or the use of econometric data analysis methods.In this article, we will cover various models for forecasting the stock price of global companies, namely the DCF model, with well-reasoned financial analysis and the ARIMA model, an integrated model of autoregression − moving average, as an econometric mechanism for point and interval forecasting. The main goal is to compare the obtained forecasting results and evaluate their real accuracy. The article is based on forecasting stock prices of two companies: Coca-Cola HBC AG (CCHGY) and Nestle S.A. (NSRGF). At the moment, it is not determined which approach is better for predicting the stock price − the analysis of financial indicators or the use of econometric data analysis methods

An empirical behavioral model of liquidity and volatility

We develop a behavioral model for liquidity and volatility based on empirical regularities in trading order flow in the London Stock Exchange. This can be viewed as a very simple agent based model in which all components of the model are validated against real data. Our empirical studies of order flow uncover several interesting regularities in the way trading orders are placed and cancelled. The resulting simple model of order flow is used to simulate price formation under a continuous double auction, and the statistical properties of the resulting simulated sequence of prices are compared to those of real data. The model is constructed using one stock (AZN) and tested on 24 other stocks. For low volatility, small tick size stocks (called Group I) the predictions are very good, but for stocks outside Group I they are not good. For Group I, the model predicts the correct magnitude and functional form of the distribution of the volatility and the bid-ask spread, without adjusting any parameters based on prices. This suggests that at least for Group I stocks, the volatility and heavy tails of prices are related to market microstructure effects, and supports the hypothesis that, at least on short time scales, the large fluctuations of absolute returns are well described by a power law with an exponent that varies from stock to stock

Markets, Contracts, or Integration? The Adoption, Diffusion, and Evolution of Organizational Form

The rise of contract farming and vertical integration is one of the most important changes in modern agriculture. Yet the adoption and diffusion of these new forms of organization has varied widely across regions, commodities, or farm types, however. Transaction cost theories and the like are not fully effective at explaining the variation of adoption rates of different organizational forms, in part because of their inherent static nature. In order to explain the adoption, diffusion and evolution of organizational form, a more dynamic framework is required. This paper lays out such a framework for understanding the evolution of organizational practices in U.S. agriculture by drawing on existing theories of economic organization, the diffusion of technological innovation, and organizational complementarities. Using recent trends as stylized facts we argue that the agrifood sector is characterized by strong complementarities among its constituent features and that these complementarities help explain the stylized facts. We also discuss several testable hypotheses concerning changes in organizational form in agriculture.contracting, vertical integration, organizational innovation, diffusion, Institutional and Behavioral Economics, L14, L22, Q13, O33,

Market Impact in Trader-Agents:Adding Multi-Level Order-Flow Imbalance-Sensitivity to Automated Trading Systems

Financial markets populated by human traders often exhibit "market impact", where the traders' quote-prices move in the direction of anticipated change, before any transaction has taken place, as an immediate reaction to the arrival of a large (i.e., "block") buy or sell order in the market: e.g., traders in the market know that a block buy order will push the price up, and so they immediately adjust their quote-prices upwards. Most major financial markets now involve many "robot traders", autonomous adaptive software agents, rather than humans. This paper explores how to give such trader-agents a reliable anticipatory sensitivity to block orders, such that markets populated entirely by robot traders also show market-impact effects. In a 2019 publication Church & Cliff presented initial results from a simple deterministic robot trader, ISHV, which exhibits this market impact effect via monitoring a metric of imbalance between supply and demand in the market. The novel contributions of our paper are: (a) we critique the methods used by Church & Cliff, revealing them to be weak, and argue that a more robust measure of imbalance is required; (b) we argue for the use of multi-level order-flow imbalance (MLOFI: Xu et al., 2019) as a better basis for imbalance-sensitive robot trader-agents; and (c) we demonstrate the use of the more robust MLOFI measure in extending ISHV, and also the well-known AA and ZIP trading-agent algorithms (which have both been previously shown to consistently outperform human traders). We demonstrate that the new imbalance-sensitive trader-agents introduced here do exhibit market impact effects, and hence are better-suited to operating in markets where impact is a factor of concern or interest, but do not suffer the weaknesses of the methods used by Church & Cliff. The source-code for our work reported here is freely available on GitHub.Comment: To be presented at the 13th International Conference on Agents and Artificial Intelligence (ICAART2021), Vienna, 4th--6th February 2021. 15 pages; 9 figure