Market Microstructure

This paper examines the role of algorithmic trading in modern financial markets. Additionally, order types, characteristics, and special features of algorithmic trading are described under the lens provided by the large development of high frequency trading technology. Special order types are examined together with an intuitive description of the implied dynamics of the order book conditional to special orders (iceberg and hidden). The chapter provides an analysis of the transaction costs associated with trading activity and examines the most common trading strategy employed in the market. It also examines optimal execution strategy with the description of the Efficient Trading Frontier. These concepts represent the tools needed to understand the most recent innovations in financial markets and the most recent advances in microstructures research.

This paper analyzes the structural mechanisms that produce and sustain the 74•89% client loss rate documented by European (ESMA/MiFID II), American (CFTC), and Australian (ASIC) regulators across the retail foreign exchange industry. We identify four layers of structural bias: (i) the B-book and hybrid dealer model, in which the broker's profit is inversely correlated with client performance; (ii) a quadruple opacity in execution infrastructure, comprising the MetaTrader Manager Terminal, the Bridge and LP rebate architecture, the voice execution channel reserved for institutional participants, and the cumulative friction calculation invisible to retail; (iii) a five-tier acquisition funnel • introducing brokers, digital affiliates, commercial educators, signal providers, and copytrading platforms • whose aggregate function is the continuous production of depositing accounts rather than profitable traders; and (iv) a pseudoscientific pedagogical corpus, centered on technical analysis, whose empirical status has been systematically rejected by five decades of academic literature.  Working paper adapted from: CrossVol Research (2026). FX Traders vs Brokers: Vanilla and Exotic Options, Forwards, and Other OTC Structures: What Retail Traders Never See. Amazon Kindle, ASIN: B0GX31WB5F. https://www.amazon.com/dp/B0GX31WB5F

Stock exchanges are the cornerstones of every nation's growth, and capital markets are the nation's foundation too. Hence, the growth of the Stock Markets of the world is directly related to the production of the economy of every country. It can be noted from the last few years that the stock markets have expanded to suit the unmet needs. Stock market improvement has been created, and different products have been produced to meet the requirements. Commodities and the financial markets are the correct examples. The goal of this paper is to assess that the SME exchange provides companies with a new forum from which they can transfer to the exchange's main board. Till 2022, 107 companies have been transferred from NSE Emerge to the NSE mainboard market. The research hypothesis of the paper is to measure the performance of the companies that migrated from the SME's exchange to the main board of the NSE market. Using the independent sample t check with SPSS tools, we took a survey of 107 companies from the NSE Emerge that is being evaluated for their success before and after migration. This study's added value is to measure that whether the migration is a mean of increasing the profitability of the migrated company or not. We used the statistical tool independent sample t test on pre-and post-migration return differences. Our analysis reveals that when a corporation opts for a main board (NSE) listing, its shares often generate a favourable anomalous return although it was not found significant for post-migration return capabilities.

The GBP/USD currency pair, commonly known as "Cable," remains one of the most traded instruments in global foreign exchange markets. Every day, billions of dollars flow through this currency pair as banks, hedge funds, corporations, proprietary trading firms, and retail traders participate in price discovery. While the pair remains attractive because of its liquidity and volatility, the environment in which it trades has changed dramatically over the past decade. Today's markets are faster, more data-driven, and increasingly dominated by automation. Economic releases are analyzed within milliseconds, algorithmic systems react instantly to price changes, and liquidity providers constantly update quotes in response to changing market conditions. As a result, many traders who rely solely on manual execution are finding it increasingly difficult to compete. In fast-moving conditions, success depends not only on predicting market direction but also on execution speed, consistency, and disciplined risk management. Manual traders often struggle with these requirements because human decision-making introduces delays and emotional biases. Automated trading systems, by contrast, can process information and execute trades at speeds impossible for humans to match. This article examines why manual GBP/USD trading is becoming less effective in modern markets, compares manual and automated approaches, and explains how advanced risk management frameworks in automated trading help improve long-term performance. The Changing Nature of GBP/USD Markets

We assess the market microstructure properties of U.S. banking firms' equity, to determine whether they exhibit more or less evidence of asset opaqueness than similar-sized nonbanking firms. The evidence strongly indicates that large banks (traded on the NYSE) have very similar trading properties to their matched nonfinancial firms, but smaller banks (traded on NASDAQ) trade much less frequently despite having very similar spreads. We also estimate the impact of portfolio composition on a bank's market microstructure characteristics. Problem (noncurrent) loans tend to raise the frequency with which the bank's equity trades, as well as the equity's return volatility. The implications for regulatory policy and future market microstructure research are discussed. We thank Bart Danielsen and John Banko for their help in constructing the data sets for this paper, and

The underutilization of women's potential is not just a social issue but a significant economic handicap that is costing the Nigerian nation dearly. The study This study dealt with unlocking women's economic potential and boosting economic growth in Nigeria. The study used secondary date source, spanning from 2000-2025. Vector Error Correction Model (VECM) was used to estimate the parameters. This study revealed that in the short run and long run, the differenced coefficients remain positive and significant for all women-related variables, suggesting that improvements in women's labour participation, employment, education, credit access, and business ownership produce immediate growth effects, provide strong evidence that women's economic inclusion plays a critical role in promoting sustainable economic growth in Nigeria. The existence of a long-run equilibrium relationship between these womenspecific variables and economic growth confirms that female participation in the economy is not merely a social objective but an economic necessity. Inflation, carried a negative coefficient, indicating that macroeconomic instability undermines growth by eroding purchasing power and increasing production costs. The study therefore recommended that Nigeria should take a bold steps to address the root causes of gender inequality, invest in girl's education, promoting women's empowerment, promoting women's leadership end gender-based discrimination/violence.

Latency arbitrage-trading against a price quote that has not yet incorporated information already reflected in a faster reference market-is among the most frequently discussed and least formally documented phenomena in retail foreign exchange. While the academic literature on low-latency trading in equity markets is mature, the retail FX context differs in structurally important ways: prices are intermediated through a chain of liquidity providers, aggregators, and brokers; the reference market against which a quote may be judged stale is fragmented rather than consolidated; and the principal counterparty to a retail latency arbitrageur is frequently the broker itself rather than another trader. This paper surveys the mechanism of latency arbitrage in retail FX, organises the strategy space into a taxonomy, examines the infrastructure that determines feasibility, and analyses the detection methods and countermeasures that brokers deploy in response. We frame the broker-arbitrageur relationship as a coevolutionary dynamic and connect it to the established literature on toxic arbitrage and the economics of trading speed. The treatment is descriptive and integrative: it aims to render a phenomenon well understood by practitioners legible to a market-microstructure research audience, and to identify open questions amenable to empirical work.

This essay argues that the apparent conflict between the Efficient Market Hypothesis and behavioral economics is not a debate to be resolved in favor of one side, but a failure to recognize that the two frameworks describe different levels of the same system. Drawing on Shiller's excess volatility findings, De Long et al.'s noise trader model, and the genetics of investment behavior, the essay develops a multi-level account in which market efficiency emerges from the aggregation of diverse biased participants, and market pathology emerges when that diversity collapses under stress. The account shares significant ground with Lo's Adaptive Markets Hypothesis while offering a specific mechanism for why transitions between efficient and dysfunctional states tend to be sudden rather than gradual.

This paper argues that in a single, reasonably efficient spot market, there exist only two fundamental trading strategies. The argument rests on a logical constraint: in spot markets, profit derives exclusively from price movement in the direction of one's position. For a trader to enter a position, they must have a reason to expect that movement. That reason must take one of two forms: either the current price is low relative to some reference level and should rise (the logic of Mean Reversion), or the current price is high relative to some reference level and signals a breakout that should continue (the logic of Momentum). There is no third positional argument. A price that is neither low nor high-a price in the middle-provides no directional justification and is untradeable in spot markets. This logical constraint, not merely empirical resemblance, makes Mean Reversion and Momentum the exhaustive primitives of spot market strategy. We demonstrate that value investing, growth investing, arbitrage, pairs trading, and trend following all reduce to variations of these two primitives, and briefly discuss the conditions under which each dominates.

Equity markets price corporations as unified entities, yet large companies are composites of fundamentally different businesses. A fund manager who believes Amazon's AWS will outperform while e-commerce underperforms has no exchange-listed instrument to express that view. This structural gap suppresses informed trading, impairs price discovery, and prevents segment-level risk transfer and alpha generation from thematic exposures. We argue that mandatory XBRL-tagged SEC filings have created for the first time a technically viable foundation for segment-level financial derivatives. Using five years of audited data for Amazon and Apple, we show that hypothetical segment strategies generate sustained alpha largely uncorrelated with parent equity returns and serve as efficient hedges for thematic portfolios. Segment-level derivatives represent a significant and addressable gap in financial market infrastructure.

The Stock Exchange of Thailand provides an ideal platform for comparing the trading characteristics of warrants and their underlying stocks since both of them trade in the same market under identical trading rules. If their patterns diverge significantly, it may be possible for an astute trader to devise profitable arbitrage strategies during the life of the warrants. We find that both their patterns are downward-sloping for spreads, U-shaped for flow toxicity, volatility, depth concentration, and trading volume; and upward-sloping for depth and market order flow ratio. This implies that trading under identical market structures leads to similar trading characteristics. We document that flow toxicity is negatively related to spread and positively related to depth, market order flow ratio, trade size, trading volume, and volatility.

We apply the path signature transform-a canonical lossless encoding of multidimensional time series rooted in Chen's theorem (1954) and Rough Path Theory (Lyons 1998)-to the joint trajectory of bid price, ask price, bid volume, and ask volume extracted from limit order book (LOB) data. Truncating the signature at order 4 yields a 341-dimensional feature vector that constitutes a sufficient statistic for predicting the next mid-price direction without any manual feature engineering. Evaluated on the FI-2010 benchmark dataset (NASDAQ, 10 stocks, 10 trading days, 10-level LOB) and on proprietary US equity tick data (2020-2024), the signature feature set outperforms standard hand-crafted LOB features (OBI, spread, VPIN, microprice) by 35-56% in terms of Information Coefficient (IC) at 100-500ms prediction horizons. We further demonstrate that the 5 most informative signature terms-cross-variation of bid price and bid volume, Lévy area between bid and ask price paths, and three third-order interaction terms-have direct microstructure interpretations, suggesting that the signature is not merely a black-box feature extractor but a structured decomposition of LOB information. GPUaccelerated computation via the Signatory library achieves full 341-feature extraction in under 0.8ms, making the approach compatible with live HFT deployment.

During China's transition toward a more flexible exchange rate, it is essential to further develop its foreign exchange (FX) derivatives markets to meet the growing hedging needs associated with greater exchange rate fluctuations. Although over-the-counter (OTC) FX derivatives markets already exist in China, it lacks a FX futures market that offers critical complementarities. With standardized products, greater transparency and centralized oversight, a FX futures market can better satisfy the hedging needs of small and mediumsized enterprises and enhance regulatory efficiency. To address concerns regarding whether FX futures market will amplify the volatility of spot exchange rates, this paper analyzes the impact of establishing FX futures markets on spot market volatility using data from major emerging market economies. The result shows that FX futures market is not empirically associated with an increase in spot market volatility; in some cases, it is even associated with a decrease in spot market volatility. This paper further suggests that for a well-functioning FX futures market to be established, it is essential for China to substitute the inefficient documentation requirement of underlying exposures with a new set of market-oriented measures for the purpose of prudent regulation.

This paper develops a unified model of performance under pressure by coupling fast evidence accumulation to slower gain, buffering, and resource dynamics. The central claim is that failure under pressure is not governed by nominal penalty alone. It is governed by how penalty is transmitted through reserve structure and by whether the resulting effective drift remains strong enough to support threshold crossing. The model treats accumulated evidence as the fast observable layer, gain as an adaptive but metabolically costly amplifier, buffering as a reserve that attenuates transmitted penalty and directly narrows diffusion, and resources as a slower supply state that replenishes or starves the buffer. A general regime law is defined by the sign of the reduced threshold distance epsilon = mu_efflambda b. This law unifies earlier gain, penalty, and buffering papers as limiting or reduced cases of one multiscale system. The paper explicitly separates endogenous states from exogenous controls, derives a nondimensional form clarifying timescale ratios, provides positivity and boundedness statements for the reserve subsystem, and formulates a quasi-stationary Fokker-Planck interpretation for the evidence layer under slow reserve variation. A reduced threshold geometry yields a closed-form critical buffer level above which deterministic crossing is restored, and a low-leak approximation provides an inverse-Gaussian observation model for response-time data with censoring. Full stochastic simulations reveal resource-supported stabilization, near-critical depletion, and collapse-prone regimes, while synthetic parameter recovery shows that effective drift, effective diffusion, and regime distance can be estimated from first-passage and withholding data. The framework therefore offers both a unified theory of regime transition and a practical route toward measurement.

Minimal decision models explain performance in terms of signal, leak, and noise, while more recent gain and penalty models show how internal amplification and expected consequence alter usable inference. The present paper develops a unifying regime-transition framework that treats performance collapse as a phase change in reserve-filtered inference dynamics. Penalty is not imposed directly on a bare evidence accumulator. It is transformed into transmitted penalty by a buffer, while gain, buffer, and slower resources evolve on coupled timescales. This creates a hierarchy in which fast evidence accumulation sits inside slower reserve dynamics. We derive a general regime law based on the sign of a reduced threshold distance, show how the earlier penalty and buffering models appear as limiting cases, formulate a nondimensional system clarifying timescale ratios, and provide positivity, boundedness, and local-stability conditions for the reserve subsystem. A quasi-stationary Fokker-Planck interpretation is given for the evidence layer under slow reserve variation. Reduced threshold geometry yields an explicit critical buffer level, while full stochastic simulations reveal buffer-dominant stabilization, near-critical depletion, and penalty-dominant collapse. A likelihood section and synthetic recovery demonstration show that effective drift and diffusion can, in principle, be recovered from response-time data. The framework provides a mechanistic account of why systems facing the same nominal penalty can occupy different operating regimes because penalty is filtered through reserve structure rather than applied directly.

Motivated by how transaction amount constrain trading volume and price volatility in stock market, we, in this paper, study the relation between volume and price if amount of transaction is given. We find that accumulative trading volume gradually emerges a kurtosis near the price mean value over a trading price range when it takes a longer trading time, regardless of actual price fluctuation path, time series, or total transaction volume in the time interval. To explain the volume-price behavior, we, in terms of physics, propose a transaction energy hypothesis, derive a time-independent transaction volume-price probability wave equation, and get two sets of analytical volume distribution eigenfunctions over a trading price range. By empiric test, we show the existence of coherence in stock market and demonstrate the model validation at this early stage. The volume-price behaves like a probability wave.

Market making plays a crucial role in providing liquidity and maintaining stability in financial markets, making it an essential component of well-functioning capital markets. Despite its importance, there is limited research on market making in the Chinese stock market, which is one of the largest and most rapidly growing markets globally. To address this gap, we employ an optimal market making framework with an exponential CARA-type (Constant Absolute Risk Aversion) utility function that accounts for various market conditions, such as price drift, volatility, and stamp duty, and is capable of describing 3 major risks (i.e., inventory, execution and adverse selection risks) in market making practice, and provide an in-depth quantitative and scenario analysis of market making in the Chinese stock market. Our numerical experiments explore the impact of volatility on the market maker's inventory. Furthermore, we find that the stamp duty rate is a critical factor in market making, with a negative impact on both the profit of the market maker and the liquidity of the market. Additionally, our analysis emphasizes the significance of accurately estimating stock drift for managing inventory and adverse selection risks effectively and enhancing profit for the market maker. These findings offer valuable insights for both market makers and policymakers in the Chinese stock market and provide directions for further research in designing

An interdisciplinary approach is necessary for the sustainable management and governance of renewable natural resources, in which "Local Ecological Knowledge" (LEK), a quintessentially interdisciplinary field, is regarded as an essential source of information. But the effective use of LEK for this purpose would first demand the recognition and correction of the serious limitations of LEK social research. A recent literature analysis by Davis and Ruddle (2010) demonstrated that the basic problems characterising social research on LEK are the use of unsophisticated theories or concepts with often undocumented and non-systematic research designs and methodologies that result in unwarranted or indefensible outcomes. In addition, standards of accountability and transparency must be raised, beginning with the elementary requirement that researchers provide descriptions of research designs and methodologies that enable assessment of the reliability and representativeness of findings, and facilitate comparison, generalisation and evidencebased conclusions. The related issues of the problems inherent in applying an interdisciplinary approach and the manipulation of the publications process to suppress undesirable opinions and research results are examined.

This paper develops a new research programme for capital markets in which the central scarce asset is not merely data, balance-sheet capacity, or execution speed, but operator capital: the institutional ability to estimate, update, own, and exploit the transition law of valuable economic processes. The paper asks whether financial systems can be modeled as graph-coupled hidden-state operators whose lifted spectral coordinates reveal regime change, contagion, liquidity fragility, and intervention leverage earlier than static return-factor or covariance-based models. We propose a Graph-Koopman State-Space (GKSS) framework in which observed market variables and multilayer financial graphs are mapped into a lifted observable space, propagated with a finite-dimensional approximation to a stochastic Koopman operator, and filtered through latent-state inference under partial observability. The resulting architecture unifies network contagion, state-space estimation, regime switching, and control into one mathematically coherent decision system. The framework yields three classes of outputs: slow fragility modes that accumulate before visible crisis, contagion eigen-dynamics that expose bridge institutions and collapse corridors, and policy maps for hedging, execution, liquidity defense, and resilience allocation. The paper formalizes the model, defines a measurable notion of operator capital, and shows how transition-law intelligence can be treated as an institutional asset with translational value for hedge funds, insurers, central banks, sovereign wealth funds, and market infrastructure operators. Theoretical originality lies in embedding graph structure directly inside lifted operator observables, coupling spectral dynamics to hidden regime filtering, and evaluating capital allocation through operator drift rather than purely backward-looking factor exposures. The manuscript closes with implications for model risk, governance, systemic safety, and frontier financial architectures.

New regulatory data reveal extensive discriminatory pricing in the foreign exchange derivatives market, in which dealer-banks and their non-financial clients trade over-the-counter. After controlling for contract characteristics, dealer fixed effects, and market conditions, we find that the client at the 75th percentile of the spread distribution pays an average of 30 pips over the market mid-price, compared to competitive spreads of less than 2.5 pips paid by the bottom 25% of clients. Higher spreads are paid by less sophisticated clients. However, trades on multi-dealer request-for-quote platforms exhibit competitive spreads regardless of client sophistication, thereby eliminating discriminatory pricing.

New regulatory data reveal extensive discriminatory pricing in the foreign exchange derivatives market, in which dealer-banks and their non-financial clients trade over-the-counter. After controlling for contract characteristics, dealer fixed effects, and market conditions, we find that the client at the 75th percentile of the spread distribution pays an average of 30 pips over the market mid-price, compared to competitive spreads of less than 2.5 pips paid by the bottom 25% of clients. Higher spreads are paid by less sophisticated clients. However, trades on multi-dealer request-for-quote platforms exhibit competitive spreads regardless of client sophistication, thereby eliminating discriminatory pricing.

This paper analyzes the causal linkage between transaction costs and financial volatility under two methodological improvements over the existing literature. First, we use panel data in which exogenous transaction cost differences in the French stock market are induced by price level dependent minimum price variation rules (tick size rules). Unlike in previous studies based on one-time regulatory tick size changes (like the U.S. decimalization), we can separately identify and control for marketwide volatility changes. Second, we avoid the pitfalls of biased volatility measurement across regimes by using the range as a tick size robust volatility metric. Panel regressions controlling for marketwide volatility effects show at high levels of statistical significance that the hourly range volatility of individual stocks increases by more than 30% for a 20% exogenous increase in transaction costs due to tick size variations in the French trading system. In the light of this evidence, higher transaction costs in general, and security transaction taxes in particular, should be considered as volatility increasing. (JEL: F3, G1, G14)

New regulatory data reveal extensive price discrimination against non-financial clients in the FX derivatives market. The client at the 90th percentile pays an effective spread of 0.5%, while the bottom quarter incur transaction costs of less than 0.02%. Consistent with models of search frictions in over-the-counter markets, dealers charge higher spreads to less sophisticated clients. However, price discrimination is eliminated when clients trade through multi-dealer request-for-quote platforms. We also document that dealers extract rents from captive clients and market opacity, but only for contracts negotiated bilaterally with unsophisticated clients.

This paper establishes a cointegration relationship for the nominal exchange rate in Costa Rica. The reporting requirements for the central bank allow me to calculate a daily measure of its dollar shortfall from trading with nonbank public companies. This and the the country's differential Emerging Market Bond Index (EMBI) are cointegrated with Costa Rica's exchange rate. Out-of-sample tests show that forecasts based on these cointegration relationships significantly outperform a random walk benchmark. I also show that informed traders with data that is only a few days more recent can generate significantly better forecasts than those available to regular investors.

The Midnight Opening Gap (MNOG) refers to the price displacement between the Previous Day's Close (23:59 New York time) and the Midnight Open (00:00 New York time). This gap represents an overnight imbalance formed during the Asian session and is proposed as a daily balancing mechanism influencing intraday price behavior, including retracements, liquidity sweeps, and directional bias. Positioned within the framework of the Inner Circle Trader (ICT) methodology developed by Michael J. Huddleston, MNOG extends concepts such as the New Week Opening Gap into a daily time-based model. While the acronym "MNOG" may be novel, the underlying principle aligns with established research on opening price gaps, mean reversion, and non-trading period effects. Empirical observations from practitioner backtesting suggest retracement probabilities in the range of 60-65%, with improved outcomes when combined with higher time frame bias and liquidity-based confluence. However, MNOG should not be considered a standalone trading strategy; its effectiveness depends on structured integration within a broader execution model.

This article synthesizes foundational theories in economics and modern quantitative finance, with particular emphasis on how stochastic analysis, market microstructure, and machine learning jointly shape contemporary research and practice. We review classic frameworks for portfolio choice and asset pricing, the martingale approach to no-arbitrage valuation, and liquidity-sensitive models of execution and market making. We then integrate recent econometric advances-especially double/debiased machine learning for causal and structural estimation-and discuss emerging uses of large language models for measurement and prediction tasks under explicit validity conditions. The methodology section proposes a unified research-to-deployment pipeline that links theory-driven modeling to disciplined empirical evaluation. The analysis highlights implications for market efficiency, risk management, and financial stability, and identifies open problems at the intersection of equilibrium modeling, strategic interaction, and data-driven inference. We also highlight recent market-structure developments-such as the growth of zero-days-to-expiry index options, the transition to T+1 settlement in U.S. securities, and the expansion of central clearing in U.S. Treasuries-and discuss their quantitative implications for liquidity and intraday risk.

Pairs trading is a popular strategy on Wall Street. Most pairs trading strategies are based on a minimum distance approach or cointegration method. In this paper, we propose an alternative model to the process of pair return spread. Specifically, we model the return spread of potential stock pairs as a three-regime threshold autoregressive model with GARCH effects (TAR-GARCH), and the upper and lower regimes in the model are used as trading entry and exit signals. An application to the Dow Jones Industrial Average Index stocks is presented.

The views expressed in this paper are those of the author(s) and do not necessarily represent those of the Swiss National Bank. Working Papers describe research in progress. Their aim is to elicit comments and to further debate. The Swiss National Bank (SNB) respects all third-party rights, in particular rights relating to works protected by copyright (information or data, wordings and depictions, to the extent that these are of an individual character).

ii BIS Working Papers are written by members of the Monetary and Economic Department of the Bank for International Settlements, and from time to time by other economists, and are published by the Bank. The views expressed in them are those of their authors and not necessarily the views of the BIS.

This dossier is a full IM-10+ exemplar applying the framework to the July 27–August 2, 2022 price dislocation in AMTD Digital Inc. (NYSE: HKD). The inquiry evaluates four competing explanations for the event: narrative-driven mispricing, structural liquidity failure, coordinated speculative behavior, and genuine information-based repricing.

The dossier is presented in canonical IM-10+ artifact form rather than as a conventional essay. It includes the full step sequence, claim and assumption cross-linking, evidence resilience scoring, model comparison, stress tests, second-order effects, and run-level compliance tracking. Its purpose is twofold: first, to analyze the HKD event in a disciplined and auditable way; second, to test whether Finance / Markets can be supported as an IM-10+ application domain through exemplar-grade dossier construction.

This document should be read as a traceable case file and methodological demonstration, not as investment advice, legal accusation, or a definitive regulatory conclusion. The analysis is limited to public information and explicitly distinguishes between what is supported, what remains uncertain, and what would change the conclusion.

This paper analyzes the S&P 500 index return variance dynamics and the variance risk premium by combining information in variance swap rates constructed from options and quadratic variation estimators constructed from tick data on S&P 500 index futures. Estimation shows that the index return variance jumps. The jump arrival rate is not constant over time, but is proportional to the variance rate level. The variance jumps are not rare events but arrive frequently. Estimation also identifies a strongly negative variance risk premium, the absolute magnitude of which is proportional to the variance rate level.

The unmediated call auction is a useful trading mechanism to aggregate dispersed information. Its ability to incorporate information of a single informed insider, however, is less well understood. We analyse this question by presenting a simple call auction game where both auction prices and limit prices of uninformed traders re?ect potential insider information. The predictions of the model are tested

Abstract: The Interactive Minority Game (IMG) is an online version of the traditional Minority Game in which human players can enter into competition with the traditional computer-controlled agents. Through the rich (and, importantly, analytically understood) behaviour of the MG, we can explore humans' behaviour in different kinds of market--crowded, efficient, critical--with a high degree of control. To make the game easily understandable even to those who are encountering it for the first time, we have presented the game with a rather ...

We formulate a market microstructure model of exchange determination we employ to investigate the impact of foreign exchange intervention on exchange rates and on foreign exchange (FX) market conditions. With our formulation we show i) how foreign exchange intervention influences exchange rates via both a portfolio-balance and a signalling channel and ii) derive a series of testable implications which are coherent with a large body of empirical research. Our investigation also proposes some normative recommendations, as we show i) that in extreme circumstances large scale foreign exchange intervention can have destabilizing effects for the functioning of FX markets and ii) that the route chosen for the implementation of official intervention has important implications for its impact on exchange rates and on market conditions. JEL Nos.: D82, G14 and G15.

We investigate the micro structure of the UK gilt market studying the behaviour of several gilt-edged market makers on the London Stock Exchange. Through a structural model of the price process we can test different microstructural hypotheses, concerning information asymmetries, transaction and inventory carrying costs, and market liquidity. Our results suggest that inventories do not alter the price process in the gilt market. Moreover, differently from customer orders, inter-dealer transactions possess an information content. Transaction costs in the inter-dealer market are also substantially smaller than those for external customers.

We formulate a market microstructure model of exchange determination we employ to investigate the impact of foreign exchange (FX) intervention on exchange rates and on FX market conditions. With our formulation we show: i) how FX intervention influences exchange rates via both a portfolio-balance and a signalling channel; and ii) derive a series of testable implications which are coherent with a large body of empirical research. Our investigation also proposes some normative recommendations, as we show: i) that in extreme circumstances large scale FX intervention can have destabilizing effects for the functioning of FX markets; and ii) that the route chosen for the implementation of official intervention has important implications for its impact on exchange rates and on market conditions. JEL Nos.: D82, G14 and G15.

Using a market microstructure analytical framework we decompose the FX forward discount bias into elements due to time-varying risk premia (related to EBS order flow) and forecast errors derived using the Reuters survey of FX market participants. We find that both elements are significant contributors to the forward bias with risk premia being particularly important in currency pairs traditionally associated with carry trade activity. Part of order flow is driven by carry trade, and from our decomposition the carry trade driven risk premia accounts for about 50% of the forward bias. JEL Nos.: D82, G14 and G15.

This article describes main risks associated with international operations in banking engineering practice. There is a review of the situation on the international market in this area. It is concluded to use the concept of VaR method for the objective estimation of the risks of commercial banks.

The one-dimensional deterministic economic model recently studied by González-Estévez et al. [Physica A 387, 4367 (2008)] is considered on a two-dimensional square lattice with periodic boundary conditions. In this model, the evolution of each agent is described by a map coupled with its nearest neighbors. The map has two factors: a linear term that accounts for the agent’s own tendency to grow and an exponential term that saturates this growth through the control effect of the environment. The regions in the parameter space where the system displays Pareto and Boltzmann-Gibbs statistics are calculated for the cases of von Neumann and of Moore’s neighborhoods. It is found that, even when the parameters in the system are kept fixed, a transition from Pareto to Boltzmann-Gibbs behavior can occur when the number of neighbors of each agent increases. Key words: Multi-agent systems. Economic models. Pareto and Boltzmann-Gibbs distributions. PACS: : 89.75.-k, 87.23.Ge, 05.90.+m 1

A deterministic system of interacting agents is considered as a model for economic dynamics. The dynamics of the system is described by a coupled map lattice with near neighbor interactions. The evolution of each agent results from the competition between two factors: the agent’s own tendency to grow and the environmental influence that moderates this growth. Depending on the values of the parameters that control these factors, the system can display Pareto or Boltzmann-Gibbs statistical behaviors in its asymptotic dynamical regime. The regions where these behaviors appear are calculated on the space of parameters of the system. Other statistical properties, such as the mean wealth, the standard deviation, and the Gini coefficient characterizing the degree of equity in the wealth distribution are also calculated on the space of parameters of the system. Key words: Multi-agent systems. Economic models. Pareto and Boltzmann-Gibbs distributions. PACS: : 89.75.-k, 87.23.Ge, 05.90.+m

We propose a new model for transaction data that accounts jointly for the time duration between transactions and for the discreteness of the intraday stock price changes. Duration is assumed to follow a stochastic conditional duration model, while price discreteness is captured by an autoregressive moving average ordinal-response model with stochastic volatility and time-varying parameters. The proposed model also allows for endogeneity of the trade durations as well as for leverage and in-mean effects. In a purely Bayesian framework we conduct a forecasting exercise using multiple high-frequency transaction data sets and show that the proposed model produces better point and density forecasts than competing models.

This study examines trade sizes used by informed traders. The selected sample includes 73 active stocks from the Stock Exchange of Thailand (SET), a pure limit order market, that cover two distinct market conditions of a bull and bear market. Using intraday data, the study finds that large sized trades (i.e., larger than the 75 th percentile) account for a disproportionately large impact on changes in traded and quoted prices. This finding compares with the results of studies conducted on U.S. markets that show informed traders employ trade sizes falling between the 40 th and 95 th percentiles (Barclay and Warner 1993; Chakravarty 2001). Our results support the hypothesis that informed traders on a pure limit order market such as the SET, where there are no market makers, are able to use larger sized trades than those employed by informed traders on U.S. markets.

que des subventions et mandats obtenus par ses équipes de recherche. CIRANO is a private non-profit organization incorporated under the Québec Companies Act. Its infrastructure and research activities are funded through fees paid by member organizations, an infrastructure grant from the

We investigate the one-dimensional telegraph random process in the presence of an elastic boundary at the origin. This process describes a finite-velocity random motion that alternates between two possible directions of motion (positive or negative). When the particle hits the origin, it is either absorbed, with probability α, or reflected upwards, with probability 1 -α. In the case of exponentially distributed random times between consecutive changes of direction, we obtain the distribution of the renewal cycles and of the absorption time at the origin. This investigation is performed both in the case of motion starting from the origin and non-zero initial state. We also study the probability law of the process within a renewal cycle.

Microstructure effects, such as bid/ask bounce, induce short-run negative autocorrelation patterns in asset returns while longer horizons exhibit momentum effects. We study the term structure of microstructure effects using half-hour observation intervals in the post-decimalization period. The microstructure induced reversal is pronounced within 24 hours. Notably, we find significant continuation of returns at intervals that are multiples of a day and this effect lasts for over twenty trading days. Trading volume exhibits similar patterns, but does not explain the return patterns. Additionally, bid/ask spreads and order imbalances do not explain the return pattern. The return continuation at daily frequencies is more pronounced for the first and last half-hour periods. These effects are not driven by firm size, systematic risk premia, or inclusion in the S&P500 index. The pattern is also not driven by particular months of the year, days of the week, or turn-of-the-month effects. This suggests that traders may wish to time portfolio rebalancing to account for these persistent intraday patterns.