Showing papers on "Electronic trading published in 2011"

Automated Trading System in an Electronic Trading Exchange

Abstract: An electronic exchange system network includes a trader site having an automated trading system capable of submitting orders and/or quotes to an exchange site. The automated trading system determines whether an order or quote should be submitted based on, for example, the current market price of an option and theoretical buy and sell prices. The theoretical buy and sell prices are derived from, among other things, the current market price of the security underlying the option. The theoretical buy and sell prices are calculated when underlying factors that contribute to the theoretical prices change. Computation times of the theoretical prices may be reduced by using precalculated values and/or using interpolation and extrapolation. Other techniques may be used in addition or in the alternative to speed automatic decision-making. In addition, a system of checks may be conducted to ensure accurate and safe automated trading. The automated trading system may be capable of automatically submitting orders in connection with the underlying security in order to hedge part of the delta risk associated with the automated option trades.

High-Frequency Trading

Abstract: High-frequency trading (HFT) has recently drawn massive public attention fuelled by the U.S. May 6, 2010 flash crash and the tremendous increases in trading volumes of HFT strategies. Indisputably, HFT is an important factor in markets that are driven by sophisticated technology on all layers of the trading value chain. However, discussions on this topic often lack sufficient and precise information. A remarkable gap between the results of academic research on HFT and its perceived impact on markets in the public, media and regulatory discussions can be observed.The research at hand aims to provide up-to-date background information on HFT. This includes definitions, drivers, strategies, academic research and current regulatory discussions. It analyzes HFT and thus contributes to the ongoing discussions by evaluating certain proposed regulatory measures, trying to offer new perspectives and deliver solution proposals.

Algorithmic Trading

Abstract: In electronic financial markets, algorithmic trading refers to the use of computer programs to automate one or more stages of the trading process: pretrade analysis (data analysis), trading signal generation (buy and sell recommendations), and trade execution. Trade execution is further divided into agency/broker execution (when a system optimizes the execution of a trade on behalf of a client) and principal/proprietary trading (where an institution trades on its own account). Each stage of this trading process can be conducted by humans, by humans and algorithms, or fully by algorithms.

Mean–Variance Optimal Adaptive Execution

Abstract: Electronic trading of equities and other securities makes heavy use of ‘arrival price’ algorithms that balance the market impact cost of rapid execution against the volatility risk of slow execution. In the standard formulation, mean–variance optimal trading strategies are static: they do not modify the execution speed in response to price motions observed during trading. We show that substantial improvement is possible by using dynamic trading strategies and that the improvement is larger for large initial positions. We develop a technique for computing optimal dynamic strategies to any desired degree of precision. The asset price process is observed on a discrete tree with an arbitrary number of levels. We introduce a novel dynamic programming technique in which the control variables are not only the shares traded at each time step but also the maximum expected cost for the remainder of the program; the value function is the variance of the remaining program. The resulting adaptive strategies a...

Intelligent stock trading system based on improved technical analysis and Echo State Network

Abstract: Stock trading system to assist decision-making is an emerging research area and has great commercial potentials. Successful trading operations should occur near the reversal points of price trends. Traditional technical analysis, which usually appears as various trading rules, does aim to look for peaks and bottoms of trends and is widely used in stock market. Unfortunately, it is not convenient to directly apply technical analysis since it depends on person's experience to select appropriate rules for individual share. In this paper, we enhance conventional technical analysis with Genetic Algorithms by learning trading rules from history for individual stock and then combine different rules together with Echo State Network to provide trading suggestions. Numerous experiments on S&P 500 components demonstrate that whether in bull or bear market, our system significantly outperforms buy-and-hold strategy. Especially in bear market where S&P 500 index declines a lot, our system still profits.

Method and Apparatus for Managing Orders in Financial Markets

Abstract: An integrated order management engine is disclosed that reduces the latency associated with managing multiple orders to buy or sell a plurality of financial instruments. Also disclosed is an integrated trading platform that provides low latency communications between various platform components. Such an integrated trading platform may include a trading strategy offload engine.

Performance of Institutional Trading Desks: An Analysis of Persistence in Trading Cost

Abstract: Using a proprietary dataset of institutional investors’ equity transactions, we document that institutional trading desks can sustain relative performance over adjacent periods. We find that trading desk skill is positively correlated with the performance of the institution’s traded portfolio, suggesting that institutions that invest resources in developing execution abilities also invest in generating superior investment ideas. Although some brokers can deliver better executions consistently over time, our analysis suggests that trading desk skill is not limited to a selection of better brokers. We conclude that the trade implementation process is economically important and can contribute to relative portfolio performance.

Lessons from the Evolution of Foreign Exchange Trading Strategies

Abstract: The adaptive markets hypothesis posits that trading strategies evolve as traders adapt their behavior to changing circumstances. This paper studies the evolution of trading strategies for a hypothetical trader who chooses portfolios from forex technical rules in major and emerging markets, the carry trade and U.S. equities. The results show that forex trading alone dramatically outperforms the S&P 500. But there is little gain to coordinating forex and equity strategies, which explains why practitioners consider these tools separately. In addition, a backtesting procedure to choose optimal portfolios does not select carry trade strategies until well into the 1990s, which helps to explain the relatively recent surge in interest in this strategy. Forex trading returns dip significantly in the 1990s but recover by the end of the decade and have greatly outperformed an equity position since 1998. Overall, trading rule returns still exist in forex markets – with substantial stability in the types of rules – though they have migrated to emerging markets to a considerable degree.

The Future of Computer Trading in Financial Markets

Abstract: The views expressed are not those of the UK Government and do not represent its policies.

Financial volatility trading using a self-organising neural-fuzzy semantic network and option straddle-based approach

Abstract: Research highlights? A straddle trading framework based on eFSM neural-fuzzy model and MACD principle. ? eFSM dynamically models and forecasts the volatility trends of the Hang Seng Index. ? MACD generates timely trading signals using projected volatility trends from eFSM. ? Straddles are bought and sold based on the MACD signals. ? Trading framework achieves significantly higher return than time deposit account. Financial volatility refers to the intensity of the fluctuations in the expected return on an investment or the pricing of a financial asset due to market uncertainties. Hence, volatility modeling and forecasting is imperative to financial market investors, as such projections allow the investors to adjust their trading strategies in anticipation of the impending financial market movements. Following this, financial volatility trading is the capitalization of the uncertainties of the financial markets to realize investment profits in times of rising, falling and side-way market conditions. In this paper, an intelligent straddle trading system (framework) that consists of a volatility projection module (VPM) and a trade decision module (TDM) is proposed for financial volatility trading via the buying and selling of option straddles to help a human trader capitalizes on the underlying uncertainties of the Hong Kong stock market. Three different measures, namely: (1) the historical volatility (HV), (2) implied volatility (IV) and (3) model-based volatility (MV) of the Hang Seng Index (HSI) are employed to quantify the implicit volatility of the Hong Kong stock market. The TDM of the proposed straddle trading system combines the respective volatility measures with the well-established moving-averages convergence/divergence (MACD) principle to recommend trading actions to a human trader dealing in HSI straddles. However, the inherent limitation of the MACD trading rule is that it generates time-delayed trading signals due to the use of moving averages, which are essentially lagging trend indicators. This drawback is intuitively addressed in the proposed straddle trading system by applying the VPM to compute future projections of the volatility measures of the HSI prior to the activation of the TDM. The VPM is realized by a self-organising neural-fuzzy semantic network named the evolving fuzzy semantic memory (eFSM) model. As compared to existing statistical and computational intelligence based modeling techniques currently employed for financial volatility modeling and forecasting, eFSM possesses several desirable attributes such as: (1) an evolvable knowledge base to continuously address the non-stationary characteristics of the Hong Kong stock market; (2) highly formalized human-like information computations; and (3) a transparent structure that can be interpreted via a set of linguistic IF-THEN semantic fuzzy rules. These qualities provide added credence to the computed HSI volatility projections. The volatility modeling and forecasting performances of the eFSM, when benchmarked to several established modeling techniques, as well as the observed trading returns of the proposed straddle trading system, are encouraging.

The $4 trillion question: what explains FX growth since the 2007 survey?

Abstract: Daily average foreign exchange market turnover reached $4 trillion in April 2010, 20% higher than in 2007. Growth owed largely to the increased trading activity of "other financial institutions", which contributed 85% of the higher turnover. Within this customer category, the growth is driven by high-frequency traders, banks trading as clients of the biggest dealers, and online trading by retail investors. Electronic trading has been instrumental to this increase, particularly algorithmic trading.

Trading at the speed of light

Abstract: Once upon a time, stock exchanges were packed with traders running, shouting, and elbowing one another on an open trading floor. Today, virtually all stock trading is done, well, virtually- through massive, globally interlinked computer systems. The rates of these transactions are now limited only by technology and, increasingly, by the speed of light. So a costly arms race has begun for telecommunications and network links that can give traders a competitive edge as small as a few tens of microseconds.

What Explains the Growth in Commodity Derivatives

Abstract: This article documents the massive increase in trading in commodity derivatives over the past decade—growth which far outstrips the growth in commodity production and the need for derivatives to hedge risk by commercial producers and users of commodities. During the past decade, many institutional portfolio managers added commodity derivatives as an asset class to their portfolios. This addition was part of a larger shift in portfolio strategy away from traditional equity investment and toward derivatives based on assets such as real estate and commodities. Institu­tional investors’ use of commodity futures to hedge against stock market risk is a relatively recent phenomenon. Trading in commodity derivatives also increased along with the rapid expansion of trading in all derivative markets. This trading was directly related to the search for higher yields in a low interest rate environment. The growth was both in organized exchanges and over-the-counter (OTC) trading, but the gross market value of OTC trading was an order of magnitude greater. This growth is important to note because a critical factor in the recent crisis was counterparty failure in OTC trading of mortgage derivatives.

System and Method for Changing Order Priority Levels in an Electronic Trading Environment

Abstract: A system and method for fee-based order priority level modification in an electronic trading environment are described. When an order reaches an exchange, a priority level of the order may be changed to a higher priority level, and the priority level of the order initially at the higher priority level may be changed to a lower priority level of the received order. In one embodiment, a trader who is gaining a higher priority level will be preferably charged a fee for having his order moved to the higher priority level, and at least a portion of that fee may be paid to a trader who is giving up his high priority level.

Price Discovery and Trade Fragmentation in a Multi - Market Environment: Evidence from the MTS System

Abstract: This paper proposes new metrics for the process of price discovery on the main electronic trading platform for euro - denominated government securities. Analyzing price data on daily transactions for 107 bonds over a period of twenty - seven months, we find a greater degree of price leadership of the dominant market when our measures (as opposed to the traditional price discovery metrics) are used. We also present unambiguous evidence that a market’s contribution to price discovery is crucially affected by the level of trading activity. The implications of these empirical findings are discussed in the light of the debate about the possible restructuring of the regulatory framework for the Treasury bond market in Europe.

The impact of trading halts on liquidity and price volatility: Evidence from the Australian Stock Exchange

Abstract: This study examines market behaviour around trading halts associated with information releases on the Australian Stock Exchange, which operates an open electronic limit order book. Using the Lee, Ready and Seguin (1994) pseudo-halt methodology, we find trading halts increase both volume and price volatility. Trading halts also increase bid-ask spreads and reduce market depth at the best-quotes in the immediate post-halt period. The results of this study imply that trading halts impair rather than improve market quality in markets that operate open electronic limit order books.

A system and method for rapidly calculating risk in an electronic trading exchange

Abstract: Latency in electronic trading is dramatically reduced by delaying trade order validation until a match or trade can potentially occur If a new order does not meet the matching criteria for an existing order in an order book, then the new order is stored in the order book without performing validation processing in a first example embodiment In a second example embodiment, the order is stored in the order book before validation has completed But if a new order meets matching criteria for an existing order stored in an order book, then order validation processing is performed for both of the matching orders Once the order validation processing is successfully completed for both of the matching orders, then the trade is executed Order validation processing includes both risk calculations and account validations, (eg, checking to ensure the party has the necessary money or collateral if a buyer or is the owner if a seller) If the order validation processing is not successfully completed for both of the matching orders, then the trade is rejected

Stealth trading: The case of the Tokyo Stock Exchange

Abstract: The stealth trading hypothesis asserts that informed traders trade strategically by breaking up their orders so as to more easily hide among the liquidity traders. Using data for the Tokyo Stock Exchange (TSE), a pure order-driven market, we find evidence that price changes are driven by small- and medium-size trades, with small trades making the greatest contribution to price change relative to their contribution to trading volume. We also find that large trades explain a greater portion of the cumulative price change on high volatility days. Hence, our results support the stealth trading hypothesis for the TSE.

Studies of Interaction Between Human Traders and Algorithmic Trading Systems

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The effect of cross-listing on trading volume: reducing segmentation versus signaling investor protection

Abstract: We examine the relation between cross-listing on the U.S. and UK regulated and unregulated exchanges and trading volume for a sample of 500 foreign firms from 34 countries. We find that the increase in trading volume is a function of both reducing segmentation and signaling investor protection. In addition, we find that home market trading volume, firm size, firm returns, and analyst forecast accuracy are the major determinants of a firm's trading volume. We also show that U.S. and UK investors trade foreign securities that originate from low-investor-protection countries more than they trade those from high-investor-protection countries, which is consistent with the bonding hypothesis.

Distinguishing manipulated stocks via trading network analysis

Abstract: Manipulation is an important issue for both developed and emerging stock markets. For the study of manipulation, it is critical to analyze investor behavior in the stock market. In this paper, an analysis of the full transaction records of over a hundred stocks in a one-year period is conducted. For each stock, a trading network is constructed to characterize the relations among its investors. In trading networks, nodes represent investors and a directed link connects a stock seller to a buyer with the total trade size as the weight of the link, and the node strength is the sum of all edge weights of a node. For all these trading networks, we find that the node degree and node strength both have tails following a power-law distribution. Compared with non-manipulated stocks, manipulated stocks have a high lower bound of the power-law tail, a high average degree of the trading network and a low correlation between the price return and the seller–buyer ratio. These findings may help us to detect manipulated stocks.

Do Short Sellers Trade on Private Information or False Information

Abstract: We investigate whether short sellers contribute towards informational efficiency of market prices by trading on their private information or destabilize market prices by trading on rumors and false information. We do so by projecting a firm's short-selling activities on contemporaneous trading activities of its insiders - our proxy for the potential availability of private information. We find that short-selling activities are considerably informative about future stock returns when there is a higher likelihood of private information in stocks. Short-sellers also bring considerable additional information to the market, especially for smaller stocks, that is not fully captured by contemporaneous insider trading. Overall, these results suggest that on average short sellers bring informational efficiency to the market rather than destabilize them.

Is a stock exchange a computer solution? Explicitness, algorithms and the Arizona Stock Exchange

Abstract: The paper examines, through a case study on the Arizona Stock Exchange, how computerization challenged the definition of the stock exchange in the context of North-American financial markets in the 1990's. It analyses exchange automation in terms of trials of explicitness: the computational formulation of what an exchange is calls for a detailed explication of the (variable, often conflicting and unanticipated) processes and properties of price formation. The paper focuses in particular on the argument of the concentration of liquidity in one single point, which was central to the development of the Arizona Stock Exchange (an electronic call auction). It then asks what kind of revolution is the ‘explicitness revolution' in the design of allocation mechanisms.

System and Method for Randomizing Orders in an Electronic Trading Environment

Abstract: When a trading application on a client terminal receives a trade order, a randomizer application may automatically randomize one or more order parameters to generate a randomized order. For example, an order quantity, a price level, and/or a time period between sending any two consecutive orders may be randomized. The randomized order is then automatically placed on the market.

When a Halt is Not a Halt: An Analysis of Off-NYSE Trading During NYSE Market Closures

Abstract: Though trading halts are a common feature in securities markets, the issues associated with the coordination of these halts across markets are not well understood. In fact, regulations often allow traders to circumvent trading halts through the use of alternative venues. Using a sample of order imbalance delayed openings on the NYSE, we examine the costs and benefits of continued trading on alternative venues when the main market calls a halt. We find that trades routed to off-NYSE venues during NYSE halts are associated with significant price discovery and lead to an improved post-halt trading environment. In addition, limit orders routed through ECNs reflect price relevant information even prior to the halt, with limit book imbalances decreasing and depth filling in during the halt around the eventual reopening NYSE price. However, these informational benefits come at a substantial cost, as both execution costs and volatility are extremely high on off-NYSE venues during NYSE halts.

Trading order validation system and method and high-performance trading data interface

Abstract: A post-trade monitor receives feedback from an exchange server and validates orders placed with the exchange server after the orders have been placed. If a recently placed order violates a rule or regulation, the monitor instructs the trading platform to change to a more restrictive trading mode. A library provides an interface between a client application program that generates proposed orders and an exchange server. The library provides pre-trade validation of the orders and sends only validated orders to the exchange server. A low- latency interface between a customer server, such as a server that employs algorithmic trading methods to generate buy and sell orders, and a brokerage server that validates such securities trading orders is optimized for handling the securities trading orders. The interface receives order acknowledgement messages and the like from the brokerage server and invokes callback routines in the customer trading application program to report status information.

System and Method for Creating Trade-Related Annotations in an Electronic Trading Environment

Abstract: A client terminal displays a trading screen interface and an annotation interface in relation to the trading screen interface. The annotation interface allows a trader to enter trade-related annotations in a quick and efficient manner or flag a predetermined time and input annotations to be associated with the flagged time a later time, while the trading screen interface allows the trader to make trades at the most favorable prices and in a speedy manner. The annotation interface may alternatively not be displayed and allow for audio input.