Strategy Articles - Automated Trader

‘Strategies’ Algorithmic Trading Articles & Financial Insight

An in depth examination of a technology or technique used in automated or algorithmic trading written by an industry practitioner.

  • Models for daily and intra-day volume prediction

    A practical approach to building an intuitive model for intra-session and all-day traded volumes. Multiple factors are combined in a straight-forward manner to give robust and usable results.

  • Simple Binary Encoding for high performance market data interfaces

    SUBSCRIBERS ONLYThe FIX Trading Community realised that its message encoding was no longer fit-for-purpose for high-performance trading. It came up with the Simple Binary Encoding (SBE) standard to balance the needs of latency versus bandwidth utilisation. We look at how the market data interfaces at the CME Group were implemented with SBE.

  • Measuring the absolute accuracy of 10GbE packet timestampingMeasuring the absolute accuracy of 10GbE packet timestamping

    Precise Ethernet timestamps are key to knowing exactly when a network event occurred. Metamako designed and implemented a rigorous test methodology to measure the absolute accuracy of a 10 Gigabit Ethernet packet capture and timestamping solution, confirming the importance of using accurate timestamps

  • Hide-and-seek in the limit order book

    Despite some disadvantages, hidden orders have become increasingly popular on the US stock exchanges. Archana and Chinmay Jain explore this hidden liquidity. Data from 2012-2015 shows that smaller stocks, more volatile stocks and less liquid stocks have higher levels of hidden liquidity.​

  • MiFID 2 double volume caps - the end of dark trading?MiFID 2 double volume caps - the end of dark trading?

    SUBSCRIBERS ONLYA controversial rule in MiFID 2 is the double volume cap mechanism for dark pools. Recently, a quantitative study presented dramatic numbers on the percentage of stocks that would be suspended under the regime. We investigate if the efficient use of large-in-scale trading can help to mitigate the caps.

  • How to align broker and customer interests and make exchanges  more competitiveHow to align broker and customer interests and make exchanges more competitive

    US regulators are focused on conflicts of interest caused by maker-taker rebates. Is there a way to align broker and customer interests and still incentivise liquidity provision?

  • Deploying PTP: Observations from the fieldDeploying PTP: Observations from the field

    SUBSCRIBERS ONLYPTP is increasingly popular for accurate time stamping and clock synchronisation across a network. When implementing PTP, problems can be hard to spot and even harder to diagnose. We look at some common - and some not so common - issues.

  • How much is your zero collar worth?

    Hint: It's not zero. A widespread shortcut used in swaption pricing led to an opportunity for dealers to engage in model arbitrage and to buy cheap convexity.

  • The difficulty of identifying multi-broker spoofing

    REGISTERED VIEWERSTrading through multiple brokers has been used by spoofers to help avoid detection. New regulations for cash equity markets in the EU and US are designed to curtail the practice.

  • Regime changes in automated trading

    SUBSCRIBERS ONLYThe term structure of interest rates provides many opportunities for systematic traders. The level, slope, curvature and volatility of interest rate markets are all heavily regime-dependent. Early identification of changes in regime is key for developing successful trading strategies.

  • The relationship between trading frequency and achievable alpha

    REGISTERED VIEWERSSome of the most successful investors have long holding periods and investors are often advised to "buy and hold". We investigate how the average holding period of an optimal trading strategy relates to the alpha it can generate. Is longer really better?

  • A novel and quantitative perspective of the SEC

    SUBSCRIBERS ONLYQuantitative analysis of speeches by the Securities and Exchange Commission (SEC) to categorize topics shows that regulators focus too often on issues of disclosure and transparency rather than on issues of market architecture and design.

  • Fetching market data into Excel using Python

    Microsoft Excel is the 'go-to' solution for data manipulation and analysis in finance. However, it lags behind the reality of how data, particularly financial or trading data, is consumed in the age of the Internet. Here is a simple, yet powerful way to enable Excel to work with a wide variety of financial databases and sources.

  • The future of dark liquidity in Europe

    The dark trading landscape faces fundamental change once again. The changes in MiFID 2/MiFIR, including dark volume caps, will profoundly affect most dark trading activity, fundamentally altering how institutional investors interact with hidden liquidity.

  • Automated trading in India

    SUBSCRIBERS ONLYIndia's securities market regulator, the Securities Exchange Board of India (SEBI), has released a discussion paper on proposed regulation in the algorithmic trading/high frequency trading space.

  • What I've learned building low latency systems

    SUBSCRIBERS ONLYSoftware development for low latency trading tends to be shrouded in mystery. Development practices are often wrapped in layers of computational alchemy that tend to be impenetrable to outsiders. The industry rarely gives insights, even though it borrows heavily from other sectors to drive its own progress.

  • Trading realized variance using listed vanillas

    SUBSCRIBERS ONLYListed futures on VIX and its cousins give exposure to implied variance. But getting exposure to realised variance is very different and usually has been the realm of OTC variance swaps. Here we examine strategies to trade the realised variance using only listed instruments, with simple time-independent formulas not requiring models such as Black-Scholes.

  • Reducing the lag of exponential moving averages

    SUBSCRIBERS ONLYMoving average-based filtering techniques bring much needed smoothing to noisy time series. But they do so at the unavoidable cost of an introduced lag. There are a number of ways of trying to mitigate this. One approach, aptly called 'twicing', is to simply add the lag itself back into the equation

  • Hacking Korea: The accidental HFT firm

    SUBSCRIBERS ONLYNecessity is the mother of invention. This is true in all areas of life, including the domain of high frequency trading. Discover how some impressive hardware and software engineering over the years led to capturing significant market share in KOSPI options.

  • AFM study finds no evidence of ghost liquidity and liquidity detection strategies

    SUBSCRIBERS ONLYJun 03rd, 2016 - The Netherlands Authority for the Financial Markets' (AFM) has published the results of its investigation into two key arguments against high-frequency trading.

  • Backtest overfitting in financial markets

    Systematic traders are cursed by the tendency of strategies - and indeed even simple estimators - to overfit historical data. A group of university researchers provide an online tool to estimate the propensity to overfit, even for very parsimonious strategies.

  • Option gamma: identifying levels of pain

    SUBSCRIBERS ONLYThe increasing popularity of shorter expiry S&P 500 options has the potential to significantly impact the underlying market. Analyzing the hedging pressure of market makers can help to identify critical points.

  • To spoof, or not to spoof, that is the question

    SUBSCRIBERS ONLYSpoofers place orders with no intention to trade. They are accused of distorting the market. But if order books in mature markets do not contain information, why ban spoofing?

  • Liquidity and quote fading

    SUBSCRIBERS ONLYCommentators on electronic markets claim that liquidity can 'disappear in an instant'. Quotes, they say, tend to fade as soon as the market notices that there is a seller around. By Remco Lenterman

  • Confidence intervals for the Kelly criterion

    SUBSCRIBERS ONLYTrade-sizing under constant probabilities and fixed payoffs is straight-forward. But having varying probabilities and payoffs introduces uncertainty into how much to bet and therefore requires additional inputs.

  • Machine Learning + Regime Switching = Profitability?Machine Learning + Regime Switching = Profitability?

    QUALIFIED REGISTRANTS & SUBSCRIBERSThe concept of regimes – such as bull and bear markets – is elemental to financial markets. The desire to predict regime switches, commonly known as turning points, is similarly elemental. Ernest Chan, CEO of E. P. Chan & Associates, examines a possible technique for this most demanding of tasks.

  • Transition Management: Best Execution through Algorithmic TradingTransition Management: Best Execution through Algorithmic Trading

    QUALIFIED REGISTRANTS & SUBSCRIBERSThe ability to restructure investment portfolios with minimal cost, risk or information leakage is a critical skill in today’s competitive fund management industry. Joseph Sidibe, Vice President, Execution Sales Desk, EMEA, Merrill Lynch, explains how use of algorithmic trading techniques can help ensure best execution in transaction management.

  • Adapting Algorithms to Realities of Asian MarketsAdapting Algorithms to Realities of Asian Markets

    REGISTERED VIEWERSIf execution algorithms are to be adopted widely in the Asian markets, both providers and users must be aware of the unique characteristics of trading in the region, says Dr Usman Malik of P. E. Lynch LLP.

  • The Role of Advanced Models in Performance BoostingThe Role of Advanced Models in Performance Boosting

    REGISTERED VIEWERSIn the second part of a two-part article, David Aronson, President of Hood River Research, examines the modelling techniques used in arriving at a valuable predictor set for boosting ‘raw’ trading model performance.

  • Using Trading Dynamics to Boost Strategy PerformanceUsing Trading Dynamics to Boost Strategy Performance

    REGISTERED VIEWERSIn the first part of a two-part article, David Aronson, President of Hood River Research, introduces the concept of performance boosting strategies and explains the selection process for their predictor inputs.

  • Backtesting: Best practice principles for beating the marketBacktesting: Best practice principles for beating the market

    REGISTERED VIEWERSIn an increasingly crowded market, traders need comprehensive, integrated backtesting capabilities to ensure their algorithms stay ahead of the competition. Jorin Daleanes, Sales and Account Manager, RTD Tango and Backtester, and Steffen Gemuenden, Co CEO, RTS Realtime Systems Group, lay out the key principles.

  • Using Order Book Data to Improve Automated Model PerformanceUsing Order Book Data to Improve Automated Model Performance

    REGISTERED VIEWERSAutomated traders now have access to unprecedented levels of market data. Thom Hartle, Director of Marketing, CQG, conducts a theoretical comparison between two trading systems to explore how order book data can be leveraged for optimal trade performance.

  • High frequency data analysisHigh frequency data analysis

    FREE ARTICLEAs the requirements for storing, manipulating and deriving intelligence from ever larger data sets continue to expand, techniques and technology have to keep pace. Brian Sentance, CEO of Xenomorph, outlines some of the prerequisites.

  • Strategies: Waiting for the IcebergStrategies: Waiting for the Iceberg

    FREE ARTICLEAlgorithmic trading has radically changed trading patterns in capital markets. Transaction volumes have increased and in the equities markets in particular, individual transaction sizes have plummeted. Debbie Williams, Group Vice President of the Capital Markets and Risk Management Practices at Financial Insights examines the implications of this for risk management and how market participants are (or aren’t) responding to the challenge.

  • Strategies: Building a Better Bear TrapStrategies: Building a Better Bear Trap

    FREE ARTICLEOne of the most critical elements in algorithmic trading lies in accurately modelling trading costs, yet this still remains a rather inexact science. While certain cost elements are relatively stable and/or easy to predict, others are not. As a result, models for estimating trading costs have tended to be reasonably predictive when viewed across a very large sample of trades, but decidedly indifferent performers on individual ones. This has in turn made the task of minimising these costs through the selection, tuning and scheduling of appropriate execution algorithms difficult. Dan diBartolomeo, president of Northfield Information Services, discusses the current limitations and suggests some additional elements that can be used to improve forecasting of trading costs and trade scheduling.

  • Strategies: Optimisation Algorithms for Automated TradingStrategies: Optimisation Algorithms for Automated Trading

    FREE ARTICLEAutomation opens up the possibility of trading multiple models or the same/similar model with multiple parameter sets. However, that raises the question of how best to optimise those parameter sets. Chris Donnan, who works in equity derivatives trading technology at a top Wall Street firm, answers it.

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