The Science of Algorithmic Trading and Portfolio Management

Robert Kissell
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Robert Kissell: Robert Kissell, PhD, is President of Kissell Research Group, a global financial and economic consulting firm specializing in quantitative modeling, statistical analysis, and algorithmic trading. He is also currently an adjunct faculty member of the Gabelli School of Business at Fordham University, and has held several senior leadership positions with prominent bulge bracket Investment Banks.

in Elsevier Monographs from Elsevier, currently edited by Candice Janco

Abstract: The Science of Algorithmic Trading and Portfolio Management , with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems. This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects. Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers. Helps readers design systems to manage algorithmic risk and dark pool uncertainty. Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives.

Keywords: AIM; ARCH; Accuracy; Adaptation tactic; Adaptation tactics; Advanced trading algorithms; Aggressive; Aggressive in the money; Algorithms; Almgren &; Alpha; Alternative Trading Systems (ATS); And of course; Andre Perold; Arrival price; Asset allocation; Auto Market Making (AMM); Back-testing; Basket algorithms; Best execution; Beta exposure; Black box models; Bollerslev; Buy order; Calibrating model parameters; Chriss; Commissions; Correlation; Cost Index; Cost curves; Covariance; Cross-sectional models; Crossing networks; Dark pools; Day of Week Effect; Day of week effect; Decay function; Deciphering black box models; Delay cost; Designated Market Maker (DMM); Direct Market Access (DMM); ETF; Efficient Trading Frontier; Efficient frontier; Efficient trading frontier; Eigenvalue-eigenvector decomposition; Electronic Communication Networks (ECNs); Engel; Equity exchanges; Evaluating algorithms; Exchange traded funds; Execution cost; Execution models; Expanded implementation shortfall; Exponential weighted moving average (EWMA); Factor models; Fixed income; Flash Crash; Forecasting; Forecasting daily volumes; Forecasting monthly volumes; Fundamental models; GARCH; Grey pools; High Frequency Trading (HFT); I-Star Model; I-Star Trading Cost Model; Implementation shortfall; Index and ETF Arbitrage; Indifference curves; Information leakage; Intraday profiles; Investment objectives; Investment strategies; Kissell &; Limit order models; Linear regression; Liquidity; Liquidity risk; MI Factors; Malamut; Market Neutral Arbitrage; Market expectations; Market exposure; Market impact; Market impact cost; Market impact models; Market impact parameters; Market microstructure; Maximizing portfolio returns; Merger (Risk) Arbitrage; Micro algorithmic decisions; Multi-asset market impact; New York Stock Exchange (NYSE); Non-linear regression; Opportunity cost; Optimal portfolios; Optimal trading strategies; Optimal trading strategies Heisenberg uncertainty principle of trading; Optimization; PIM; Parameter estimation error; Passive; Passive in the money; Portfolio algorithms; Portfolio construction; Portfolio optimization; Portfolio risk; Pre-trade; Pre-trade of pre-trades; Price appreciation; Price benchmark; Principal component analysis; Real-time decision making; Real-time trading costs; Returns; Risk; Risk exposure; Risk models; Sectors; Sell orders; Short term risk models; Short-term risk model; Single stock trading; Singular value decomposition; Slippage; Smart order routers; Spreads; Statistical Arbitrage (Stat Arb); Statistical analysis; Statistical performance testing; Supplemental Liquidity Provider (SLP); Time series; Tiquidity trading; Trade schedules; Trade strategies; Trade trajectories; Trader's dilemma; Trading costs; Trading futures; Transact costs; Transaction Cost Analysis (TCA); Transaction Costs (TCA); Triangular Arbitrage; Unifying the investment and trading decisions; Volatility; Volume Weighted Average Price (VWAP); Volumes; Wayne Wagner (search for similar items in EconPapers)
Date: 2013 Originally published 2013-10-14.
Edition: 1
ISBN: 978-0-12-401689-7
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Citations: View citations in EconPapers (6)

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