Systematic trading

Last updated June 20, 2023

Systematic trading (also known as mechanical trading) is a way of defining trade goals, risk controls and rules that can make investment and trading decisions in a methodical way.^[1]

Systematic trading includes both manual trading of systems, and full or partial automation using computers. Although technical systematic systems are more common, there are also systems using fundamental data such as those in equity long:short hedge funds and GTAA funds. Systematic trading includes both high frequency trading (HFT, sometimes called algorithmic trading) and slower types of investment such as systematic trend following. It also includes passive index tracking.

The opposite of systematic trading is discretionary trading. The disadvantage of discretionary trading is that it may be influenced by emotions, isn't easily back tested, and has less rigorous risk control.^[2]

Systematic trading is related to quantitative trading. Quantitative trading includes all trading that use quantitative techniques; most quantitative trading involves using techniques to value market assets like derivatives but the trading decision may be systematic or discretionary.

History

Systematic trading began with the growth of computers in the 1970s. The Designated Order Turnaround (DOT) system used by the New York Stock Exchange to electronically route orders.

In the 1990s, various trading strategies were developed by major banks, including statistical arbitrage, trend following and mean reversion. High-frequency trading strategies that combined computing power, speed, and large databases were gaining more popularity due to their success rates.^[3]

After 2000, millions of trades were executed by the largest hedge funds in mere seconds with their black box systems.^[3]

Approach

Suppose we need to replicate an index with futures and stocks from other markets with higher liquidity levels. An example of a systematic approach would be:

Identify, using fundamental analysis, which stocks and futures should be used for replication.
Analyze correlations between the targeted index and selected stocks and futures, looking for the strategy which provides a better approximation to index.
Define a coherent strategy to combine dynamically stocks and futures according to market data.
Simulate the strategy including transaction costs, rollovers, stop-loss orders, and all other wanted risk controls.
Apply the strategy in the real world using algorithmic trading for signal generation and trying to optimize the P&L, controlling continuously the risks.

Risk management

Systematic trading associates with a number of risks, the returns can be very volatile and funds can quickly amass substantial trading losses without proper risk management.^[4] Therefore, systematic trading should take into account the importance of risk management, using a systematic approach to quantify risk, consistent limits and techniques to define how to close excessively risky positions.

Systematic trading, in fact, lends itself to control risk precisely because it allows money managers to define profit targets, loss points, trade size, and system shutdown points objectively and in advance of entering each trade.^[5]

By holding a diversified portfolio of individual systematic trading funds, the high level of volatility and manager-specific model risk can be mitigated.^[4]

Systematic Traders

Perry J. Kaufman, American systematic trader, index developer, and quantitative financial theorist.^[6]

Related Research Articles

Passive management is an investing strategy that tracks a market-weighted index or portfolio. Passive management is most common on the equity market, where index funds track a stock market index, but it is becoming more common in other investment types, including bonds, commodities and hedge funds.

Day trading is a form of speculation in securities in which a trader buys and sells a financial instrument within the same trading day, so that all positions are closed before the market closes for the trading day to avoid unmanageable risks and negative price gaps between one day's close and the next day's price at the open. Traders who trade in this capacity are generally classified as speculators. Day trading contrasts with the long-term trades underlying buy-and-hold and value investing strategies. Day trading may require fast trade execution, sometimes as fast as milli-seconds in scalping, therefore direct-access day trading software is often needed.

<span class="mw-page-title-main">Hedge (finance)</span> Concept in investing

A hedge is an investment position intended to offset potential losses or gains that may be incurred by a companion investment. A hedge can be constructed from many types of financial instruments, including stocks, exchange-traded funds, insurance, forward contracts, swaps, options, gambles, many types of over-the-counter and derivative products, and futures contracts.

In finance, statistical arbitrage is a class of short-term financial trading strategies that employ mean reversion models involving broadly diversified portfolios of securities held for short periods of time. These strategies are supported by substantial mathematical, computational, and trading platforms.

Long/short equity is an investment strategy generally associated with hedge funds. It involves buying equities that are expected to increase in value and selling short equities that are expected to decrease in value. This is different from the risk reversal strategies where investors will simultaneously buy a call option and sell a put option to simulate being long in a stock.

Financial risk management is the practice of protecting economic value in a firm by managing exposure to financial risk - principally operational risk, credit risk and market risk, with more specific variants as listed aside. As for risk management more generally, financial risk management requires identifying its sources, measuring it, and the plans to address them. See Finance § Risk management for an overview.

Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. This type of trading attempts to leverage the speed and computational resources of computers relative to human traders. In the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders. A study in 2019 showed that around 92% of trading in the Forex market was performed by trading algorithms rather than humans.

A pairs trade or pair trading is a market neutral trading strategy enabling traders to profit from virtually any market conditions: uptrend, downtrend, or sideways movement. This strategy is categorized as a statistical arbitrage and convergence trading strategy. Pair trading was pioneered by Gerry Bamberger and later led by Nunzio Tartaglia's quantitative group at Morgan Stanley in the 1980s.

Global macro is an investment strategy based on the interpretation and prediction of large-scale events related to national economies, history, and international relations. The strategy typically employs forecasts and analysis of interest rate trends, international trade and payments, political changes, government policies, inter-government relations, and other broad systemic factors.

The following outline is provided as an overview of and topical guide to finance:

Tactical asset allocation (TAA) is a dynamic investment strategy that actively adjusts a portfolio's asset allocation. The goal of a TAA strategy is to improve the risk-adjusted returns of passive management investing.

Alternative beta is the concept of managing volatile "alternative investments", often through the use of hedge funds. Alternative beta is often also referred to as "alternative risk premia".

In finance, a stock market index future is a cash-settled futures contract on the value of a particular stock market index. The turnover for the global market in exchange-traded equity index futures is notionally valued, for 2008, by the Bank for International Settlements at US$130 trillion.

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Portfolio insurance is a hedging strategy developed to limit the losses an investor might face from a declining index of stocks without having to sell the stocks themselves. The technique was pioneered by Hayne Leland and Mark Rubinstein in 1976. Since its inception, the portfolio insurance strategy has been dubiously marketed as a product. However, this is a misnomer as it is not a policy and there is no insurer of last resort.

High-frequency trading (HFT) is a type of algorithmic financial trading characterized by high speeds, high turnover rates, and high order-to-trade ratios that leverages high-frequency financial data and electronic trading tools. While there is no single definition of HFT, among its key attributes are highly sophisticated algorithms, co-location, and very short-term investment horizons. HFT can be viewed as a primary form of algorithmic trading in finance. Specifically, it is the use of sophisticated technological tools and computer algorithms to rapidly trade securities. HFT uses proprietary trading strategies carried out by computers to move in and out of positions in seconds or fractions of a second.

A quantitative fund is an investment fund that uses quantitative investment management instead of fundamental human analysis.

Perry J. Kaufman is an American systematic trader, rocket scientist, index developer, and quantitative financial theorist. He is considered a leading expert in the development of fully algorithmic trading programs.

A managed futures account (MFA) or managed futures fund (MFF) is a type of alternative investment in the US in which trading in the futures markets is managed by another person or entity, rather than the fund's owner. Managed futures accounts include, but are not limited to, commodity pools. These funds are operated by commodity trading advisors (CTAs) or commodity pool operators (CPOs), who are generally regulated in the United States by the Commodity Futures Trading Commission and the National Futures Association. As of June 2016, the assets under management held by managed futures accounts totaled $340 billion.

Michael Dever is an American businessman, futures trader, entrepreneur, and author. Dever is the founder and CEO of Brandywine Asset Management, Inc., an investment management firm founded in 1982, and he is the author of the best-selling investment book "Jackass Investing: Don't do it. Profit from it."

References

↑ Carver, Robert (2015). Systematic Trading. UK: Harriman House. p. 10. ISBN 9780857194459.
↑ "Systematic Trading: Benefits and Risks : Tradestation Strategies : Adaptrade Software". www.adaptrade.com.
1 2 "History Of Systematic Trading". SeekingAlpha. 20 March 2013.
1 2 "Systematic Trading". thehedgefundjournal.com.
↑ "Managed Futures Today, Systematic Trading, Systematic Risk Control".
↑ "Archived copy" (PDF). Archived from the original (PDF) on March 12, 2013. Retrieved November 14, 2015.{{cite web}}: CS1 maint: archived copy as title (link)