Trading strategy

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In finance, a trading strategy is a fixed plan that is designed to achieve a profitable return by going long or short in markets.

Contents

The difference between short trading and long-term investing is in the opposite approach and principles. Going short trading would mean to research and pick stocks for future fast trading activity on one's accounts with a rather speculative attitude. [1] [2] While going into long-term investing would mean contrasting activity to short one. Low turnover, principles of time-tested investment approaches, returns with risk-adjusted actions, and diversification are the key features of investing in a long-term manner. [3]

For every trading strategy one needs to define assets to trade, entry/exit points and money management rules. Bad money management can make a potentially profitable strategy unprofitable. [4]

Trading strategies are based on fundamental or technical analysis, or both. They are usually verified by backtesting, where the process should follow the scientific method, and by forward testing (a.k.a. 'paper trading') where they are tested in a simulated trading environment. [5]

Types of trading strategies

The term trading strategy can in brief be used by any fixed plan of trading a financial instrument, but the general use of the term is within computer assisted trading, where a trading strategy is implemented as computer program for automated trading.

Technical strategies can be broadly divided into the mean-reversion and momentum groups. [6]

All these trading strategies are basically speculative. In the moral context speculative activities are considered negatively and to be avoided by each individual. [8] [9] Who conversely should maintain a long-term horizon avoiding any types of short term speculation. [2]

Development

The trading strategy is developed by the following methods:

The development and application of a trading strategy preferably follows eight steps: [10] (1) Formulation, (2) Specification in computer-testable form, (3) Preliminary testing, (4) Optimization, (5) Evaluation of performance and robustness, [11] (6) Trading of the strategy, (7) Monitoring of trading performance, (8) Refinement and evolution.

Performance measurement

Usually the performance of a trading strategy is measured on the risk-adjusted basis. Probably the best-known risk-adjusted performance measure is the Sharpe ratio. However, in practice one usually compares the expected return against the volatility of returns or the maximum drawdown. Normally, higher expected return implies higher volatility and drawdown. The choice of the risk-reward trade-off strongly depends on trader's risk preferences. Often the performance is measured against a benchmark, the most common one is an Exchange-traded fund on a stock index. In the long term a strategy that acts according to Kelly criterion beats any other strategy. However, Kelly's approach was heavily criticized by Paul Samuelson. [12]

Executing strategies

A trading strategy can be executed by a trader (Discretionary Trading) or automated (Automated Trading). Discretionary Trading requires a great deal of skill and discipline. It is tempting for the trader to deviate from the strategy, which usually reduces its performance.

An automated trading strategy wraps trading formulas into automated order and execution systems. Advanced computer modeling techniques, combined with electronic access to world market data and information, enable traders using a trading strategy to have a unique market vantage point. A trading strategy can automate all or part of your investment portfolio. Computer trading models can be adjusted for either conservative while the price variation is favorable or aggressive trading styles e.g. Scalping is considered a form of trading in financial markets with a very short-term approach that is why it is associated with aggressive style. [13] [14]

Trading activity boost and development is connected with the era of internet inception. First online related trading activity and rapid growth of electronic commerce started in 1997–98. [15]

See also

Related Research Articles

In finance, technical analysis is an analysis methodology for analysing and forecasting the direction of prices through the study of past market data, primarily price and volume. As a type of active management, it stands in contradiction to much of modern portfolio theory. The efficacy of technical analysis is disputed by the efficient-market hypothesis, which states that stock market prices are essentially unpredictable, and research on whether technical analysis offers any benefit has produced mixed results. It is distinguished from fundamental analysis, which considers a company's financial statements, health, and the overall state of the market and economy.

<span class="mw-page-title-main">Day trading</span> Buying and selling financial instruments within the same trading day

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.

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.

<span class="mw-page-title-main">Volatility smile</span> Implied volatility patterns that arise in pricing financial options

Volatility smiles are implied volatility patterns that arise in pricing financial options. It is a parameter that is needed to be modified for the Black–Scholes formula to fit market prices. In particular for a given expiration, options whose strike price differs substantially from the underlying asset's price command higher prices than what is suggested by standard option pricing models. These options are said to be either deep in-the-money or out-of-the-money.

<span class="mw-page-title-main">Bollinger Bands</span> Statistical price volatility chart

Bollinger Bands are a type of statistical chart characterizing the prices and volatility over time of a financial instrument or commodity, using a formulaic method propounded by John Bollinger in the 1980s. Financial traders employ these charts as a methodical tool to inform trading decisions, control automated trading systems, or as a component of technical analysis. Bollinger Bands display a graphical band and volatility in one two-dimensional chart.

In finance, an investment strategy is a set of rules, behaviors or procedures, designed to guide an investor's selection of an investment portfolio. Individuals have different profit objectives, and their individual skills make different tactics and strategies appropriate. Some choices involve a tradeoff between risk and return. Most investors fall somewhere in between, accepting some risk for the expectation of higher returns.

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.

<span class="mw-page-title-main">Pairs trade</span> Trading strategy

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.

<span class="mw-page-title-main">Stock trader</span> Person or company involved in trading equity securities

A stock trader or equity trader or share trader, also called a stock investor, is a person or company involved in trading equity securities and attempting to profit from the purchase and sale of those securities. Stock traders may be an investor, agent, hedger, arbitrageur, speculator, or stockbroker. Such equity trading in large publicly traded companies may be through a stock exchange. Stock shares in smaller public companies may be bought and sold in over-the-counter (OTC) markets or in some instances in equity crowdfunding platforms.

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

Trend following or trend trading is a trading strategy according to which one should buy an asset when its price trend goes up, and sell when its trend goes down, expecting price movements to continue.

In finance, an option is a contract which conveys to its owner, the holder, the right, but not the obligation, to buy or sell a specific quantity of an underlying asset or instrument at a specified strike price on or before a specified date, depending on the style of the option.

An automated trading system (ATS), a subset of algorithmic trading, uses a computer program to create buy and sell orders and automatically submits the orders to a market center or exchange. The computer program will automatically generate orders based on predefined set of rules using a trading strategy which is based on technical analysis, advanced statistical and mathematical computations or input from other electronic sources.

High-frequency trading (HFT) is a type of algorithmic trading in finance 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 in trading securities. HFT uses proprietary trading strategies carried out by computers to move in and out of positions in seconds or fractions of a second.

Forex autotrading is a slang term for algorithmic trading on the foreign exchange market, wherein trades are executed by a computer system based on a trading strategy implemented as a program run by the computer system.

A forex signal is a suggestion for entering a trade on a currency pair, usually at a specific price and time. The signal is generated either by a human analyst or an automated forex robot supplied to a subscriber of the forex signal service. Due to the timely nature of signals, they are usually communicated via email, website, SMS, RSS, tweet or other relatively immediate method. In many jurisdictions signal services need to be registered with the authorities.

Social trading is a form of investing that allows investors to observe the trading behavior of their peers and expert traders. The primary objective is to follow their investment strategies using copy trading or mirror trading. Social trading requires little or no knowledge about financial markets.

<span class="mw-page-title-main">Brandywine Asset Management</span>

Brandywine Asset Management, Inc. is an American investment management firm founded and managed by Michael Dever. The firm is registered as a commodity trading advisor.

The S&P/ASX200 VIX (A-VIX), is a financial market product, which is traded based on the implied volatility in the underlying Australian equity index.

References

  1. 1 2 "Yale Champions Social Investing (Whatever That Is)". Bloomberg.com. 2018-10-19. Retrieved 2023-12-02.
  2. 1 2 3 4 Hill, John (2020). Environmental, social, and governance (ESG) investing: a balanced analysis of the theory and practice of a sustainable portfolio. London: Academic Press, an imprint of Elsevier. ISBN   978-0-12-818693-0.
  3. ↑ Proctor, Clint. "Trading and investing are two approaches to playing the stock market that bring their own benefits and risks". Business Insider. Retrieved 2023-12-02.
  4. ↑ Nekrasov, V. Knowledge rather than Hope: A Book for Retail Investors and Mathematical Finance Students. 2014, pages 24-26. ISBN   978-3000465208
  5. ↑ "Day Trading Strategies: 4 Timeless Approach". DayTradeTheWorld. 8 November 2021.
  6. ↑ "Master One Strategy Before Learning Others". www.thebalance.com.
  7. ↑ Low, R.K.Y.; Tan, E. (2016). "The Role of Analysts' Forecasts in the Momentum Effect" (PDF). International Review of Financial Analysis. 48: 67–84. doi:10.1016/j.irfa.2016.09.007.
  8. ↑ Ryan, John A (1902). "The Ethics of Speculation". International Journal of Ethics. 12 (3): 335–347. doi:10.1086/intejethi.12.3.2376347. JSTOR   2376347. S2CID   143227107.
  9. ↑ "CATHOLIC ENCYCLOPEDIA: Speculation". www.newadvent.org.
  10. ↑ Pardo, R. The Evaluation and Optimization of Trading Strategies. J. Wiley & Sons, 2008, page 18. ISBN   978-0-470-12801-5
  11. ↑ "R&D BLOG - Oxfordstrat". Oxfordstrat.
  12. ↑ Samuelson, P. (1971). The "fallacy" of maximizing the geometric mean in long sequences of investing or gambling. Proceedings of the National Academy of Sciences, 68(10):2493–2496
  13. ↑ "Passive Order. Definition and Meaning". capital.com. Retrieved 2023-05-21.
  14. ↑ "What is Scalping". capital.com. Retrieved 2023-05-21.
  15. ↑ Wu, Jennifer; Siegel, Michael; Manion, Joshua (June 1999). "Online Trading: An Internet Revolution" (PDF). Sloan School of Management. Massachusetts Institute of Technology.


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