Algorithmic Trading Strategies

Algorithmic Trading - Representative Strategies

• Involves using computer programs to automatically execute trades based on predefined rules and conditions.

Trend Following

• It is assumed that security prices tend to move persistently in a given direction.
• Long positions are entered when the price trend is up.
• Short positions are entered when the price trend is down.

Moving Averages

• The moving averages are a technical analysis tool that smooths out price data by creating a constantly updated average price.

Simple Moving Average (SMA)

• It is the average price over a specified period.
• Formula: $$SMA = \frac{\sum_{i=1}^{n} P_i}{n}$$

Exponential Moving Average (EMA)

• It applies more weight to recent prices.
• Formula: $$EMA_t = (P_t \times \frac{2}{N+1}) + (EMA_{t-1} \times (1 - \frac{2}{N+1}))$$

Mean Reversion

• It is assumed that security prices tend to move toward their average value over time.
• Long positions are entered when the price is below its average value.
• Short positions are entered when the price is above its average value.

Bollinger Bands

• It is a technical analysis tool that defines upper and lower price levels based on a security's moving average and standard deviation.
• A moving average is usually a 20-day SMA.
• An upper band is at K times the standard deviation above the moving average.
• A lower band is at K times the standard deviation below the moving average.
• Upper Band Formula: $$Upper Band = MA + K \times \sigma$$
• Lower Band formula: $$Lower Band = MA - K \times \sigma$$

Arbitrage

• It exploits price differences for the same asset in different markets.
• It involves simultaneously buying and selling an asset to profit from the imbalance.
• The aim is to secure a risk-free profit.

Backtesting

• A process of testing a trading strategy on historical data.
• This is done to determine its potential profitability.

Key Steps for Backtesting

• Collect historical price data for the assets to be traded.
• Code the trading strategy based on the chosen indicators and rules.
• Assess the strategy's performance using metrics.
  • Total Return: The percentage change in the value of the investment over the entire period.
  • Total Return Formula: $$\frac{Ending Value - Beginning Value}{Beginning Value} \times 100$$
  • Annualized Return: The average annual return of the investment.
  • Annulized Return Formula: $${(\frac{Ending Value}{Beginning Value})^{\frac{1}{n}} - 1}$$
  • Sharpe Ratio: Measures risk-adjusted return.
  • Sharpe Ratio Formula: $$\frac{R_p - R_f}{\sigma_p}$$
    • $R_p$ = Portfolio Return
    • $R_f$ = Risk-free Rate
    • $\sigma_p$ = Standard Deviation of Portfolio Return
  • Maximum Drawdown: The largest peak-to-trough decline during a specific period.

Risk Management

• An important aspect of algorithmic trading to protect capital and limit potential losses.

Stop Loss

• An order placed with a broker to buy or sell a security when it reaches a certain price.
• Designed to limit an investor's loss on a position.
• A stop loss is set 1% below the purchase price for a long position.

Position Sizing

• Determining the appropriate size of each trade.
• Kelly Criterion is a formula used to determine the optimal size of a series of bets.
• Kelly Criterion Formula: $$f^* = \frac{p - (1 - p)}{b}$$
  • $f^*$ = Optimal fraction of portfolio to bet
  • $p$ = Probability of winning
  • $b$ = Fraction won per dollar bet

Portfolio Diversification

• Reducing risk by allocating investments across various financial instruments, industries, and other categories.
• The goal is to reduce risk by allocating investments across various financial instruments, industries, and other categories.
• By investing in a variety of assets, a portfolio will be less vulnerable to the risk associated with any individual asset.