backtestEngine
Create backtestEngine object to backtest strategies and
analyze results
Description
Create a backtestEngine to run a backtest of portfolio
investment strategies on historical data.
Use this workflow to develop and run a backtest:
Define the strategy logic using a
backtestStrategyobject to specify how a strategy rebalances a portfolio of assets.Use
backtestEngineto create abacktestEngineobject that specifies parameters of the backtest.Use
runBacktestto run the backtest against historical asset price data and, optionally, trading signal data.Use
summaryto summarize the backtest results in a table format.
For more detailed information on this workflow, see Backtest Investment Strategies.
Creation
Description
backtester = backtestEngine(strategies)backtestEngine object. Use the
backtestEngine object to backtest the portfolio
trading strategies defined in the backtestStrategy objects.
backtester = backtestEngine(___,Name,Value)backtester =
backtestEngine(strategies,'RiskFreeRate',0.02/252,'InitialPortfolioValue',1000).
Input Arguments
Properties
Object Functions
runBacktest | Run backtest on one or more strategies |
summary | Generate summary table of backtest results |
Examples
Backtest Strategy Using backtestEngine
Use a backtesting engine in MATLAB® to run a backtest on an investment strategy over a time series of market data. You can define a backtesting engine by using backtestEngine object. A backtestEngine object sets properties of the backtesting environment, such as the risk-free rate, and holds the results of the backtest. In this example, you can create a backtesting engine to run a simple backtest and examine the results.
Create Strategy
Define an investment strategy by using the backtestStrategy function. This example builds a simple equal-weighted investment strategy that invests equally across all assets. For more information on creating backtest strategies, see backtestStrategy.
% The rebalance function is simple enough that you can use an anonymous function equalWeightRebalanceFcn = @(current_weights,~) ones(size(current_weights)) / numel(current_weights); % Create the strategy strategy = backtestStrategy("EqualWeighted",equalWeightRebalanceFcn,... 'RebalanceFrequency',20,... 'TransactionCosts',[0.0025 0.005],... 'LookbackWindow',0)
strategy =
backtestStrategy with properties:
Name: "EqualWeighted"
RebalanceFcn: [function_handle]
RebalanceFrequency: 20
TransactionCosts: [0.0025 0.0050]
LookbackWindow: 0
InitialWeights: [1x0 double]
Set Backtesting Engine Properties
The backtesting engine has several properties that you set by using parameters to the backtestEngine function.
Risk-Free Rate
The RiskFreeRate property holds the interest rate earned for uninvested capital (that is, cash). When the sum of portfolio weights is below 1, the remaining capital is invested in cash and earns the risk-free rate. The risk-free rate is defined as the "per-time-step" rate, meaning that it is the interest rate that cash earns for each step of the backtest, not the annualized rate. For this example, you run the backtest using daily data and the risk-free interest rate is 2% annualized, so set the RiskFreeRate property to 0.02 / 252 to approximate the daily interest rate.
% Approximate a 2% annualized risk-free rate for daily backtest data
riskFreeRate = 0.02 / 252;Cash Borrow Rate
The CashBorrowRate property sets the interest accrual rate applied to negative cash balances. If at any time the portfolio weights sum to a value greater than 1, then the cash position is negative by the amount in excess of 1. This behavior of portfolio weights is analogous to borrowing capital on margin to invest with leverage. Like the RiskFreeRate property, the CashBorrowRate property is defined as the per-time-step rate, you must provide the annualized rate divided by the number of time steps per year.
% Approximate a 6% annualized margin interest rate for daily backtest data
cashBorrowRate = 0.06 / 252;Initial Portfolio Value
The InitialPortfolioValue property sets the value of the portfolio at the start of the backtest for all strategies. The default is $10,000.
% Start backtest with $1M
initPortfolioValue = 1000000;Create Backtest Engine
Using the prepared properties, create the backtesting engine using the backtestEngine function.
% The backtesting engine takes an array of backtestStrategy objects as the first argument backtester = backtestEngine(strategy,... 'RiskFreeRate',riskFreeRate,... 'CashBorrowRate',cashBorrowRate,... 'InitialPortfolioValue',initPortfolioValue)
backtester =
backtestEngine with properties:
Strategies: [1x1 backtestStrategy]
RiskFreeRate: 7.9365e-05
CashBorrowRate: 2.3810e-04
InitialPortfolioValue: 1000000
NumAssets: []
Returns: []
Positions: []
Turnover: []
BuyCost: []
SellCost: []
Several additional properties of the backtesting engine are initialized to empty. The backtesting engine populates these properties, which contain the results of the backtest, upon completion of the backtest.
Load Data and Run Backtest
Run the backtest over daily price data from the 30 component stocks of the DJIA.
% Read table of daily adjusted close prices for 2006 DJIA stocks T = readtable('dowPortfolio.xlsx'); % Remove the DJI index column and convert to timetable pricesTT = table2timetable(T(:,[1 3:end]),'RowTimes','Dates');
Run the backtest using the runBacktest function.
backtester = runBacktest(backtester,pricesTT)
backtester =
backtestEngine with properties:
Strategies: [1x1 backtestStrategy]
RiskFreeRate: 7.9365e-05
CashBorrowRate: 2.3810e-04
InitialPortfolioValue: 1000000
NumAssets: 30
Returns: [250x1 timetable]
Positions: [1x1 struct]
Turnover: [250x1 timetable]
BuyCost: [250x1 timetable]
SellCost: [250x1 timetable]
Examine Results
The backtesting engine populates the read-only properties of the backtestEngine object with the backtest results. Daily values for portfolio returns, asset positions, turnover, and transaction costs are available to examine.
% Generate a histogram of daily portfolio returns histogram(backtester.Returns{:,1}) title('Daily Portfolio Returns')
