Automated Trading with R Quantitative Research and Platform Development by Chris Conlan

Automated Trading with R Quantitative Research and Platform Development by Chris Conlan

PART 1

Problem Scope

CHAPTER 1

Fundamentals of Automated 
Trading

The fundamental goal of trading is to maximize risk-adjusted return. When developing strategies, we will 
simulate trading performance in an attempt to maximize risk-adjusted return in simulation. There are 
many ways to measure risk-adjusted return. They involve examining the shape of the equity curve and the 
return series.
Equity Curve and Return Series
The equity curve is the trading account value plotted against time. It can otherwise be thought of as cash 
on hand plus the equity value of portfolio assets plotted against time. We want it to rise linearly if we trade 
with a uniform account size or exponentially if we reinvest gains. The return series is the list of returns on 
the account at each trading period. The return series depends only on which assets are traded when, not the 
trading account size, so it will be the same whether or not we reinvest gains.
Figure 1-1 shows an example of an equity curve generated by a strategy that is long up to ten S&P 500 
stocks at a time with a trading account of $10,000, trading once per day, without reinvesting gains. A gray 
reference line is plotted for an equivalent investment in the SPY S&P 500 ETF, a tradable fund that closely 
mimics the behavior of the S&P 500.

Automated Trading with R Quantitative Research and Platform Development by Chris Conlan