Plan Options

Onyx

Reports: 5/month
Strategy Predictions: ∞

Free

Gold

Reports: 20/month
Strategy Predictions: ∞

$9/month

Diamond

Reports: ∞
Strategy Predictions: ∞

$49/month

Optimization

• Optimization Objective
  The search for parameters during the optimization that satisfies the chosen objective. For example, if “Maximize revenue” is selected the QuantShift algorithm will optimize the strategy aiming for the most revenue in the date range “start date” to “end date” as selected earlier. Different objectives can lead to different optimal strategies parameters found by the algorithm.

Trade setup

• Market type
  Select the type of market you want to trade in. The equities market simply involves buying/shorting shares of a company. A futures market (currently not supported) is an auction market in which participants buy and sell commodity and futures contracts for delivery on a specified future date. The FOREX market (currently not supported) enables you to trade currency pairs. We will soon support all of these market types and more.


• Stocks/Tickers
  A ticker symbol is an arrangement of characters—usually letters—representing particular securities listed on an exchange or otherwise traded publicly. When a company issues securities to the public marketplace, it selects an available ticker symbol for its securities that investors and traders use to transact orders. Every listed security has a unique ticker symbol, facilitating the vast array of trade orders that flow through the financial markets every day.


• Strategy
  Which strategy to use for deciding when to buy and sell the financial instrument in question. The strategy decides whether to buy long, exit a long position, sell short, or cover a short position. Currently a pre-defined list of strategies are supported, but soon you will be able to define/upload your own strategy.


• Market position
  Whether to enter the market in a long position: buy in expectation of the market going up, i.e., increasing in price, or whether to enter the market in a short position: "sell short" in expectation of the market going down, i.e., decreasing in price, but profiting off this decrease.

Backtesting

Basic settings:

• Start date
  Choose the date for to start backtesting. This is a date in the past. It can be as far back as there is data for the financial instrument chosen. In a machine learning setting, think of this as setting the starting point of the data used for testing the strategy parameters found during optimization.


• End date
  Choose a date to end backtesting. This is a date later than the start date. We recommend do at least 6 months of backtesting. The backtesting will take place between the start date and the end date. In a machine learning setting think of this as setting the ending point of the data used for testing the strategy parameters found during optimization.

Advanced settings:

• Commission
  Provide the round trip (r/t) commission assumed lost on each trade. For example, we can assume that each trade costs $5 r/t. Then input “5”.


• Position
  Here we can define how many shares are bought in each transaction. This can be defined as a fixed number or as a percentage of equity at the time of purchase. Currently, we only support fixed values here throughout the backtesting – in other words, if 100 units is selected, we always buy 100 shares for each trade (in the case of equity).


• Slippage
  How much slippage is assumed per trade? It should be given as a percentage which reduces the net profit in each trade. For a 2% slippage a net profit of $100 now becomes $98 and a profit of $10 becomes $9.8. Slippages simulate erratic market movements such as opening higher or lower than the close, e.g. It helps keep a conservative and prudent look at the strategy in question.