A Market on Close (MOC) order is entered before the market closes and the transaction takes place at the day’s closing price.  

The US stock exchanges process these orders.  Check with your broker for exact instructions on how to enter them.

Extra Insight:

Due to using historical end-of-day data, a ”this bar at close” order in backtesting behaves similar to a Market-on-Close order because it takes today’s closing price.   A key difference is that the backtest actually “sees” the closing price before placing the order.   I wish I could do that in real life!

I use the MOC or “this bar at close” order in backtesting only for timed exits because the decision to exit in this case doesn’t depend on the closing price, only the number of days in the trade.

For large orders in thinly traded markets, a live market order might move the live market, resulting in a different closing price than would have occurred without the order – an effect that’s not modeled with historical end-of-day data.

Read a professional’s report here that live MOC orders often execute at the published closing prices.

A small private trader is unlikely to move a large liquid market.   By sticking to high volume stocks, its not only possible to backtest market orders, its also possible to understand more about the differences between market orders and limit orders via backtesting.

Updated: 11/12/08.

Tags: backtesting, data, exit, market order, market-on-close, trading

A Market on Open (MOO) order is entered before the market opens and the transaction takes place at the day’s opening price.  

The US stock exchanges process these orders.  Check with your broker for exact instructions on how to enter them.

Extra Insight:

Due to using historical end-of-day data, a next day market order in backtesting behaves most like a Market-on-Open order because it takes the opening price.   

For large orders in thinly traded markets, a live market order might move the live market, resulting in a different opening price than would have occurred without the order – an effect that’s not modeled with historical end-of-day data.

Several traders report that live MOO orders don’t always execute at the published open prices.   Read a trader complain of worse prices here, and a professional find better prices here.

Updated 11/12/08.

Tags: backtesting, data, market order, market-on-open, trading

Here’s the scoop straight from the SEC on market orders. 

Extra Insight:

Backtesting with end-of-day data differs from live trading with respect to market orders.   No way can an order in backtesting move the market — it is assumed to execute at the historical price.  One way to account for this discrepency is to specify a slippage assumption that the backtesting engine applies to each trade.

Another approach is to reduce slippage by trading in liquid markets — I look for a volume of 500,000 shares to trade.

A small private trader is unlikely to move a large liquid market.   By sticking to high volume stocks, its not only possible to backtest market orders, its also possible to understand more about the differences between market orders and limit orders via backtesting.

Updated: 11/13/08.

Tags: backtesting, data, market order, slippage, trading

When using a market order, the price is not agreed in advance. An order, even a small one but especially large ones, might move the market and be executed at a surprising price!   The difference between the price quote and the price paid is known as Slippage in the stock trading world and skid among commodity traders.  Most backtesting engines allow the user to make an assumption of how much slippage effects each trade.

Extra Insight:

For my backtesting, I assumed zero slippage.  This is not realistic for market orders but is realistic for limit orders.

Using limit orders in live trading is one way to reduce the cost of slippage.    Trading less frequently is another.

(Backtesting Blog is an Amazon Associate.)

Updated 11/13/08.

Tags: backtesting, limit order, market order, skid, slippage, trading

I start this blog while immersed in the early phases of my fourth major US stock market backtesting effort. 

The purpose of the blog is to record my key decisions and tactics for backtesting.   I intend it to be a resource for traders and active investors . I hope that others will learn from my efforts and we all learn from each others’ comments and discussion.

My goals for backtesting are:

1. Design trading strategies for my own use.   Specifically, 

• US Stock Market
• both buying long and short selling 
• investigate both trend following and band trading  
• swing trading: end-of-day (EOD) or daily charts and trades that last several weeks  

2. Provide information that other traders can use to develop their own systems.    That includes the areas above, and in addition, I want to illustrate for new traders such key concepts as:

• stop loss orders 
• market orders vs limit orders vs stop entry orders
• trailing stops
• price targets
• indicators like moving average, RSI, MACDH, Stochastic

3. Do this with a scope and scale that goes beyond the resources typically available to private traders, including:

• delisted stocks
• over 15 years of historical data
• clean database
• multiple time periods to avoid curve fitting
• crude and robust strategies only…limited fussing with parameters
• statistically sound methodologies
• monte carlo simulations to generalize beyond the given data

 Let’s dive in!

(Backtesting Blog is an Amazon Associate.)

Tags: backtesting, data, goals, limit order, macdh, market order, rsi, stochastic, stop loss, swing trading