[β¦]how often a buy and hold strategy on the S&P500 index is making new equity highs. Then, I wanted to compare the results to a new strategy I am working on for my trading. From previous experience, this number is a lot lower than people expect. Percent Trading Days Making New Equity Highs A trading strategy is at a previous equity high, a new equity high or in a drawdown. Our metric will be % trading days making new equity highs,Β % NEH. This is the number of days that the equity is at a new equity high divided by [β¦]
[β¦]I have been telling my trading buddy and anyone else that would listen that I fully expected XIV to open at zero one day. Now I did not expect it to happen so soon or the way it did. I trade a strategy that can be long XIV or long VXX or in cash. Because of the very likely possibility of XIV blowing up, I had constructed my portfolio using ideas from the barbell portfolio and this post, Taming High Return and High Risk. I was lucky and not in XIV when it did implode on Feb 6, 2018. Could [β¦]
[β¦]these sector ETFs only consisted of nine ETFs. In late 2015, they did a revamp and added XLRE. To test farther back, I tested without it. Baseline Test dates will be from 4/1/2009 to 6/30/2017 (bull market only) and 1/1/2007 to 6/30/2017 (bear and bull markets). For strategies like this, they will probably underperform during bull markets, 2009 to 2017. But they make it up during bear markets. I will use two baseline strategies. The first is buy and hold of the SPY. The second is my new favorite way of trading the MA200. Buy the SPY when it is [β¦]
[β¦]experience required AmiBroker Custom Charts Learn how to create custom indicator charts and custom backtest report charts Intermediate AmiBroker and Backtesting 201 Learn more advanced topics in AmiBroker. AmiBroker Custom Backtester Course Learn how to take full control of the backtesting process with this powerful feature For more information on all courses: AmiBroker Courses Sample AmiBroker Code On Sample AmiBroker Code page, find code for ConnorsRSI ReverseRSI/RSI Solver Historical Volaility Indicator Best and worst trade in backtest report And much more External AmiBroker Resources Howard Bandyβs AmiBroker books AmiBroker [β¦]
[β¦]90 percent and 100 percent are the same. Obviously, they are not. Β Recall model assumptions before jumping to conclusions I have written numerous times in this space about the importance of examining your assumptions before taking any action on quantitative research. Β Advantages With Mechanical Strategies A lot of the best traders (at least the ones I know) use some kind of mechanical rules in their trading. βMechanicalβ implies that the rules are based on some kind of objective rules, usually quantified data. The trader should follow these rules exactly without hesitation or emotion. In this respect mechanical trading [β¦]
[β¦]The CourseEight 45 minute downloadable pre-recorded video classes. These videos will be available to download at one per week.AmiBroker files from classesOne and one access to Cesar to ask any questions you may haveA 100% money back guarantee. See below for details.PrerequisitesAmiBroker 6.0 or greater (may work with lower versions but I am not sure)Daily data source connected to AmiBrokerAbility to program simple strategies. Comfortable with IF-ELSE statements and FOR loops.A desire to put the time in to learn Both Amibroker 101 & 201 are fantastic courses that are packed with excellent information and Cesar is genuinely interested in making [β¦]
[β¦]platform used: AmiBroker. Data provider: Norgate Data (referral link) Good quant trading, Fill in for free [β¦]
[β¦]platform used: AmiBroker. Data provider: Norgate Data (referral link) Good quant trading, Fill in for free [β¦]
[β¦]a lot more slippage than the larger stocks I typically trade. These test results use $.05/share for commission and $.05/share for slippage. I want to add a percentage amount of slippage to the entry and exit price. Adding this may make the results a lot less enticing because the CAR will drop and MDD will increase. Probably a future post. Backtesting platform used: AmiBroker. Data provider: Norgate Data (referral link) Good quant [β¦]
[β¦]out-of-sample test can change our results. How luck can play a role if you use only one strategy to test out-of-sample. How you split your in-sample(IS) and out-of-sample(OOS) can change results. The Strategy I will be using a stock mean reversion strategy with an average hold of three days. Some of my comments may not apply in different situations. Any mention of ConnorsRSI is using the default parameters of (3, 2, 100). The parameters tested below will give 1000 variations. Set up Rules Stock is member of the S&P 500 index It has been less than (10,15,20,25,30) days since a [β¦]
