[…]the market does up a lot. Let us focus on down days only. What is average return of these days? Again 2018, falls in the middle. % Days Down For The Year What if we look at the percent of days down for the year? 2018 now is the second worst since the bull market start in 2009. Spreadsheet File the form below to get the spreadsheet with the data used to generate these tables. You can use my data to slice it the way you want. Final Thoughts Was “2018 was one of the most volatile years on record […]
[…]ideas, finding trades, and creating strategies so you can profit. Click here for more information Tech Comets Click here for more information Volatility Trend Trader Click here for more information Market Surfer Click here for more information Big Cap Alpha Click here for more information Exploding Stars Click here for more […]
[…]in your exit can have a huge impact on the results as was driven into me during some recent research. I am guilty of not be as thorough in my testing of exits as I should be. Hopefully, this will convince you to look at them more at the beginning of your research. The Strategy I was talking with a fellow researcher about a mean reversion strategy I created a while ago. How it was a simple strategy but did well then. We were wondering how it held up recently. We did not remember the rules exactly. A typical mean […]
[…]of PPO-Histogram (5%) 14-day RSI (5%) Each stock raw SCTR value is calculated and then sorted against all the others in the universe. Then divided by the number in the universe to give all stocks a value between 0 and 99.99 with approximately the same number of stocks in each decile. To get the full details on the calculation see StockCharts Technical Rank (SCTR). Notice that the longer term indicator has 60% weighting vs 10% for the shorter term one. This leads me to believe that longer holds will do better. StockCharts applies SCTR to these universes Large-Cap – US […]
[…](bad) his chosen backtesting solution is when the strategy is traded live. However I am always amazed how little some traders pay attention to how closely their backtest match their live results.” Torturing Historical Market Data “There’s no such thing as right or wrong data, just better or worse. Stock market data looks spotless when you just see the performance numbers, but looks can be deceiving.” Screw It, I’m All In, Baby A little humor for your day but oh so true. Improving the Simple ETF Rotational Trading Model “What I love about trading models like this is […]
[…]free access to the first part of the first class with no credit card needed. Two hours of professional instruction plus bonuses for $175. If you like the first part, email me and I will send you a PayPal invoice. This course assumes you have a good working knowledge of AFL. If you don’t yet have those skills, please consider taking the AmiBroker and Backtesting 101 course first. Thank you, Cesar […]
[…]the Investing Unicorn: Give me “High Returns with Limited Risk”’ Algorithm Aversion — Why people don’t follow the model! “However, given this knowledge that models beat experts, forecasters still prefer to use the human (expert) prediction as opposed to using the model.” Good Quant […]
Often one runs a optimization of a testing idea, then using some set metrics from these results, one picks a variation to trade. What often comes as a surprise to people, and myself the first time I saw this, is that your optimization runs are often mean reverting. What do I mean by this? For example, you have a 100 run optimization from 2000 to 2012. Now you sort by your metric, say Compound Annual Return. Now do the same optimization from 2013 to 2015. You will notice that your top runs from the first period moving toward the middle […]
[…]last few days is more likely to bounce back up. Another way of looking at this as a stock moves away from the average price, it is more likely to bounce back to (and through that average). Benefits/drawbacks of Mean Reversion Some of the pros of MR strategies are they have short hold periods of 3 to 7 days. They perform well during volatile times. Some of the drawbacks of MR strategies are as follows. During low volatile times, like we have now, they can stay mostly in cash which can be frustrating. They work better without stops, meaning it […]
[…]dates are from 2007 to 2014. We start in 2007 because that is when our leverage ETF data starts. I spent five minutes developing these rules so don’t expect stellar results. Buy rules RSI2 < 5 Down two or more days Buy on the close Sell Rules RSI2 > 50 Sell on the close Results on SPY & QQQ Not great results but what would happen if we apply these rules to the 2x leveraged ETF. The results could be good. Looking at the QQQ results one would think that the CAR would double to 21.6 with MDD to […]
