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[…]in individual returns, changes in volume, missed stock splits, missing symbols and a lot more. A common fallacy people have is that they believe that past data should stay unchanged. I can tell you this is not the case. If the data provider is adjusting for splits or dividends or any other reason, they can and will make mistakes that changes past data. You also run into precision rounding when doing adjustments which can change price data slightly. I find this one useful. Some people expect that if they run a backtest today and then run it again sometime in […]
[…]year rally. I can make good arguments for and against each of the start years. None of them is a wrong one or a right one. This is discretionary and we can see different results based on our choice. A reader brought this up in my previous post, that had I used a different start date, I would have seen different results. My general rule is to try to be consistent. So most of my studies start either in 2000 or 2007. How would I use this information? I would likely not because of the small sample size and the […]
[…]and made me think. For more articles see the quant mashup Quantocracy. Tactical Asset Allocation: Beware of Geeks Bearing Formulas “The first time one can actually realize how good (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 […]
[…]be more liquid than the underlying, and we know the underlying can become highly illiquid.” Computers are the new Dumb Money “Rational, experienced people understood that an ETF with holdings that were down an average of 5% should not have a share price down 30%.” Avoiding the Big Drawdown: Is Downside Protection Helpful or Heresy? ‘Chasing 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 […]
[…]are there fewer stocks becoming oversold? The blue line is the percent of stocks with RSI2 < 5 compared to all the stock for a given year. This has hovered between 5.1% in 2009 and 8.0% in 2008. The green line is a liner regression of the data. We can see that the trend has been down since 2001 but not a lot. The trend from 2005 to 2007 compared to the trend from 2011 to 2013 looks very similar. Is this trend because we are in the same cycle of a bull market? Is mean-reversion in hibernation? Given the […]
[…]to help us think about re-balancing. Here are some relevant statistics on the two ETFs from 2002-07-31 through 2014-12-31 (TLT was first available to trade on 2002-07-26): The correlation of monthly returns for TLT and SPY during this history was -0.307. Given that the correlation is negative (i.e., low), we should observe the benefits described above in a regularly re-balanced portfolio of SPY and TLT. The following table shows the benefit for CAR[ii]: The horizontal axis is the percent weight given to SPY in the portfolio. We can gain as much as 1% extra in Compound Annual Return if […]
[…]platform used: AmiBroker. Data provider:Norgate Data (referral link) Good Quant Trading, Fill in for free spreadsheet and […]
[…]SP 500 Total Return index data from 1/1/1996 to 9/30/2018. Entry and exit are done at the close. For example, if tomorrow will be a best day, then the test exits at today’s close and enter on the next day’s close. The argument for why you should not try and time the market Here is what happens when you miss the best days. As expected the returns get worse and worse as you miss more days. Missing good days is bad. The argument for why you should try and time the market Here is what happens when you miss […]
[…]a lower value, yes, but I do not have a hard cut off. They are shades for grey. For more information on the issues and interpretation of p-values, you can read the following: ASA statement on p-values We’re using a common statistical test all wrong. Statisticians want to fix that. An unhealthy obsession with p-values is ruining science % Profit/Loss Results Now given what I just said, I will use a cutoff of 5% for the p-value to narrow down results to show. There are 720 variations and 443 of those have p-values under 5%. RSI2 & 5 Day Hold […]
[…]July 31 as 444%! How much did the CAR depend on this year’s numbers? The Strategy The reason for my start of looking into this strategy was I was wondering how some basic mean reversion ideas did during this recent sell off and bounce. The strategy focuses on lower liquidity stocks therefore I will be giving no rules. Conceptually it is a basic mean reversion strategy. Wait for a stock to have a sell off, buy. Then when it bounces, sell. The test range is from 1/1/2007 to 7/31/2020. Initial Results When initially testing an idea, I simply look at […]
