My Books


In case you're wondering, no I don't know how to read Japanese.



This blog is free. There is no premium content for subscribers only. It has no ads. I don't sell software, trading courses, newsletters, or do coaching. Hopefully that means the material in it should be free of bias of all kinds (Except for my own stubborn opinions). To be crystal clear: I make no money whatsoever from it!

So if you appreciate this blog and want to say 'thanks'; then you might consider buying one or all of these books (which will have the added advantage of hopefully significantly improving your trading or investing).






17 comments:

  1. Hi Rob, in your book "systematic trading" you show that it takes an unexpectedly long period of backtesting data to support a significant positive Sharpe ratio. I would have thought that the significance of backtesting Sharpe ratio would be related to the number of trades rather than the duration of the backtest. Hence, a backtest of strategy with thousands of trades in say two years may be more signifncant that 20 years of backtesting of a strategy with only 100 trades.... Could you please elaborate? Thank you.

    ReplyDelete
    Replies
    1. You could look at the distribution of trades rather than of time history, but it won't usually give you more statistical significance unless by trading more often you also get higher annualised performance. I haven't got time or space to explain the maths here, but this would be a good choice for a future blog post.

      Delete
    2. I'd love to see a blog post on this!

      by annualised performance do you mean sharpe ratio for that year or straight returns?

      Delete
    3. supposing it is only returns for that year, I guess you'd also gain statistical significance if trading more often also gave you lower variance?

      Delete
    4. Annualised performance is just performance for the year.

      Delete
    5. Update: in my newest book "Leveraged Trading" I look at testing the significance of profits on a trade by trade basis

      Delete
  2. Hi Rob, while we're on the topic of Sharpe, could you elaborate on how you generate the standard of deviation of Sharpe (in the part where you talk about significant length of data)?

    You mention "random variables," does this mean your randomly change the optimizeable parameters for that year, and use the standard deviation?

    What do you run your t-test again? The rolling period?

    Thanks! Kayley

    ReplyDelete
    Replies
    1. Standard deviation of SR estimate can be generated using bootstrapping or closed form:

      sqrt[(1+.5SR^2)/N]

      for N data points.

      For the rest of your query I'm confused as to what article you're talking about so maybe post on that article as the answer could be different depending on the context.

      Delete
  3. hi Rob. one question to your "Smart Portfolios" book. in the "Bonds" section you recommend exposure of around 25% risk weighting to Emerging Market bonds? I've tracked two good ETFs for that in which I can invest in Germany. One is investing in US-Dollar-bonds issued by Emerging market countries. The other one is investing in Bonds issued in their local currency of the EM countries. Would you have a preference for any of them (2nd one has 0.25% more cost per annum) ?

    cheers!

    ReplyDelete
    Replies
    1. Difficult. I'd probably go for the cheapest

      Delete
  4. hi rob, a bit of a random question, but I bought your first and second book and am considering to buy the third one, but I realised it does not include option, what is your thought on options trading on retail level ?

    Volatility selling has been one of the "good" factors like momentum, is it not ?

    ReplyDelete
    Replies
    1. Yes this is a source of risk premium, but riskier and trickier than trading 'delta 1' instruments like futures.

      Delete
  5. Hi Rob. I have read your books and yes I do understand Systematic Trading much better after reading Leveraged Trading.

    I have built and backtested a long only strategy using multiple MAC's and Breakouts as you describe in Leveraged Trading. To your credit I used your forecast weighting values and this comes out quite solid. By solid I mean that when backtesting the strategy I get the best performance with an opening rule of 0 on the combined weighted forecast. It also nicely demonstrates improvements in sharpe ratios as new rules are added. I am now working on the short side version, however, and I find that I get better backtested performance opening a short on a forecast of say -4 to -2. I have an itch to test each rule separately on the short side to find this best entry forecast. Then I would add this fudge factor into each of the forecast calculations to take it back to a 0 opening. Then reweight and rerun all the rules together that should open with an ideal 0 forecast. Am I overfitting here?

    I find the short strategies difficult. I am not ready to do continuous trading as you advocate. Not enough capital and I find it difficult to hang around in sideways markets. For now I prefer the security of a few different strategies with forecast weightings to select the best opportunities.

    ReplyDelete
    Replies
    1. I dont' really understand what you are saying, for example what does "an opening rule of 0 on the combined weighted forecast" mean? But it does sound massively like overfitting.

      Delete
  6. So I have 4 Breakout rules and 4 MA Crossover rules. Each have a -20 to 20 forecast using your published scaling factors. I then weight them to come up with a combined forecast. I open a short position when this combined weighted forecast turns negative. I close it on a calculated Trailing Stop adjustment factor again based on rule weightings.

    I am just saying on the Short only side I get better backtested performance opening at say a -4 forecast on a -20 to 20 scale.

    ReplyDelete
    Replies
    1. Ok I think I understand.

      Yes, definitely overfitting. It might make sense to ignore forecasts between -4 and +4 to use capital more efficiently (see this post https://qoppac.blogspot.com/2016/03/diversification-and-small-account-size.html) but assymetric filtering is definitely overfitting.

      Delete
  7. OK. As I suspected. Yes, in practice I do something similar to this in terms of selecting the best forecast and most diversifying of what my strategy is telling me to own. In practice I do not need to ignore much but I do like a systematic rule.

    ReplyDelete