Tommorrow marks the official release of my **4th book****:**

*Henceforth to be known as AFTS*

(I've had authors copies since the 24th February, but modern supply chains being what they are it takes considerably longer for the book to arrive in the hands of my readers; although plenty of people on twitter have been bragging about receiving their copies earlier).

You can buy it here (why haven't you already!), or read about the detail a bit more here. It's my longest book so far, and in my personal opinion the best written as well (I feel like I'm getting better with practice!).

What I thought I would do in this post is explain in some more detail why I decided to write it, what it's about, and how it relates to my other books.

## Why I decided to write it

*futures*. But I've never really written about specifically trading them in my books, except to discuss how to adapt my workhorse forecasting/vol adjusting portfolio management equations to that particular asset class, as well as the odd reference to the fact you have to roll them every now and then. An obvious exception is 'Leveraged Trading', where they appear as one of five classes of leveraged instruments that I specifically discuss.

So my third source of motivation was a book I wrote a few years ago, but which very few people will ever read. When I took over the fixed income team at AHL the team consisted of a disparate group of people, not all of whom had deep familarity with the asset class. So I wrote a 'book', which mostly consisted of a lot of graphs showing how various instruments had behaved in the past, their volatility patterns, how the yield curve had behaved, and how various types of trading strategies performed across different instruments. I can't remember the exact title, but if I wrote such a book today I would call it the 'Fixed Income Almanac'.

It once occured to me that a 'Futures Almanac' would be an interesting project. There used to be a book (probably out of print, and certainly out of date now we have the internet) that listed all the futures markets in the world (perhaps someone old like me can put the title in the comments). I imagined a book with a couple of pages per market, with a graph showing the price and performance of various simple trading strategies, plus some interesting market statistics.

Of course such a book wouldn't be commercially viable, would go out of date, and more worryingly for me would become a license for overfitting ("Look, from page 925, Iron has clearly the best momentum ewmac4,16 performance").

However it struck me that if I did write a book about trading strategies, I could make it 'alamanac-like' by testing my strategies over a huge set of futures markets, and showing the results.

## What it's about

## How it relates to my other books

**Leveraged Trading.**Once you have a good understanding of the asset class, then it would make sense to move on to

**Advanced Futures Trading Strategies**. My first book,

**Systematic Trading**, is probably one to read next if you want to move on to designing your own trading strategies.

**Smart Portfolios**of course is a book about investing and not trading, but naturally still worth buying.

## Credits

*Darcey the cat, looking for spelling mistakes*

Dear Rob, really appreciate the publishing of this book, bought it the first moment it is available, such a masterpiece!

ReplyDeleteJust would like to highlight that in the Resources section, Strategysheets 18, 19 and 22 require additional permission to view, unlike others. Appreciate if you could help fix this special requirement, or advise how to get the additional access right on these 3 sheets. Much appreciated!

Cheers,

Stan

Fixed, thanks for pointing out

DeleteIs figure 3 on page 25 computed using the mini contract instead of the micro? Assuming a 5x multiplier it should top out around $4k x 5 = $20,000, no?

ReplyDeleteI think you might be right, but I don't think it affects any of the other numbers or findings.

DeleteHi Rob, if there is any position variation, seems you would place the adjustment orders at next day's Close, this is a reading from how the PnL gets calculated in your sample spreadsheet. Is this how you would manage the trades in the backtest process? If so, in order to achieve what the backtest system indicates, we should have the best execution as close or better than the Futures Settlement price as possible. Though at chapter Tactic Two Execution you mainly focused on how best to manage the bid/ask spread or so call the liquidity cost. Just wondering what are your considerations on the execution reference price used in the backtest, certainly it is more on the timing risk at certain time of the day rather than the liquidity risk throughout the day. Thanks!

ReplyDelete"If so, in order to achieve what the backtest system indicates, we should have the best execution as close or better than the Futures Settlement price as possible."

DeleteWhy does it matter to exactly match the backtest? At the speed we are trading, who cares?

(On the other hand getting best execution will actually make me real money)

What do I do: I run the backtest with and without a 1 day delay. There is 0 difference in the performance. That gives me confidence I shouldn't be that bothered about a 1 day delay. In fact it takes about a 5 day delay before I lose 0.01 SR units.

Then when I'm trading I compare the 'reference price' (normally the previous days close, i.e. when I generated the signals) with the mid price when I come to submit the order at some point the following day, but almost certainly before the closing price. The difference between these two prices is the effect of delay in my trading system, and will produce a live/backtest difference. Some days it could be quite big, but on average it should come out to zero, which is what I would expect given the effect of delaying in the backtest.

Hi Rob!

ReplyDeleteThanks for a great new book!

I have noticed that you are becoming more and more conservative with your target risk level: from 50% in ST to 20% in AFTS (25% is only for a well-differentiated portfolio). Back in LT, you allowed us (small traders) a little more drive than in AFTS. Is this a consequence of your expirience or systems productivity declining in recent years?

The second question is about the recommended formula for calculating the minimum capital. It was presented before the concept of forecast. But after we had known about forecasting, this formula have not changed. But I remember your recommendation to calculate the minimum capital for a strength of forecast = 20 (in ST and LT). So we can double minimum capital, calculated before forecasting.

25% is what I would recommend given the sorts of backtested SR in AFTS. In theory if you had something much better you could still go to 50%. I wouldn't.

DeleteActually you would be halving the minimum capital.

Hi Rob!

ReplyDeleteI have noticed (in pysytemtrade's rob_system and this blog) that your own weights of volatility futures are much less, than by equal handcrafting weighting (1/7 of capital). What is the reason? I guess, it is because this asset class has only two assets, so weights is too big. Maybe your are capping maximum weight? Thank you.

Yes it's because it only has 2 assets. The handcrafting code I use for this automatically corrects for this.

DeleteOnly available if you buy the book

DeleteHi Rob! I'm a little confused about turnover.

ReplyDeleteAs I remember from Systematic Trading, turnover is a round trip trade.

From ST glossary:

"A way of measuring trading speed. Turnover is measured in round trips per year, where a round trip consists of a buy and a sell of an average sized position. So a trading system with a turnover of 10 units is expected to do ten buys and ten sells in a year. See page 184."

If so, shouldn't we double the transaction costs in the formula from chapter 3 (AFTS):

Risk adjusted transaction costs = Risk adjusted costs per trade * Turnover * 2 ?

Thank you.

No because, in a deliberate attempt to confuse, I've changed my definition of turnover. Ten buys and ten sells a year would now be a turnover of 20.

DeleteHi Rob,

ReplyDeleteThank you for publishing such a great book.

I tried to replicate Strategy 26 (fast mean reversion) with my own data but my backtest turned out to be a very steep decline in P&L at almost all times in the sample.

Then I found out about the Resources section. I ran the code in chapter26.py as is using your daily and hourly datasets and I was surprised to also see a straight line down in P&L when i run perc_returns_dict['sp500'].cumsum().plot().

Am I missing something obvious?

Thank you,

Florian

Thanks you very much, I was trying to replicate some example in the dynamic portfolio chapter, for example the calculations between table 115 and table 116 return the standard deviation of the portfolio as 0.0267. However if I exactly replicate the calculation I get 0.02890789. Am I missing something?

ReplyDeleteok, I was confused because the result of that example was eventually 0 1 3 and not 0 1 2, and it seemed mostly related with the calculation of the tracking error.

DeleteHey, is this book helpful for other market traders? I am from India and trades in NSE.

ReplyDelete