Books_20170913

Update of Results YTD

The last months have been a real roller coaster ride! As mentioned in previous post my ROI started to decline in February/March, but I stayed with my models all the way into July. There I took the decision to accept that my models had lost their edge, and I went back to my analysis tools and after some hard work came up with a new set of models to implement. They were implemented in the middle of August.

It might sound like a trivial thing to determine when your models are without edge, but it is not! Betting volatility is hard to see through, and my models had served me well for a couple of years (with only minor changes during that time). Betting is a long term game, but in retrospective I held on to my models to long. Lesson learned: Update and improve models more frequent!

My new models are in many ways much better than previous – They contain more pricing variables (and hopefully a more accurate odds calculation)  and they are estimated on more recent data. Now I need to wait and follow them for a while before optimizing them.

I have updated some graphs which contains accumulated figures of turnover, profit/loss and yield for 2016 and 2017 YTD.

 

I have exactly the same behavior 2017 as I did in 2016, it starts great and then it  declines from February/March. My yield now 2017 YTD is 0.45%, for 2016 same time (week 36) was 0.65%.

The turnover is much bigger than 2016, the only reason for this is that my bank has grown and therefor also my stakes. I just passed 7.000.000 SEK in 2017, and at the same time in 2016 I had staked around 3.000.000 SEK. Due to the fact that I am using new models I decided to change my requested stake size from 3% to 2%. Therefor I expect the accumulated turnover to grow slower for the rest of the year.

Thanks to the higher turnover I also have a higher PL (31.000 SEK 2017 YTD) compared with 20.000 SEK at the same time in 2016.

In 2016 I had a real good 4th quarter, it will be very exciting to see if my new models will continue to perform for the rest of the year.

Books_20170913

Match size potential

One of the most important things to get rich on betting is NOT to create the best model – Instead you need to balance your model with how much liquidity that is available in the market. No use of calculating the most accurate odds, load it with your margin, just to find out that there is no one in the market to take your bets.

 

I know for my self that I haven’t really been on top of this issue, the reason mainly for betting with low stakes (and therefore almost all the time getting matched). As my account has grown the requested bet size has become bigger and bigger and it will eventually be an issue that I need to address with more intelligence.

 

I made a graph to see how much I manage to get matched (as percentage) by different requested amounts:

post_20161004_1

The “amount asked” is rounded to nearest 250 interval, so 0 means asked amounts < 125 SEK. Just as expected there is a quite obvious trend that shows the problem of getting full amounts through at higher stakes.

 

I’ve also added a linear trend so that I can make a very simple prediction of my match% as my account (and stakes) grows. Actually when playing around with the trend I found out that the exponential trend had the best fit so I use:

y= 0,8412*exp(-0,06x) where x equals my group (0=0 SEK,1=250 SEK, 2=500 SEK …). Extrapolating this on higher stakes gives:

post_20161004_2

Ouch! I hope that the curve flattens out more when reaching higher stakes in practise.

One reason to be bothered about this fact is that I suspect that I risk getting more matched in parts of my model where there is a lower expected value, meaning that the ROI of my model will eventually also decline as I reach higher stakes. So far I have no evidence of this, but in my mind it is logical.

I will follow up on this, I expect to reach the 2000 and 3000 stakes within a year and will then return to this subject.

 

 

Books_20170913

Optimizing betsize with Kelly criteria

I will take a few minutes discussing which bet size to use. Within my current betting strategy I use a flat bet stake, meaning I put down the same amount of money on each bet without considering factors such as the implied probability of winning/loosing the bet or the value of the bet (my calculated overvalue).

So far I have only done a few simulations of portfolio developments and from those chosen a bet size which seems to avoid ruin. My current bet size is about 0.5% of the portfolio, but as I mentioned I keep it flat. My original plan was to update it once every quarter to get a slow and stable increasing risk take.

Lately I’ve been looking into optimizing the bet size, something that is done within both the betting and investment communities. The formula to determine the fraction of portfolio for each bet is given by:


p = my estimated probability of the bet
b = the odds for the event given by the market
f = fraction of portfolio to use as bet