Wednesday, May 23, 2018

Flipped Back to Short

The model was long NQ for one day and lost a little (it remained short ES, surprisingly). Now it has flipped back to short. Given yesterday's post, I'm still thinking this is a limited correction. Here is a possible interpretation based on Elliott Wave Theory:



We are now in wave C of 4. Based on Elliott Wave Theory that wave should stop before price falls below the maximum point of Wave 1, as shown on the graph. I find Elliott Wave very useful in understanding the different things that might happen, but I don't think it is an exact fit to what the market does, especially on very long and very short time scales. Over the time scale shown on this chart, it is particularly useful. On the other hand, Eliott Wave is notorious for continually morphing and following what the market does, rather than predicting it.

Of course, my model has nothing to do with Elliott Wave Theory it is just nice to have some other approach that does not conflict with the model or confirms it.

If you look closely you'll see I'm short from 6911.5 and up quite nicely, but I was up $500 when long yesterday evening too and that reversed...

P.S.
The downside didn't last long! Market turned around in the morning US time and went up, eventually reaching above the top of the triangle in the chart above. At one point I was up USD 1500, but unfortunately I didn't take profits as I was sticking to what the model said to do. Now I am considering doubling my position during the Australian daytime - the US overnight and then closing half in the US morning. If I had done that yesterday I would have ended up on the day. I am going to backtest the strategy of course. 10 years back when I previously was trading futures, I did look at "overnight trading" as a strategy, and now it has come up again.

Model has now flipped back to long. S&P model was short till today, and now has also gone long.

Tuesday, May 22, 2018

Getting Bullish

The model is switching back to long today. The last seven business days it was short but the market just went sideways more or less and it netted USD 1,200 a contract or 0.85% for the effort. The previous 10 days of being long, by contrast yielded USD 5k (3.67%). That's an indication of the bullishness. Australian and European markets have been more bullish throughout this period - the US market has been lagging perhaps due to relative over-valuation and to all this trade war and other nonsense.


So far for the month, the model is up USD 7k per contract and I am about matching that.

Sunday, May 20, 2018

Backtesting 1987


You would want to make sure that your trading model put you in the right direction in the 1987 crash (which I am old enough to remember very well), wouldn't you? So, I backtested the model for 1986-87. The main model would be short going into the crash. But a more primitive model I am using in conjunction with the main model would switch to long on the Friday before the crash. That day the market went down 5%, so it would have already been a bad idea on the Friday. Recently, this secondary model has been doing well and I have combined its signals with my main model. So, we need some new rules about how and why to combine them. In this chart you can see that the buy signal would have come with the price already outside the +/- 2 standard deviations envelope (S&P 500 index):


These are "Bollinger Bands", though I use a 34 day moving average instead of Bollinger's 20 day MA. So, the new rule is not to take that signal when the price is outside the Bollinger Bands and the width of the Bollinger Bands is increasing. That wouldn't change much recently (NASDAQ 100 index):


The secondary model gave some very good buy signals just as price hit the Bollinger Bands in early February and late March. In these cases the price was not outside the Bollinger Bands or they weren't expanding.

The model is short for Monday.

Saturday, May 19, 2018

How Big Should the Trading Program Be?

At the moment I am still in the experimental phase of the trading program. A 1 contract S&P or NASDAQ position either adds or subtracts about 0.1 beta to the portfolio. So if the beta of our portfolio to the market was 1.0, trading modifies this to 0.9 when short to 1.1 when long. My goal is to be able to hedge our portfolio against a market crash. That means we need to subtract up to 1 full beta from the portfolio. On the long side we then would double exposure. This means that the trading program needs eventually to be 10 times the size it is now. Using 3 times leverage on the cash in the trading account that implies allocating 25% of assets to trading. My existing allocation has 25% of assets allocated to managed futures. This total could be allocated between my own trading and "outside managers" such as Winton and meet this goal.

Why 3 times leverage? Simulation shows that about a 12% drawdown is possible. Remember that we use stops and or hedging to limit possible daily losses. So this drawdown means a string of large losses. With 3 times leverage that would wipe out 1/3 of the trading account. More than that and it will reduce the earning potential of the account too much going forward, I think. And be way too scary.

Thursday, May 17, 2018

Formal Rules for Stops

I have decided on formal rules for setting daily stop losses. It is based on the pivot-point method. The pivot point is the average of the high, low, and close for the previous day. When short the stop loss is set at the second resistance level - the pivot point plus the previous day's high-low range - and when long it is set at the second support level - the pivot point minus the previous day's high-low range. If this results in a stop that is less than 1% from the opening price, I instead set a 1% stop. These stops increase the Sharpe ratio of the model though they slightly decrease returns. The chart below shows the last month of daily pivot points and first and second resistance levels:


The model got stopped out on 26 April when short - losing 1.42% that day. The market closed up 2.08%. So that saved 0.66% of losses The model also got stopped out on 3 May when long losing 1%. The market closed only down 0.02%. So that increased loss by 0.98%. That shows you why this reduces returns...

These numbers don't quite match what you can see on the chart as the chart shows the 24/5 futures market and the model is based on the NASDAQ 100 index. I am thinking of switching the model to use actual futures prices. Will need to pay for the data, I think.

Tuesday, May 15, 2018

Trying to Learn the Lesson about Narrow Stops Again


Yesterday the model said to go short NQ (NASDAQ) and long ES (S&P500). I started off the day, doing exactly that, though I entered the trade badly and ended up down on the NQ part of the trade relative to the ES part of the trade. Then, I closed the ES long for a small profit and based on "pivot points", I set a stop loss at 7010 - 50 points above my entry point. As you can see from the chart, the market briefly went through the stop but then turned and ended the day near where it started. So, I lost a lot more money than the model did. If I had set the stop at 1% (7030) or kept the hedge without stops, I would have ended the day with only a small loss. Really, it was fear of missing out on making a profit on the ES trade that screwed me up.

I also did a long CL (crude oil) trade yesterday and was stopped out too. Then the market also turned around and actually ended the day higher. The lesson I am learning from that one is to stick to the stock market for the moment so I can set wider stops and not worry about the potential loss from multiple positions going wrong.

The model is again short NQ and long ES for today. I was going to sit out for today, but writing this post has inspired me to put on that hedged trade. For the record, I sold NQ at 6969.75 and bought ES at 2729.50.

Saturday, May 12, 2018

Weekly Update

Another successful week. Now up USD 8k for the month and USD 6k since the trading experiment started. On Friday I was long NQ when I should have been short. I only lost USD 150 luckily (though double that relative to what I would have got if I had done the correct trade). This was because of an error in a link in a spreadsheet. That link is now fixed. The model says short NQ (NASDAQ), long ES (S&P 500), long CL (Crude) for Monday. I think the short NQ is only a short term correction in NQ and probably it will switch back to long by Tuesday. It is a bit of an unusual feeling to see myself keep winning trades. I said to Moominmama that it felt like I was cheating or something. She said: "Please don't feel like that, please make lots of money :)". So far, this month I just have had to stay long, which isn't so easy for me as I tend to be bearish. And apart from Monday it looks like that staying long will continue to be the challenge for a little while till the model actually shifts to the short side. So, for the meantime we are still in phase 2 of this experiment, which is to see if I can stick to what the model says to do. Only, when we've been through both a long and a short phase successfully, will we be able to say that I think.

Sunday, May 06, 2018

These 13F Tracking ETF's Have Horrible Performance

13F is a form lodged quarterly by US based investment funds. A 13F following strategy takes the stock picks from top hedge funds as revealed by their 13F forms. Two ETF's that follow this strategy are ALFA and GURU. But both have horrible performance with negative alpha of of -5% and -7%, which is rather ironic. Does this strategy no longer work?

Saturday, May 05, 2018

Cracking Horse-Racing, the Lottery, and the Stockmarket?


Articles about Bill Benter who "cracked" gambling on horse-racing by using a model to predict which horses would win and Eddie Tipton who cracked the state lottery, illegally. I'm testing whether I've cracked the stock market :) So far, so good this month, but it is early days.  

P.S.
More on quant betting on horse-racing. Model remains long stocks (NDX and SPX) and switches to long oil for Monday. Yes, I added a model for predicting oil, so far I only did very quick trades in oil.

P.P.S.
More on Zeljko Ranogajec.

Friday, May 04, 2018

Fear of Missing Out versus Loss Aversion

The key to sleeping better in Australia while trading in the US markets seems paradoxically to be using wider stop losses rather than tighter stop losses. With a tighter stop, I am concerned that the market will hit the stop and then bounce back up strongly, which is what would have happened last night except I stayed up and adjusted the stop. This is the fear of missing out - crystallizing a loss and then missing the upside. I need to be more accepting of the possibility of large losses to allow the possibility of gains. I actually seem to have less aversion to losses if they aren't tied to then missing out on gains. FOMO seems to beat loss aversion. This is because my trading model has a high win rate. Traders with techniques that have a small edge or no edge have to make sure that wins are bigger than losses - letting winners run and cutting losses. They need the asymmetry to make money. I don't.

Wednesday, May 02, 2018

April 2018 Report

A very active month financially. The Australian stock market rebounded quite strongly and now looks pretty bullish to me. I also started trading futures again, which so far had the opposite effect on the results for the month :)

The Australian Dollar fell from USD 0.7680 to USD 0.7540. The MSCI World Index rose 1.08%, and the S&P 500 0.38%. The ASX 200 rose 3.92%. All these are total returns including dividends. We gained 2.86% in Australian Dollar terms and 0.98% in US Dollar terms. So, we underperformed the Australian market and to a small degree the international markets but outperformed the U.S. market.

The best performing investment in dollar terms was CFS Geared Share Fund up AUD17k. The worst performer in dollar terms was IPE, down AUD3k. My holding is now quite large (more than 1% of the value of the company - it's a very low value company) and the price is quite erratic. The best performing asset class was large cap Australian stocks, which gained 2.84%. The worst performing asset class was private equity, losing 2.04%, the only asset class to lose money this month.

A new item that I am reporting from this month is trading income. This includes trading in futures and options etc and interest on cash dedicated to trading. It doesn't include any trading done on fundamental grounds. This month I lost money - USD1,987 - which isn't surprising as I was experimenting with different models and approaches and learning to trade more confidently. I pretty much reversed that on the first day of this month, but anything could happen. Less than 3% of net worth is dedicated to trading at this point, which mainly means a deposit of Australian and US dollars used as margin for derivatives. The plan for this month is to consistently trade one futures contract according to the trades that the model provides, while learning about entering trades more optimally and setting stops or using options as hedges (much wider hedges than I was using last month).

We made a bit more progress towards the new long-run asset allocation:


Total leverage includes borrowing inside leveraged (geared) mutual (managed) funds. The allocation is according to total assets including the true exposure in leveraged mutual funds. I have reduced the allocation to cash, because assuming I will be trading, there will always be plenty of cash in the trading account plus the ability to borrow, though the latter can be reduced in a financial crisis. Commodities now includes managed futures, trading, and gold.

The "improvement" in allocation, came partly due to market movements and partly due to investment activity. We invest AUD 2000 monthly in a set of managed funds, and there are also retirement contributions. Then there are distributions from funds and dividends. During the month, I also:
  • Invested in a venture capital fund.
  • Bought more IPE (private equity) at below net asset value.
  • Sold out of Leucadia National (LUK) and bought more 3i (III.L, private equity) and China  Fund (CHN).
  • Bought more units in the Winton Global Alpha fund (managed futures - in the commodities category).
  • Transferred cash into my trading account and did a lot of trading of futures and options while developing my trading model.
As a result the allocation to private equity and commodities increased quite a bit.