Sunday, January 22, 2012

What do you get for the fund management fees?

I've recently mentioned that only some small Polish non-benchmark (semi-hedge) funds decoupled from the general market deterioration in 2011.

But how they really compare to the market and how they are correlated between themselves?

From June 2009 till January 2012 Gandalf SFIO virtually didn't change its value:

The annualized return over this period is -0.14%. Meanwhile, WIG20 returned +12.15%.

The main feature of Gandalf SFIO is its low negative correlation with the index.

As for Opera Alfa-Plus, the fund returned +22.8% since inception and +8.62% annualized:

Still that's worse than WIG20 which grew by +31.2%:

In contrast to Gandalf SFIO, the correlation between Opera Alfa-Plus and WIG20 is slightly positive.

It gets quite interesting when you compare performance between the funds:

Opera Alfa-Plus has clearly been better performing than Gandalf SFIO so far, but the funds have been negatively correlated, so the future may change that.

Nevertheless, beating the index (basic buy and hold strategy) is not an easy task. So what do you get for the management fees?

Friday, January 20, 2012

Distance and dimensions

Something totally different, today :)

At least as measured by Minkowski distance, distance between three-dimensional objects is inversely proportional to the number of dimensions of the space in which one measures distance.

For example, distance between two randomly selected points may be 150.90 units in R^3, while it drops to 129.86 units, or by 13,94%, in R^96.

So, if one would be able to make shortcuts through some hypothetical additional dimensions, one could  travel faster than others moving in plain R^3. The potential gains are not huge, though.

The difference between distances in various R^n spaces decreases quite significantly and around R^20, the incremental gains are usually smaller than 1% per additional dimension:

      dimensions distance    difference   difference%
 [1,]          3 150.9008  1.509008e+02           Inf
 [2,]          4 140.6339 -1.026687e+01 -6.8037222878
 [3,]          5 135.7465 -4.887388e+00 -3.4752557745
 [4,]          6 133.1936 -2.552873e+00 -1.8806176731
 [5,]          7 131.7919 -1.401690e+00 -1.0523697580
 [6,]          8 130.9986 -7.933852e-01 -0.6019982623
 [7,]          9 130.5400 -4.585113e-01 -0.3500124575
 [8,]         10 130.2709 -2.691661e-01 -0.2061942603
 [9,]         11 130.1109 -1.600260e-01 -0.1228409661
[10,]         12 130.0147 -9.616443e-02 -0.0739096136
[11,]         13 129.9564 -5.832922e-02 -0.0448635601
[12,]         14 129.9207 -3.567275e-02 -0.0274497876
[13,]         15 129.8987 -2.197770e-02 -0.0169162448
[14,]         16 129.8851 -1.363012e-02 -0.0104928834
[15,]         17 129.8766 -8.503742e-03 -0.0065471273
[16,]         18 129.8712 -5.334217e-03 -0.0041071429
[17,]         19 129.8679 -3.362549e-03 -0.0025891404
[18,]         20 129.8658 -2.129199e-03 -0.0016395115
[19,]         21 129.8644 -1.353778e-03 -0.0010424441
[20,]         22 129.8635 -8.640018e-04 -0.0006653107

Thursday, January 12, 2012

Reconstructing missing observations with R

I've been playing with reconstruction of missing observations for the last couple of days.

Say you've got a quotations of some equity that miss some data points.

You may want to have them reconstructed for example for pairs trading.

What do you do then?

Chart: example of VAR reconstruction of missing data

I've preliminary tested a number of potential methods from simple mean to Dynamic Linear Models to Random Forest.

Performance varies, but for the moment three reconstruction methods seems to lead the pack: simple mean, some Dynamic Linear Model and Vector Autoregression.

Chart: comparison of various reconstruction methods for one case

Some thoughts on the Polish pension funds

The Polish (mandatory) pension funds - OFEs - were down in 2011. Average one year performance (as of yesterday) was -3.72%.

Nevertheless, they are on average +192% up over their 13 year period of existence. And that translates into a quite nice +8,6% CAGR.

And - what's important - they have clearly beaten the stock market:

Chart: ING OFE vs WIG20, 1999-2012,

However, what's worrying is a very high correlation between all the funds:

Chart: OFE prices 1999-2011

The correlation rank between OFEs keeps between amazingly thin range of 99,51% and 99,97%:

Chart: OFE correlation distribution 1999-2011

Clearly, OFEs are not competitive. For extremely high correlation they are also a potential source of systemic risk.

Wednesday, January 11, 2012

WIG20 - S&P500 decoupling

Chart: WIG20 vs S&P500 futures 5 days, 2012-01-10,

The Polish stock market index WIG20 has recently decoupled from the US market index S&P500 quite significantly.

This divergence has lasted for some time now:

Chart: WIG20 vs S&P500 futures 3 months, 2012-01-10,

Something will have to correct... But which one?

Or is it just an opportunity for a convergence trade without trying to guess the direction?

Was the yesterday's funny WIG20 action a signal of the future developments?

Questions, questions and more questions... :)

Nevertheless, it's worth keeping in mind that even though Polish and US markets are highly correlated, correlation is not a stable measure. It's much safer to check the spread between the markets based on their cointegration.

Tuesday, January 10, 2012

A WIG20 mystery today

I'm a little too tired to think clearly and research today (it's nearly 22:00 and I'm awake since 4:50), but I've noticed something funny with WIG20 today:

Chart: WIG20 vs FW20 continous futures, 2012-01-10,

It may be connected with Getin - GetBank merger, but I'm not sure...

Nevertheless, WIG20 separated with the most liquid futures by 45 points.

Herd mentality

2011 was definitelly a bad year for many hedge funds. The Paulson Advantage Plus fund managed by John Paulson who had made a killing during the recent sub prime crisis, lost more than 50% this year.

The Polish "near hedge funds", such as Investor FIZ and Opera FIZ didn't fare much better. But the worst part is their performance this year was highly correlated with the market :(

Chart: Investor FIZ and Opera 3gr vs WIG20; source:

Seems one of the better asset management companies in the previous years - IDMSA - unfortunately also employed similar strategy:

Chart: Investor FIZ, Opera FIZ and IDMSA ZZP portfolio vs WIG20

Decoupling was demonstrated by small funds like Opera Alfa-Plus and Gandalf SFIO, but that allowed only for capital preservation instead of accumulation. Opera Alfa-Plus finished the year just 1.24% higher, while Gandalf returned 3.75% (January 4th, 2010 - January 3rd, 2011).

Meanwhile quantitative SuperFund lost -20.2% (SuperFund A SFIO PLN) to conclude its six years of presence on the Polish market more than 22% under the water...

Hedge fund / non-benchmark funds were advertised as market neutral, able to withstand market turbulence. Unfortunately it seems most of them demonstrate unhealthy herd mentality.

Friday, January 6, 2012

US military expenditures vs GDP

And now for something completely different, as the Month Python guys would say :)

President Obama visited Pentagon yesterday to announce significant military budget reductions over the next decade. The military expenses should be restricted to $487 billion annually reduced by $487 billion in the coming years.

Taking into consideration, that the United States spent $698 billion for its military in 2010, that translates into an unprecedented cut by 30% and CAGR of -3.5% over 10 years an average cut of 7% annually.

However, the US military budget was close to "just" $500 billion as close as in 2005, before it shoot to the last year's level of nearly $700 billion.

Nevertheless, the announced military cut can possibly have some significant implications to the economy, for:
  1. military expenditures constitute close to 5% of the GDP, and
  2. acted as counter cyclical factor in the most recent recession.

Chart: US military expenditures 1988-2010, billion USD

Chart: US military expenditures as % of GDP, 1988-2010

Chart: growth of US military expenditures vs GDP growth, 1988-2010

Wednesday, January 4, 2012

WIG20 oversold?

Chart: "Context model" for WIG20 as of 2012-01-03

Continuing experiments with the "context models" mentioned before, I have prepared a preliminary model for WIG20.

Above you see the visualization of the model result as of 2012-01-03. Seems the Polish market may be oversold versus its "context".

This would correspond pretty well with the "market prediction for 2012" described here.

The time will verify that :)

Sunday, January 1, 2012

Shortsightedness and bipolar disorder?

I've been reading today about the analysts expectations for the performance of the stock market in 2012. Surprised by this year's market turmoil, they expect volatility to remain heightened. They expect either side-bound market or further declines, before later increases. The Q1 should give the definitive answer about the direction of the market in the rest of the year. In total, they are much more worried and divided than last year. And - as I wrote earlier - they are not alone.

Let's compare what the analysts were expecting at the beginning of 2011. The consensus on December 24th, 2011, when WIG20 was at 2768.66, was for the market to raise by 10-15%, most probably after expecting correction to 2500 in 2011Q1, possibly to 3300-3500.

In reality, the WIG20 decreased by 22.15% (from the open of 2754.67 on January 3rd, 2011 to the close of 2144.48 on December 30th, 2011). In the meantime, it reached the peak of 2942.39 (i.e. +6.81% from the beginning of the year (BYD) and +6.27% from December 23rd, 2010) on April 8th to fall to 2018.99 (i.e. -26.70% from the BYD) on September 23rd, 2011.

Since it seems, analysts are usually dead wrong, the best strategy would be to take to opposite view to their current predictions.

Hence, we should either expect the volatility to come down and market to go up (scenario 1) or the market to go up at the beginning of the year, before correcting later (scenario 2). 

I both cases, the market should finish the year much higher than it's current level:

Chart: Contrarian to analysts' predictions for WIG20 for 2012

Update 2012-01-04:

Analysts' predictions for S&P500 in 2012:
  • Morgan Stanley - 1167
  • HSBC - 1190
  • Goldman Sachs - 1250
  • Oppenheimer - 1400
  • JP Morgan - 1430
  • Deutsche Bank - 1500
  • average (Birinyi Associates) - 1334
  • mean: 1363
  • range: 1167 - 1500