The global stock indexes have been so boring the last few months, at least for me. Finally there appears to be action, and its not only in the stock indexes it is happening in currencies and bonds as well.
I am trying not to get ahead of myself but I think finally there is some economic reality entering into the picture. Of course the market gurus are all saying that we mustn’t compare Greece to Lehman Brothers, and others are trying to dismiss all the current volatility as nothing to be alarmed about.
I have felt for some time that Hyman Minsky’s instability thesis has been gathering fragile energy. Greece in my opinion is a big story as it has archetypal connotations. Greece has been going bust and leaving the Euro forever, but the only way to treat something that is bankrupt on your balance sheet is to accept it is worthless and write it off. We know that creditors with dubious debts simply close their eyes to that reality and make as if it is ok by playing with the terms of the repayment in the hope it will all come good.
I myself have a loan to a company that I value anywhere from zero cents in the dollar to the full amount depending on my mood of the day. We delude ourselves into believing what we want to believe and what is the most convenient to making us feel good.
Check the sell off of the Shanghai Exchange the last few weeks, I am comparing it to the S&P500 and the FTSE 100. Clearly it has been shooting the lights out over the last year, in fact the last 2 years it has been flying. Could this also be the end of a major cycle.
I thought I would bring to your attention how the Swiss Frank has performed against the Euro and the USD since the SNB unpegged on the 15th January. What is particularly interesting is the CHFUSD chart which has the Frank bank exactly where it was before the unpegging.
I am doing some work with return distributions. In a previous gig we did a lot of work on this subject, and I was really encouraged by the track of work we were following.
A quick recap: we know that trading returns do not typically follow a normal Gaussian distribution path, yet most of the models in modern day finance still use these less than perfect solutions. Its typical human nature, the solutions give us a nice elegant quick solution most of the time. Because a more accurate solution is more difficult to figure out we rather dismiss the facts that bad things happen more often than we anticipate in the name of progress.
We were determined to find a more realistic solution, in keeping with my previous post, keeping it real 🙂 .
In the 2 charts I am going to illustrate how our most likely estimate (MLE) model using Alpha Stable Levy distributions does a much better job than the blue line normal distribution model.
I wonder if any of you will guess who this company is?
One dollar invested in this company in 1968 was worth $US6638 last Friday (including dividends). That’s an annual return of 20.6% per year for nearly half a century. No other company comes close to matching its long-term results, according to Wharton professor Jeremy Siegel.
The same dollar invested in the S&P 500 over the same period would be worth $US87, or 98% less.
This has been a big week for me, and I see my posting slowing down some in the next few weeks. One of the main reasons is that yours truly has recently started a new software company. In due course you will learn more about this venture as it progresses. Now that I can share that distraction with you I feel a tremendous sense of relief.
Being creative is what I love most and I hope this new outlet will provide me an opportunity to keep learning and sharing “the inner wisdom of the market complex” on this blog.
I have to admit, the rally to new highs on the S&P500 is simply quite marvelous. For all my errors forecasting collapse, I have to be honest with myself, this climb is quite majestic given the horrible news that accompanied this journey.
Nothing however goes up forever, I am very satisfied with the performance of the Sefirot Freestyle portfolio todate, and while I cannot forecast what tomorrow will bring, I can say that given the amazing performance over the last few years, the returns for the broad markets over the next 10 years will be sub-par even factoring in robust GDP growth.
For now the law of LARGE NUMBERS awaits, and I suspect the S&P500 will crest the 3000 mark and the Dow will pass the 18,000 level probably before the weekend; sparking a whole bunch of noise in the market place.
I really didn’t think the RBA would cut rates, but I guess things must be pretty bad in the real economy.
We all hear that many institutions look at the momentum strategy where you go long when the 50 day moving average is above the 200 day average. As you will see below from 1993 this has been a pretty effective strategy using daily data applied to the S&P 500. For your information the strategy is still long despite the recent volatility.
Here is a chart showing the moving averages, the yellow is the 50 day and the red is the 200 day.
Here are the backtest results:
For those wanting to see the R code generating these charts and stats here it is:
#get the data and fill out the MA
SPY$ma200 <- SMA(Cl(SPY), 200)
SPY$ma50 <- SMA(Cl(SPY), 50)
#lets look at it from 1990 to 2015
spy <- SPY['1990/2015']
#our baseline, unfiltered results
ret <- ROC(Cl(spy))
#our comparision, filtered result
ma_sig <- Lag(ifelse(SPY$ma50 > SPY$ma200, 1, 0))
ma_ret <- ROC(Cl(spy)) * ma_sig
colnames(golden) = c('GoldCross','Buy&Hold')
#Plot to visually see the actual moving averages
type = "line",
name = "Moving Average : Golden Cross",
TA= c(addSMA(50, col = 'yellow'), addSMA(200)))
# lets see what the latest signals are 1 being a buy signal
table.AnnualizedReturns(golden, Rf= 0.02/252)
charts.PerformanceSummary(golden, Rf = 0.02, main="Golden Cross",geometric=FALSE)
Created by Pretty R at inside-R.org