Drop and Gain Clustering

I decided to build on John Hussman’s clustering of large moves research. As demonstrated in a previous post we showed how large drops -3% seemed to cluster. This time I superimposed the gains to see if there was a similar pattern the gain behaviour and as you can clearly see there is. My takeaway is volatility begets volatility, but where is the start and the finish? (subject for another time)

---
title: "Drop and Gain Clustering"
author: "Michael Berman"
date: "Thursday, October 30, 2014"
output: html_document
---
 
require(quantmod)
require(PerformanceAnalytics)
 
#get the data of S&P500
getSymbols('SPY', from='1990-01-01')
 
#lets look at it from 1990 to 2015
spy <- SPY['1990/2015']
 
#our baseline, unfiltered results
ret <- ROC(Cl(spy)) 
 
#our comparision, filtered result
filter.d <- Lag(ifelse(ret < -0.02, 1, 0))
drops<- rollapply(filter.d==1,100,sum)
filter.g <- Lag(ifelse(ret > 0.02, 1, 0))
gain<- rollapply(filter.g==1,100,sum)
 
#two versions of plots - A
plot(gain, main = "Drop and Gain Clustering", sub = "sum of 2% movements over 100 prior days")
par(new=T)
plot(drops, main = "Drop and Gain Clustering", labels = FALSE, col = "red")

# plots - B
plot(drops, main = "Drop and Gain Clustering", sub = "sum of 2% movements over 100 prior days", ylab ="drops")
par(new=T)
plot(gain, main = "Drop and Gain Clustering", labels = FALSE, col = "red")
axis(side =4)
mtext("gains", side = 4)

Created by Pretty R at inside-R.org

I am actually not sure of which one is a better way to look at it.

The Greatest Bargain

When I read this I think RAPA has to be one of the greatest bargains in the world.

IMatchative Announces a $20 Million Capital Raise  

IMatchative Inc.’s CEO, Sam Hocking, today announced the completion of its Series B Funding Round. The company raised $20 million to support the continued development and adoption of AltX, a leading data analytics platform and marketplace for capital introduction in the global alternative asset class space.

Lead investors include Wells Fargo & Company, Control Empresarial de Capitales, S.A. de C.V., controlled by Carlos Slim, David Bonderman, founding partner of TPG Capital, and Andy Redleaf, the CEO of Whitebox, which are providing the majority of the capital. Jeff Ubben, founder of Value Act Capital, led the Series A round and also invested in this round. Sterne, Agee & Leach, Inc. served as IMatchative’s financial adviser for the Series B funding round.

Mr. Hocking said: “We are delighted to have this distinguished team of strategic investors. Having some of the most successful and sophisticated investors in the world as our allies in the development of AltX is testament to the value our product provides to the marketplace, as well as the need for a more efficient and lower cost method for discovering, evaluating and investing in the hedge fund space.”

AltX uses science and technology – a combination of big data, intelligent analytics, behavioral science, and matching algorithms – to assess the risk tolerance, investment goals and preferences of investors in the fund selection process. AltX also enables hedge funds to gain deeper insights into the motivations and perceptions that shape investors’ decision-making processes. The result is an innovation that improves decision-making, transparency and engagement among hedge funds and investors.

For more information on AltX, go to http://www.getAltX.com.

About IMatchative

IMatchative is a San Francisco based company that uses science and technology to drive better decisions and to transform businesses. The company specializes in superior data aggregation and analysis, behavioral psychology and algorithms. AltX is IMatchative’s first product.

Cumulative -3% Corrections

I mentioned a few posts earlier I wanted to post some R code replicating Hussman’s chart.

 

require(quantmod)
require(PerformanceAnalytics)
 
#get the data of S&P500
getSymbols('SPY', from='1990-01-01')
 
#lets look at it from 1990 to 2015
spy <- SPY['1990/2015']
 
#our baseline, unfiltered results
ret <- ROC(Cl(spy)) 
 
#our comparision, filtered result
filter <- Lag(ifelse(ret < -0.03, 1, 0))
drops<- rollapply(filter==1,50,sum)
plot(drops)

Created by Pretty R at inside-R.org

Don’t get caught in the hype

I am sure a lot of people have been caught in the hype with the fact that the markets have been making new all time highs. So let us ignore the rhetoric and look at how global markets are performing this year. The S&P500 is up a satisfactory 6.13% but nothing to write home about, more disturbing are the European bourses which are tracking negatively for the year.

For markets to continue growing at the pace of the last few years, we need to see high economic growth prospects. Macro economic data isn’t supporting a growth story, so the fact that markets are not performing on fire despite their highs is a potential warning sign. Take heed.

Bank Liquidity

The ECB report that 25 out of 120 banks did not having sufficient liquidity is damaging not so much in its content but more so in its context. It gives a nervous market something to worry about.

Last week saw the biggest outflow of banking ETFs since 2009 so the market is nervous about the vehicles that have driven this rally.

The Poison we call Debt

Following my previous post about deflation we see a further factor that my add fuel to the deflation fire. Despite increased growth in money supply we see the velocity of money falling off a cliff, why with all this monetary stimulus?

Irving Fisher would not be at all surprised by the current impact of excessive debt since he argued in his famous 1933 paper “The Debt-Deflation Theory of Great Depressions”, that falling money velocity is a symptom of extreme over-indebtedness. Van R. Hoisington and Lacy H. Hunt, Ph.D