Meeting on 8/20/17 at 5pm, San Francisco

Our next meeting is scheduled for 8/20/17 (Sunday) at 5pm in San Francisco on the 2nd floor lounge of the Marriott Marquis (780 Mission Street).  See here for more information about the venue. Once you enter the hotel, go to the 2nd floor using the escalator and you will see a lounge with sofas and tables. Feel free to send an email if you have trouble finding it.

We will be having a discussion on an analysis of the size premium of small-cap and micro-cap stocks. See here for paper.

Advertisements

Size Matters, If You Control Your Junk

Yes, that is the actual title of the paper. And it actually has some meaningful, interesting results.

From the abstract:

“The size premium has been challenged along many fronts: it has a weak historical record, varies significantly over time, in particular weakening after its discovery in the early 1980s, is concentrated among micro-cap stocks, predominantly resides in January, is not present for measures of size that do not rely on market prices, is weak internationally, and is subsumed by proxies for illiquidity. We find, however, that these challenges are dismantled when controlling for the quality, or the inverse “junk”, of a firm. A significant size premium emerges, which is stable through time.”

“Size Matters, If You Control Your Junk”, Clifford Asness, Andrea Frazzini, Ronen Israel, Tobias Moskowitz, Lasse Pederson, Feb 2017

See here for paper.

Meeting on 8/6/17 in San Francisco, 5:00pm

Our next meeting is scheduled for 8/6/17 (Sunday) at 5pm in San Francisco on the 2nd floor lounge of the Marriott Marquis (780 Mission Street).  See here for more information about the venue. Once you enter the hotel, go to the 2nd floor using the escalator and you will see a lounge with sofas and tables. Feel free to send an email if you have trouble finding it.

Our agenda for next time:

  1. Continue discussion on wavelets.
  2. Discuss paper listed here.
  3. Discuss Mandelbrot’s book, “Misbehavior of Markets, A Fractal View of Turbulence”, Benoit Mandelbrot.

Feel free to comment below with your questions.

Application of Wavelets to estimate the Fractal Dimension of the S&P 500

from abstract:

“S&P 500 index data sampled at one-minute intervals over the course of 11.5 years (January 1989- May 2000) is analyzed, and in particular the Hurst parameter over segments of stationarity (the time period over which the Hurst parameter is almost constant) is estimated. An asymptotically unbiased and efficient estimator using the log-scale spectrum is employed. The estimator is asymptotically Gaussian and the variance of the estimate that is obtained from a data segment of N points is of order 1 N . Wavelet analysis is tailor made for the high frequency data set, since it has low computational complexity due to the pyramidal algorithm for computing the detail coefficients. This estimator is robust to additive non-stationarities, and here it is shown to exhibit some degree of robustness to multiplicative non-stationarities, such as seasonalities and volatility persistence, as well. This analysis shows that the market became more efficient in the period 1997-2000.” See here.

“Estimating the Fractal Dimension of the S&P 500 Index using Wavelet Analysis.” Erhan Bayraktar, H. Vincent Poor , K. Ronnie Sircar, June 2002; revised December 2003

Wavelet Multi-scale Analysis for Hedge Funds: Scaling and Strategies

This paper applies wavelets to measure the market risk (via correlation) of various popular hedge fund strategies at varying time scales. We might be able to adapt this technique for the objective of our next meeting.

Abstract: “The wide acceptance of Hedge Funds by Institutional Investors and Pension Funds has led to an explosive growth in assets under management. These investors are drawn to Hedge Funds due to the seemingly low correlation with traditional investments and the attractive returns. The correlations and market risk (the Beta in the Capital Asset Pricing Model) of Hedge Funds are generally calculated using monthly returns data, which may produce misleading results as Hedge Funds often hold illiquid exchange-traded securities or difficult to price over-the-counter securities. In this paper, the Maximum Overlap Discrete Wavelet Transform (MODWT) is applied to measure the scaling properties of Hedge Fund correlation and market risk with respect to the S&P 500. It is found that the level of correlation and market risk varies greatly according to the strategy studied and the time scale examined. Finally, the effects of scaling properties on the risk profile of a portfolio made up of Hedge Funds is studied using correlation matrices calculated over different time horizons.”

Link here.

 

 

Meeting on 7/16/17 in San Francisco, 5:00pm

Our next meeting is scheduled for 7/16/17 (Sunday) at 5pm in San Francisco on the 2nd floor lounge of the Marriott Marquis (780 Mission Street).  See here for more information about the venue. Once you enter the hotel, go to the 2nd floor using the escalator and you will see a lounge with sofas and tables. Feel free to send an email if you have trouble finding it.

Our goal for next time is to create a simple wavelet model and apply it to the Mandelbrot market model:

  1. Find a candidate historical time-series dataset of some traded asset.
  2. Select and implement a simple wavelet model.
  3. Attempt to replicate the findings in the Berghorn paper.

Feel free to comment below with your questions.

Updated: Meeting on 7/2/17 in San Francisco, 5:00pm

Given the parade on Sunday and related festivities downtown, I’m going to delay our meeting by one week:

Our next meeting is scheduled for 7/2/17 (Sunday) at 5pm in San Francisco on the 2nd floor lounge of the Marriott Marquis (780 Mission Street).  See here for more information about the venue. Once you enter the hotel, go to the 2nd floor using the escalator and you will see a lounge with sofas and tables. Feel free to send an email if you have trouble finding it.

We will be having a discussion on Mandelbrot’s market model for momentum effects. See this post.