Skip to main content

Next Week's Earnings Calendar...

Next week will be another busy earnings stretch with some notable names reporting across a myriad of sectors that epitomize the good, the bad and the ugly.

First, the good... biotech has been one of the best performing sectors in a year of general market apathy.  The group will be front and center early next week and here are some of the names to watch:

ESRX  GILD  MRK  PFE  VRTX  AMGN  SGEN 


The bad sectors are kind of like the food at a sports bar... it's all varying degrees of bad but none of it is good.

Let's start with the least bad.  Technology has been a mixed bag thus far with some names showing upside lately (i.e. GOOG and FB).  Other parts of the sector have been burned, however.  Cloud computing and virtual storage stocks have been punished and a strong quarter can do a lot to turn the tide back in their favor.  Here are the names reporting next week:

AKAM  EQIX  TWTR  YELP  FB  WDC  FEYE  LNKD  SSYS  YNDX  STX


The debate surrounding the soundness of Chinese markets has been one story line throughout the second quarter and next week we'll hear from a couple of notable Chinese stocks (or at least stocks that are heavily exposed to China):

BIDU  WYNN


Financials have been a mixed bag... the sector's performance has mirrored that of the overall market.  Financials reporting next week include:

AMT  MA  MET 


Finally, the ugly.  Natural resources and energy stocks have gotten slammed this year as the rising dollar and supply/demand imbalances have caused the sectors to readjust.  Next week, we'll get a look at the toll falling commodity prices have had on corporate bottom lines with the following names:

ARG  APC  NOV  HES  APD  COP  FLR  LINE  MPC  VLO  CVX  XOM  PSX


Other notable names reporting next week include:

CTRP  GPN  SPWR  SCTY  EA  DECK  EXPE  PG  TMUS


With all of the upcoming announcements, it is reasonable to assume that we will see idiosyncratic and systemic volatilites.  Tomorrow, I will outline some trades to try to capture that vol.

Comments

Popular posts from this blog

Modeling Credit Risk...

     Here's a link to a presentation I gave back in August on modeling credit risk.  If anyone would like a copy of the slides, go ahead and drop me a line... https://www.gotostage.com/channel/39b3bd2dd467480a8200e7468c765143/recording/37684fe4e655449f9b473ec796241567/watch      Timeline of the presentation: Presentation Begins:                                                                0:58:00 Logistic Regression:                                                                1:02:00 Recent Trends in Probabilities of Default:                              1:10:20 Machine Learning:                                                                  1:15:00 Merton Structural Model:                                                        1:19:30 Stochastic Asset Simulation Model:                                        1:27:30 T-Year Merton Model:                

Modeling Black-Litterman; Part 1 - Reverse Optimization

  "The 'radical' of one century is the 'conservative' of the next." -Mark Twain In this series, I'm going to explore some of the advances in portfolio management, construction, and modeling since the advent of Harry Markowitz's Nobel Prize winning Modern Portfolio Theory (MPT) in 1952. MPT's mean-variance optimization approach shaped theoretical asset allocation models for decades after its introduction.  However, the theory failed to become an accepted industry practice, so we'll explore why that is and what advances have developed in recent years to address the shortcomings of the original model. The Problems with Markowitz For the purpose of illustrating the benefits of diversification in a simple two-asset portfolio, Markowitz's model was a useful tool in producing optimal weights at each level of assumed risk to create efficient portfolios.   However, in reality, investment portfolios are complex and composed of large numbers of holdin

Evidence the SPY is Overbought...

 A quick note on the recent market rally here of late.  It's plain to see the markets have been on a tear for the month of June (and going back into May for the QQQ) as the SPY closed today at its highest level in almost fourteen months. If we start to look at the historical levels, however, it appears the SPY may be overbought in the short-run and susceptible to a mean-reverting pattern. Here's the daily chart of the SPY as of today's (6/15/23) close... When looking at the distance between the closing price and the 50-day moving average (illustrated by the yellow bar), we're noticing a large gap... this can be measured by a statistic I developed which I casually refer to as "variance"... or the distance between current prices and their respective moving averages. Historically, throughout the life of the SPY (which debuted in January of '93), the variance over the 50-day moving average has peaked at a reading of 3.20... today's reading posts up at 2.49