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Stock Market: Put a MACD Crossover on your Holiday Shopping List

In late February, the Shanghai stock market reminded us how inter-related the world’s markets are when its 9% plunge reverberated around the world and concluded with the DOW closing down 400 points.  The market recovery started once all three major market indexes (DOW, S&P 500 and NASDAQ) flirted with their 200 Day EMA. 

The July/August credit induced correction ended in the same fashion.  In that case the DOW was stubborn.  It would take it an additional 14 days before it followed the S&P 500 below the dreaded 200 Day EMA.

Continue reading “Stock Market: Put a MACD Crossover on your Holiday Shopping List”

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Using Basket Trading to Get Ahead of the Herd

Wall Street has been advocating diversification forever.  I have my cynical reasons why, but that’s a story for a different day.  However, in certain sectors diversification is necessary.  Gold mining is a great example.  I have been trading these stocks for a number of years.  Apparently a 10-15% meltdown, when least expected, is part of a gold miner’s DNA. On the flip side, since the industry is consolidating 20-30% pops to the upside are not uncommon either. 

Many analysts suggest buying at least 10 stocks to sufficiently protect your self in highly volatile sectors.  Thus, commissions could become excessive if trading multiple sectors in a small account.  Mutual Funds were the first vehicles designed to provide sufficient diversification at a reasonable cost. Exchange Traded Funds (ETF) are Wall Street’s latest incarnation and have become extremely popular.  Their fees are often lower than mutual funds and offer some trading advantages over mutual funds.  ETFs are great, but I contend that the next best thing is already here with basket trading.

Continue reading “Using Basket Trading to Get Ahead of the Herd”

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Real Money Portfolio – Half Year Stats

This thread tracks real trades in one of my portfolios. Refer to backgrounder for more info. 

Here are some interesting half-year stats:

  • Closed trades: 31
  • Winners: 17
  • Losers: 14
  • Fewest Calendar Days in Trade: 1 
  • Most Calendar Days in Trade: 98
  • Average Calendar Days in Trade:  28
  • Largest Winner: 25.6%
  • Largest Loser: -8.9%
  • Closed Return: 5.5%
  • Open Positions Return: 5.4%
  • Closed + Open Return: 10.9%
  • S&P 500 Return: 6.0%

At the half-year point Real Money has outperformed the market 10.9% v. 6.0%, while the number of winners versus losers are virtually even.  Many people are overly concerned with making winning trades.  The secret to outperforming the market is limiting your losses.  If you manage your risk – the rest will take care of itself.

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Trading Thru the Housing Blood Bath

You don’t have to be a brain surgeon to realize that housing market is not going to turn around overnight.  Even the homebuilder CEOs are finally admitting that this environment “sucks.”  Economist Nouriel Roubini has been calling this blood bath for what is for awhile.  I haven’t seen him on Kudlow and Company in awhile.  My guess is that he is a little too bearish for old Larry.

Excuse me as I digress for a moment, but speaking of bears….  Peter Schiff is by far the most bearish guest to ever set foot in CNBC studios.  It cracks me up when they invite him on the show.  In the midst of possibly the most bullish market since 2000, Schiff, a U.S. market bear, is out performing most bulls by investing in foreign securities.  It throws the bulls for a loop in the bull/bear debates as they expect him to sit in a corner eating humble pie.  At the end of the debates, they wish that they were more bearish.  LOL – Sorry, sometimes I write this stuff for my own entertainment.

Back to Nouriel…. Continue reading “Trading Thru the Housing Blood Bath”

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Stalking a Trade Thru the Eyes of a Trader

I am often asked how I determine entries and exits for my trades.  Let’s take a look at a real time example and walk through the process.  It is currently 11:00 AM New York Time on Tuesday June 19, 2007.

First and most importantly, I determine how much risk I am willing to take on a trade.  My preference is to limit risk to 1-2% of my portfolio.  In this example, I will use a portfolio size of $50,000 and limit the risk to 1%.  So that means I am willing to only lose $500 on a trade (1% of $50K).  Continue reading “Stalking a Trade Thru the Eyes of a Trader”