Coronavirus and S&P

It is the first time that I have a situation like this while studying indicators like these ones, so I am going to document what is going on.

The starting snapshot

4 weeks after the historical highest SPX when was at 3400 points this is what happens.

Initial view

  1. The McClellan oscillator seems to decrease the fall, in theory it begins to draw a divergence, which to me it still needs a few days to confirm.
  2. The “strong hand” sales volume is supposed to be decreasing, but the SPX is still down.

Things to watch:

  1. The US senate, congress and the FED agree;
  2. the impact of the COVID-19 in US.

To be updated soon…

Utility Stocks-2020

This article , titled as “Top 10 Utility Stocks For Dividend Growth And Income”, show a table with data of the selected companies. The analysis is very rich and didactic about the data he collects and how he assess it.

To me this table is very good summary. I was thinking about how to retrieve data from different list of companies and have a quick look on dividend growth indicators in a semi-automatic way.

So, how could I do it?

Sources of data

Google Sheets enables you to retrieve data from their page with a nice set of formulas, it’s very easy to retrieve data, the problem is that the amount of data is very limited.

Then I went to https://www.finviz.com/ and I discovered that you can take all different parameters of a given company.

Last but not least, I missed some data, so I went to yahoo finance and I got what I missed.

The sheet

I have build a sheet that tries to:

  • Build quickly a numeric analysis of a list of companies (as in this example utilities companies).
  • Be able to define the data I want to analyze using the map of finviz.com and other related data from yahoo finance.
  • Be able to adequate 5 – 8 indicators oriented to whatever you want to analyze: fundamental analysis on growth, technical analysis, fundamental analysis on revenue and gross margin…

The outcome

This google sheets document contains the analysis I did on the same list of utilities companies.

It’s not as complete and professional analysis as the one done by Eric Landis, but it’s a quick way to discard companies and then focus on a short list.

Things to improve

Some of the parameters do not refresh always in the right way, so from time to time you have to review the tables where the data come from: specially from yahoo finance.

 

 

The Dividend Investing Resource Center

This is a must link I am using since some time, and I wanted to keep it outside of my laptop.

https://www.dripinvesting.org/Tools/Tools.asp

I love the excel with the updated data, specially:

  • The table of changes of the major dividend players, specially those that are “out” of the dividend kings or aristocrats lists.
  • The fact that is in excel, that enables me easily to have the Chowder number.

 

Robinhood App is down

Today, March 2nd 2020 Robinhood application is down. One interesting day to trade as volumes are up, so I cannot do it.

Yes, fees are small, and they are covered by the acceptance of the terms of use, but by this reason I operate with this broker only the R&D portfolio.

Renault

I started this positions some months ago, I read about the company, about the valuation and how things were running in the sector, so I decided to open a long position on it.

After some months with 3 long events the margin was so bad that was over the limit to the protection of my portfolio, so I short it with loss.

Bad move, let’s continue with the method and improving it.

 

 

Trade on Lyft

Abstract

  • Reason to Long = Fall after Q4 results. Results fine, forecast defensive.
  • Target = > 0,8% of long size.
  • Strategy: fall after Earning results. Use of 2 or 3 slots.

Table

Evolution

14/February: second long executed.

Outputs

Reason to Short = To be completed

How was short? = Sell order, Stop-loss order or stop-profit

Postmortem Analysis

 

The perfect trade

Alexander Elder in the book “The new Trading for a Living” comments that you have to know what are the type of trades you want to perform and what are these the perfect moves you are chasing.

So, here is the list of moves and data:

Moving average Crossover tactic:

Dividend King Stumble (tropezón de un rey del dividendo)

More to come when they are shown…

Year 3, trading training Q1

Year 3

This year 3 my goal is to focus on the swing trading and the acquisition of knowledge and experience on this type of trading.

The ideal swings will take only days (no in-day trading at this minute).

Year 3, Quarter 1

As usual these are the goals for this quarter, following the V2MOM model:

  • Vision: organize the trading activities under a framework and specific commands that enable me to long and short stocks. Manage the portfolio of money based on Automatic trading principles.
  • Values: have fun, learn a lot, do practices and more practices.
  • Method: learn about specific trading tactics, learn about the context of the market and finance fundamentals.
  • Obstacles: Time.
  • Measures:
    • Read 2 books.
    • 3 podcasts listened every week, this will be a total of around 39 hours of podcasts.
    • have a tactic plan.
    • Read at least 13 earning reports.
    • Keep track of the portfolio in a weekly basis.
    • Avoid in-day trading.

Death line = 31/March/2020

Results (April, 2020)

  • Read 2 books.
    • The new trading for a living (Alexander Elder).
  • 3 podcasts listened every week, this will be a total of around 39 hours of podcasts = 42 hours.
  • have a tactic plan.
  • Read at least 13 earning reports.
    1. Exxon (XOM)
    2. Simon Property Group (SPG)
    3. DuPont (DD)
    4. Corteva (CTVA)
    5. Unum Group (UNM)
    6. Google (GOOG)
    7. Microsoft (MSFT)
    8. Bristol-Myers Squibb (BMY)
    9. Hanes Brands Inc (HBI)
    10. T Rowe Price (TROW)
  • Keep track of the portfolio in a weekly basis = done
  • Avoid in-day trading = not achieved.

Trading learning year 2

In 2018, I created a Robinhood account and I added 1000$. I had a goal, it was to trade with that money, and learn about how to trade in a systematic way and understand how the environment was going on.

I started slowly, with few amount of moves, practicing on stocks I knew and using the learning I acquired trading with crypto-currencies (year 1).

As the money was limited, I divided the trades in 4 units, so every long event should be around 250$. My initial goal was to obtain a 6% growth through 2019.

I did not want to limit myself to a goal number, as the market would have a direction that I cannot control in 12 months, but I wanted to set a reference and initially it was 6%, then I moved to 10%, then I moved to 25%.

The math result? I did a 40%

This final result was an unexpected result, I started doing individual moves and learning from my previous experience, understanding the SPX behavior and trying to learn from the results. Initially I was psychologically stressed with the situation, but I learned how to handle it and the results started to be positive once I keep the actions aligned to my convictions.

The learning result?

I have learned a lot of things, as in the middle of the process I had no money to trade, or I had problems to be with time in front of the computer, or there were times where the market was not in the conditions I defined to trade. Some of the things I learned:

  • To be as much systematic as possible:
    • defining a set of environmental factors that I checked before to trade.
    • I have defined a set of companies that I use for trading, depending on different conditions.
    • I have been able (not 100% of times) to close the computer and read a book when the conditions where not the right ones.
    • I started to be more systematic after reading Systematic trading 🙂
  • Analysis:
    • Analysis of companies, about how they generate cash-flow, in which part of the cycle they are, etc.
    • I learned how to follow trends (differentiate when market is pushing or is moved by inertia).
    • I learned to focus on quote ranges, not on trends. There is a space where the market is moving, I have tried to focus on that range of realistic moves, focusing on small trades.
  • Act aligned to my convictions, and recognize that I have to be flexible about convictions:
    • I have learned a lot about how bad I am about this. I need to improve a lot if I really want to be successful. To trade with 1000$ is nuts, and when the number will increase I have to be more mature on this area. Let’s say that I am more aware of my problem with early shorts that could gave me bigger returns.
    • I learned that I am mainly a negative skew trader. The good thing is that now I’m aware of that and I’m adding some actions on my habit at the time of adding stop-loss actions.
    • I have to improve better to short on loses before the lose is too high. I have earned an average of 2,32$ per trade, if I remove the 10% of biggest loses I would have obtained an average of 3,78% which is a lot.
    • The thesis I have done have changed with respect the environmental conditions that have been happening. I have used the China-US trade news, brexit, Brent price and euro/dollar exchange as variables to modify my thesis and market behavior.
  • You are managing a portfolio of money, and you have to be consequent with the limits of resources:
    • Sometimes I had no money to trade, when the market was in the best moment to short.
    • I learned to anticipate to the best moments and short some moves with the purpose of doing small margins but have cash for next days.
    • During the last 2 months I was able to do 5 units, as I was over 1200$, so I could trade a little bit more.

Analysis of data

I have done 157 trades during these 12 months.

  • 20 trades were below zero (loses), 137 were over zero (gains).
  • The worst 10% of the trades supposed me to lose 173$. If I would have stopped these loses before I would have earned more. I have to take into account too that the use of stop-loss in the wrong way would have made me to lose some margin on trades that I have finally be over zero.
    • Using pareto principle (six sigma), where solving 20% of the issues you can solve 80% of the consequences, I have added to my habits:
      • Stop losses in a controlled way: do not let the loses to be over the defined range.
      • Use stop loss actions to sell, and in this way not stop the positive trend of a stock.
      • Divide the money in 2 for the longs, so in case of a small negative trend, I use the second part of the money and I reduce the average cost.
  • The average of the earnings have been 2,32$.
  • Without the 10% of the worst trades the average would have been 3,78%.
  • Without the 10% of the best trades the average would have been 1,1%. This is interesting, because reviewing some of the trades, I have realized that I’m not trading with negative skew the 100% of the times. I have progressed to a more positive skew habits.

Distribution of the trades depending on the days that took to open and close a trade:

Best values I traded:

Company Gross marging
GE $78,08
CRM $38,50
CTVA $32,17
BA $28,74
TXN $28,10
MSFT $25,54
INTC $23,33
GIS $19,05
GMRE $18,68
WDAY $18,66

Worst values I traded:

Company Gross margin
PTC $2,02
DUK $1,51
WELL $1,50
CELG $0,93
XOM $0,88
T -$1,52
KO -$6,54
JNJ -$7,82
MMM -$8,67
DWDP -$46,08