Appaloosa 1st quarter changes in its portfolio

The other day  I read an interesting article on ZeroHedge (http://www.zerohedge.com/news/2018-05-18/tepper-trounces-competition-outperforms-peers-600-ytd). It was related to the portfolio changes on the Appaloosa’s portfolio. Appaloosa Asset Management is outperforming its peers, this is why I decided to investigate what they are doing differently from the rest. Reading the 13-F from the biggest hedge funds can help you understand how they take the investment decisions. However, you won't be able to know the price in which they entered or exited the positions.

I´ve only focused on the new positions:

Lam Research Corp (LRCX)

    Lam Research Corp, source: TradingView

The strong fundamentals and the high margins will help the stock to go up.

Lam Research Corp ratios, source: TradingView                               

Wells Fargo (WFC)      

    Wells Fargo, source: TradingView

This company has been punished in the markets due to the regulatory constraints. However, it showed earnings that beat expectations. I think Wells Fargo is capable to provide good returns for investors via earnings growth, dividends. The net margins are good and the P/E ratio is better than its sector peers.

UBS Group AG (UBSG)

    UBS AG Group, source: TradingView

This investment brings geographical diversification. It’s the largest global wealth manager and has a large exposure to Asia.  It offers a 4% dividend plus buybacks. It showed the best quarterly results in 3 years on the 23rd April. The lower revenues and rising cost are one of the main concerns. I think investing long term in this company is not a bad idea. However, I would prefer to buy under 15CHF.

Applied Materials (AMAT)

    Applied Materials, source: TradingView

The strong fundamentals are driving the price of this stock higher. The sound financial situation allows the company to increase the investments. The biggest concern at the moment is that the makers of displays and chips to store data in high-end phones are slowing some projects. (The best example is the disappointing sales from the iPhone X)

SMH semiconductor ETF (SMH)

    SMH semiconductor ETF, source: TradingView

This chart shows the incredible performance of this semiconductor ETF. I would like to remind you that I am not an expert on this sector. I can understand the growth from 2013 until now, basically, it has been driven by a strong demand for this devices. When something becomes popular there is two ways of making money:

                -Mass production with the smallest cost possible

                -Limited production of high performance devices

At this point is up to the clients. Will we see strong demand in the best devices out there? (We have seen disappointing sales in some of them) Will the price of these devices decrease ? If so, the net margins will do as well and their rating will be downgraded. I’m not saying that is a bad investment, I have only expressed my point of view.

ALPS ETF

There are 16 ETFs listed under this asset management. I believe that they use for diversification purposes. 

Knight Swift (KNX)

    Knight Swift, source: TradingView

This company has great fundamentals. The financial leverage is really small. The main concern is to hire and retain truck drivers as the company said when the 1st quarter earnings were released.

Boyd Gaming (BYD)

    Boyd Gaming, source: TradingView

It has good fundamentals for a short-term investment. The resistance is around 40 so it doesn’t have a lot of upside potential (in the short-term). The analysts think that this kind of business has one of the lowest growth prospects.

Platform Speciality Prods Cor (PAH)

    Platform Speciality Prods Corp, source: TradingView

It has an attractive P/E ratio and upside potential. I believe that Appaloosa bought under 10. One of the biggest problems is the financial situation.

United Contl Hldgs Inc (UAL)

    United Continental Holdings, source: TradingView

The enterprise value to sales under 0.80 and the P/E under 10 make it attractive for investors.

Nvidia (NVDA)

    Nvidia, source: TradingView

Nvidia is a successful company that its share price can continue to rise in the following year. The sales growth forecast is positive for the next years and if we consider that the margins are high, we will see this stock higher.

Sum Up

Today’s article has been different from the other ones. I haven’t analyzed all the stocks properly but I’ve given a quick overview. In the case of the stocks above, they have good fundamentals and some of them are down around 20% from the last max. If the market continues rising, Appaloosa will deliver a strong performance.

As I said, we can learn a lot with the 13 F even if we don’t know the prices in which the trades were executed.  Obviously, we should do our own research but we can compare if some of the biggest funds are taking the same positions. Another thing to consider, that I haven´t mentioned, is the type of investor, maybe they are looking for a short-term investment while you can be considering a longer time frame.

Have a good trading!!

Disclaimer

I wrote this article myself, and it expresses my own opinions that shouldn't be used as a trading advice. Trading carries considerable risk due to the high leverage involved

FANG Stocks, tech portfolio

Everyone knows about the FANG stocks rally. But what does FANG mean? It’s a group of technology stocks, Facebook, Amazon, Netflix, and Google. If we look back to the beginning of 2015, we would regret not having invested in these stocks. Please bear in mind that it’s my first article using Python, so it can seem a little bit simple.

Stocks summary

Facebook

       Facebook stock, own elaboration with python and Quandl

Facebook is the biggest social network. It enables users to share opinions, ideas, photos, videos, and other activities online. It´s involved in the development of social media applications for people to connect through electronic devices. Its products include Facebook, Instagram, Messenger, WhatsApp, and Oculus. The revenue comes mainly from advertising.

Amazon

         Amazon stock, own elaboration with python and Quandl

It´s engaged in the provision of online retail shopping services  The efficiency of its distribution centers makes difficult to compete with Amazon. In addition, they have Amazon Web that it’s focused on the global sales of computing, storage, database, and AWS service offerings for start-ups, enterprises, government agencies, and academic institutions.

Netflix

        Netflix stock, own elaboration with python and Quandl

This company provides subscription service streaming movies and TV episodes over the Internet and sending DVDs by mail. Netflix obtains content from various studios and other content providers through fixed-fee licenses, revenue sharing agreements and direct purchases.

Google

        Google stock, own elaboration with python and Quandl

Alphabet operates as a holding company with interests in software, health care, transportation and other technologies. It operates through 2 segments: Google and Other Bets segments. The first one includes the following services: Search, Ads, Commerce, Maps, YouTube, Apps, Cloud, Android, Chrome, Google Play as well as hardware products, such as Chromecast, Chromebooks, and Nexus. The other one includes: as Access or Google Fiber, Calico, Nest, Verily, GV, Google Capital, X, and other initiatives.

Individual Stocks

At this point, I believe that you have your own preferences but let´s imagine that we are in 2015. Wouldn’t be better to create a portfolio with all of them?  Also, it´s another way to diversify our portfolio

    Log returns own elaboration using python

We can see how the individual stocks performed in the period. As you can see Netflix has been the more volatile. 

                                                                 Arithmetic Returns of the individual stocks

Google was the worst performer but it doubled in value. I would like to remind you that the Nasdaq index has returned 63% since 2015.

Before we put together all these stocks, let´s check the individual distributions:

             Log return distributions own elaboration

All of them have in common that the extreme observations are positive, which explains in part the reason of the rise in these stocks.

The Portfolio

After reviewing these companies and considering that they have different business units, we decide to create a portfolio. In order to make it simple, we can assign the same weight for each stock, in this case 25% of the initial capital. 

     Portfolio statistics and log returns distribution own elaboration

Considering the long run and this portfolio´ strategy (buy and hold), it´s easy to think that the majority of the daily returns are bigger than zero. This is confirmed by the chart above.

Is it safe to build a portfolio like we have done?  No, some of the reasons are that it´s not properly diversified and the correlation between the assets is positive. Luckily the companies have diversified some of their activities and they are heavily investing in technology which will bring revenue in the future. 
The portfolio return has been 104%.

                                                            Portfolio return own elaboration

Now it's the time to check the risk:

    Portfolio drawdown history, own elaboration

One of my favourites risk metrics is the drawdown. I created this chart showing the portfolio drawdown over the time. The maximum drawdown was 14.10%. This figure surprised me but the main concern is that the stock market raised on a daily basis

Sum up

I hope you like it. We have seen how the main tech portfolio has behaved since 2015. I wouldn’t invest in this kind of portfolio for the reasons mentioned above. In addition, I think that the index rally has been supported by an accommodative monetary policy. Using Python and Quandl has been great and I hope to bring more content in the future. Thanks.

Have a good trading!!

Disclaimer

I wrote this article myself, and it expresses my own opinions that shouldn't be used as a trading advice. Trading carries considerable risk due to the high leverage involved

#Alphabet #Amazon #drawdown #Facebook #FANG #Google #investing #maxdrawdown #Netflix #portfolio #python #quandl #stocks #Trading

Trading system based on a proprietary indicator Part 1

This is a new concept. I will do three parts to analyze the trading system in a better way and compare it with a benchmark. The idea is introducing the trading system, showing the backtesting (last 5 years), comparing with the 10 years backtesting, studying the system vs the benchmark and applying money management to see how the performance and risk parameters change.

Brief explanation of the trading system

The system is based on a proprietary indicator as you can see in the title. The idea behind this system is mean reversion. The levels are chosen from the study of the returns’ distribution. Does it sound familiar to you? In addition, a strict risk management system has been applied. The maximum loss allowed is 0.5% as we will see in the next points. The trading system trades 1000 shares in each trade (in the future I will apply money management) The initial portfolio

 

Results after the last 5 years (backtesting)

     Backtesting statistics from RStudio and Excel, own elaboration

As you can see the system makes 95.86 euros on average per trade. I would like to make clear that the system traded 133 trades and the commissions are not included. The maximum profit in a trade was 1650 euros while the biggest loss was limited to 100 euros.  The return was 12750 euros which is the equivalent of 63.75% in 5 years (around 12.75% per year). As you can imagine, considering the strict risk management, the losing trades percentage is higher than the winning trades percentage. But the average winner is higher than the average loss. The Sharpe Ratio is 4.32, which confirms the profitability of the system.

                                  Max Drawdown, own elaboration using RStudio

This is the measure that I like the most. The system only loses 925 euros in the worst trading period. If we check in percentage terms, it represents a 3.53% loss. According to the asymmetrical leverage rule with a gain of 3.57%, we offset the loss. This shows the importance of risk management.

      Trading system track record, own elaboration using RStudio

Here you can see how the portfolio has been performing. The most important is its consistency.

As a curiosity, performance comparison with different initial capital

With these numbers, we would be tempted to invest 5000 euros or less. The system doesn’t require a lot of capital. The main problem with a 5000 portfolio is that we will struggle because the costs are not included and we couldn´t trade 1000 shares each time.

Conclusion

This has been the first part of a series of posts about the same trading system. In my opinion, the performance and the risk metrics are good. In the next post, I will review the 10 years backtest. The purpose of that is to check that the system hasn´t been overfitted for the last 5 years and show how it performed in a longer period. I hope that you like it.

Have a good trading!!

Disclaimer

I wrote this article myself, and it expresses my own opinions that shouldn't be used as a trading advice. Trading carries considerable risk due to the high leverage involved