What I am reading: Sept. 2, 2015

Recent articles that I found interesting and made me think. For more articles see the quant mashup Quantocracy.

Was Monday’s ETF Collapse Just A Warmup?

“The ETF can’t be more liquid than the underlying, and we know the underlying can become highly illiquid.”

Computers are the new Dumb Money

“Rational, experienced people understood that an ETF with holdings that were down an average of 5% should not have a share price down 30%.”

Avoiding the Big Drawdown: Is Downside Protection Helpful or Heresy?

‘Chasing the Investing Unicorn: Give me “High Returns with Limited Risk”’

Algorithm Aversion — Why people don’t follow the model!

“However, given this knowledge that models beat experts, forecasters still prefer to use the human (expert) prediction as opposed to using the model.”

Good Quant Trading,

What I am reading: July 15, 2015

Recent articles that I found interesting and made me think. For more articles see the quant mashup Quantocracy.

Five Myths About Data-Mining Bias

“Data-mining is widely used nowadays for trading algo development. There are several myths about how to deal with data-mining bias.”

Average Returns, Rarer Than You Think

“During the course of the 89 years covered by the chart, we never had a single year when the annualized compound return was simply the average!”

All Strategies “Blow Up”

“In this article, we will explain why even good strategies must test investors’ ReSolve every now and then in order to deliver long-term excess returns.”

Annual Asset Class Returns

I always love seeing this chart.

Good Quant Trading,

What I am reading: June 10, 2015

Recent articles that I found interesting and made me think. For more articles see the quant mashup Quantocracy.

Tactical Asset Allocation: Beware of Geeks Bearing Formulas

“The first time one can actually realize how good (bad) his chosen backtesting solution is when the strategy is traded live. However I am always amazed how little some traders pay attention to how closely their backtest match their live results.”

Torturing Historical Market Data

“There’s no such thing as right or wrong data, just better or worse. Stock market data looks spotless when you just see the performance numbers, but looks can be deceiving.”

Screw It, I’m All In, Baby

A little humor for your day but oh so true.

Improving the Simple ETF Rotational Trading Model

“What I love about trading models like this is the simplicity. So often simplicity trumps complication. Simple systems often have one important characteristic. They often get you out of the market during bear markets and get you back in to ride the next bull cycle. That is, if you are disciplined enough to actually follow the rules, which of course is another entire topic.“

What I am reading: April 1, 2015

Recent articles that I found interesting and made me think. For more articles see the quant mashup Quantocracy.

99 Problems But A Backtest Ain’t One– “The first time one can actually realize how good (bad) his chosen backtesting solution is when the strategy is traded live. However I am always amazed how little some traders pay attention to how closely their backtest match their live results.”

Torturing Historical Market Data – The first sentence is so true. “There’s no such thing as right or wrong data, just better or worse. Stock market data looks spotless when you just see the performance numbers, but looks can be deceiving.”

Screw It, I’m All In, Baby – A little chart humor but so true.

Improving the Simple ETF Rotational Trading Model – “What I love about trading models like this is the simplicity. So often simplicity trumps complication. Simple systems often have one important characteristic. They often get you out of the market during bear markets and get you back in to ride the next bull cycle. That is, if you are disciplined enough to actually follow the rules, which of course is another entire topic.”

The Martian by Andy Weir – I read maybe one fiction book every 2-3 years. This is a great book. A fun and entertaining read. Be warned you will lose sleep.

Good Quant Trading,

What I am reading: Feb 11, 2015

Recent articles that I found interesting and made me think.

S&P 500 Snapshot: Check out the ‘A Perspective on Drawdowns’ to see how shallow drawdowns have been overall since 2009.

This Is The Best Illustration Of History’s Bull And Bear Markets We’ve Seen Yet – A longer term look at the markets. Our current bull market does not look so great compared to others. I am sucker for pretty charts if you could not tell.

Missing What is Missing – A good TED talk about survivorship bias outside the trading world with plenty of application back to the trading world.

Mindfulness, meditation and investing – I thought that I would never do it but I started practicing mindfulness about 2-3 months ago and have been surprised by thoughts that jump into my head.

Good Quant Trading,

What I am reading: 10/6/2014

Recent articles that I found interesting and made me think.

Learn Math or Get Left Behind

Every now and again, events occur that cause me to shake my head in dismay at people’s math skills. When the weather forecast is a 90 percent chance of a sunshine, and it rains, that doesn’t mean the forecast was wrong; rather, it was one of those cases where the low probability event occurred. Some people seem to believe that 90 percent and 100 percent are the same. Obviously, they are not.

Recall model assumptions before jumping to conclusions

I have written numerous times in this space about the importance of examining your assumptions before taking any action on quantitative research.

Advantages With Mechanical Strategies

A lot of the best traders (at least the ones I know) use some kind of mechanical rules in their trading. “Mechanical” implies that the rules are based on some kind of objective rules, usually quantified data. The trader should follow these rules exactly without hesitation or emotion. In this respect mechanical trading is the complete opposite of discretionary trading.

The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing

In most domains of life, skill and luck seem hopelessly entangled. Different levels of skill and varying degrees of good and bad luck are the realities that shape our lives—yet few of us are adept at accurately distinguishing between the two. Imagine what we could accomplish if we were able to tease out these two threads, examine them, and use the resulting knowledge to make better decisions.

What I am reading: 8/25/2014

Recent articles that I found interesting and made me think.

VIX-Adjusted Momentum

The addition of many small details can make a big difference in seemingly simple strategies. I often like to use cooking analogies, and so I like to think of tomato sauce as a classic example: it contains few ingredients and is simple to make but difficult to master without understanding the interaction between components. Trend-following strategies are no different: anyone can create a simple strategy, few can master the nuances.

Do Risk-Adjusted Returns Matter?

The firm’s latest piece looks at smart beta and a host of factor investing data. One factor they looked into was the small cap anomaly. Past research has shown that small cap stocks have outperformed large cap stocks over longer time frames. Research Affiliates determined that this actually isn’t the case:

The Remarkable Truth about 52-Week High Stocks

On Wall Street, there are many highly publicized metrics that can trigger an emotional response in investors. The “52-week high” signal is a great example. It is a widely reported (e.g., Barron’s, WSJ, MarketWatch) and easily noticed statistic. Stocks at 52-week highs are at their peak versus historical values, and this is, presumably, valuable information. Also, peaks per se are salient, almost by definition, and so we tend to pay a lot of attention to them.

The Market Has Not Seen a Strong Up Day for Longer Than It Has Not Seen a Strong Down Day

Older post. We have recently seen the 2% down day but not a 2% up day.

It is a fact that the S&P 500 hasn’t had a -2% drop in the last 68 days but it also hasn’t had a 2% rise for 193 days. The market has given bears plenty of room to escape.

Frustrated by not being to test your own trading ideas? My AmiBroker & Backtesting 101 course starts in 2 weeks and there is still space left.. Click here to find out more.

Enjoy,

Cesar

What I am reading: 7/28/2014

Recent articles that I found interesting and made me think.

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What I am reading: 6/30/2014

Recent articles that I found interesting.

We’re all Smart

When everyone in your field of choice is intelligent it’s much harder to separate yourself from the crowd.  The paradox of skill is what makes it so difficult to beat the market over time.  Finding undervalued assets isn’t as easy today as it was in the past because there are more smart people who know where to look. …

Trend following does not work on stocks

There’s a good reason why most professionals who apply models similar to trend following to stocks call them momentum models. It’s not just a clever rebranding, it’s really a very different game. To blindly cling to trend following as a religion, disregarding any real world evidence and attacking anyone presenting ideas that differ to the trend following mantra is not only unprofessional, it’s outright dangerous….

Is your risk random?

Your trading model might have a random risk element and you might not even be aware of it. In particular longer term models need special care to avoid ending up with random risk. …

Where Have All the Traders Gone?

What is causing the plunge in trading volume (and volatility)?

Four good reads from the past week

Articles I enjoyed from the past week.

Sophisticated versus Effective

In any field where complexity is part of the discipline (think: finance, technology, etc.) there is a temptation to appear more sophisticated than others. More specifically, the idea is to appear to know the information that other people do not know and to have a certain cleverness about your approach and how you look at problems.

Absolute Returns LOL

If your so-called “Absolute Returns” hedge fund crushed it over the last 18 months, I have two pieces of news for you: A) it’s not really an absolute returns vehicle after all and B) it’s going to crush you when the worm turns, regardless of what you’re counting on it to do.

Volume and Volatility: Why Many Traders Have Not Been Making Money Lately

Here’s an update of a 2009 post, showing how daily volatility in the S&P 500 Index varies as a function of daily volume.  Specifically, we’re looking at daily true range in percentile terms as a function of hundreds of millions of shares in SPY.  What we can see is that, as volume comes out of a market, movement also becomes less.

600 Days Without a 3% Daily Change

It’s been a long time now since the S&P 500 had a big change in a single day. You have to go back to November of 2011 to find the last day that the S&P 500 rose or fell by 3% in one day. Since 1950 there have been 200 trading days out of 16,202 in which the S&P changed by 3% or more, which implies that we get one 3% day for every 81 days.

Testing my next idea is taking longer than expected. Blog post next week on the test.