My original plan was to post a study on Time Diversification like the previous study posts. Actually I think this post will provide more value. I will try to get the study out on next weekend post.
Today's post covers an important topic that is often glossed over but critical. IMO a good part of trading involves knowing the environment we are in, context around the trade and making quality decisions. Now all these three factors depend (besides psychology) a lot on quality of data available to us and the time spent on analysis. This is one reason many of us spend a large part of time shifting through lot of data.
Problem is there is so much information on net and most of it is not that good. So we end up spending most of our precious time either on finding information (or) shifting through available information to find nuggets in haystack. This actually hurts our trading in multiple ways like cutting into time available for analysis to understand the environment & context, getting influenced by useless stuff while searching for nuggets etc.
I got tired of this i.e., going to multiple sites inefficiently and shifting through to keep myself updated on what's happening with markets, what is driving, what is the mood, various experts perspectives (more better if the perspectives contradict ours) etc. Also the linear nature of newsreaders are more annoying than useful.
So I created some tools for my own use a while back. My experience and the feedback I got was it is very useful and convenient. So I decided to convert into a
site and share it with others. You will see the site is clean i.e., no ads or selling of services etc. The ReadMe page on the site describes how I use it to get an idea of environment, context and answer to other questions listed on the site.
If you find the site useful for your trading/investing then please share it with others. I would not have found some blogs included in the site currently without sharing first. Also if you are tech savvy and would like to contribute then please let me know. I have some technical questions.
It looks like last couple of posts were
not completely included in the email for email based subscribers. For example, "Study: Strategy diversification" has much more content along with graph then what was included in the email. I suspect the problem is with RSS feed settings. I will fix it tonight. Thanks again for subscribing to ATraderJournal blog.
Often when people think of diversification, the primary consideration is asset diversification. One challenge with asset diversification is in recent years most assets are highly correlated. I think there are low hanging fruit available to traders like strategy and time diversification which are more robust in providing diversification, are simple and compliment well any asset diversification.
This study is about measuring performance of swing trading setup by trend direction and strength. The later part is bit tricky. The problem is standard indicators like ADX, ROC, Z-Score etc are not pure trend strength indicators. They implicitly include the effects of market volatility.
Probably that may be ok for regular trading but for this test my desire is to isolate the trend regime impact on swing trading performance and measure it. So for the test I leveraged a trend indicator (ATS) based off my proprietary work in past.
Different market regimes favor different types of strategies. Some regimes favor trend following strategies while other regimes favor mean reversion strategies. Similarly some market regimes favor growth strategies whereas other regimes favor value based strategies. Similarly some regimes favor following crowd while other regimes favor going against crowd.
Also within each regime the performance of strategies varies.
I think knowing systematically what kind of market regime we are in and what type of strategies will be favored and by how much will be extremely helpful on several fronts.
Following tables has the results of a mean reversion strategy categorized by different levels (deciles) of market volatility for 3 markets - SPY, QQQ, DIA. (1990 - July 2012).
Traditionally when people think of diversification, we approach from asset class diversification perspective. A big problem with this approach is the portfolio risk protection (i.e., diversification) disappears exactly when it is needed most like during regime shifts that happened in 2000 or 2008. The reason being whenever major market drops happen, most assets become highly correlated making diversification not effective. Actually I think substantial increase in correlation of typically diverse asset classes is good indicator that a regime shift is underway.
So how do one address this issue? Following is a good paper that approaches diversification from risk factor perspective. On average, correlations across risk factors are lower than correlations across asset classes, and risk factor correlations tend to be more robust to regime shifts.
Diversification - the only free lunch in finance!
Markets can be relatively stable at some points in time and explosively volatile at others. This means that the risk associated with a traditional (fixed-weight) strategic asset allocation policy can be highly variable over time. This paper explores the possibility of a dynamic asset allocation policy that varies as market volatility changes. The conclusion of the paper is that a volatility responsive asset allocation policy can lead to a more consistent outcome and a better trade-off between risk and return.
One thought I had from this paper that I felt would be interesting to traders is - How about overweighting mean reversion setups when market volatility is high and breakout methods when volatility is low? Mean reversion works better when market has good swings (i.e., high volatility). Now many traders use volatility or ATR in bet sizing for valid reasons. But this makes the position size for MR methods small when volatility is high i.e., exactly when environment is conducive to the method.
Feel free to let me know any corrections to above or your thoughts.
We're quite volatile as individuals, but that doesn't work exponentially when we are together. Relationships are about eating humble pie ~ Unknown
High correlations affect traders and investors several ways. It makes diversification less effective at reducing portfolio risk, and it makes correctly sizing positions and managing risk increasingly important. Most people think of correlation as a single number; however, a single number cannot capture the dynamic nature of correlation.
One reason for a dynamic approach to correlation is that correlations can change as fundamental market forces change. The below article discusses capturing correlation from a rolling period perspective. Similarly another problem with traditional measures of correlation is they are treated as linear relation between the assets. But correlations are dependent on how well the assets themselves are behaving. The articles discusses capturing this aspect (non linear relationship) via scatter plots.
Let me know any other interesting methods you come across to capture correlations between assets. Article link:
Correlations
"Correlation does not imply causation"
