Jump to content

Welcome to the new Traders Laboratory! Please bear with us as we finish the migration over the next few days. If you find any issues, want to leave feedback, get in touch with us, or offer suggestions please post to the Support forum here.

  • Welcome Guests

    Welcome. You are currently viewing the forum as a guest which does not give you access to all the great features at Traders Laboratory such as interacting with members, access to all forums, downloading attachments, and eligibility to win free giveaways. Registration is fast, simple and absolutely free. Create a FREE Traders Laboratory account here.

Do Or Die

Stationarity and Trading Regimes

Recommended Posts

Previous article in this series are: Trend Following Vs Mean Reversion: Trading Regimes, Introduction to Understanding Volatility, Trading Regime Analysis Using RSI, Trading Regime Analysis Using RWI, Trading Regime Analysis Using Chart Patterns- Part 1, and Trading Regime Analysis Using Chart Patterns- Part 2.

 

People spend most of the time trying to ‘find’ a better indicator but it is ironic that very little time is spent to analyze phases in which a particular indicator works well and how these phases change.

 

Stationarity is the statistician’s term for regimes in price behavior. It is defined as a lookback period for which the averages and other statistics (e.g. flux densities, variances) do not change over time. For example, range-bound markets where tops and bottom tend to appear after predictable drift. Non-stationarity implies that the characteristics of sample data change from time to time. Now the fact is that markets move in cycles of low-stationarity to high-stationarity.

 

To expect an indicator (for example, moving average or ‘double top’) to perform consistently over time is a capital mistake because it assumes stationarity in market prices. If you study a pattern’s forecasting ability in 2010 and expect that ability to remain same in 2011 irrespective of market characteristics in 2011, it simply does not make sense. There is a fundamental uncertainty in price behavior. You can never tell if the trading regime will shift with your next trade (except ofcourse, if you are a vendor who needs to prove his accuracy). This is also why trade/risk management becomes very important- ability to handle losing trades. From the technical analysis side, it also implies the ability to quickly ‘adjust’ to the market.

 

So if I’m using a strategy- say the ubiquitous moving average crossover, the consistency of its profitability depends upon the stationarity cycle of the market. The ‘amount’ of stationarity over a lookback period depends over time frames and instruments. For example, stationarity on intraday time frames in stocks is far less than stationarity on intraday time frame in DJI. In general, stationarity on EOD time frames tends to more than the stationarity on intraday timeframes. It makes sense to chose a time frame on which you are quick to identify the phases of high stationarity.

 

Measuring Stationarity and Identifying Stable Stationary Cycles

 

For day-to-day trading, the focus is to find longest lookback period for which the market exhibits high amount of stationarity. Now the first important question is, how you measure stationarity. Dr. Steenbarger suggests the ‘dirty’ t-test which can be achieved in MS Excel via TTEST function. T-test is a poor approximation for stationarity, but a good start. You can divide the time series into two halves and see how closer the t-test is to zero (the distributions are similar during that lookback period). The process will be repetitive to find the optimal window for a phase of high stationarity.

 

Once you have the window, confirm the behavior of a trading indicator/strategy during that time. Check if they respond well to price swing highs and lows and the optimal stops/drawdown for such strategy. Finally, start trading with this strategy until the profitability starts coming down (which means the trading regime is shifting).

 

As previously questioned, some may think this is curve-fitting. To quote Dr. Steenbarger:

My response is that optimization is only a problem when you fail to take stationarity into account. If you know you are trading within a stable regime, it makes sense to do your best to capture the rules the market is following over that period. My swing trading methodology might best be described as serial optimization: continually hunting for periods of stationary market behavior and trading optimized models derived from those periods.
…Perhaps this is why we see so few traders incorporating stationarity into their analyses: It is time-consuming to assess market windows, operative trading rules, and test strategies for exploiting those rules. It is easier—and far more beguiling—to assume that a single system or indicator will produce consistent profits. More than one person has encouraged me to make my writing, research, and trading strategies less complex so that they can be more readily understood and accepted by the bulk of traders who attend seminars, buy trading books, and hire gurus for advice.

 

Using historical backtests you can determine regimes in which you strategy works best. For example, test over 10,000 bars of history to test how long and how frequent were the windows in which the strategy trades profitability. This increases your confidence in strategy and your task remains to identify (future) regime phases in which your strategy works good.

The next important question is to identify short-term non-stationarities which indicate a regime change. This depends on how you measure stationarity, as well the particular regimes you want to identify. Compare this chart to the third chart in Trading Regime Analysis Using RSI icon12.gif

 

 

attachment.php?attachmentid=26088&stc=1&d=1315641565

pep.thumb.png.6d9c722630db9d00587d9c6f6d3357c9.png

Share this post


Link to post
Share on other sites

Hi Zdo, I'm not sure if I understand you correctly.

 

The way I define a 'trading regime' is- a phase when particular strategy consistently outperforms/underperforms. Trading regimes can be identified in certain time intervals and certain instruments.

 

In this market approach- indicators, patterns, and methods of analysis are just 'windows' to see the market. For example take the 20 period MA- if it's sloping upwards you can say market is trending upwards; if prices are too far from the MA you can say they are due for correction and so on. A trading strategy can formed with this window with buy-sell rules.

 

So a trading regime is a phase when a particular window captures most of price behavior, and its associated strategy is significantly profitable. The strategy itself could be trend following, mean reversion, momentum buying, breakouts and so on. For example, some stocks will show more profitability in breakout trading than others. This can be backtested per 100 breakouts on 15 min time frame (say).

 

Gong away from a mean or coming back to mean should solely depend upon how the mean is defined. A trading regime can be defined and backtested based on this analysis method.

Share this post


Link to post
Share on other sites

I will recommend the book "Trading Regime Analysis: The Probability of Volatility" for discretionary traders. The good part is that it clarifies the concepts and provides many ideas. The other side is that the book is verbose.

Share this post


Link to post
Share on other sites

Join the conversation

You can post now and register later. If you have an account, sign in now to post with your account.
Note: Your post will require moderator approval before it will be visible.

Guest
Reply to this topic...

×   Pasted as rich text.   Paste as plain text instead

  Only 75 emoji are allowed.

×   Your link has been automatically embedded.   Display as a link instead

×   Your previous content has been restored.   Clear editor

×   You cannot paste images directly. Upload or insert images from URL.


  • Topics

  • Posts

    • Back in the early 2000s, Netflix mailed DVDs to subscribers.   It wasn’t sexy—but it was smart. No late fees. No driving to Blockbuster.   People subscribed because they were lazy. Investors bought the stock because they realized everyone else is lazy too.   Those who saw the future in that red envelope? They could’ve caught a 10,000%+ move.   Another story…   Back in the mid-2000s, Amazon launched Prime.   It wasn’t flashy—but it was fast.   Free two-day shipping. No minimums. No hassle.   People subscribed because they were impatient. Investors bought the stock because they realized everyone hates waiting.   Those who saw the future in that speedy little yellow button? They could’ve caught another 10,000%+ move.   Finally…   Back in 2011, Bitcoin was trading under $10.   It wasn’t regulated—but it worked.   No bank. No middleman. Just wallet to wallet.   People used it to send money. Investors bought it because they saw the potential.   Those who saw something glimmering in that strange orange coin? They could’ve caught a 100,000%+ move.   The people who made those calls weren’t fortune tellers. They just noticed something simple before others did.   A better way. A quiet shift. A small edge. An asymmetric bet.   The red envelope fixed late fees. The yellow button fixed waiting. The orange coin gave billions a choice.   Of course, these types of gains are rare. And they happen only once in a blue moon. That’s exactly why it’s important to notice when the conditions start to look familiar.   Not after the move. Not once it's on CNBC. But in the quiet build-up— before the surface breaks.   Enter the Blue Button Please read more here: https://altucherconfidential.com/posts/netflix-amazon-bitcoin-blue  Profits from free accurate cryptos signals: https://www.predictmag.com/ 
    • What These Attacks Look Like There are several ways you could get hacked. And the threats compound by the day.   Here’s a quick rundown:   Phishing: Fake emails from your “bank.” Click the link, give your password—game over.   Ransomware: Malware that locks your files and demands crypto. Pay up, or it’s gone.   DDoS: Overwhelm a website with traffic until it crashes. Like 10,000 bots blocking the door. Often used by nations.   Man-in-the-Middle: Hackers intercept your messages on public WiFi and read or change them.   Social Engineering: Hackers pose as IT or drop infected USB drives labeled “Payroll.”   You don’t need to be “important” to be a target.   You just need to be online.   What You Can Do (Without Buying a Bunker) You don’t have to be tech-savvy.   You just need to stop being low-hanging fruit.   Here’s how:   Use a YubiKey (physical passkey device) or Authenticator app – Ditch text message 2FA. SIM swaps are real. Hackers often have people on the inside at telecom companies.   Use a password manager (with Yubikey) – One unique password per account. Stop using your dog’s name.   Update your devices – Those annoying updates patch real security holes. Use them.   Back up your files – If ransomware hits, you don’t want your important documents held hostage.   Avoid public WiFi for sensitive stuff – Or use a VPN.   Think before you click – Emails that feel “urgent” are often fake. Go to the websites manually for confirmation.   Consider Starlink in case the internet goes down – I think it’s time for me to make the leap. Don’t Panic. Prepare. (Then Invest.)   I spent an hour in that basement bar reading about cyberattacks—and watching real-world systems fall apart like dominos.   The internet going down used to be an inconvenience. Now, it’s a warning.   Cyberwar isn’t coming. It’s here.   And the next time your internet goes out, it might not just be your router.   Don’t panic. Prepare.   And maybe keep a backup plan in your back pocket. Like a local basement bar with good bourbon—and working WiFi.   As usual, we’re on the lookout for more opportunities in cybersecurity. Stay tuned.   Author: Chris Campbell (AltucherConfidential) Profits from free accurate cryptos signals: https://www.predictmag.com/   
    • DUMBSHELL:  re the automation of corruption ---  200,000 "Science Papers" in academic journal database PubMed may have been AI-generated with errors, hallucinations and false sourcing 
    • Does any crypto exchanges get banned in your country? How's about other as Bybit, Kraken, MEXC, OKX?
    • Does any crypto exchanges get banned in your country? How's about other as Bybit, Kraken, MEXC, OKX?
×
×
  • Create New...

Important Information

By using this site, you agree to our Terms of Use.