Markets move fast. Prices jump, fall, and recover — sometimes all in a single week. But is there a pattern behind the chaos?
According to the famous Efficient Market Hypothesis, prices should behave like a random walk:
👉 Yesterday’s returns shouldn’t help you predict tomorrow’s.
But is that true around the world?
To find out, I analyzed six major stock markets — one for each continent — and checked whether returns behaved like randomness or whether they showed signs of predictability.
🌍 What I Did
I used one large index for each region:
Oceania: S&P/ASX 50
Europe: EURO STOXX 50
Asia: Nikkei 225
North America: S&P 500
South America: IBOVESPA
Africa: JSE Top 40
Then I tested whether past price movements helped predict future ones by looking at 5-year rolling periods.
If a period showed patterns, that meant the market was behaving less efficiently.
If not, the market was behaving randomly, just as theory suggests.
📊 What I Found
Most developed markets behave almost perfectly efficiently.
Australia: 100% efficient
Europe: 100% efficient
Asia: 99% efficient
North America: 93% efficient
Emerging markets showed more predictability.
South America: 92% efficient
Africa: 80% efficient
In simple terms:
👉 wealthier markets behave more randomly; developing markets leave more patterns behind.
⚠️ But Here’s the Catch
Even when markets do show patterns, it usually happens during:
financial crises
political turbulence
sudden volatility
times when liquidity dries up
In other words:
👉 Markets become predictable exactly when they are too risky to trade.
So even if a pattern appears, exploiting it is extremely difficult.
🧠 Why This Makes Sense
This behaviour fits perfectly with the Adaptive Markets Hypothesis:
Markets act efficiently most of the time
But during stress, human behaviour kicks in
Panic, fear, and liquidity shortages create temporary predictability
And once things calm down, markets return to randomness
Markets are not static machines — they adapt.
🌐 Global Average: Efficiency Wins
I also looked at the time period common to all markets.
When you average everything out?
➡️ The line stays very close to zero.
➡️ Across continents, randomness dominates.
Meaning:
💡 Markets around the world are mostly efficient over time.
✔️ Why This Matters
For investors:
Don’t rely on past returns to predict future ones
Crises are dangerous, not opportunities for easy profit
Long-term discipline still wins
For researchers:
Rolling analysis reveals periods of stress that simpler models miss
Emerging markets need more study — their patterns are meaningful
For policymakers:
Liquidity and market structure shape efficiency
Improving financial infrastructure reduces inefficiencies
📌 Bottom Line
Markets aren’t perfectly random, but they’re close
Predictability appears mostly during crises
Long-run behaviour across the world points strongly toward efficiency
Efficiency isn’t fixed — it adapts with conditions.
And across continents, the story is surprisingly consistent.
Disclaimers & Limitations
The indices used are proxies for each continent.
Autocorrelations were computed over different sample lengths, depending on data availability.
While autocorrelation is an inherent time-series property, comparing windows of unequal historical context may reflect differences in investor behavior across eras.
Serial correlation is a classic test of weak-form EMH, but not the only one.
Additional tests (unit root tests, runs tests, variance-ratio tests, etc.) could strengthen the analysis.
Links
Blog
(1) Google: https://panagiotismoutsiopoulos.blogspot.com/
(2) LinkedIn: https://www.linkedin.com/in/panagiotis-moutsiopoulos/
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