Hey! I’m doing a short anonymous school research survey on how short-form content (TikTok/Reels/Shorts) affects attention span and study habits in students.
It takes less than 5 mins so I would really appreciate your response so much 🙏
Link: https://forms.gle/wQRfW21Tp422vfEw7
Thank you!!
Hi r/BehavioralEconomics,
I'm running a study for my bachelor's thesis on cooperative behaviour in an iterated trust game.
The protocol: Pre-survey (~2 min): demographics, prior gaming/AI experience, ATAI (Sindermann et al., 2021), WVS generalised trust item, attention check
10-round iterated trust task with a partner, gamified in a space-smuggler setting (~6–8 min)
Post-survey (~2 min): manipulation check, outcome Likerts, attention check, optional open text
Full debriefing at the end disclosing the design
Total: ~12–18 min. Adults 18+. Available in English, German, and Romanian.
Privacy: Fully anonymous (no name, email, or IP collected). GDPR-compliant, EU-hosted (Supabase). Data can be withdrawn at any point during the session.
Link: https://splitthespice.maximilianzimmer.com
Happy to discuss methodology and design choices in comments after you've participated, keeping things neutral here to avoid priming. Thanks!
Most novice investors lose money not because they chose the wrong stock. They lose money because of the way they think about money.
Having looked at thousands of investing journeys, the same mental traps repeat themselves over and over. These are the 7 that do the most damage — and what they really look like in real life.
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1. FOMO – Fear Of Missing Out
What it looks like: You’ve ignored Bitcoin for years. It mooned. You purchase at the peak.
The trap is to trade on price action instead of fundamentals. By the time something is "everywhere" the easy money is usually gone.
Ask yourself: "would I buy this if no one was talking about it?
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2. Loss Aversion
The way it looks: You sell winners early to “lock in profits” but never sell losers because selling feels like admitting a mistake.
The trap: Losses are twice as painful as equivalent gains are good (Kahneman & Tversky, 1979). So you do irrational things to not feel that pain.
Catch yourself thinking, “Am I holding this because I believe in it, or because I can't face the loss?”
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3. Confirmation Bias
What it looks like: You do some research on a stock, like what you see, then spend the next hour reading only the bullish takes.
The trap: Your brain filters information to affirm what it already wants to believe. The bearish case is not getting a fair hearing.
Do your homework: before you buy, try to find the best argument *against* your position.
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4. The Overconfidence Effect
What it looks like: You make 3 good trades in a row and begin to think you’ve figured something out.
The trap: Markets are full of luck in the short-term results. Overconfidence means bigger positions, less diversification, and eventually a wipeout.
Catch yourself: Keep a track of your actual decisions and their results for at least 20+ trades before you reach any conclusions.
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5. Ancoragem
What it looks like: $200 was stock. Now it’s 80 bucks. You think it's 'cheap' -- but the original $200 was never a meaningful reference.
The trap: your brain latches onto an arbitrary number (the all time high, the price you paid, a round number) and makes decisions relative to that.
Don't look at what the stock "was" and see what it is *today* with the current data. Catch yourself.
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6. Crowd Psychology
What it is: Everyone on Reddit/Twitter/your group chat is investing in something. You don’t want to be the one who missed out.
The trap: Markets are mostly rational over the long run, but crowds can remain irrational longer than you can remain solvent. This bias explains the existence of meme stocks.
Catch yourself thinking, “If this wasn’t trending, would I still want it?”
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7. Recency Bias
What it looks like: Markets have been up for 18 months so you think they will be up forever. Or they crash and you think it will never recover.
The trap: Whatever just happened feels like the new normal It’s almost never.
Catch yourself: Look at 10, 20, 30 year charts before making any big allocation decision.
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The brutal truth:
Knowing these biases does not make you immune to them. The point isn’t to eliminate emotion from investing – but to build a process that doesn’t rely on you being emotionally perfect in the moment.
That’s why rules-based investing (automatic contributions, pre-set rebalancing, written criteria for buying and selling) always trumps discretionary decisions over the long haul.
Which of these have you found yourself doing? Really curious which is the hardest to shake.
Halving is attempting to think like a long-term investor. But his emotional responses remain synchronized with short-term volatility. The strategy changed faster than the nervous system.
Maybe the interesting part is that most people only notice the value of these tiny amounts once they see them accumulated.
Most people ignore the tiny numbers sitting to the right of their account balance.
0.03, 0.11, 0.27… amounts so small they usually feel meaningless.
I want to run a simple experiment:
To see how much real value can emerge purely from digital financial leftovers that people normally ignore.
I’m not looking for large amounts.
In fact, the whole idea only works because these are tiny fractions most people don’t even perceive as real money.
I’ll document how much can accumulate and what it eventually becomes over time.
If anyone wants to participate, feel free to DM me and I’ll share where to send any tiny leftover amount you normally wouldn’t use.
Loss aversion isn't a personality flaw. It's 200,000 year old evolutionary hardware running on modern problems it was never designed for.
Made a video breaking down the actual science.
Feedback welcome from people who know this stuff.
I was recently admitted to Carnegie Mellon and planning to pursue Econ.
Cmu is one of only handful schools that offer an undergrad degree in behavioral economics, but curious whether this path is rlly worth it.
what are your thoughts on Behavioral economics in terms of career outcomes?
Given the strong resources at CMU in business/cs/stem, should I study simply economics at their business school?
Imposter syndrome maps surprisingly well onto several well-documented biases like reverse Dunning-Kruger, loss aversion via prospect theory, anchoring to a fixed self-image, and the availability heuristic applied to self-assessment.
I´m curious whether anyone here has thought about this link.
I wrote a piece connecting the two and would love any pushback or additions from people who know this field better than I do!