Your Fund's Track Record Is Lying to You

When individual investors confront the evidence on retail underperformance — that the stocks they pick tend to decline after purchase, that their portfolios carry far more risk than the market for far less return — the natural response is: fine, I will stop picking stocks and buy a fund instead. Delegate to the professionals. Let diversification do its work.

This is a reasonable instinct. It is also, in most cases, insufficient. The same informational and behavioral problems that distort individual stock selection are embedded inside the majority of actively managed funds — just harder to see.

The Illusion of Active Management

Active funds promise something specific: that their managers possess skill, information, or discipline that will generate returns above a passive benchmark after fees. The evidence on whether this promise is kept is unambiguous and has been for decades. The majority of actively managed equity funds underperform their benchmark index over any horizon longer than three years. The minority that outperform in one period do not systematically outperform in the next. Past performance, the most widely used metric for fund selection, has essentially no predictive power for future risk-adjusted returns.

This is not a fringe finding. It is one of the most replicated results in financial economics, consistent across US, European, and emerging market datasets. Yet retail investors continue to allocate heavily to actively managed funds on the basis of historical track records — precisely the signal that research tells us to ignore.

Why does past performance fail to predict future performance? Because most of what looks like fund manager skill is actually factor exposure, market-cycle timing, or plain luck — all of which mean-revert. A fund that outperformed in a bull market driven by high-momentum stocks did not necessarily display skill; it may have simply held the right characteristics at the right moment. When those characteristics rotate out of favor, the performance disappears, and the investor who selected the fund on the basis of its three-year return is left holding an expensive, underperforming vehicle.

The Closet Indexer Problem

Beyond the performance question, there is a structural problem with how most active funds are actually constructed: they look far more like their benchmark than they claim.

Closet indexing is the practice of charging active management fees while holding a portfolio that closely replicates a passive index. A fund that holds the top 40 stocks in the BIST-100 at roughly market-cap weights is, in practice, an index fund — but it charges an active management fee, often several times higher than a comparable passive product. The investor pays for differentiation they are not receiving.

This practice is more widespread than fund marketing materials suggest. Research measuring active share — the fraction of a portfolio that differs from the benchmark — consistently finds that a large proportion of funds classified as "active" have active shares below 50 percent, meaning more than half the portfolio is indistinguishable from the index. These funds provide neither the cost efficiency of passive management nor the genuine differentiation of true active management. They are the worst of both worlds.

For Turkish retail investors navigating the TEFAS universe, this problem is acute. The fund market offers hundreds of options, and their marketing materials are largely indistinguishable. Without a way to look through the fund's stated strategy to its actual holdings and evaluate those holdings on their expected-return characteristics, investors are selecting blind.

The Hidden Risk: Lottery Stocks Inside Your Fund

Beyond closet indexing, there is a more subtle problem: funds that are genuinely active often achieve their differentiation by concentrating in exactly the kind of stocks that individual investors are already overexposed to — high-volatility, high-attention, speculative securities that score poorly on fundamental expected-return metrics.

A fund that has generated strong recent returns by concentrating in high-momentum, high-volatility names looks attractive on its track record. What it actually represents is a leveraged bet on sentiment-driven securities — the same lottery-stock profile that our own research shows leads to systematic underperformance when the cycle turns. An investor who buys this fund believing they are getting diversification and professional judgment is often getting the opposite: higher concentration in the riskiest part of the market, packaged in a format that obscures rather than clarifies the exposure.

This is the fund version of the lottery-stock bias documented in individual trading behavior. The mechanism is different — it runs through manager incentives and benchmark-relative thinking rather than direct retail psychology — but the outcome is the same: capital systematically allocated toward overpriced, sentiment-inflated securities with poor long-run expected returns.

What Fund Evaluation Should Actually Look Like

If historical performance is a poor predictor of future returns and active share metrics are not widely published for Turkish funds, how should a retail investor evaluate the funds available to them?

The answer is to look through the fund to its holdings, and evaluate those holdings on the same empirical basis used to evaluate individual stocks: forward-looking expected-return characteristics rather than backward-looking track records.

This is the logic behind SmartFundSkor. Rather than asking "how has this fund performed?", it asks "given what this fund currently holds, what does the evidence suggest about its future risk-adjusted performance?" The score is computed as a holdings-weighted average of the SmartSkor rankings for each underlying security — the same forward-looking, empirically grounded expected-return estimates used to evaluate individual stocks, aggregated to the portfolio level.

The result is a composite that rewards funds holding high-expected-return securities and penalizes funds holding securities that are overpriced relative to fundamentals, regardless of what their recent performance history shows. A fund that has produced strong recent returns by concentrating in lottery-type stocks will score poorly on SmartFundSkor, flagging the risk before the investor commits capital. A fund that holds fundamentally sound, undervalued securities that have underperformed recently — precisely the kind of neglected opportunity that the evidence favors — will score well.

Additional diagnostics sit alongside the composite: active share and benchmark overlap to identify closet indexing; factor alignment to measure whether the fund's exposures correspond to documented return predictors; and speculative tilt, capturing overexposure to sentiment-driven securities.

The Practical Implication for Turkish Fund Investors

For investors navigating the TEFAS universe, SmartFundSkor offers something that does not currently exist in the market: a forward-looking, holdings-based evaluation of fund quality that is grounded in the same academic evidence used to evaluate individual securities.

It does not require the investor to understand factor models, parse fund prospectuses, or interpret active share calculations. It produces a single, interpretable score — with the underlying components available for those who want to look deeper — and it is updated as fund holdings change.

The practical decision this enables is simple but powerful: instead of selecting the fund with the best three-year return, select the fund whose current holdings have the highest expected risk-adjusted returns going forward. Instead of discovering that a fund was a closet indexer or a lottery-stock vehicle after the fact, identify it before allocating capital.

The Broader Point

Funds are not a solution to the behavioral problems that drive retail underperformance. They can be — if the right funds are selected for the right reasons. But selecting funds on the basis of historical performance, brand recognition, or the quality of a sales pitch replicates exactly the same pattern of backward-looking, attention-driven decision-making that characterizes the worst individual stock picks.

The same evidence-based discipline that SmartSkor applies to individual securities applies equally to the portfolios of funds holding those securities. The methodology scales. The behavioral traps scale too — which is why the corrective infrastructure needs to reach the fund level, not just the stock level.

SmartFundSkor is an analytical product of TuneUp Fintech, built on holdings-weighted SmartSkor aggregation and peer-reviewed research in empirical asset pricing.

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