Exposing my Risk Management Protocol

Summary

The presenter argues that risk management should be designed around the purpose and rules of each trading environment. Hedge funds, prop-firm accounts, competitions, and personal accounts have different objectives, so a strategy suited to one may be inappropriate for another. The central theme is to assess risk-adjusted returns, drawdowns, probability of ruin, and survivability, rather than judging performance by raw returns alone.

Risk frameworks by account type

• Hedge fund: Prioritize sustainable, risk-adjusted compounding and survival over maximum returns. The presenter describes diversifying across strategies such as global macro, event-driven, quantitative, trend-following, arbitrage, and high-frequency trading. He also emphasizes independent risk, research, execution, operations, legal, and audit functions. Models should be tested out of sample and assessed for liquidity capacity: a strategy that works at small scale may not handle large amounts of capital without slippage.
• Prop-firm account: Optimize for passing evaluations and receiving payouts under the firm’s rules. The presenter recommends lower-variance approaches over “sniper” trades with high risk-to-reward ratios but low win rates. He also cautions against leaving accumulated profits with a prop firm; withdraw payouts where possible, given the risk of the firm having financial or regulatory problems.
• Trading competitions: Optimize for leaderboard placement rather than using the same risk profile as an investment portfolio. The presenter describes a staged process: test strategies early, identify the market regime and competitors, validate a promising approach under live execution costs, and then increase risk later if the contest objective warrants it. He warns that excessive aggression early can lead to elimination.
• Personal account: Aim for risk-adjusted returns, psychological stability, and long-term compounding. Diversify across strategies and time horizons, as well as brokers and platforms, to reduce exposure to a single brokerage failure. Track performance and set automated daily and weekly risk limits.

Methodologies and trading guidance

• Prop-firm evaluations: Use strategies with a high win rate—the presenter cites above 60–70%—moderate risk per trade, and moderate reward-to-risk targets. Examples include approximately 1:1, 1:0.75, and up to 1:1.5. He argues that lower variance may improve pass rates and reduce drawdowns.
• Competition trading:
  1. Test multiple approaches against the current market regime, such as trend-following, mean-reversion, and volatility-breakout strategies.
  2. Evaluate them under live-market conditions, including commissions and slippage, rather than relying on simulation results alone.
  3. Validate and scale the model that appears best suited to the regime.
  4. Consider increasing risk later in the competition to pursue a higher leaderboard position, while retaining a plan to avoid total elimination.
• Model validation: Include commissions, execution costs, slippage, and liquidity constraints. The presenter says these factors can turn an apparently profitable model into an unprofitable one, particularly for high-frequency or scalping strategies.
• Longer-term investment research: The presenter mentions post-earnings drift, a Bitcoin accumulation model informed by blockchain data and miner activity, and research into public ownership disclosures, including holdings associated with politicians and large investors.

Performance figures and examples cited

The following are the presenter’s examples and personal claims; they are not independently verified in the subtitles.

• For 2025, he contrasts a cited 20% return for “MCA World” (possibly a transcription error) with 17.5% for the S&P 500, arguing that raw returns do not show the risk taken to achieve them.
• He cites the Medallion Fund as returning 15% in 1988 and 1% in 1989, then gives examples of much stronger returns in other periods, including 57%, 43%, and 92.5% in 2008, when he says the market fell 46%. The exact periods and comparison figures are unclear in the subtitles.
• For a CME Group competition, he reports 50–60 executions, 54.6% net profit, a 0.42% maximum drawdown, and a leaderboard position around the top 0.6%. He stresses that this was an aggressive, competition-specific approach—not a suitable hedge-fund risk protocol.
• For the World Trading Cup, he cites a three-month contest, says leading positions may require returns around 50–150%, and describes making several hundred trades: roughly 300–400 in a late stage, with other references to 500–650 executions. A reported performance reconstruction includes 89.5%, 158% cumulative, and 22% maximum drawdown, but the subtitle’s figures are unclear and should be treated cautiously.
• For personal-account risk, he mentions 0.5% to 1.25% per trade as a conservative-to-moderate range. He contrasts this with risking 5% per trade, which he warns could cause severe losses during a losing streak.

Assets, markets, and organizations mentioned

• Assets and instruments: S&P 500, Bitcoin, cryptocurrencies, equities and stocks, futures, options, CFDs, and UAE real estate.
• Strategies and sectors: Global macro, event-driven, quantitative, trend-following, mean-reversion, volatility breakout, arbitrage, high-frequency trading, options strategies, and post-earnings drift.
• Organizations and named entities: CME Group, World Trading Cup, Trading Pit, FTX, BlackRock, Medallion Fund, hedge funds, and prop firms.
• Market context: The presenter uses Middle East geopolitical developments, U.S. tariffs, and shifts in market direction or volatility as examples of why strategies may behave differently across regimes.

Cautions and disclosures

The presenter says competition results are not typical and should not be assumed reproducible. He also cautions that prop firms carry counterparty and payout risk, and that simulation-based testing can misstate performance when it omits real execution costs. The subtitles end with a reference to a disclaimer but do not capture its full wording.

Presenter and sources mentioned

Presenter: Fabervaale, speaking on the Fabervaale ENG channel.

People and organizations referenced: Jim Simons and the Medallion Fund; CME Group; World Trading Cup; Trading Pit; FTX; BlackRock; and traders or collaborators identified as Nasri Khan, Luca, and Matteo.