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Risk Management Latest Activity

Methods for position sizing, drawdowns, tail risk, and stress testing.

49 related activitiesLast 30 days 35 itemsFeatured among them 0 items

Updated

Activity Archive · Page 3 页

28 AugFriIssue 41–49 items
  1. AQR: Research38

    AQR Research: Accessing Liquidity Without Liquidating

    AQR research explores whether tax-aware equity strategies can provide sufficient liquidity without full liquidation, while preserving investment objectives. The study finds that substantial capital can be extracted while maintaining tracking error, leverage, and pre-tax information ratio. The tax-efficient extraction capability of long-short strategies is generally superior to that of direct indexing strategies, and improves with higher strategy tracking error and leverage levels.

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11 AugTue
  1. Aswath Damodaran：Musings on Markets56

    Damodaran on the Situational Awareness fund blowup: the collateral damage of investment conviction

    Aswath Damodaran, a valuation professor at New York University, uses the complete journey of Leopold Aschenbrenner's Situational Awareness hedge fund—from explosive growth to liquidation following a blowup—as a case study to systematically break down the definition, sources, and real-world impact of investment conviction.

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23 JunTue
  1. Rob Carver：This Blog is Systematic74

    How to Automatically Identify Structural Breakpoints in Momentum Strategy Parameter Estimation

    This article introduces a method for automatically identifying structural breakpoints in the Sharpe ratio of trading rules, using independent t-tests to compare mean differences across subsamples, recursively splitting the sample while requiring each subsample to retain at least 5 years of data. The authors provide complete Python implementation code, using the momentum4 rule for CORN futures as an example, with the algorithm automatically identifying August 26, 1982 as the breakpoint.

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15 JunMon
  1. Rob Carver：This Blog is Systematic62

    Comparing Portfolio Optimization Shrinkage Methods Using Real Return Data: Backtesting Conclusions for Monte Carlo, Bootstrap, and Double Shrinkage

    In the fourth installment of the Summer 2026 Portfolio Optimization Series, the author backtests Monte Carlo, bootstrap, double shrinkage, naive mean-variance, equal weight, maximum diversification, and EPO using real trading rule and instrument return data. Each test randomly selects 9 trading rules and one instrument, comparing portfolios over 1-, 5-, and 10-year in-sample periods and 1- and 5-year out-of-sample periods. The results show that under real data, correlation estimates are less stable than Sharpe ratios, requiring more correlation shrinkage rather than more Sharpe ratio shrinkage.

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8 JunMon
  1. Robot Wealth45

    How Independent Traders Should Allocate Resources for a Triangulated Statistical Arbitrage Business

    This article is the sixth part of a series on statistical arbitrage for independent traders. It explains the three core modules of triangulated statistical arbitrage and their resource allocation priorities. High-quality pair screening is the core foundation: using 24 months of historical data, the top 10% of pairs are screened monthly and divided into 5 quality tiers, with the best tier achieving a Sharpe ratio of 1.6 and the worst only 0.42. The author discloses only the general methodology and does not reveal specific implementation details.

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1 JunMon
  1. Robot Wealth54

    Triangulated statistical arbitrage: how to identify genuine pricing deviations rather than mispricing

    This article is the fifth in a statistical arbitrage series for independent traders, focusing on the triangulated statistical arbitrage method. Using the energy sector spread network as an example, the author explains how to cross-validate multiple overlapping spreads to identify genuinely mispriced individual stocks, rather than treating deviations in a single spread as a direct trading signal.

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22 MayFri
  1. Robot Wealth53

    From Pairs to Portfolios, Part 4: A Triangulated Statistical Arbitrage Approach for Independent Traders

    This article introduces a triangulated statistical arbitrage approach. Using 8 spread groups constructed from 6 energy stocks as an example, the z-score signal of each spread is decomposed into opposite votes for the two individual stocks, which are then aggregated into long-short signals at the individual stock level. This allows direct trading of undervalued or overvalued stocks, replacing the traditional pairs-trading model of hedging both legs simultaneously. The approach can improve capital efficiency, reduce transaction costs, and increase signal utilization, while achieving variance control similar to pairs trading through a long-short basket portfolio. The article will further explain how to evaluate the quality of aggregated signals.

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10 AprFri
  1. Robot Wealth53

    Trend or No Trend? That's the Wrong Question

    The author argues that mean reversion, trend, and momentum are merely labels for price movements rather than trading edges. A true edge requires first identifying the underlying structural cause and then validating it with data. The article uses three types of mean-reversion scenarios as examples: forced liquidation by leveraged funds, scheduled rebalancing of crypto leveraged tokens, and month-end stock-bond rebalancing by wealth management institutions. All three scenarios involve identifiable trading flows that are insensitive to price.

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23 MarMon
  1. Robot Wealth54

    AI Will Create Millions of Quantitative Traders, Most of Whom Will Lose Money

    The author notes that AI has dramatically lowered the barrier to developing quantitative strategies, enabling fully coded and backtested strategies to be generated within minutes. However, cheap experimentation amplifies the multiple-testing problem, producing a flood of false backtest results that appear effective but are actually overfit to noise.

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