A Critical Perspective on Hyperliquid: Drawing Parallels with FTX
liquiditygoblin @ twitter
orig
Hyperliquid is essentially the on-chain equivalent of FTX, lacking credibility. Its design choices, marketed as trader-friendly, are often misguided or intentionally deceptive. I can identify and front-run all TWAPs, indicating a structural flaw. Additionally, the tender mint sequencing is centralized under the same entities managing the HLP vault and development. This mirrors the environment of FTX, raising serious concerns about trust and integrity in the platform.
@quant_feed
liquiditygoblin @ twitter
orig
Hyperliquid is essentially the on-chain equivalent of FTX, lacking credibility. Its design choices, marketed as trader-friendly, are often misguided or intentionally deceptive. I can identify and front-run all TWAPs, indicating a structural flaw. Additionally, the tender mint sequencing is centralized under the same entities managing the HLP vault and development. This mirrors the environment of FTX, raising serious concerns about trust and integrity in the platform.
@quant_feed
The Hidden Value of Beta Compression: Insights from Real Readers
__paleologo @ twitter
orig
Beta compression is a key strategy that can enhance asset pricing models. It’s gratifying to see genuine engagement with work, rather than it just being decorative or functional in a trivial way. Raises a critical point that not all market strategies are equally effective—low volatility environments present challenges, and I advise caution against loading on BaB strategies; they’re not as easily exploitable as they may seem.
@quant_feed
__paleologo @ twitter
orig
Beta compression is a key strategy that can enhance asset pricing models. It’s gratifying to see genuine engagement with work, rather than it just being decorative or functional in a trivial way. Raises a critical point that not all market strategies are equally effective—low volatility environments present challenges, and I advise caution against loading on BaB strategies; they’re not as easily exploitable as they may seem.
@quant_feed
Observing Kaggle Grandmasters: A Valuable Learning Experience for Aspiring Data Scientists
quantymacro @ twitter
orig
I've always been intrigued by Kaggle but haven't had the time to dive in. Observing a Kaggle Grandmaster tackle problems for a stretch would be invaluable; there's a wealth of learning to be gained despite Kaggle's disconnection from “real world” scenarios. I'm particularly drawn to the nuanced aspects of data science—the remaining 10% that involves feature engineering and model diagnostics rather than just model training, which feels less engaging.
@quant_feed
quantymacro @ twitter
orig
I've always been intrigued by Kaggle but haven't had the time to dive in. Observing a Kaggle Grandmaster tackle problems for a stretch would be invaluable; there's a wealth of learning to be gained despite Kaggle's disconnection from “real world” scenarios. I'm particularly drawn to the nuanced aspects of data science—the remaining 10% that involves feature engineering and model diagnostics rather than just model training, which feels less engaging.
@quant_feed
🤨1
Examining the Medium-Term Impact of Ethereum's Transition from Proof of Work to Proof of Stake on Price Performance
0xdoug @ twitter
orig
The transition from Proof of Work (PoW) to Proof of Stake (PoS) in Ethereum might appear beneficial in terms of resource efficiency, yet it may have contributed to the underperformance of ETH in the medium term. The departure of miners, while reducing environmental impact, also eliminated a cohort of significant market participants who provided liquidity and stability. Without miners' capital and operational support, Ethereum's dynamics shifted, potentially leading to bearish pressure. The longer-term effects of this structural change will be crucial in assessing ETH's performance relative to other assets in a changing landscape.
@quant_feed
0xdoug @ twitter
orig
The transition from Proof of Work (PoW) to Proof of Stake (PoS) in Ethereum might appear beneficial in terms of resource efficiency, yet it may have contributed to the underperformance of ETH in the medium term. The departure of miners, while reducing environmental impact, also eliminated a cohort of significant market participants who provided liquidity and stability. Without miners' capital and operational support, Ethereum's dynamics shifted, potentially leading to bearish pressure. The longer-term effects of this structural change will be crucial in assessing ETH's performance relative to other assets in a changing landscape.
@quant_feed
Examining Market Manipulation in High-Frequency Trading: Lessons from 2012
ltrd_ @ twitter
orig
There’s ongoing concern about potential market manipulation, particularly through quote placements. Reflecting on early HFT days, we encountered significant spoofing and manipulative behaviors. A notable event in 2012 showcased rapid trading activity, revealing that the optimal strategy might have been to withdraw from the order book entirely. We missed that opportunity, highlighting the necessity of mastering volatility—it can either work for or against us. I encourage discussion on these insights and your perspectives on navigating such market dynamics.
@quant_feed
ltrd_ @ twitter
orig
There’s ongoing concern about potential market manipulation, particularly through quote placements. Reflecting on early HFT days, we encountered significant spoofing and manipulative behaviors. A notable event in 2012 showcased rapid trading activity, revealing that the optimal strategy might have been to withdraw from the order book entirely. We missed that opportunity, highlighting the necessity of mastering volatility—it can either work for or against us. I encourage discussion on these insights and your perspectives on navigating such market dynamics.
@quant_feed
Rethinking Trading: Focusing on Entry and Exit for Profit Without Timing the Market
gametheorizing @ twitter
orig
Profit is determined by the difference between entry and exit, not the duration of the trade. Most traders focus merely on market direction—up or down—while my approach revolves around assessing the probability of achieving a profitable exit and evaluating the potential loss if that exit doesn't materialize. This perspective shifts the focus to risk/reward dynamics rather than directional forecasting. Additionally, capital sizing and allocation are critical components that I simplify for clarity.
@quant_feed
gametheorizing @ twitter
orig
Profit is determined by the difference between entry and exit, not the duration of the trade. Most traders focus merely on market direction—up or down—while my approach revolves around assessing the probability of achieving a profitable exit and evaluating the potential loss if that exit doesn't materialize. This perspective shifts the focus to risk/reward dynamics rather than directional forecasting. Additionally, capital sizing and allocation are critical components that I simplify for clarity.
@quant_feed
The Reality Behind Index Inclusions: Price Movements and Market Dynamics
macrocephalopod @ twitter
orig
In analyzing index inclusion, it's clear that price movements don’t always align with expectations. The assumption that inclusion guarantees price appreciation often proves false due to various market dynamics. This underscores the importance of prudent risk management, a principle I grasped well during my time at Archegos Capital Management. Additionally, a deeper dive into expectation theory reveals how market behaviors tend to layer expectations on top of one another, complicating investment strategies. This interplay creates opportunities as well as pitfalls, emphasizing the need for nuanced understanding and adaptability in trading approaches.
@quant_feed
macrocephalopod @ twitter
orig
In analyzing index inclusion, it's clear that price movements don’t always align with expectations. The assumption that inclusion guarantees price appreciation often proves false due to various market dynamics. This underscores the importance of prudent risk management, a principle I grasped well during my time at Archegos Capital Management. Additionally, a deeper dive into expectation theory reveals how market behaviors tend to layer expectations on top of one another, complicating investment strategies. This interplay creates opportunities as well as pitfalls, emphasizing the need for nuanced understanding and adaptability in trading approaches.
@quant_feed
Shifts in Compensation Structures: The Impact of Noncompete Agreement Changes on Trading Firms
macrocephalopod @ twitter
orig
Longer notice periods and increased deferred compensation are emerging as responses to the elimination of non-compete agreements in trading firms, mirroring practices already in place in the UK. The narrative that this is a significant victory for employees or a game-changer for prop firms is misguided; the actual impact on trading personnel is likely minimal.
@quant_feed
macrocephalopod @ twitter
orig
Longer notice periods and increased deferred compensation are emerging as responses to the elimination of non-compete agreements in trading firms, mirroring practices already in place in the UK. The narrative that this is a significant victory for employees or a game-changer for prop firms is misguided; the actual impact on trading personnel is likely minimal.
@quant_feed
The Limits of Data Analysis in Establishing Causality in Finance
predict_addict @ twitter
orig
Causality cannot be solely derived from data analysis; it requires assumptions or external arguments. Reminder to remain cautious of causality claims, especially from product vendors. It's essential to consider mathematical conditions that guarantee causality rather than relying on semantic interpretations. Semantics must be backed by rigorously defined mathematical frameworks to clarify when causality can and cannot be established from data.
@quant_feed
predict_addict @ twitter
orig
Causality cannot be solely derived from data analysis; it requires assumptions or external arguments. Reminder to remain cautious of causality claims, especially from product vendors. It's essential to consider mathematical conditions that guarantee causality rather than relying on semantic interpretations. Semantics must be backed by rigorously defined mathematical frameworks to clarify when causality can and cannot be established from data.
@quant_feed
Analyzing Daily Close Volatility: The Impact of Rebalancing Algorithms
nik_algo @ twitter
orig
The daily close rebalancing algo is a key driver of volatility, especially notable at 00:00 UTC. I've observed intriguing patterns where some days lead to immediate mean-reversion, while others trigger momentum ignition. This duality creates a fascinating environment for trading strategies. Capitalizing on these spikes offers ample opportunities, though it's a gamble between the two outcomes. Personally, I've had better success when taking risks during these volatility spikes, despite the inherent uncertainty.
@quant_feed
nik_algo @ twitter
orig
The daily close rebalancing algo is a key driver of volatility, especially notable at 00:00 UTC. I've observed intriguing patterns where some days lead to immediate mean-reversion, while others trigger momentum ignition. This duality creates a fascinating environment for trading strategies. Capitalizing on these spikes offers ample opportunities, though it's a gamble between the two outcomes. Personally, I've had better success when taking risks during these volatility spikes, despite the inherent uncertainty.
@quant_feed
👍2
Understanding the Strategy: Selling Tail Risk in Market Dynamics
BeatzXBT @ twitter
orig
I'm seeing impressive action in tail risk options, with around ~$625K of volume in just 10 days—remarkable, given it’s about 3300x my initial balance. While volume itself doesn’t directly translate to profits, the heightened interest is notable. In the current market, it feels like a constant grind of stink bidding on shitcoins, trying to scrape together a few basis points if filled. The pressure is building, and I’m searching for a streamlined approach—ideally one that avoids the clutter of managing multiple tmux instances. There's no room for complacency as the market dynamics tighten.
@quant_feed
BeatzXBT @ twitter
orig
I'm seeing impressive action in tail risk options, with around ~$625K of volume in just 10 days—remarkable, given it’s about 3300x my initial balance. While volume itself doesn’t directly translate to profits, the heightened interest is notable. In the current market, it feels like a constant grind of stink bidding on shitcoins, trying to scrape together a few basis points if filled. The pressure is building, and I’m searching for a streamlined approach—ideally one that avoids the clutter of managing multiple tmux instances. There's no room for complacency as the market dynamics tighten.
@quant_feed
Exploring the Benefits of Stacking Gold and Crypto Exposure as a Hedge Against Currency Debasement
choffstein @ twitter
orig
Stacking commodity, gold, or bitcoin exposure onto a portfolio acts as a hedge against currency debasement. For instance, a 60/40 portfolio with a 20% gold overlay can effectively shield 20% of the portfolio from dollar depreciation against gold. Currency futures can also be integrated for additional fiat risk exposure. International equity diversification provides similar benefits. Although gold does have a lending rate that incurs financing costs, viewing it as a hedge offers an interesting perspective. This discussion centers exclusively on gold's value in dollars, distinct from its correlation with stocks and bonds.
@quant_feed
choffstein @ twitter
orig
Stacking commodity, gold, or bitcoin exposure onto a portfolio acts as a hedge against currency debasement. For instance, a 60/40 portfolio with a 20% gold overlay can effectively shield 20% of the portfolio from dollar depreciation against gold. Currency futures can also be integrated for additional fiat risk exposure. International equity diversification provides similar benefits. Although gold does have a lending rate that incurs financing costs, viewing it as a hedge offers an interesting perspective. This discussion centers exclusively on gold's value in dollars, distinct from its correlation with stocks and bonds.
@quant_feed
Exploring the Potential of Emerging Market Currencies for Enhanced Carry Strategy Returns
quantseeker @ twitter
orig
Returns from G10 currency factors have stagnated, prompting a pivot to emerging market currencies for potential performance enhancement. Research by Chernov et al. highlights that carry strategies, especially, offer significant net-of-cost benefits. This shift could be a game changer for those looking to optimize currency-based investments.
@quant_feed
quantseeker @ twitter
orig
Returns from G10 currency factors have stagnated, prompting a pivot to emerging market currencies for potential performance enhancement. Research by Chernov et al. highlights that carry strategies, especially, offer significant net-of-cost benefits. This shift could be a game changer for those looking to optimize currency-based investments.
@quant_feed
Understanding the Price Discrepancy: Iced Latte vs. Flat White in Australia
liquiditygoblin @ twitter
orig
Why does an iced latte cost more than a flat white of the same strength? It doesn’t involve steaming milk, yet I’m seeing $7 for an iced latte versus $5 for a flat white. Ice and a different cup can't account for a $2 difference. It’s frustrating when I get handed a paper straw on top of that. I wonder about the market dynamics here—if someone mentions “more buyers than sellers,” spare me. Could we have identified a pricing gap? Also, I recently tried iced batch bee, which was enjoyable but still came in at $7.50. Where's the economies of scale in all this?
@quant_feed
liquiditygoblin @ twitter
orig
Why does an iced latte cost more than a flat white of the same strength? It doesn’t involve steaming milk, yet I’m seeing $7 for an iced latte versus $5 for a flat white. Ice and a different cup can't account for a $2 difference. It’s frustrating when I get handed a paper straw on top of that. I wonder about the market dynamics here—if someone mentions “more buyers than sellers,” spare me. Could we have identified a pricing gap? Also, I recently tried iced batch bee, which was enjoyable but still came in at $7.50. Where's the economies of scale in all this?
@quant_feed
😁4👏1
Maximizing VIP Rewards: The Trade-Off of High-Risk Trading Strategies
BeatzXBT @ twitter
orig
High-risk strategies, like "stink bidding," can be effective for accelerating volume and reaching higher VIP tiers, despite their dangers. My average account balance of around $1.9K has led to a staggering turnover of approximately 105 times daily. I’ve shared a strategy breakdown in earlier tweets that details my approach better.
My pinned tweet outlines a market-making strategy designed for passive inventory management, contrasting with "stink bidders" who rapidly liquidate their positions. I typically quote no less than 75 bps on any pair, often going up to 100 bps or more. I've had to adjust my minimum distance from 100 to 150 bps due to frequent fills.
I'm often sitting on open orders that are 6-8 times my account balance, which is indicative of my trading style. Currently, I'm facing a 50% drawdown caused by bugs in my code and API failures following the recent market crash, but I'm working on a recovery.
@quant_feed
BeatzXBT @ twitter
orig
High-risk strategies, like "stink bidding," can be effective for accelerating volume and reaching higher VIP tiers, despite their dangers. My average account balance of around $1.9K has led to a staggering turnover of approximately 105 times daily. I’ve shared a strategy breakdown in earlier tweets that details my approach better.
My pinned tweet outlines a market-making strategy designed for passive inventory management, contrasting with "stink bidders" who rapidly liquidate their positions. I typically quote no less than 75 bps on any pair, often going up to 100 bps or more. I've had to adjust my minimum distance from 100 to 150 bps due to frequent fills.
I'm often sitting on open orders that are 6-8 times my account balance, which is indicative of my trading style. Currently, I'm facing a 50% drawdown caused by bugs in my code and API failures following the recent market crash, but I'm working on a recovery.
@quant_feed
Understanding the Different Variants of Principal Component Analysis
PtrPomorski @ twitter
orig
PCA is fundamental for dimensionality reduction, but understanding the nuances between various types is crucial. Linear PCA is straightforward, while KernelPCA extends it to non-linear transformations, choosing an appropriate kernel is essential. For massive datasets, IncrementalPCA provides a linear approach without overwhelming memory. SparsePCA adds a layer of feature selection to linear PCA, optimizing the retained dimensions. Robust PCA deals effectively with outliers. On a different note, UMAP is an excellent tool for visualization but tends to be very slow, which can be a significant drawback. SSA also brings fresh insights to this space.
@quant_feed
PtrPomorski @ twitter
orig
PCA is fundamental for dimensionality reduction, but understanding the nuances between various types is crucial. Linear PCA is straightforward, while KernelPCA extends it to non-linear transformations, choosing an appropriate kernel is essential. For massive datasets, IncrementalPCA provides a linear approach without overwhelming memory. SparsePCA adds a layer of feature selection to linear PCA, optimizing the retained dimensions. Robust PCA deals effectively with outliers. On a different note, UMAP is an excellent tool for visualization but tends to be very slow, which can be a significant drawback. SSA also brings fresh insights to this space.
@quant_feed
🔥2
Analyzing the Performance of Our AI Long/Short Basket: Insights on Genuine Beneficiaries vs. Hype
Citrini7 @ twitter
orig
Our AI Long/Short basket, initiated in June 2023, is performing notably well, emphasizing the importance of distinguishing between companies that are truly benefiting from AI innovation and those that are simply capitalizing on its hype. This divergence in performance serves as a strong signal in our strategy. Additionally, it’s worth noting that market tops often see a surge in overhyped stocks that outpace genuine leaders, pointing to a potential cautionary sign. Collaborative insights with @netcapgirl highlight the ongoing updates to this basket, reinforcing our analytical approach.
@quant_feed
Citrini7 @ twitter
orig
Our AI Long/Short basket, initiated in June 2023, is performing notably well, emphasizing the importance of distinguishing between companies that are truly benefiting from AI innovation and those that are simply capitalizing on its hype. This divergence in performance serves as a strong signal in our strategy. Additionally, it’s worth noting that market tops often see a surge in overhyped stocks that outpace genuine leaders, pointing to a potential cautionary sign. Collaborative insights with @netcapgirl highlight the ongoing updates to this basket, reinforcing our analytical approach.
@quant_feed
The Risks of Overfitting: A Closer Look at Pair Trading and Cointegration in Backtest Results
systematicls @ twitter
orig
I'm seeing a lot of excitement around "pair trading," but it makes me groan. The usual buzzwords—cointegration and ADF tests—are there, and of course, there's a backtest making a case for a very specific pair, ETC-RLC, out of hundreds of combinations. This is classic overfitting, yet it remains the go-to signal for many quants. It's funny; I lost my quant virginity to pairs trading as well, so I get the allure. Just don't get fooled by the shiny metrics and be cautious about validation.
@quant_feed
systematicls @ twitter
orig
I'm seeing a lot of excitement around "pair trading," but it makes me groan. The usual buzzwords—cointegration and ADF tests—are there, and of course, there's a backtest making a case for a very specific pair, ETC-RLC, out of hundreds of combinations. This is classic overfitting, yet it remains the go-to signal for many quants. It's funny; I lost my quant virginity to pairs trading as well, so I get the allure. Just don't get fooled by the shiny metrics and be cautious about validation.
@quant_feed
Recent Enhancements to Data Infrastructure and Trading Tools
BeatzXBT @ twitter
orig
- Implemented parallel data feeds; integration of websockets proved more complex than expected. I explored various options for managing client sessions and tested ZMQ handling by running 50 identical Binance full market depth streams, achieving an impressive 100K messages in ~2.36s.
- Started further normalization of order types and sides; considered using dataclasses for simplicity in trading logic and OMS, but faced performance issues with serialization and deserialization.
- Divided features into categories for easier updating. Deleted existing strategy from the SMM and decided to rewrite it from scratch to incorporate new insights.
- Transitioning from a skewed pricing system to a fair pricing model to enhance reliability for features.
- Tackling the design of the risk engine, focusing on the calculation and structuring of global, exchange, and symbol deltas. Encountered challenges with JIT class construction in Numba, leading me to revert to native Python for better manageability.
- Looking to enhance exchange integrations while updating my existing HL code, and actively engaging with peers who might find this progress relevant.
@quant_feed
BeatzXBT @ twitter
orig
- Implemented parallel data feeds; integration of websockets proved more complex than expected. I explored various options for managing client sessions and tested ZMQ handling by running 50 identical Binance full market depth streams, achieving an impressive 100K messages in ~2.36s.
- Started further normalization of order types and sides; considered using dataclasses for simplicity in trading logic and OMS, but faced performance issues with serialization and deserialization.
- Divided features into categories for easier updating. Deleted existing strategy from the SMM and decided to rewrite it from scratch to incorporate new insights.
- Transitioning from a skewed pricing system to a fair pricing model to enhance reliability for features.
- Tackling the design of the risk engine, focusing on the calculation and structuring of global, exchange, and symbol deltas. Encountered challenges with JIT class construction in Numba, leading me to revert to native Python for better manageability.
- Looking to enhance exchange integrations while updating my existing HL code, and actively engaging with peers who might find this progress relevant.
@quant_feed
Exploring the Impact of Tails on Crypto Data with Toraniko's Factor Momentum Analysis
0xLightcycle @ twitter
orig
I experimented with @0xfdf's toraniko GitHub, incorporating crypto data, and uncovered that crypto datasets exhibit significantly longer tails than traditional equities. The exploration included three plots analyzing the toraniko factor_mom across different universes: utilizing the full crypto universe, a dynamic universe based on volume, and applying higher clipping through winsorization. These insights are crucial for understanding risk and return profiles in crypto assets. The framework presents a robust multi-factor equity risk model tailored for quantitative trading in this volatile space.
@quant_feed
0xLightcycle @ twitter
orig
I experimented with @0xfdf's toraniko GitHub, incorporating crypto data, and uncovered that crypto datasets exhibit significantly longer tails than traditional equities. The exploration included three plots analyzing the toraniko factor_mom across different universes: utilizing the full crypto universe, a dynamic universe based on volume, and applying higher clipping through winsorization. These insights are crucial for understanding risk and return profiles in crypto assets. The framework presents a robust multi-factor equity risk model tailored for quantitative trading in this volatile space.
@quant_feed
Rethinking Model Evaluation: Why ROC AUC Falls Short in Business Contexts
predict_addict @ twitter
orig
ROC AUC is fundamentally flawed as a metric for business applications. It lacks the nuance required for actionable insights, particularly around customer churn predictions. In dialogues between data scientists and business managers, it's crucial to focus on metrics that drive decisions rather than abstract performance scores.
The emphasis should be on understanding the model's utility in real-world scenarios, not just its statistical accuracy. A tailored approach is necessary; employing thresholds that cater to individual customer profiles could yield more relevant predictions. Ultimately, aligning metrics with business objectives is vital to ensure our efforts translate into tangible outcomes.
@quant_feed
predict_addict @ twitter
orig
ROC AUC is fundamentally flawed as a metric for business applications. It lacks the nuance required for actionable insights, particularly around customer churn predictions. In dialogues between data scientists and business managers, it's crucial to focus on metrics that drive decisions rather than abstract performance scores.
The emphasis should be on understanding the model's utility in real-world scenarios, not just its statistical accuracy. A tailored approach is necessary; employing thresholds that cater to individual customer profiles could yield more relevant predictions. Ultimately, aligning metrics with business objectives is vital to ensure our efforts translate into tangible outcomes.
@quant_feed