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
Enhancing Sequence Processing with Transformer Memory Integration
HighFreqAsuka @ twitter
orig
The approach involves breaking long sequences into shorter segments while utilizing a transformer for each segment along with a memory vector, which helps to maintain context across segments. This method improves memory retention, but the fixed size of the memory vector at 10 raises questions about its influence on memorization capacity—a variable that deserves further exploration. I think curriculum learning is a significant factor here, yet it wasn't ablated in the study. Additionally, this method reintroduces the sequential training drawbacks of RNNs that Transformers were designed to overcome, affecting GPU utilization. They cleverly mitigate this by leveraging a pretrained model. It's intriguing that there are two separate studies on this; one likely overlooked critical observations that the other picks up on.
@quant_feed
HighFreqAsuka @ twitter
orig
The approach involves breaking long sequences into shorter segments while utilizing a transformer for each segment along with a memory vector, which helps to maintain context across segments. This method improves memory retention, but the fixed size of the memory vector at 10 raises questions about its influence on memorization capacity—a variable that deserves further exploration. I think curriculum learning is a significant factor here, yet it wasn't ablated in the study. Additionally, this method reintroduces the sequential training drawbacks of RNNs that Transformers were designed to overcome, affecting GPU utilization. They cleverly mitigate this by leveraging a pretrained model. It's intriguing that there are two separate studies on this; one likely overlooked critical observations that the other picks up on.
@quant_feed
Rethinking Quant Skills: The Role of Analytics in Portfolio Management and Risk Optimization
systematicls @ twitter
orig
Analytics and optimization are the essence of quant skills. Portfolio managers may possess advanced capabilities, but much of their skillset diverges from quant methodologies. Enterprise risk managers embody the true quant spirit, adeptly managing risk through analytical frameworks. The humor in the hiring process highlights a key misunderstanding: it’s not just about PhDs—it's about finding minds that can digest complex data sets like Compustat with precision and attention to detail.
@quant_feed
systematicls @ twitter
orig
Analytics and optimization are the essence of quant skills. Portfolio managers may possess advanced capabilities, but much of their skillset diverges from quant methodologies. Enterprise risk managers embody the true quant spirit, adeptly managing risk through analytical frameworks. The humor in the hiring process highlights a key misunderstanding: it’s not just about PhDs—it's about finding minds that can digest complex data sets like Compustat with precision and attention to detail.
@quant_feed
Navigating Coffee Quality: An Australian's Travel Challenge in Switzerland
liquiditygoblin @ twitter
orig
The biggest hassle of traveling as an Australian is lugging coffee gear everywhere because the local brews rarely measure up. Swiss coffee is especially disappointing—it's like drinking flavored ash. Also, I’d rather avoid chains like Starbucks altogether. Compared to Australia, other countries just can’t compete on coffee quality, and even when skiing in Japan, their coffee is just average. When you’re shelling out 5-6 AUD for good specialty coffee back home, it stings to pay about the same in Switzerland for subpar options. Plus, the daily cost to ski in Cervinia is outrageous—totally not worth it.
@quant_feed
liquiditygoblin @ twitter
orig
The biggest hassle of traveling as an Australian is lugging coffee gear everywhere because the local brews rarely measure up. Swiss coffee is especially disappointing—it's like drinking flavored ash. Also, I’d rather avoid chains like Starbucks altogether. Compared to Australia, other countries just can’t compete on coffee quality, and even when skiing in Japan, their coffee is just average. When you’re shelling out 5-6 AUD for good specialty coffee back home, it stings to pay about the same in Switzerland for subpar options. Plus, the daily cost to ski in Cervinia is outrageous—totally not worth it.
@quant_feed
😭3
Understanding US Bonds: Transforming Debt into Liquidity and Investment Options
perfiliev @ twitter
orig
US bonds represent money rather than just debt. They offer high liquidity, allowing you to sell them easily for cash. Alternatively, bonds can serve as valuable collateral for borrowing. You can also choose to invest exclusively in bills and wait for maturity to access funds. This versatility highlights the functional role of bonds in financial transactions.
@quant_feed
perfiliev @ twitter
orig
US bonds represent money rather than just debt. They offer high liquidity, allowing you to sell them easily for cash. Alternatively, bonds can serve as valuable collateral for borrowing. You can also choose to invest exclusively in bills and wait for maturity to access funds. This versatility highlights the functional role of bonds in financial transactions.
@quant_feed
👍3
The Pragmatic Approach to Market Insights: Balancing Quantitative Models and Real-Time Trading
liquiditygoblin @ twitter
orig
Price action reveals market sentiment, and understanding this is crucial. Small lots can provide insights into trading behavior without the burden of extensive modeling. Focus on efficiency; it’s about smart execution rather than exhaustive analysis. The goal isn’t accolades—it’s profitability. Leverage quick, tactical trades to align with market psychology. Prioritize getting a feel for the market over complex methodologies.
@quant_feed
liquiditygoblin @ twitter
orig
Price action reveals market sentiment, and understanding this is crucial. Small lots can provide insights into trading behavior without the burden of extensive modeling. Focus on efficiency; it’s about smart execution rather than exhaustive analysis. The goal isn’t accolades—it’s profitability. Leverage quick, tactical trades to align with market psychology. Prioritize getting a feel for the market over complex methodologies.
@quant_feed
Rethinking Options Strategies: The Risks of Trading on Personal Price Bias
salr_nyc @ twitter
orig
Market-making is about setting the price of leverage, distinct from typical trading strategies. I’ve seen effective trading groups, particularly ex-Salomon players in London, who excel at understanding the value of risk transfer and are willing to pay for it. They appreciate the intricacies of pricing risk, which leads to better outcomes. On the other hand, I also have a solid working relationship with a prominent firm that thrives through cooperation and mutual benefit. Their collaborative approach has yielded better results for all involved. This highlights the importance of understanding not just the mechanics of trading, but also the dynamics of working with different groups in the market.
@quant_feed
salr_nyc @ twitter
orig
Market-making is about setting the price of leverage, distinct from typical trading strategies. I’ve seen effective trading groups, particularly ex-Salomon players in London, who excel at understanding the value of risk transfer and are willing to pay for it. They appreciate the intricacies of pricing risk, which leads to better outcomes. On the other hand, I also have a solid working relationship with a prominent firm that thrives through cooperation and mutual benefit. Their collaborative approach has yielded better results for all involved. This highlights the importance of understanding not just the mechanics of trading, but also the dynamics of working with different groups in the market.
@quant_feed
Embracing the Basics: The Value of Starting from the Fundamentals in Quant Finance
quantymacro @ twitter
orig
I find value in embracing the basics; they’re the foundation for deeper understanding. Critics labeling my insights as "too basic" miss the point—it's a signal of growth potential. Sticking to fundamentals at this stage sets me up to tackle more complex topics down the line. If I'm already advanced and still presenting basic concepts, that would indeed be concerning. Focusing on low-hanging fruit allows me to steadily build my knowledge and skills without feeling overwhelmed. It's a strategic approach to learning and mastering more intricate ideas as I progress.
@quant_feed
quantymacro @ twitter
orig
I find value in embracing the basics; they’re the foundation for deeper understanding. Critics labeling my insights as "too basic" miss the point—it's a signal of growth potential. Sticking to fundamentals at this stage sets me up to tackle more complex topics down the line. If I'm already advanced and still presenting basic concepts, that would indeed be concerning. Focusing on low-hanging fruit allows me to steadily build my knowledge and skills without feeling overwhelmed. It's a strategic approach to learning and mastering more intricate ideas as I progress.
@quant_feed