The blog post details the author's experience market making on Kalshi, a prediction market platform. They outline their automated strategy, which involves setting bid and ask prices around a predicted probability, adjusting spreads based on liquidity and event volatility. The author focuses on "Will the Fed cut interest rates before 2024?", highlighting the challenges of predicting this complex event and managing risk. Despite facing difficulties like thin markets and the need for continuous model refinement, they achieved a small profit, demonstrating the potential, albeit challenging, nature of algorithmic market making on these platforms. The post emphasizes the importance of careful risk management, constant monitoring, and adapting to market conditions.
The New York Stock Exchange (NYSE) is establishing a new trading floor in Arlington, Texas, called NYSE Texas. Scheduled to open in 2027, this facility will serve as a disaster recovery and backup site for the NYSE's existing operations. It will also house a physical trading floor mirroring the iconic NYSE in New York City, offering a venue for in-person trading and important corporate events like IPO ceremonies. This expansion aims to increase the exchange's resiliency and geographical diversity.
Hacker News commenters were generally cynical about the announcement of NYSE Texas. Many saw it as a thinly veiled attempt to circumvent regulations, potentially relating to taxes or data sovereignty, with some speculating about connections to Texas's lax regulatory environment. Several pointed out the irony of a New York institution establishing a Texas branch for supposed advantages, while others questioned the practical implications and whether any significant trading activity would actually relocate. Some suggested the move was more about optics and public relations than genuine operational needs, especially given the existing electronic nature of trading. A few commenters expressed curiosity about the specifics of the "cutting edge financial technology" mentioned in the press release, but overall the sentiment was skeptical.
Summary of Comments ( 8 )
https://news.ycombinator.com/item?id=43073377
HN commenters discuss the intricacies and challenges of market making on Kalshi, particularly regarding the platform's fee structure. Some highlight the difficulty of profiting given the 0.5% fee per trade and the need for substantial volume to overcome it. Others point out that Kalshi contracts are generally illiquid, making sustained profitability challenging even without fees. The discussion touches on the complexities of predicting probabilities and the potential for exploitation by insiders with privileged information. Some users express skepticism about the viability of retail market making on Kalshi, while others suggest potential strategies involving statistical arbitrage or focusing on less efficient, smaller markets. The conversation also briefly explores the regulatory landscape and Kalshi's unique position as a CFTC-regulated exchange.
The Hacker News post "Making Markets on Kalshi" discussing the linked blog post about market making on the Kalshi prediction market platform has generated a modest number of comments, offering several perspectives on the topic.
One commenter highlights the potential legal complexities of market making on Kalshi, questioning whether it falls under similar regulations as traditional financial market making. They express uncertainty about how the CFTC (Commodity Futures Trading Commission), which regulates Kalshi, views these activities and if specific licenses or registrations are required. This comment raises a pertinent legal concern regarding the regulatory landscape of prediction markets.
Another commenter discusses the practical challenges of market making on Kalshi, particularly the difficulty of accurately pricing contracts, especially in illiquid markets. They mention the complexities of predicting event outcomes and managing risk effectively. This comment sheds light on the practical realities of participating in prediction markets, highlighting the expertise required for profitable market making.
Further discussion centers around the limited liquidity and order book depth on Kalshi, suggesting this makes profitable market making more challenging. One commenter observes that the smaller market size compared to traditional financial markets can lead to greater price volatility and difficulty in executing larger orders. This contributes to the discussion about the practicalities and potential limitations of market making on Kalshi.
A separate thread of conversation explores the broader potential of prediction markets and their potential impact on information discovery and forecasting. One commenter suggests that while prediction markets can be valuable tools, the limited liquidity and participation on platforms like Kalshi can hinder their effectiveness. This comment broadens the scope beyond Kalshi to the general challenges faced by prediction markets.
One commenter shares a personal anecdote about attempting to predict the outcome of Supreme Court cases on Kalshi, which sparked further discussion about the challenges and potential biases in such predictions. This adds a practical example to the broader conversation about using prediction markets for real-world events.
Overall, the comments on the Hacker News post provide a mix of practical considerations, regulatory concerns, and broader reflections on the potential and limitations of prediction markets, specifically in the context of Kalshi. They offer valuable insights into the challenges and opportunities presented by this emerging financial landscape.