How I Rewired My Brain to Become Fluent in Math
Plus, more links to make you a little bit smarter today.
Creating A Halloween Game But I Made It Too Scary...
In a World of Cancel Culture, Reputation Doesn’t Matter Anymore
Back in the day, old school “thinkers” — careerists and academics, mostly — believed that reputation was everything. But now, reputation doesn’t have the same weight it once did.
Financial Market Applications of LLMs
The AI revolution drove frenzied investment in both private and public companies and captured the public’s imagination in 2023. Transformational consumer products like ChatGPT are powered by Large Language Models (LLMs) that excel at modeling sequences of tokens that represent words or parts of words [2]. Amazingly, structural understanding emerges from learning next-token prediction, and agents are able to complete tasks such as translation, question answering and generating human-like prose from simple user prompts.
Decentralised Finance and Automated Market Making: Predictable Loss and Optimal Liquidity Provision
Constant product markets with concentrated liquidity (CL) are the most popular type of automated market makers. In this paper, we characterise the continuous-time wealth dynamics of strategic LPs who dynamically adjust their range of liquidity provision in CL pools. Their wealth results from fee income, the value of their holdings in the pool, and rebalancing costs. Next, we derive a self-financing and closed-form optimal liquidity provision strategy where the width of the LP’s liquidity range is determined by the profitability of the pool (provision fees minus gas fees), the predictable losses (PL) of the LP’s position, and concentration risk. Concentration risk refers to the decrease in fee revenue if the marginal exchange rate (akin to the midprice in a limit order book) in the pool exits the LP’s range of liquidity. When the drift in the marginal rate is stochastic, we show how to optimally skew the range of liquidity to increase fee revenue and profit from the expected changes in the marginal rate. Finally, we use Uniswap v3 data to show that, on average, LPs have traded at a significant loss, and to show that the out-of-sample performance of our strategy is superior to the historical performance of LPs in the pool we consider.
How I Rewired My Brain to Become Fluent in Math
Sorry, education reformers, it’s still memorization and repetition we need.
Quantifying Price Improvement in Order Flow Auctions
This work introduces a framework for evaluating onchain order flow auctions (OFAs), emphasizing the metric of price improvement. Utilizing a set of open-source tools, our methodology systematically attributes price improvements to specific modifiable inputs of the system such as routing efficiency, gas optimization, and priority fee settings. When applied to leading Ethereumbased trading interfaces such as 1Inch and Uniswap, the results reveal that auction-enhanced interfaces can provide statistically significant improvements in trading outcomes, averaging 4- 5 basis points in our sample. We further identify the sources of such price improvements to be added liquidity for large swaps. This research lays a foundation for future innovations in blockchain based trading platforms.
Jane Street is big. Like, really, really big
FT Alphaville’s main takeaways from the secretive trading firm’s bond prospectus