One consistent theme of markets is that there is always the potential for change just around the corner, and no two changes are the same.
Following strong growth in US equities markets, geopolitical events are triggering some risk-off strategies, at least on the surface.
Whilst firms taking some risk off their books isn’t new, the data impacting decision-making is new compared to other risk-off events.
There are ongoing debates about whether this will be a repeat of the DotCom bust, whether the rush for AI has overinflated the Magnificent Seven, and whether there is uncertainty about the return on investment into LLMs.
Are the markets correcting? This is the multi-trillion dollar question everyone in capital markets will be asking.
While Code Willing can’t answer the above, what we do know is that there are heightened levels of uncertainty, which will continue to generate see-saw swings, causing relentless spikes in volume and volatility. The big question is how financial institutions and investment funds will cope with the strains on legacy systems and strategies to respond to market conditions. The even bigger question is what happens if you can’t respond.
Hedge funds, especially those running market-neutral strategies, are well placed in turbulent markets as many firms benefit from volatility and uncertainty. However, if you don’t have a savvy tech platform that can harness unlimited compute options and streamline the adoption of more and more critical datasets, it becomes a really expensive challenge to adapt your current models or signals to the market trend or create new models to respond in time to take advantage of the conditions while generating returns.
How can you achieve adaptation while controlling costs without sacrificing performance?
CWIQ, the flagship platform from Code Willing, is made for rapid prototyping and timely releases of thoroughly back-tested new models into trading engines. The trading engine has been hyper-tuned for high throughput and low latency to overcome increases in throughput and speed while not comprising critical risk checks.
From Data to Execution: CWIQ’s Edge in Modern Trading
Often, research teams must roll their sleeves up and grapple with the first stages of leveraging a new dataset: ingestion frameworks, cleansing, mapping, and finally, chopping away at the outliers. Aside from what has been a truly convoluted process, it takes precious time away from valuable output such as signals, optimization, new features, and eventual alphas.
This is all streamlined in CWIQ, where the data is ingested, mapped, and processed into a format that allows for the rapid merging and joining of other datasets to create new methods, models, and signals. CWIQ combines this with a robust workbench that enables the researcher to navigate cloud instances, giving the researcher a sophisticated ability to concentrate on the workloads that generate real returns.
CWIQ SIM provides robust backtesting and simulation to ensure that the models generate the expected returns, not just noise. CWIQ leverages an elastic compute toolkit that enables backtests and simulations to run on any cloud, whether the compute resources are in colo or public cloud environments. With a unique automated process to find the cheapest cloud computing resources, you can keep research costs in check and budgets tightly controlled.
Traditionally, a researcher develops a model, which is handed to a software engineer to get it ready for release to the production environment. This is where it can get bumpy; there are things a researcher may have done with the dataset, potential rewriting of modules for optimization, and the niggle that the rewrite has somehow missed something. CWIQ helps with this step, allowing the researcher to work with clean data and simple mechanisms to switch from simulation to live.
The final and essential piece of the puzzle is actual trading. The best models are only as good as the quality of the execution your platform can provide. In volatile markets, latency and the ability to process much higher volumes of real-time information are imperative for the success of a strategy. The CWIQ platform’s execution capabilities have been battle-tested across global markets, covering equities, futures, and options without breaking a sweat. As the entire CWIQ platform is seamless, your backtests are immediately tradeable in the OMS without any code changes, offering true speed to market and lowering the potential for mistakes after the backtest. From data to execution, it’s one seamless platform.
Market Shifts and CWIQ: Adapting to Financial Uncertainty
Volatile trading markets pose significant challenges for investors seeking stability and risk-adjusted returns. Their ability to adapt to changing market conditions and minimize downside risks makes them essential to sophisticated investment strategies.
Hedge funds and investment firms must embrace innovation, leveraging platforms like CWIQ to streamline data processing, optimize model development, and execute trades with precision.
By integrating cutting-edge tools, financial institutions can stay ahead of the curve, turning volatility into opportunity and ensuring long-term success in an unpredictable market.