Recent Questions - Quantitative Finance Stack Exchange

Suppose a backtest pipeline is evaluated at a historical cutoff T. Let F_T be the information legitimately available by T. I am testing temporal causality by applying a mutation M_T that leaves F_T unchanged but perturbs only information that should still be unavailable, then rerunning the pipeline and checking whether the historical artifact A_T changes. Formally, the test is: M_T(D)|F_T = D|F_T…

This question comes from implementing the consensus engine in iPulse AI, an Open Agentic Investment Research Platform that I'am developing with my team for 3 years now. I mention the platform purpose only to explain the applied setting and context. By “open,” I mean that the research questions, methodology, evaluation procedures, historical forecasts, limitations, results and unsuccessful approac…

Has anyone tried to map RIC to Bloomberg tickers using AI tools: ChatGPT, Gemini, Claude?

I've googled and read many articles about "ROIC" and "Invested Capital", but I'm still confused about how to calculate them. The best explanation I've seen so far is: Invested Capital (from CFI) Invested Capital Formula (from EDUCBA) Invested Capital Formula (from WallStreetMojo) There are at least two ways to calculate "Invested Capital": financing approach: $Invested Capital = Total Debt \& Lea…

Background Specifically, the 2026 value of $\sim5.01\%$ Deriving the model We can derive the Hull–White analytical solution $$r_t = r_s e^{-\kappa(t-s)} + \int_s^t e^{-\kappa(t-u)} \theta(u) du + \sigma \int_s^t e^{-\kappa(t-u)} dW_u$$ where the continuous-time Vasicek SDE is given by: $$dr_t = \kappa (\theta - r_t) dt + \sigma dW_t$$ (Note: We use $\kappa$ for the speed of mean reversion and $\t…

I have been looking to understand the H-model in finance, that is used for stock price valuation. In particular, I wanted to formally derive the final formula: $$PV=\frac{D}{r-g_2}\left[1+g_2+\frac{H}{2}(g_1-g_2)\right]$$ Here $PV>0$ is the present value (price) of the stock, $D>0$ is the constant dividend payment that is paid forever, $r\in(0;1)$ is the required rate of return on the stock and t…

A pension company has an asset side and a liability side, and some capital. The key equation is $$A = L + C$$ Let's say the company wants to compute a 10-year VaR of its capital C. Normally, this would be easy. We just simulate the assets forward in time, and simulate the liability forward in time, and compare. But, for a pension company, the assets are typically fund investments . The liability …

I am designing an event-driven capital allocator for several trading strategies. I currently have three strategies, although the allocator should eventually support additional ones. This is a mathematical modeling question, not a request for investment advice, a package recommendation, or help debugging an existing implementation. Available information Each strategy generates signals at a differe…

I am building an event-driven capital allocator for three trading strategies. This is a portfolio-optimization and validation question, not a request for investment advice. This question follows an earlier question about pricing capital reserved for stochastic future signals . A new experiment appears to have resolved that particular issue, but it has isolated a different one: estimating the appr…

I am looking to price a Bermudan-callable EUR/USD cross-currency interest rate swap in QuantLib. Assume a three-factor model with: one Hull-White model for USD rates, one Hull-White model for EUR rates, a Black-Scholes FX process, correlations between both rate factors and FX, the appropriate quanto/measure-change drift adjustment. Pricing would require Monte Carlo with Longstaff-Schwartz regress…

I am building an event-driven capital allocator for three trading strategies. This is a portfolio-optimization and validation question, not a request for investment advice. Signals arrive asynchronously. Several signals can be available at the same time, positions lock capital until they close, and the arrival times, holding periods, and returns of future signals are uncertain. For each current s…

I am working on a project that includes risk/return characteristics for a certain strategy and its benchmark (SPX). Included on the outputs is a sensitivity table, which may be showing signs of overfitting. I tested sharpe ratio with varying risk-free rates, and while the table does show a worse sharpe for higher rates, to be expected, it also shows a worse sharpe for lower rates which I don't be…

In the (wonderful) book "The Dao of Capital", the author, M. Sptiznagel, describes at pag. 242 this procedure to estimate the crash losses and bootstrap standard errors that follow high MS Indices: Upon bucketing two-months returns by their starting MS index quartiles (over a 3 year window of overlapping two month returns following bucketing) and calculating the 2nd and 5th percentiles in each b…

On National Stock Exchange, BrihanMumbai stock Exchange in India, Bracket order, trailing stop loss limit buy/sell, trailing stop loss limit trigger buy/sell, trail at price, trail amount, book profit price order are not executed. Indian Stock Exchange reject these abovementioned orders to execute. Are these orders not executed on every Stock exchanges globally? Can we execute these orders in Fo…

I come from a different field (Machine learning/AI/data science), but aim to ask a philosophical question with the utmost respect: Why do quantitative financial analysts (analysts/traders/etc.) prefer (or at least seem) traditional statistical methods (traditional = frequentist/regression/normal correlation methods/ts analysis) over newer AI/machine learning methods? I've read a million models, b…

A potential issue with automated trading systems, that are based on Machine Learning ( ML ) and/or Artificial Intelligence ( AI ), is the difficulty of assessing the risk of a trade. An ML/AI algorithm may analyze thousands of parameters in order to come up with a trading decision and applying standard risk management practices might interfere with the algorithms by overriding the algorithm's dec…

I am trying to improve the discipline of my strategy research process and would appreciate insight from those with experience in systematic/quant research. Current workflow I am testing: Formulate a clear hypothesis Conduct the research (features, labeling, validation, costs) Fully document methods, assumptions, and results Subject the work to critical review before any development Only promote i…

I'm writing a backtester and using an order-by-order Nasdaq ITCH feed whilst testing it. Let's say the bid-ask spread is 100 @ 9-11 @ 100 My strategy inserts an bid order for 100 @ 10 and this becomes the new best bid. I continue parsing the ITCH feed and I see that the 100 @ 9 has traded. This implies had I really placed a bid for 10, that would have traded now. So instead of removing the bid at…

I have a list of booleans that correspond to buy and sell signals that I would like to backtest. To achieve this, I calculated the return ret of a security and when the signal is False I modify the corresponding return to 0 (corresponds to a cash position), and when the signal is True I kept the return. The result is a Pandas series like this: > signal 2018-01-01 00:00:00+00:00 NaN 2018-0…

I created a portfolio rebalancing strategy, that I am currently paper trading with. It is, primarily, based on mean-reversion principle with a few rules in place, and geared towards cryptocurrencies, in general. I double the commission to account for slippage as well as when rebalancing I first sell all assets I am holding and then, buy them even if same. This adds a few pips of random slippage a…