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Fixed income has received far less attention than equity portfolio optimisation since Markowitz' original work of 1952, partly as a result of the need to model rates and credit risk. We argue that the shape of the efficient frontier is mainly controlled by linear constraints, with the standard deviation relatively unimportant, and propose a two-factor model for its time evolution.
When is a large trade news, and when is it a liquidity shock? We study this question in a sequential competitive limit order book with asymmetric information. In our model, liquidity suppliers observe aggregate order flow but not its decomposition into informed demand and uninformed liquidity demand. We model uninformed order flow with Student-$t$ tails, interpreted as a reduced form for rare liquidity regimes. The t…
An automated market maker (AMM) provides a method for creating a decentralized exchange on the blockchain. For this purpose, individual investors lend liquidity to the AMM pool in exchange for a stream of fees earned from its operations as a market maker. Within this work, we reinterpret the loss-versus-rebalancing as the implied fee stream generated by an AMM so that a risk-neutral investor is indifferent in the dec…
Uniswap is a decentralized exchange (DEX) and was first launched on November 2, 2018 on the Ethereum mainnet [1] and is part of an Ecosystem of products in Decentralized Finance (DeFi). It replaces a traditional order book type of trading common on centralized exchanges (CEX) with a deterministic model that swaps currencies (or tokens/assets) along a fixed price function determined by the amount of currencies supplie…
We study a one period limit order market with informed traders, noise traders, and competitive liquidity suppliers, in which the number of informed traders is random. Liquidity suppliers know the distribution of the informed trader count, but not its realization, and therefore face uncertainty about both the presence and the intensity of informed trading. We characterize equilibrium by a fixed point integral equation…
We consider an optimal trading problem under a market impact model with endogenous market resistance generated by a sophisticated trader who (partially) detects metaorders and trades against them to exploit price overreactions induced by the order flow. The model features a concave transient impact driven by a power-law propagator with a resistance term responding to the trader's rate via a fixed-point equation invol…
This paper studies a type of periodic utility maximization problem for portfolio management in incomplete stochastic factor models with convex trading constraints. The portfolio performance is periodically evaluated on the relative ratio of two adjacent wealth levels over an infinite horizon, featuring the dynamic adjustments in portfolio decision according to past achievements. Under power utility, we transform the …
This book, which is in Spanish, provides detailed descriptions, including over 550 mathematical formulas, for over 150 trading strategies across a host of asset classes (and trading styles). This includes stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility (as an asset class), real estate, distressed assets, cash, cryptocurrencies, miscella…
A novel high-frequency market-making approach in discrete time is proposed that admits closed-form solutions. By taking advantage of demand functions that are linear in the quoted bid and ask spreads with random coefficients, we model the variability of the partial filling of limit orders posted in a limit order book (LOB). As a result, we uncover new patterns as to how the demand's randomness affects the optimal pla…
We propose and study the integration of sentiment analysis and deep reinforcement learning ensemble algorithms for stock trading by evaluating strategies capable of dynamically altering their active agent given the concurrent market environment. In particular, we design a simple-yet-effective method for extracting financial sentiment and combine this with improvements on existing trading agents, resulting in a strate…
In this paper, optimal consumption and investment decisions are studied for an investor who can invest in a fixed interest rate bank account and a stock whose price is a log normal diffusion. We present the method of the HJB equation in order to explicitly solve problems of this type with modifications such as a fixed percentage transaction cost and a mandatory bequest function. It is shown that the investor treats t…
This paper studies the switching of trading strategies and its effect on the market volatility in a continuous double auction market. We describe the behavior when some uninformed agents, who we call switchers, decide whether or not to pay for information before they trade. By paying for the information they behave as informed traders. First we verify that our model is able to reproduce some of the stylized facts in …
This paper compares different methods for forecasting the term structure of U.S. and European zero-coupon government bonds using both traditional econometric and Machine Learning (ML) approaches. We compare classical models (e.g., Dynamic Nelson-Siegel (DNS) and Principal Component Analysis (PCA)) with different Neural Network (NN) architectures, including those inspired by the classical models, on the U.S. Treasury …
Prediction markets are attracting growing attention as trading volumes rise and their practical relevance increases. To ensure efficient price discovery, liquidity provision becomes ever more important. Due to the binary settlement structure in prediction markets, optimal market making leads to an optimization problem that is fundamentally different from the ones studied in classical settings. In this paper, we devel…
Automated market makers (AMMs) for prediction markets descend from market scoring rules, where a mechanism operator subsidizes a market to aggregate beliefs about uncertain events. The existing literature has focused on bounding the total worst-case loss to the subsidizer, but has not addressed how that loss is distributed across price states or over time. We use the framework of loss-versus-rebalancing (LVR) to stud…
Collateralization with daily margining has become a new standard in the post-crisis market. Although there appeared vast literature on a so-called multi-curve framework, a complete picture of a multi-currency setup with cross-currency basis can be rarely found since our initial attempts. This work gives its extension regarding a general framework of interest rates in a fully collateralized market. It gives a new form…
We audit whether candle-based machine-learning models can turn predictions of cryptocurrency extrema or short-horizon outcomes into positive Binance Spot paper policies after assumed costs. Numerical results come from scripted fixed-seed model runs and deterministic simulators; human-supervised AI agents supported the July 20 evidence-integrity revision through literature retrieval, separately tasked critique, artifa…
Recent works have increasingly applied Large Language Models (LLMs) as agents in financial stock market simulations to test if micro-level behaviors aggregate into macro-level phenomena. However, a crucial question arises: Do LLM agents' behaviors align with real market participants? This alignment is key to the validity of simulation results. To explore this, we select a financial stock market scenario to test behav…
Indirect bidder allotment tracks the share of Treasury auctions awarded to indirect bidders, often used as a proxy for foreign and institutional demand.
Treasury auction tail measures how much the auction clears above or below the expected market yield, providing a sensitive signal of auction quality and investor demand.
Treasury auction bid-to-cover ratio measures the amount of demand relative to supply at an auction and is used to assess investor appetite for government debt.
Duration Risk — Interest-rate sensitivity of bond portfolios, amplified in low-yield high-duration regimes.
Convexity Risk — Non-linear price response to yield changes, especially relevant in MBS and long bonds.
Key Rate Duration — Bucketed rate sensitivity across curve points for relative-value and hedge construction.
Steepener Flattener Trade — Curve trades expressing views on growth, inflation, and term premium independently of level.
Carry and Roll Down — Expected return from holding higher-yielding tenor as it rolls down a positively sloped curve.
Asset Swap Spread — Spread between bond yield and floating leg, linking credit and funding markets.
Z Spread — Static spread over the government curve capturing credit and liquidity premium.
Option-Adjusted Spread — Spread adjusted for embedded prepayment options in callable bonds and MBS.
MBS Prepayment Speed — Refinancing and turnover driven cash-flow uncertainty in agency mortgages.
TBA Roll Specialness — Delivery-option value in TBA markets signaling collateral scarcity or abundance.
Agency MBS Basis — Spread between MBS and hedging Treasury futures, a core RV monitor.
Commercial Mortgage Delinquency — Office and retail stress feeding through CRE credit and regional bank risk.
Leveraged Loan Index — Floating-rate corporate credit sensitive to defaults, spreads, and CLO demand.
CLO Issuance — Structured credit supply that absorbs leveraged loans and shapes spread regimes.
Distressed Debt Ratio — Share of debt trading at deep discounts — early warning for credit cycle turns.
Fallen Angels — Investment-grade downgrades into high yield, creating forced selling and index rebalancing flows.
Rising Stars — High-yield upgrades into investment grade, often supporting spread tightening episodes.
CDS Basis Trade — Arbitrage between cash bonds and CDS contracts revealing funding and counterparty frictions.
Credit Default Swap Spread — Market-implied default risk premium for single names and indices.
Primary Dealer Survey — Desk-level policy expectations that front-run official communications.
CMBS Delinquency (Fixed Income).
CLO Spreads (Fixed Income).
Leveraged Loan Price (Fixed Income).
HY OAS (Fixed Income).
IG OAS (Fixed Income).
Fallen Angel Risk (Fixed Income).
Rising Star Credit (Fixed Income).
Default Rate Cycle (Fixed Income).
Recovery Rate Cycle (Fixed Income).
Distressed Ratio (Fixed Income).
Catastrophe Bond (Fixed Income).
ILS Market (Fixed Income).
Longevity Risk (Fixed Income).
5y5y Forward Inflation (Fixed Income).
ABS Tranche 10Y (Fixed Income).
ABS Tranche 1M (Fixed Income).
ABS Tranche 1Y (Fixed Income).
ABS Tranche 20Y (Fixed Income).
ABS Tranche 2Y (Fixed Income).
ABS Tranche 30Y (Fixed Income).
ABS Tranche 3M (Fixed Income).
ABS Tranche 5Y (Fixed Income).
ABS Tranche 6M (Fixed Income).
ABS Tranche 7Y (Fixed Income).
ABS Tranche agency (Fixed Income).
ABS Tranche Australia (Fixed Income).
ABS Tranche belly (Fixed Income).
ABS Tranche Canada (Fixed Income).
ABS Tranche CEEMEA (Fixed Income).
ABS Tranche China (Fixed Income).
ABS Tranche EM Asia (Fixed Income).
ABS Tranche Euro Area (Fixed Income).
ABS Tranche front (Fixed Income).
ABS Tranche HY (Fixed Income).
ABS Tranche IG (Fixed Income).
ABS Tranche Japan (Fixed Income).
ABS Tranche LatAm (Fixed Income).