| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A minimal model of money creation under regulatory constraints |
0 |
0 |
1 |
11 |
0 |
0 |
3 |
8 |
| A minimal model of money creation within secured interbank markets |
0 |
0 |
7 |
7 |
2 |
3 |
12 |
12 |
| Analyzing and modelling 1+1d markets |
0 |
0 |
0 |
27 |
4 |
4 |
5 |
115 |
| Baldovin-Stella stochastic volatility process and Wiener process mixtures |
0 |
0 |
0 |
12 |
3 |
4 |
5 |
74 |
| Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps? |
0 |
0 |
0 |
10 |
4 |
5 |
11 |
25 |
| Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps? |
0 |
0 |
0 |
0 |
2 |
3 |
8 |
22 |
| Cleaning the covariance matrix of strongly nonstationary systems with time-independent eigenvalues |
0 |
0 |
0 |
51 |
1 |
3 |
3 |
14 |
| Collective rationality and functional wisdom of the crowd in far-from-rational institutional investors |
0 |
0 |
0 |
0 |
2 |
2 |
4 |
4 |
| Comment on: Thermal model for Adaptive Competition in a Market |
0 |
0 |
0 |
10 |
2 |
4 |
8 |
55 |
| Consistent time travel for realistic interactions with historical data: reinforcement learning for market making |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
| Consistent time travel for realistic interactions with historical data: reinforcement learning for market making |
0 |
0 |
0 |
0 |
8 |
10 |
12 |
20 |
| Covariance matrix filtering and portfolio optimisation: the Average Oracle vs Non-Linear Shrinkage and all the variants of DCC-NLS |
0 |
0 |
0 |
16 |
2 |
4 |
9 |
38 |
| Covariance matrix filtering and portfolio optimisation: the Average Oracle vs Non-Linear Shrinkage and all the variants of DCC-NLS |
0 |
0 |
0 |
0 |
2 |
2 |
7 |
14 |
| Covariance matrix filtering with bootstrapped hierarchies |
0 |
0 |
0 |
6 |
3 |
8 |
9 |
20 |
| Covariance matrix filtering with bootstrapped hierarchies |
0 |
0 |
0 |
0 |
1 |
2 |
3 |
3 |
| Criticality and finite size effects in a simple realistic model of stock market |
0 |
0 |
1 |
18 |
4 |
5 |
8 |
70 |
| Deep Prediction Of Investor Interest: a Supervised Clustering Approach |
0 |
0 |
0 |
7 |
1 |
2 |
3 |
28 |
| Deep Prediction of Investor Interest: a Supervised Clustering Approach |
0 |
0 |
0 |
18 |
1 |
2 |
5 |
35 |
| Dissecting the explanatory power of ESG features on equity returns by sector, capitalization, and year with interpretable machine learning |
0 |
0 |
5 |
21 |
1 |
2 |
13 |
53 |
| Dissecting the explanatory power of ESG features on equity returns by sector, capitalization, and year with interpretable machine learning |
0 |
0 |
0 |
59 |
1 |
4 |
5 |
15 |
| Do Google Trend data contain more predictability than price returns? |
0 |
0 |
1 |
3 |
4 |
6 |
7 |
52 |
| Do Google Trend data contain more predictability than price returns? |
0 |
0 |
0 |
70 |
3 |
6 |
11 |
112 |
| Do investors trade too much? A laboratory experiment |
0 |
0 |
0 |
2 |
1 |
2 |
3 |
46 |
| Do investors trade too much? A laboratory experiment |
0 |
0 |
1 |
77 |
3 |
6 |
11 |
91 |
| Dynamical regularities of US equities opening and closing auctions |
0 |
0 |
0 |
9 |
3 |
7 |
11 |
37 |
| Dynamical regularities of US equities opening and closing auctions |
0 |
0 |
0 |
7 |
2 |
4 |
5 |
34 |
| Emergence of product differentiation from consumer heterogeneity and asymmetric information |
0 |
0 |
0 |
19 |
1 |
1 |
3 |
75 |
| Equity auction dynamics: latent liquidity models with activity acceleration |
0 |
0 |
0 |
5 |
0 |
2 |
6 |
10 |
| Equity auction dynamics: latent liquidity models with activity acceleration |
0 |
0 |
2 |
2 |
0 |
0 |
4 |
4 |
| Exact Hurst exponent and crossover behavior in a limit order market model |
0 |
0 |
0 |
28 |
0 |
3 |
7 |
94 |
| Feedback and efficiency in limit order markets |
0 |
0 |
0 |
20 |
1 |
1 |
4 |
62 |
| Filtering time-dependent covariance matrices using time-independent eigenvalues |
0 |
0 |
0 |
0 |
0 |
4 |
7 |
9 |
| Financial factors selection with knockoffs: fund replication, explanatory and prediction networks |
0 |
0 |
0 |
2 |
2 |
3 |
5 |
13 |
| Financial factors selection with knockoffs: fund replication, explanatory and prediction networks |
0 |
0 |
0 |
0 |
2 |
6 |
6 |
7 |
| From Minority Games to real markets |
0 |
0 |
0 |
47 |
3 |
5 |
7 |
140 |
| Inter-pattern speculation: beyond minority, majority and $-games |
0 |
0 |
0 |
84 |
4 |
5 |
11 |
305 |
| Large large-trader activity weakens the long memory of limit order markets |
0 |
0 |
0 |
11 |
2 |
3 |
3 |
22 |
| Large large-trader activity weakens the long memory of limit order markets |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
| Learning the Spoofability of Limit Order Books With Interpretable Probabilistic Neural Networks |
0 |
0 |
0 |
0 |
2 |
2 |
2 |
2 |
| Learning the Spoofability of Limit Order Books With Interpretable Probabilistic Neural Networks |
0 |
0 |
6 |
6 |
9 |
21 |
35 |
35 |
| Limit order market analysis and modelling: on an universal cause for over-diffusive prices |
0 |
0 |
0 |
24 |
1 |
2 |
3 |
67 |
| Minority Games and stylized facts |
0 |
0 |
1 |
20 |
1 |
3 |
7 |
56 |
| Modeling Market Mechanism with Minority Game |
0 |
0 |
0 |
67 |
2 |
3 |
6 |
163 |
| Multi-Timescale Recurrent Neural Networks Beat Rough Volatility for Intraday Volatility Prediction |
0 |
0 |
0 |
0 |
3 |
4 |
4 |
4 |
| News and price returns from threshold behaviour and vice-versa: exact solution of a simple agent-based market model |
0 |
0 |
0 |
9 |
4 |
5 |
6 |
48 |
| Noise-proofing Universal Portfolio Shrinkage |
0 |
0 |
0 |
0 |
7 |
9 |
9 |
9 |
| Non-linear shrinkage of the price return covariance matrix is far from optimal for portfolio optimisation |
0 |
0 |
0 |
35 |
4 |
7 |
8 |
20 |
| Nonparametric sign prediction of high-dimensional correlation matrix coefficients |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
2 |
| Nonparametric sign prediction of high-dimensional correlation matrix coefficients |
0 |
0 |
0 |
0 |
2 |
4 |
5 |
14 |
| On the origins of extreme wealth inequality in the Talent vs Luck Model |
0 |
0 |
0 |
0 |
1 |
3 |
4 |
5 |
| One- and two-sample nonparametric tests for the signal-to-noise ratio based on record statistics |
0 |
0 |
0 |
32 |
0 |
0 |
0 |
41 |
| Optimal approximations of power-laws with exponentials |
0 |
0 |
0 |
34 |
1 |
1 |
3 |
146 |
| Optimal execution on Uniswap v2/v3 under transient price impact |
0 |
0 |
0 |
0 |
5 |
5 |
5 |
5 |
| Optimal risk-aware interest rates for decentralized lending protocols |
0 |
0 |
3 |
3 |
1 |
7 |
13 |
13 |
| Optimal risk-aware interest rates for decentralized lending protocols |
1 |
1 |
1 |
1 |
2 |
2 |
4 |
4 |
| Predicting financial markets with Google Trends and not so random keywords |
0 |
1 |
3 |
126 |
0 |
1 |
5 |
163 |
| Predicting financial markets with Google Trends and not so random keywords |
0 |
0 |
0 |
0 |
5 |
7 |
14 |
47 |
| Prediction accuracy and sloppiness of log-periodic functions |
0 |
0 |
0 |
67 |
2 |
6 |
7 |
205 |
| Price impact in equity auctions: zero, then linear |
0 |
0 |
2 |
2 |
2 |
2 |
2 |
2 |
| Price impact in equity auctions: zero, then linear |
0 |
1 |
2 |
10 |
4 |
8 |
15 |
30 |
| Price return auto-correlation and predictability in agent-based models of financial markets |
0 |
0 |
0 |
29 |
2 |
4 |
6 |
100 |
| Reactive Global Minimum Variance Portfolios with $k-$BAHC covariance cleaning |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
2 |
| Reactive Global Minimum Variance Portfolios with $k-$BAHC covariance cleaning |
0 |
0 |
0 |
2 |
2 |
8 |
9 |
21 |
| Recurrent Neural Networks with more flexible memory: better predictions than rough volatility |
0 |
0 |
0 |
13 |
2 |
3 |
3 |
14 |
| Recurrent Neural Networks with more flexible memory: better predictions than rough volatility |
0 |
0 |
0 |
2 |
1 |
7 |
9 |
13 |
| Regrets, learning and wisdom |
0 |
0 |
0 |
1 |
1 |
3 |
3 |
82 |
| Regrets, learning and wisdom |
0 |
0 |
0 |
32 |
1 |
2 |
4 |
35 |
| Sharper asset ranking from total drawdown durations |
0 |
0 |
0 |
10 |
3 |
4 |
7 |
56 |
| Sharper asset ranking from total drawdown durations |
0 |
0 |
0 |
0 |
2 |
4 |
5 |
19 |
| Shedding light on El Farol |
0 |
0 |
0 |
172 |
2 |
4 |
5 |
565 |
| Statistical Mechanics of Competitive Resource Allocation using Agent-based Models |
0 |
0 |
0 |
18 |
3 |
7 |
8 |
78 |
| Statistical inference of lead-lag at various timescales between asynchronous time series from p-values of transfer entropy |
0 |
2 |
3 |
31 |
7 |
11 |
14 |
26 |
| Statistical mechanics of competitive resource allocation using agent-based models |
0 |
0 |
0 |
0 |
0 |
4 |
4 |
13 |
| Statistically validated lead-lag networks and inventory prediction in the foreign exchange market |
0 |
0 |
0 |
8 |
4 |
4 |
5 |
51 |
| Statistically validated leadlag networks and inventory prediction in the foreign exchange market |
0 |
0 |
0 |
5 |
2 |
5 |
6 |
27 |
| Statistically validated network of portfolio overlaps and systemic risk |
0 |
0 |
0 |
28 |
3 |
8 |
11 |
76 |
| Statistically validated network of portfolio overlaps and systemic risk |
0 |
0 |
0 |
3 |
1 |
12 |
20 |
62 |
| Strategic behaviour and indicative price diffusion in Paris Stock Exchange auctions |
0 |
0 |
0 |
29 |
1 |
1 |
5 |
27 |
| Strategic behaviour and indicative price diffusion in Paris Stock Exchange auctions |
0 |
0 |
0 |
0 |
2 |
2 |
3 |
22 |
| Stylized facts in money markets: an empirical analysis of the eurozone data |
0 |
5 |
5 |
5 |
3 |
3 |
3 |
3 |
| Stylized facts in money markets: an empirical analysis of the eurozone data |
0 |
0 |
0 |
7 |
4 |
8 |
13 |
19 |
| Stylized facts of financial markets and market crashes in Minority Games |
0 |
0 |
0 |
28 |
2 |
4 |
5 |
88 |
| Sudden Trust Collapse in Networked Societies |
0 |
0 |
0 |
73 |
0 |
2 |
7 |
62 |
| Sudden trust collapse in networked societies |
0 |
0 |
0 |
0 |
1 |
4 |
5 |
34 |
| Taking a shower in Youth Hostels: risks and delights of heterogeneity |
0 |
0 |
0 |
52 |
6 |
8 |
11 |
337 |
| Testing the causality of Hawkes processes with time reversal |
0 |
0 |
0 |
32 |
1 |
2 |
3 |
32 |
| Testing the causality of Hawkes processes with time reversal |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
13 |
| The Oracle estimator is suboptimal for global minimum variance portfolio optimisation |
0 |
0 |
0 |
0 |
2 |
3 |
3 |
4 |
| The Universal Shape of Economic Recession and Recovery after a Shock |
0 |
0 |
0 |
106 |
8 |
10 |
12 |
309 |
| The Ups and Downs of Modeling Financial Time Series with Wiener Process Mixtures |
0 |
0 |
1 |
18 |
4 |
4 |
6 |
99 |
| The demise of constant price impact functions and single-time step models of speculation |
0 |
0 |
0 |
10 |
2 |
2 |
2 |
50 |
| The limits of statistical significance of Hawkes processes fitted to financial data |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
11 |
| The limits of statistical significance of Hawkes processes fitted to financial data |
0 |
0 |
0 |
8 |
2 |
5 |
8 |
41 |
| The market nanostructure origin of asset price time reversal asymmetry |
0 |
0 |
0 |
0 |
4 |
4 |
7 |
21 |
| The market nanostructure origin of asset price time reversal asymmetry |
0 |
0 |
0 |
7 |
2 |
2 |
2 |
30 |
| The tick-by-tick dynamical consistency of price impact in limit order books |
0 |
0 |
0 |
54 |
1 |
5 |
6 |
124 |
| The universal shape of economic recession and recovery after a shock |
0 |
0 |
0 |
23 |
9 |
12 |
14 |
111 |
| The ups and downs of the renormalization group applied to financial time series |
0 |
0 |
1 |
43 |
1 |
4 |
10 |
200 |
| Trading behavior and excess volatility in toy markets |
0 |
0 |
0 |
18 |
1 |
1 |
4 |
81 |
| Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior |
0 |
0 |
0 |
39 |
2 |
3 |
5 |
142 |
| When Small Wins Big: Classification Tasks Where Compact Models Outperform Original GPT-4 |
0 |
0 |
2 |
2 |
1 |
1 |
11 |
19 |
| When is cross impact relevant? |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
3 |
| When is cross impact relevant? |
0 |
0 |
0 |
3 |
0 |
2 |
4 |
11 |
| Why have asset price properties changed so little in 200 years |
0 |
0 |
2 |
53 |
4 |
7 |
11 |
52 |
| Why have asset price properties changed so little in 200 years |
0 |
0 |
0 |
0 |
0 |
4 |
6 |
18 |
| Wisdom of the institutional crowd |
0 |
0 |
0 |
9 |
4 |
6 |
9 |
42 |
| Wisdom of the institutional crowd |
0 |
0 |
0 |
14 |
3 |
4 |
6 |
29 |
| Total Working Papers |
1 |
10 |
50 |
2,084 |
242 |
442 |
710 |
6,097 |