Consulting in data science and machine learning applied to finance, forecasting, and risk

QUANTITATIVE SOLUTIONS

SLQ is a quantitative analysis consultancy. We combine tools from data science, machine learning and statistics to provide solutions in finance, forecasting, and risk.

The judicious combination of applied mathematics, statistical techniques, and computational methods allows one to for instance improve the management and risk analysis of an investment portfolio; minimize the costs and transit times of the distribution of a product; or forecast the probabilities and outcomes of various scenarios in a given sector.

Whatever the task at hand, our network of economists and mathematicians brings together theory and practice to develop solutions tailored to the needs of our clients.

TEAM

FLAVIO ABDENUR

  • Managing partner at SLQ and consulting partner at Vérios Investimentos
  • Holds a postdoctorate in mathematics from the Université de Paris 13, a doctorate in mathematics from IMPA, and a bachelor’s degree in economics from PUC-Rio
  • Certified as an investment manager (CGA) and as an financial analyst (CPA-20) by ANBIMA, the Brazilian finance association
  • Has worked as a lecturer at the master’s program in finance at IMPA, as the senior risk analyst at Ventor Investimentos, and as a tenured professor of mathematics at PUC-Rio
  • Proficient in applied mathematics, data science, and machine learning applied to finance and risk via R programming
  • Fields of expertise at SLQ: data science and optimization, forecasting and prospective scenarios, lectures and seminars, machine learning, quantitative finance, risk analysis

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ALEX DE CASTRO

  • Data Scientist at OVO Energy (London)
  • Holds a postdoctorate in mathematics from the Fields Institute (Toronto), a PhD in mathematics from the University of California at Santa Cruz, and a bachelor’s degree in mathematics from UNICAMP
  • Has worked as a professor of mathematics at PUC-Rio, a visiting researcher at Imperial College London, and a lecturer at the master’s program in finance at IMPA
  • Proficient in applied mathematics, data science, and machine learning via Python, R, and Scala
  • Fields of expertise at SLQ: data science and optimization, machine learning

JAIRO BOCHI

  • Tenured professor of mathematics at PUC-Chile
  • Holds a doctorate in mathematics from  IMPA and a bachelor’s degree in mathematics from the Federal University of Rio Grande do Sul (UFRGS)
  • Junior member of the Brazilian Academy of Sciences
  • Has worked as a tenured professor of mathematics at PUC-Rio and as a professor of mathematics at UFRGS
  • Proficient in applied mathematics and optimization
  • Field of expertise at SLQ: data science and optimization

PEDRO HENRIQUE SIMÕES

  • Senior Researcher at CNseg (Brazil’s National Insurance Federation)
  • Holds a masters in statistics from ENCE/IBGE and a bachelor’s degree in economics from PUC-Rio
  • Has worked as an economics consultant, initially at Galanto Consulting Services and on projects for various institutions on market analysis, demographic dynamics, and macroeconomic forecasting
  • Proficient in economic modeling, econometrics, forecasting, and statistics via EViews, SAS, and R
  • Fields of expertise at SLQ: data science and optimization, forecasting and prospective scenarios

PEDRO LIPKIN

  • Researcher at Endeavor Brasil
  • Holds a masters in economics from EESP-FGV and a bachelor’s degree in economics from FGV-Rio
  • Has worked as an economics researcher and consultant at the Centro de Políticas Sociais (Center for Social Policy) at FGV-Rio and at Macroplan Consulting, on projects involving prospective scenarios, microeconomic analysis, and strategic planning for clients from both the public and private sectors
  • Proficient in economic modeling, econometrics, forecasting, and statistics via STATA and R
  • Fields of expertise at SLQ: data science and optimization, forecasting and prospective scenarios

SERVICES

DATA SCIENCE AND OPTIMIZATION

  • Data set cleaning, exploration and visualization
  • Analysis and pattern recognition
  • Analytical and computational optimization of target functions such as cost, revenue, and production levels

FORECASTING AND PROSPECTIVE SCENARIOS

  • Development of time series models for forecasting
  • Development of leading indicators for economic and financial activity
  • Forecasting and trend analysis
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LECTURES AND SEMINARS

  • Presentations on the applications of mathematics to economics and finance
  • Seminars on the areas in which SLQ is active
  • Lectures and seminars at education and research institutions are delivered pro bono

QUANTITATIVE FINANCE

  • Analysis and construction of portfolio risk-return metrics
  • Pricing and mathematical modeling of financial assets
  • Development of portfolio optimization and trading algorithms

RISK ANALYSIS

  • Financial risk, including credit risk, metrics for diversification and liquidity, stress testing, and VaR
  • Non-financial risk, including scenario analysis and Monte Carlo simulations
  • “Black swan” analysis and estimates of losses in the case of extreme events

MACHINE LEARNING

Optimized ensembles of machine learning models for:

  • Prediction of numerical variables such as risk levels and product demand
  • Classification tasks such as credit approval and economic cycle identification
  • Exploratory analysis and data clustering (i.e., “unsupervised learning”)

CLIENTS AND PARTNERS

CONTACT

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SLQ Soluções Quantitativas
Rua Atílio Innocenti 165
Vila Nova Conceição, São Paulo – SP
CEP 04538-000
+55 21 3281-2183
contato@slq.com.br