Sahand (Sean) Ahmad verfügbar

Sahand (Sean) Ahmad

SENIOR VICE PRESIDENT at AMM E-FX TRADING, SENIOR RESEARCH FELLOW, QUANTITATIVE STRATEGIST ON QIS (Q

verfügbar
Profilbild von SahandSean Ahmad SENIOR VICE PRESIDENT at AMM E-FX TRADING, SENIOR RESEARCH FELLOW, QUANTITATIVE STRATEGIST ON QIS (Q aus FrankfurtamMain
  • 60316 Frankfurt am Main Freelancer in
  • Abschluss: PhD in Electrical Engineering-Systems , University of Michigan-Ann Arbor (Stochastic Control , Dynamic Programming, Game Theory)
  • Stunden-/Tagessatz:
  • Sprachkenntnisse: arabisch (Grundkenntnisse) | deutsch (verhandlungssicher) | englisch (Muttersprache)
  • Letztes Update: 13.03.2020
SCHLAGWORTE
PROFILBILD
Profilbild von SahandSean Ahmad SENIOR VICE PRESIDENT at AMM E-FX TRADING, SENIOR RESEARCH FELLOW, QUANTITATIVE STRATEGIST ON QIS (Q aus FrankfurtamMain
SKILLS
Data Science , Machine Learning , Artificial Intelligence , Algorithmic Trading , Systematic Investing , Systematic Portfolio Management , High-Frequency Trading , Algorithmic Market Making , Image Processing ,Time-series Forecasting , Database (MongodB , SQL , Kdb/Q , ...) , Recommendation Systems , Survival Analyics , Cohort Aalysis , A/B testing , Statistical Hypotheis Testing , ....

python, C++, Pandas, Keras, Scikitlearn, tensorflow, AWS, Docker, Algorithm, CTA, Python packages, matplotlib, statlib, datetime, numpy, Pyspark, Deep Learning, large data, machine learning, Neural Networks, large data sets,  ALGORITHMIC TRADING, Programming, VIX, Game Theory, Information Theory, scipy, sklearn, * C++, C#, LINK, Multithread, Event-based(publisher, seaborn, fb prophet, statlib Shared Memory, Lock-free queues, MySql, R, VBA/Excel
PROJEKTHISTORIE
  • 06/2017 - 03/2018

    • BNP PARIBAS
  • SENIOR VICE PRESIDENT at AMM E-FX TRADING
  • * Contributed nearly 1M$ per year to desk's P&L by researching and developing signals and strategies for hedging and trading of eFx book based
    on classification of market and client data (Alpha research, Strategy design and backtest, FX 10- minute alpha from orderbook, price action, client
    trades/order flow, CLS/EBS volume, news sentiment, events, other currency pairs, other asset prices, ...) successfully monetizing toxic client flow
    using machine learning/predictive modeling, python
    * Designed an Event-Driven model designed for post-event (2-20 min) market reaction based on surprise factor and other features with accuracy
    score more than 0.65
    * Designed a classifier for predicting Min Ask and Max Bid within a 5-10 min interval using market prices and orderbook states for use within the
    market making framework, exiting trades passively (accuracy score>0.49)
    * Used Ravenpack and Federal Reserve news analysis methodology for creating an online news sentiment score for currencies with 10-minute
    Alpha (Incomplete)
    * Worked closely with software developers in building the book for customized hedging of the toxic clients (Shared Memory,...)

  • 07/2016 - 06/2017

    • SINGAPORE MANAGEMENT UNIVERSITY
  • SENIOR RESEARCH FELLOW
  • * Applied Recurrent Neural Network to enhanced technical data (implied vol, sentiment) of Russel1000 in order to train the network in predicting
    subsequent price move (Accuracy 0.21 out-of-sample vs. 0.1 random, Long-Short Equity based on this strategy produces 0.6% average daily
    return without transaction/shorting costs)
    * Enhanced OLMAR (Online Learning Moving Average Reversion) with a predictive model based on volume (interacting factor), momentum,
    adjusting for Industry bias and Implementing transaction cost
    * Applyed Deep Learning to options data for designing a volatility trading strategy (Not Completed)
    * Worked on a CTA using standard systematic macro factors (Momentum, Volatility, Mean-Reversion around trend-line, ...) combined by a
    Recurrent Neural Network (portfolio optimization wasn't completed)

  • 01/2014 - 01/2016

    • GOLDMAN SACHS ASSET MANAGEMENT
  • QUANTITATIVE STRATEGIST ON QIS (QUANTITATIVE INVESTMENT STRATEGIES) TEAM
  • * Contributed to Research on 2 equity factors based on Indication of Interest data& Intraday trade imbalance (alpha signals extracted were
    implemented within the portfolio optimization signal set, with Sharpe ratios of 0.6 and 1.4)
    * Researched and Implemented an orthogonal 6-factor model for a fast trading model enhancing the current trade execution system with a daily
    up/down forecast signal (open to close)
    * Implemented accounts based on the GTAA (Global Tactical Asset Allocation) model of the Macro team, enhancing and implementing the
    accounts in the codebase in SECDB
    * Implemented and migrated Equity Alpha Factors (Industry-Specific Data, Intraday Market Data, Value, Quality, Momentum, Sentiment,
    Profitability, ...) of the Quantitative Equity team into SECDB codebase




    * Conducted and completed Research projects using large data sets for investigating Alpha in certain market datasets using standard criteria for
    verification of Alpha/Factor Interaction/Factor Turnover (IC, IR, U-chart,5-1 Decile Long-Short ,63-day Gamma, Residual regression, Turnover
    heat map, ...)
    * Implemented a Non-linear(L-1) filter with Mann-statistic for trend Filtering/Detection in equity trend

  • 01/2013 - 12/2013

    • BARCLAYS CAPITAL
  • ALGORITHMIC TRADING QUANT ON FX SPOT TEAM IN INVESTMENT BANKING DIVISION
  • * Designed and Implementated hedging strategies based on decay profiles/trade patterns of streams (calculating riskiness of each currency
    position based on toxicity score of the counterparty clients)
    * Designed and Implemented methods for Trade Cost Analysis (risk reduction and slippage measures for child trades)
    * Designed and Implementated of an optimal execution strategy for large orders based on Dynamic Programming model and Risk-Return Profile of
    small trades
    * Implemented robust strategies for detection of regime shift in the trend of currencies
    * Built a vector autoregression model for predicting intraday bid-ask spread (EBS/Reuters), volume and volatility for multiple pairs/crosses
    * Studied distribution of risk-increasing/risk-decreasing trades, for different currency crosses and different clients
    * Implemented Variance-Covariance VAR method for our portfolio, testing different skews on currency Pairs for reduction of risk, checking their
    effectiveness in terms of speed of risk-reduction vs. P&L

  • 01/2012 - 03/2012

    • FERI TRUST
  • QUANTITATIVE PORTFOLIO RESEARCH INTERN
  • * Devised quantitative methods for detecting market panic using comparison of current VIX index to implied 30-day forward VIX calculated using
    VIX futures
    * Analyzed and compared put options with different maturities and strike prices in order to find relatively more expensive ones to short
    * Researched possible correlation at times of distress between different asset pairs within a class of assets and recommending pairs with strong
    correlation for trade

  • 09/2007 - 07/2010

    • UNIVERSITY OF MICHIGAN
  • RESEARCH ASSISTANT
  • * Researched applications of Game Theory and Stochastic Control in Resource Allocation over Wireless Networks

  • 09/2003 - 05/2007

    • UNIVERSITY OF ILLINOIS
  • RESEARCH ASSISTANT
  • * Researched on Information Theory and Wireless Communication

KONTAKTANFRAGE VERSENDEN

Nachricht:

Absenderdaten: