HFT and Algo Trading


Algorithmic and High-Frequency Trading, Alvaro Cartea, Sebastian Jaimungal, Jose Penalva, Cambridge University Press, 2015

Generic Description

In recent years due to higher frequency and newtechnology the finance industry is confronted with new sets of challenges. This special lecture series will address this problem by considering algorithmic trading and data processing in a high frequency context.

We will use python as a support to implement any content addressed during the lecture on the basis of real dataset.


1. Introduction

● Introduction to the technological changes in finance and their impact.

● Structure of a stock exchange.

● Concept of limit order book.

● Orders (limit, market, cancel) and execution queues.

● market maker rewards.

● Limit order book processing on level 2 data.

2. Statistical features and calibration

● Price movement, Volume.

● Imbalance, placement, latency

● Market depth and trade side liquidity costs.

● Calibration of those models on real data and price/volume movement prediction.

3. Trading Strategies Market Takers

● Almgreen Chris model

● Optimal control and stopping (HJB, DPP)

● Continuous time extensions

● Targeting average volume

4. Trading strategies Market Makers and advanced models

● Jump processes DPP

● Algo trading with limit orders

● Implementation strategies

● non markovian nature of HFT data

● Transient market impact model

● Implementation/calibration

Time Table for the Mini Course


Date & Time



Dec 14 (Tue), 14:00-16:00

BNU, Lijiao B414


Dec 15 (Wed),14:00-16:00

UIC, T7-505


Dec 17 (Fri), 14:00-16:00

UIC, T7-505


Dec 21 (Tue), 14:00-16:00

BNU, Lijiao B414


Dec 24 (Fri), 14:00-16:00

UIC, T7-505