## Performance Metrics, Risk Metrics, and Strategy Optimization – An Overview

The performance of a trading strategy is measured with a set of parameters. For example, if you are trading in equity then your returns are compared against the benchmark index. The consistency of returns of the strategy also proves to be a significant factor. (more…)

## Volatility and measures of risk-adjusted return with Python

In this post we see how to compute historical volatility in python, and the different measures of risk-adjusted return based on it. We have also provided the python codes for these measures which might be of help to the readers.

#### Introduction

Volatility measures the dispersion of returns for a given security. Volatility can be measured by the standard deviation of returns for a security over a chosen period of time. Historic volatility is derived from time series of past price data, whereas, an implied volatility is derived using the market price of a traded derivative instrument like an options contract.

## Sharpe Ratio and Its Applications in Algorithmic Trading

To measure the performance of a trading strategy, annualized returns are often a common metric. However comparing two strategies based on annualised returns may not always be a logical way due to several reasons. Some strategies might be directional, some market neutral and some might be leveraged which makes annualized return alone a futile measure of performance measurement. Also, even if two strategies have comparable annual returns, the risk is still an important aspect that needs to be measured. A strategy with high annual returns is not necessarily very attractive if it has a high-risk component; we generally prefer better risk-adjusted returns over just ‘better returns’. Sharpe Ratio takes care of risk assessment and the problem related to the comparison of strategies.

Sharpe ratio is a measure for calculating the risk-adjusted return. It is the ratio of the excess expected return of an investment (over risk-free rate) per unit of volatility or standard deviation. (more…)

## Securities Master System Explained

By Gasa Mzolo, a Java Developer

As a developer in the world of vast technologies available to us at the click of a button, many of us more often than not, care about the fun part of building a program from scratch and seeing it work, eventually. Hoping that requirements don’t change from a higher power that basically fills our hearts with enough stress to, if ever converted to poison, would kill a whole colony of rats. They do however, fill our hearts with glee come payday right?! These higher powers only care about the final product working and not about the art of how it was built. In the same breath, there are those jobs which many programmers don’t consider as art, and that is my focus today. (more…)

## Changing Trends in Trading Risk Management

Algorithmic trading risks can be categorized into the following:

• Access
• Consistency
• Quality
• Algorithm
• Technology
• Scalability

There are 2 places where Risk Management is handled –

Within the application – We need to ensure that wrong parameters are not set by the trader. It should not allow a trader to set grossly incorrect values nor any fat-finger errors.

Before generating an order in the Order Management System – Before the order flows out of the system we need to make sure it goes through some risk management system. This is where the most critical risk management check happens. (more…)

## Risk and Asset Management Career Opportunities

A position in risk management is intellectually stimulating. After the market downturn of 2008 risk management has gained prominence in terms of growth as well as financial reward. Career path begins as a risk analyst and can take various routes depending upon the industry type and exposure. Some of the domains that offer risk manager’s positions are insurance companies, banks, asset management companies and corporate finance. (more…)

## Global Trends in Bank Treasury Risk Management

Bank Treasury departments are facing major challenges on multiple fronts, including need to meet regulatory requirements and managing the balance sheet in a truly efficient and optimised manner. We will highlight the main problems and present some recommendations on how a bank treasury should respond to these challenges. Ultimately Treasury departments have to implement “Strategic ALM“, which is the most effective way a bank can optimise its balance sheet. (more…)

## Risk and Asset-Liability Management in Banks

Simply put, risk is likelihood of an undesirable or unexpected event or things going wrong. Risk is inherent to any business, including banks and therefore it is critical to have effective risk management in place. A borrower defaulting, or bank running out of liquidity to pay back to the depositors, or interest rates changing the payoffs from loans are some of the types of risks banks run. (more…)

## Risk Management in Financial Institutions

Have you ever watched the British movie Rogue Trader? It tells the true story of Nick Leeson, an employee of Barings Bank whose speculative trading resulted in wiping out of the bank that existed for 200 years. Lesson that came at a cost was, “It is important to define unambiguous risk limits for traders and then monitor carefully that the limits are being adhered to”. (more…)

## The Greeks in Options: Delta, Gamma, Theta and Vega

The key requirement in successful options trading involves understanding and implementing options pricing models. In this post, we will get a brief understanding about Greeks which will help in creating and understanding the pricing models.

Before we start understanding Greeks, it is important to get a hang of properties of option contracts. We recommend you read the basic concepts here if you are already not familiar with options. Additionally, there are a few other properties about options which you should know before we delve into Greeks. (more…)