Learn2Quant: Risk Management | Lesson 9

[Music] risk management hi I'm NES Manny your partner in exploring Quant Finance research I'm the chief strategy officer at World Quant in my role I help to Define our firm strategy and drive several cross functional business initiatives including new avenues for growth and Innovation so in this video let's look at Factor risks what they are why they matter and how we minimize that risk in our research as we develop the range of alpha ideas we have to consider risks the first is exposure to Broad Market or style factors such as size value momentum and volatility

these are known as Factor risks the second component component is the ideosyncratic signal that is specific to that particular Alpha as a reminder World Quant defines an alpha as a mathematical model that seeks to predict the future price movement of various financial instruments Factor risks originated with academic Financial models like the capital asset pricing model also known as the capm model which links the expected stock returns with Market risk Steven Ross's Arbitrage pricing theory in 1976 also asserted that an asset's returns can be predicted by its relationship with common factor risks let's review some common

factor risks beta risk this is the portfolio's exposure to Market Direction it is the result of a Time series regression of a Stock's returns against the returns of the market momentum is a portfolio exposure to stocks recent uptrends or downtrends this is formed by going long on the stocks which continue to be in an upward Trend in the recent 6 to 12 months and shorting the ones which have been on the downward Trend in the same time period size is the return difference between large cap stocks and small cap stocks value contains three factors earnings

yield dividend yield and book to price the factors capture the return difference based on the company's earnings dividend payout and last reported Book value respectively the growth factor differentiates stocks based on the prospects for sales or long-term predicted earnings growth other factors include residual volatility leverage and liquidity you might wonder why we should eliminate exposure to Factor risks whatever may be the asset class that is used in your Alpha idea risk will always be present this means that the factor risks can increase correlations among different approaches if your investment style suffers a draw down due

to a factor it might cause a draw down in other investment Styles exposed to the same factor there is also a liquidation effect these common factors across investment Styles can transfer the negative impact from Liquidation to otherwise unrelated areas of your research let's break this down during a downturn in a portfolio if a portfolio manager with high exposure to the factor risk Cuts their exposure quickly their actions may cause draw Downs in these factors and the effect can pass on to other portfolios with similar Factor exposures in this situation if portfolio with unmitigated Factor risk

exposure can experience draw downs and may also have to be liquidated further amplifying the losses therefore it is recommended to maintain a novel ideosyncratic Alpha pool and minimize these common factor exposures to seek to stabilize the pool's performance here is an example of one factor which is prone to such crashes momentum which has experienced sudden losses of 10 to 30% in the last 60 [Music] years in order to address these concerns Quant researchers can create a risk neutral Alpha the process of making a risk neutral Alpha is fairly simple we follow the similar cycle of

creating an alpha starting with an idea implementing it back testing it and finally improving the alpha the only difference is that the positions generated by the alpha are neutralized to our list of Target Factor risks and the alpha creation process focuses on building a stronger ideosyncratic component let's go to brain our simulation platform and try this out here is a sample Alpha for illustration purposes the first plot is an alpha before risk neutralization once we neutralize the alpha to the commonly known Factor risks the Improvement in the alpha is typically a higher sharp and lower

draw Downs at the expense of a marginal increase in turnover generally it is a good practice to manage exposures to factor risks when designing research ideas we reviewed the types of factor risks that could be present as you build your Alpha pool why they are important and how to seek to eliminate them using risk neutral Alphas quantitative research requires not just a sophisticated approach to identifying and implementing research ideas but also a rigorous focus on risk management throughout these different videos I have shown you how to think about the Quant research cycle Quant research is

an area like many fields it takes time to build expertise and requires a strong intuition to improve your ideas the key is deepening your understanding by reading research papers and applying these ideas to different Alphas which you can test out on brain let's Quant on [Music]