ML4T Exam 1 2025 (Actual Exam) Questions with
verified Answers (Latest Update 2025) UPDATE!!
ML4T Study guide WITH QUALIFIED QUESTIONS
AND ANSWERS.
About how many hedge funds exist now? - correct answers 10,000.
Between Simple Bagging and AdaBoost, which is more likely to overfit as the number of models
(bags) increases? - correct answers AdaBoost, because it is striving to "fit" the data and
therefore is more susceptible to overfitting.
Can the sharpe ratio vairy based on how frequently you sample? - correct answers Yes.
Can you treat a DataFrame like an ndarray? - correct answers Yes.
Define "Adjusted Close" for stock data. - correct answers A number provided by the data
provider, adjusted for stock splits and dividend payments.
,Define "Close" for stock data. - correct answers The actual price that was recorded at the
exchange for that day.
Header rows of a CSV should represent what type of data? - correct answers Data that changes
over time.
How are most of the important indexed weighted? - correct answers The are cap weighted.
How can we interpret alpha in linear regression? - correct answers It is the systematic difference
in performance of a stock compared to the market.
How can we interpret beta in linear regression? - correct answers It represents the stock's price
volatility relative to the overall market.
How could a Hedge Fund exploit inefficiencies in market mechanics? - correct answers Have a
machine co-located with the exchange to beat other orders. Geographic arbitrage.
How could you join two DataFrames and drop nan values in a single line? - correct answers
df_1.join(df_2, how='inner')
How did hedge funds get their name? - correct answers Because the first hedge fund strove
through positive returns through hedging: making contrary bets that would pay off if their main
bet failed.
How do we measure how well a fund performs? - correct answers Cumulative return, volatility,
risk/reward (sharpe ratio).
How do you add additional dimensions to the construction of a np array? - correct answers Add
additional values to the sequence passed to np.empty for each dimension
, How do you calculate Book Value? - correct answers total_assets - (intangible_assets +
liabilities)
How do you calculate Market Capitalization? - correct answers # shares \* price
How do you calculate the cap weight of an index? - correct answers w_i = market_cap_i /
sum_j(market_cap_j)
How do you calculate the intrinsic value of a company? - correct answers future_value /
discount_rate
How do you calculate the Simple Moving Average (SMA) over an n day window for day "t"? -
correct answers SMA[t] = (price[t] / mean(price[t - n: t])) - 1
How do you calculate the value of a future dollar? - correct answers present_value =
future_value / (1 + interest_rate) ^ years_in_future
How do you compute momentum for any given day "t" and n days prior? - correct answers
momentum[t] = price[t] / price[t - n]
How do you create Bollinger Bands? - correct answers By calculating 2 rolling standard
deviations above and below your rolling mean.
How do you fill backward in Pandas for DataFrame df? - correct answers df.fillna(method='bfill',
inplace=True)
How do you fill forward in Pandas for DataFrame df? - correct answers df.fillna(method='ffill',
inplace=True)
verified Answers (Latest Update 2025) UPDATE!!
ML4T Study guide WITH QUALIFIED QUESTIONS
AND ANSWERS.
About how many hedge funds exist now? - correct answers 10,000.
Between Simple Bagging and AdaBoost, which is more likely to overfit as the number of models
(bags) increases? - correct answers AdaBoost, because it is striving to "fit" the data and
therefore is more susceptible to overfitting.
Can the sharpe ratio vairy based on how frequently you sample? - correct answers Yes.
Can you treat a DataFrame like an ndarray? - correct answers Yes.
Define "Adjusted Close" for stock data. - correct answers A number provided by the data
provider, adjusted for stock splits and dividend payments.
,Define "Close" for stock data. - correct answers The actual price that was recorded at the
exchange for that day.
Header rows of a CSV should represent what type of data? - correct answers Data that changes
over time.
How are most of the important indexed weighted? - correct answers The are cap weighted.
How can we interpret alpha in linear regression? - correct answers It is the systematic difference
in performance of a stock compared to the market.
How can we interpret beta in linear regression? - correct answers It represents the stock's price
volatility relative to the overall market.
How could a Hedge Fund exploit inefficiencies in market mechanics? - correct answers Have a
machine co-located with the exchange to beat other orders. Geographic arbitrage.
How could you join two DataFrames and drop nan values in a single line? - correct answers
df_1.join(df_2, how='inner')
How did hedge funds get their name? - correct answers Because the first hedge fund strove
through positive returns through hedging: making contrary bets that would pay off if their main
bet failed.
How do we measure how well a fund performs? - correct answers Cumulative return, volatility,
risk/reward (sharpe ratio).
How do you add additional dimensions to the construction of a np array? - correct answers Add
additional values to the sequence passed to np.empty for each dimension
, How do you calculate Book Value? - correct answers total_assets - (intangible_assets +
liabilities)
How do you calculate Market Capitalization? - correct answers # shares \* price
How do you calculate the cap weight of an index? - correct answers w_i = market_cap_i /
sum_j(market_cap_j)
How do you calculate the intrinsic value of a company? - correct answers future_value /
discount_rate
How do you calculate the Simple Moving Average (SMA) over an n day window for day "t"? -
correct answers SMA[t] = (price[t] / mean(price[t - n: t])) - 1
How do you calculate the value of a future dollar? - correct answers present_value =
future_value / (1 + interest_rate) ^ years_in_future
How do you compute momentum for any given day "t" and n days prior? - correct answers
momentum[t] = price[t] / price[t - n]
How do you create Bollinger Bands? - correct answers By calculating 2 rolling standard
deviations above and below your rolling mean.
How do you fill backward in Pandas for DataFrame df? - correct answers df.fillna(method='bfill',
inplace=True)
How do you fill forward in Pandas for DataFrame df? - correct answers df.fillna(method='ffill',
inplace=True)
